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+ + diff --git a/GinanYamlInspector.html b/GinanYamlInspector.html new file mode 100644 index 000000000..3ed242b80 --- /dev/null +++ b/GinanYamlInspector.html @@ -0,0 +1,122932 @@ + + + +Ginan YAML Inspector + + + + + + + + +

Ginan YAML Inspector

+

Use the checkboxes to enable editing and modification of options. +

Existing yaml files and their configuration can be loaded by importing them below. +

+ + + + + +

+ +
inputs: ⯆ + # This section of the yaml file specifies the lists of files to be used for general metadata inputs, and inputs of external product data. + +
+
+
+ +
inputs_root: + # Root path to be added to all other input files (unless they are absolute) +
+ +
+
+ +
include_yamls: + # List of yaml files to include before this one +
+ +
+
+ +
gnss_observations: ⯆ + # Signal observation data from gnss receivers to be used as measurements +
+
+
+ +
gnss_observations_root: + # Root path to be added to all other gnss data inputs (unless they are absolute) +
+ +
+
+ +
rnx_inputs: +
+ +
+
+ +
rtcm_inputs: +
+ +
+
+ +
custom_inputs: +
+ +
+
+ +
ubx_inputs: +
+ +
+
+
+
+ +
satellite_data: ⯆ +
+
+
+ +
rtcm_inputs: ⯆ + # This section specifies how State State Representation (SSR) corrections are applied after they are downloaded from an NTRIP caster. +
+
+
+ +
rtcm_inputs_root: + # Root path to be added to all other rtcm inputs (unless they are absolute) +
+ +
+
+ +
rtcm_inputs: + # List of rtcm inputs to use for corrections +
+ +
+
+ +
ssr_antenna_offset: + # Ephemeris type that is provided in the listed SSR stream, i.e. satellite antenna-phase-centre (APC) or centre-of-mass (COM). This information is listed in the NTRIP Caster's sourcetable {unspecified, apc, com} +
+ +
+
+ +
qzl6_inputs: + # List of qzss L6 inputs to use for corrections +
+ +
+
+ +
code_bias_validity_time: + # Valid time period of SSR code biases +
+ +
+
+ +
global_vtec_valid_time: + # Valid time period of global VTEC maps +
+ +
+
+ +
local_stec_valid_time: + # Valid time period of local STEC corrections +
+ +
+
+ +
local_trop_valid_time: + # Valid time period of local Troposphere corrections +
+ +
+
+ +
one_freq_phase_bias: + # Used stream have one SSR phase bias per frequency +
+ +
+
+ +
phase_bias_validity_time: + # Valid time period of SSR phase biases +
+ +
+
+ +
validity_interval_factor: +
+ +
+
+
+
+ +
sisnet_inputs: ⯆ + # Configuration for SiSNet stream input. SiSNet broadcast SBAS messages +
+
+
+ +
sisnet_inputs: + # List of sisnet inputs to use for corrections +
+ +
+
+ +
sisnet_inputs_root: + # Root path to be added to all other sisnet inputs (unless they are absolute) +
+ +
+
+ +
sbas_carrier_frequency: + # Carrier frequency of SBAS channel +
+ +
+
+ +
sbas_prn: + # PRN for SBAS satelite +
+ +
+
+
+
+ +
satellite_data_root: + # Root path to be added to all other satellite data files (unless they are absolute) +
+ +
+
+ +
bsx_files: + # List of biassinex files to use +
+ +
+
+ +
clk_files: + # List of clock files to use +
+ +
+
+ +
dcb_files: + # List of dcb files to use +
+ +
+
+ +
nav_files: + # List of ephemeris files to use +
+ +
+
+ +
obx_files: + # List of orbex files to use +
+ +
+
+ +
sp3_files: + # List of sp3 files to use +
+ +
+
+ +
com_files: + # List of com files to use - retroreflector offsets from centre-of-mass for spherical sats +
+ +
+
+ +
crd_files: + # List of crd files to use - SLR observation data +
+ +
+
+ +
sid_files: + # List of sat ID files to use - from https://cddis.nasa.gov/sp3c_satlist.html/ +
+ +
+
+
+
+ +
pseudo_observations: ⯆ + # Use data from pre-processed data products as observations. Useful for combining and comparing datasets +
+
+
+ +
pseudo_observations_root: + # Root path to be added to all other pseudo obs data files (unless they are absolute) +
+ +
+
+ +
filter_files: + # List of inputs to use for custom pseudoobservations +
+ +
+
+ +
snx_inputs: +
+ +
+
+ +
eci_pseudoobs: + # Pseudo observations are provided in eci frame rather than standard ECEF SP3 files +
+ +
+
+ +
sp3_inputs: +
+ +
+
+
+
+ +
tides: ⯆ + # Files specifying tidal loading and potential inputs +
+
+
+ +
atl_blq_col_order: + # Column order for amplitude and phase components in ATL BLQ files [m2, s2, n2, k2, s1, k1, o1, p1, q1, mf, mm, ssa] +
+ +
+
+ +
atl_blq_row_order: + # Row order for amplitude and phase components in ATL BLQ files [east, west, north, south, up, down] +
+ +
+
+ +
atmos_oceean_dealiasing_files: + # List of tide files to use +
+ +
+
+ +
atmos_tide_loading_blq_files: + # List of atl blq files to use +
+ +
+
+ +
atmos_tide_potential_files: + # List of tide files to use +
+ +
+
+ +
ocean_pole_tide_loading_files: + # List of opole files to use +
+ +
+
+ +
ocean_pole_tide_potential_files: + # List of tide files to use +
+ +
+
+ +
ocean_tide_loading_blq_files: + # List of otl blq files to use +
+ +
+
+ +
ocean_tide_potential_files: + # List of tide files to use +
+ +
+
+ +
otl_blq_col_order: + # Column order for amplitude and phase components in OTL BLQ files [m2, s2, n2, k2, s1, k1, o1, p1, q1, mf, mm, ssa] +
+ +
+
+ +
otl_blq_row_order: + # Row order for amplitude and phase components in OTL BLQ files [east, west, north, south, up, down] +
+ +
+
+
+
+ +
troposphere: ⯆ + # Files specifying tropospheric model inputs +
+
+
+ +
gpt2grid_files: + # List of gpt2 grid files to use +
+ +
+
+ +
orography_files: + # List of orography files to use +
+ +
+
+ +
vmf_files: + # List of vmf files to use +
+ +
+
+
+
+ +
ionosphere: ⯆ + # Files specifying ionospheric model inputs +
+
+
+ +
atm_reg_definitions: + # List of files to define regions for compact SSR +
+ +
+
+ +
ion_files: + # List of IONEX files for VTEC input +
+ +
+
+
+
+ +
atx_files: + # List of atx files to use +
+ +
+
+ +
erp_files: + # List of erp files to use +
+ +
+
+ +
cmc_files: + # List of cmc files to use +
+ +
+
+ +
egm_files: + # List of egm files to use +
+ +
+
+ +
hfeop_files: + # List of hfeop files to use +
+ +
+
+ +
igrf_files: + # List of igrf files to use +
+ +
+
+ +
planetary_ephemeris_files: + # List of jpl files to use +
+ +
+
+ +
snx_files: + # List of snx files to use +
+ +
+
+
+
+ +
outputs: ⯆ + # Specifies options to enable outputs and specify file locations. + +Each section typically contains an option to `output` the filetype, and a `directory` to place the files named `filename`, along with any ancillary options. + +
+
+
+ +
outputs_root: + # Directory that outputs will be placed in +
+ +
+
+ +
colourise_terminal: + # Use ascii command codes to highlight warnings and errors +
+ +
+
+ +
warn_once: + # Print warnings once only +
+ +
+
+ +
metadata: ⯆ + # Options for setting metadata for inputs and outputs +
+
+
+ +
config_description: + # ID for this config, used to replace tags in other options +
+ +
+
+ +
pass: + # Password for connecting to NTRIP casters +
+ +
+
+ +
user: + # Username for connecting to NTRIP casters +
+ +
+
+ +
ac_contact: + # Contact person for output files headers +
+ +
+
+ +
analysis_agency: + # Agency for output files headers +
+ +
+
+ +
analysis_centre: + # Analysis centre for output files headers +
+ +
+
+ +
analysis_software: + # Program for output files headers +
+ +
+
+ +
analysis_software_version: + # Version for output files headers +
+ +
+
+ +
atmospheric_tide_loading_model: + # Atmospheric tide loading model applied +
+ +
+
+ +
config_details: + # Comments and details specific to the config +
+ +
+
+ +
geoid_model: + # Geoid model name for undulation values +
+ +
+
+ +
gradient_mapping_function: + # Name of mapping function used for mapping horizontal troposphere gradients +
+ +
+
+ +
ocean_tide_loading_model: + # Ocean tide loading model applied +
+ +
+
+ +
reference_system: + # Terrestrial Reference System Code +
+ +
+
+ +
rinex_comment: + # Comment for output files headers +
+ +
+
+ +
time_system: + # Time system - e.g. "G", "UTC" +
+ +
+
+
+
+ +
trace: ⯆ + # Trace files are used to document processing +
+
+
+ +
directory: + # Directory to output trace files to +
+ +
+
+ +
level: + # Threshold level for printing messages (0-6). Increasing this increases the amount of data stored in all trace files +
+ +
+
+ +
output_config: + # Output configuration files to top of trace files +
+ +
+
+ +
output_initialised_states: + # Output states after state transition 2 +
+ +
+
+ +
output_predicted_states: + # Output states after state transition 1 +
+ +
+
+ +
output_residual_chain: + # Output component-wise details for measurement residuals +
+ +
+
+ +
output_residuals: + # Output measurements and residuals +
+ +
+
+ +
output_network: + # Output trace files for complete network of receivers, inclucing kalman filter results and statistics +
+ +
+
+ +
output_receivers: + # Output trace files for individual receivers processing +
+ +
+
+ +
output_ionosphere: + # Output trace files for ionosphere processing, inclucing kalman filter results and statistics +
+ +
+
+ +
output_satellites: + # Output trace files for individual satellites processing +
+ +
+
+ +
network_filename: + # Template filename for network trace files +
+ +
+
+ +
receiver_filename: + # Template filename for receiver trace files +
+ +
+
+ +
ionosphere_filename: + # Template filename for ionosphere trace files +
+ +
+
+ +
satellite_filename: + # Template filename for satellite trace files +
+ +
+
+ +
output_json: + # Output json formatted trace files +
+ +
+
+
+
+ +
output_rotation: ⯆ + # Trace files can be rotated periodically by epoch interval. These options specify the period that applies to the template variables in filenames +
+
+
+ +
period: + # Period that times will be rounded by to generate template variables in filenames +
+ +
+
+ +
period_units: + # {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+
+
+ +
ssr_outputs: ⯆ + # This section specifies how State State Representation (SSR) corrections are calculated before being published to an NTRIP caster. +
+
+
+ +
code_bias_sources: + # Sources for SSR code biases [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
phase_bias_sources: + # Sources for SSR phase biases [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
atmospheric: ⯆ +
+
+
+ +
cmpssr_stec_format: + # Format of STEC gridded corrections: 0:4bit(LSB=0.04) , 1:4bit(LSB=0.12), 2:5bit, 3:7bit, 4:16bit +
+ +
+
+ +
cmpssr_trop_format: + # Format of Trop. ZWD corrections: 0:8bit, 1:6bit +
+ +
+
+ +
grid_type: + # Grid type for gridded atmospheric corrections +
+ +
+
+ +
lat_int: +
+ +
+
+ +
lat_max: +
+ +
+
+ +
lat_min: +
+ +
+
+ +
lon_int: +
+ +
+
+ +
lon_max: +
+ +
+
+ +
lon_min: +
+ +
+
+ +
npoly_iono: +
+ +
+
+ +
npoly_trop: +
+ +
+
+ +
region_id: + # Region ID for atmospheric corrections +
+ +
+
+ +
region_iod: + # Region IOD for atmospheric corrections (default: -1 for undefined) +
+ +
+
+ +
sources: + # Sources for SSR ionosphere [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
use_grid_iono: + # Grid type for gridded atmospheric corrections +
+ +
+
+ +
use_grid_trop: + # Grid type for gridded atmospheric corrections +
+ +
+
+
+
+ +
clock_sources: + # Sources for SSR clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
cmpssr_cell_mask: +
+ +
+
+ +
ephemeris_sources: + # Sources for SSR ephemeris [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
extrapolate_corrections: +
+ +
+
+ +
max_stec_sigma: +
+ +
+
+ +
prediction_duration: +
+ +
+
+ +
prediction_interval: +
+ +
+
+
+
+ +
streams: ⯆ +
+
+
+ +
root_url: + # Root url to be prepended to all other streams specified in this section. If the streams used have individually specified root urls, usernames, or passwords, this should not be used. +
+ +
+
+ +
labels: + # List of output stream is with further information to be found in its own section, as per XMPL below +
+ +
+
+ +
xmpl: ⯆ +
+
+
+ +
messages: ⯆ +
+
+
+ +
rtcm_0: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1019: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1020: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1042: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1044: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1045: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1046: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1057: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1058: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1059: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1060: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1061: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1062: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1063: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1064: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1065: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1066: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1067: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1068: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1074: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1075: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1076: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1077: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1084: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1085: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1086: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1087: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1094: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1095: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1096: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1097: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1114: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1115: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1116: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1117: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1124: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1125: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1126: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1127: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1240: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1241: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1242: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1243: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1244: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1245: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1246: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1247: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1248: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1249: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1250: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1251: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1252: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1253: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1254: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1255: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1256: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1257: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1258: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1259: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1260: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1261: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1262: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1263: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1265: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1266: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1267: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1268: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1269: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_1270: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_00: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_01: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_02: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_03: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_04: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_05: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_06: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_07: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_08: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_09: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_10: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_11: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4073_12: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_000: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_001: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_002: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_003: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_004: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_005: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_006: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_007: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_008: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_020: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_021: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_022: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_023: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_024: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_025: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_026: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_027: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_040: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_041: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_042: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_043: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_044: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_045: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_046: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_047: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_060: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_061: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_062: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_063: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_064: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_065: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_066: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_067: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_080: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_081: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_082: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_083: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_084: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_085: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_086: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_087: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_100: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_101: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_102: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_103: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_104: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_105: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_106: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_107: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_120: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_121: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_122: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_123: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_124: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_125: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_126: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_127: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4076_201: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+ +
rtcm_4082: ⯆ + # Message type to output +
+
+
+ +
udi: + # Update interval +
+ +
+
+
+
+
+
+ +
url: + # Url of caster to send messages to +
+ +
+
+ +
itrf_datum: +
+ +
+
+ +
provider_id: +
+ +
+
+ +
solution_id: +
+ +
+
+
+
+
+
+ +
clocks: ⯆ + # Rinex formatted clock files +
+
+
+ +
output: + # Output clock files +
+ +
+
+ +
directory: + # Directory to output clock files to +
+ +
+
+ +
filename: + # Template filename for clock files +
+ +
+
+ +
output_interval: + # Update interval for clock records +
+ +
+
+ +
receiver_sources: + # [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
satellite_sources: + # [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
gpx: ⯆ + # GPX files contain point data that may be easily viewed in GIS mapping software +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
log: ⯆ + # Log files store console output in files +
+
+
+ +
output: + # Enable console output logging +
+ +
+
+ +
directory: + # Log output directory +
+ +
+
+ +
filename: + # Log output filename +
+ +
+
+
+
+ +
pos: ⯆ + # POS files contain point data that may be easily viewed in GIS mapping software +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
bias_sinex: ⯆ + # Rinex formatted bias sinex files +
+
+
+ +
output: + # Output bias sinex files +
+ +
+
+ +
bias_time_system: + # Time system for bias SINEX "G", "C", "R", "UTC", "TAI" +
+ +
+
+ +
code_output_interval: + # Update interval for code biases +
+ +
+
+ +
directory: + # Directory to output bias sinex files to +
+ +
+
+ +
filename: + # Template filename for bias sinex files +
+ +
+
+ +
output_rec_bias: + # output receiver biases +
+ +
+
+ +
phase_output_interval: + # Update interval for phase biases +
+ +
+
+
+
+ +
cost: ⯆ + # COST format files are used to export troposhere products, such as ZTD and delay gradients. +
+
+
+ +
output: + # Enable data exporting to troposphere COST file +
+ +
+
+ +
cost_centre: + # Processing centre +
+ +
+
+ +
cost_format: + # Format name & version number +
+ +
+
+ +
cost_met_sources: + # Source of met. data +
+ +
+
+ +
cost_method: + # Processing method +
+ +
+
+ +
cost_orbit_type: + # Orbit type +
+ +
+
+ +
cost_project: + # Project name +
+ +
+
+ +
cost_status: + # File status +
+ +
+
+ +
directory: + # Directory to export troposphere COST file +
+ +
+
+ +
filename: + # Troposphere COST filename +
+ +
+
+ +
sources: + # Source for troposphere delay data - KALMAN, etc. [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
time_interval: + # Time interval between entries in troposphere COST file (sec) +
+ +
+
+
+
+ +
erp: ⯆ + # Earth rotation parameters can be output to file +
+
+
+ +
output: + # Enable exporting of erp data +
+ +
+
+ +
directory: + # Directory to export erp data files +
+ +
+
+ +
filename: + # ERP data output filename +
+ +
+
+
+
+ +
orbex: ⯆ +
+
+
+ +
output: + # Output orbex file +
+ +
+
+ +
attitude_sources: + # Sources for orbex attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
clock_sources: + # Sources for orbex clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
directory: + # Output orbex directory +
+ +
+
+ +
filename: + # Output orbex filename +
+ +
+
+ +
orbit_sources: + # Sources for orbex orbits [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
output_interval: + # Update interval for orbex records (irregular epoch interval is currently NOT supported) +
+ +
+
+ +
record_types: + # List of record types to output to orbex file [pcs, vcs, cpc, cvc, pos, vel, clk, crt, att] +
+ +
+
+
+
+ +
sinex: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
sp3: ⯆ + # SP3 files contain orbital and clock data of satellites and receivers +
+
+
+ +
output: + # Enable SP3 file outputs +
+ +
+
+ +
clock_sources: + # List of sources for clock data for SP3 outputs [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
directory: + # Directory to store SP3 outputs +
+ +
+
+ +
filename: + # SP3 output filename +
+ +
+
+ +
orbit_sources: + # List of sources for orbit data for SP3 outputs [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
output_inertial: + # Output the entries using inertial positions and velocities +
+ +
+
+ +
output_interval: + # Update interval for SP3 records +
+ +
+
+ +
output_velocities: + # Output velocity data to SP3 file +
+ +
+
+ +
predicted_filename: + # Filename for predicted SP3 outputs +
+ +
+
+
+
+ +
trop_sinex: ⯆ + # Troposphere SINEX files are used to export troposhere products, such as ZTD and delay gradients. +
+
+
+ +
output: + # Enable data exporting to troposphere SINEX file +
+ +
+
+ +
const_code: + # Troposphere SINEX const code +
+ +
+
+ +
directory: + # Directory to export troposphere SINEX file +
+ +
+
+ +
filename: + # Troposphere SINEX filename +
+ +
+
+ +
obs_code: + # Troposphere SINEX observation code +
+ +
+
+ +
sol_type: + # Troposphere SINEX solution type +
+ +
+
+ +
sources: + # Source for troposphere delay data - KALMAN, etc. [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+ +
version: + # Troposphere SINEX version +
+ +
+
+
+
+ +
ionex: ⯆ + # IONEX formatted ionospheric mapping and modelling outputs +
+
+
+ +
output: + # Enable exporting ionospheric model data +
+ +
+
+ +
directory: + # Directory to export ionex data +
+ +
+
+ +
filename: + # Ionex data filename +
+ +
+
+ +
grid: ⯆ +
+
+
+ +
lat_centre: + # Center lattitude for models +
+ +
+
+ +
lat_resolution: + # Interval between lattitude outputs +
+ +
+
+ +
lat_width: + # Total lattitudinal width of model +
+ +
+
+ +
lon_centre: + # Center longitude for models +
+ +
+
+ +
lon_resolution: + # Interval between longitude outputs +
+ +
+
+ +
lon_width: + # Total longitudinal width of model +
+ +
+
+ +
time_resolution: + # Interval between output epochs +
+ +
+
+
+
+
+
+ +
ionstec: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
orbit_ics: ⯆ + # Orbital parameters can be output in a yaml that Ginan can later use as an initial condition for futher processing. +
+
+
+ +
directory: + # Output orbital initial condition directory +
+ +
+
+ +
filename: + # Output orbital initial condition filename +
+ +
+
+ +
output: + # Output orbital initial condition file +
+ +
+
+
+
+ +
sbas_ems: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
network_statistics: ⯆ +
+
+
+ +
output: + # Enable exporting network statistics data to file +
+ +
+
+ +
directory: + # Directory to export network statistics data +
+ +
+
+ +
filename: + # Network statistics data filename +
+ +
+
+
+
+ +
ntrip_log: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
rinex_nav: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+ +
version: +
+ +
+
+
+
+ +
rinex_obs: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+ +
output_doppler: +
+ +
+
+ +
output_phase_range: +
+ +
+
+ +
output_pseudorange: +
+ +
+
+ +
output_signal_to_noise: +
+ +
+
+ +
version: +
+ +
+
+
+
+ +
rtcm_nav: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
rtcm_obs: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
decoded_rtcm: ⯆ + # RTCM messages that are received may be recorded to human-readable json files +
+
+
+ +
output: + # Enable exporting decoded RTCM data to file +
+ +
+
+ +
directory: + # Directory to export decoded RTCM data +
+ +
+
+ +
filename: + # Decoded RTCM data filename +
+ +
+
+
+
+ +
encoded_rtcm: ⯆ + # RTCM messages that are encoded and transmitted may be recorded to human-readable json files +
+
+
+ +
output: + # Enable exporting encoded RTCM data to file +
+ +
+
+ +
directory: + # Directory to export encoded RTCM data +
+ +
+
+ +
filename: + # Encoded RTCM data filename +
+ +
+
+
+
+ +
raw_custom: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
raw_ubx: ⯆ +
+
+
+ +
output: +
+ +
+
+ +
directory: +
+ +
+
+ +
filename: +
+ +
+
+
+
+ +
slr_obs: ⯆ + # SLR_OBS files are used as temporary files to arrange SLR observations by time. SLR observations are taken from CRD files, which are not strictly in time-order). +
+
+
+ +
output: + # Enable data exporting to tabular SLR obs file +
+ +
+
+ +
directory: + # Directory to export tabular SLR obs file +
+ +
+
+ +
filename: + # Tabular SLR obs filename +
+ +
+
+
+
+
+
+ +
processing_options: ⯆ + # Various sections and parameters to specify how the observations are processed +
+
+
+ +
epoch_control: ⯆ + # Specifies the rate and duration of data processing +
+
+
+ +
end_epoch: + # (YYYY-MM-DD hh:mm:ss) The time of the last epoch to process (all observations after this will be skipped) +
+ +
+
+ +
epoch_interval: + # Desired time step between each processing epoch +
+ +
+
+ +
max_epochs: + # Maximum number of epochs to process +
+ +
+
+ +
start_epoch: + # (YYYY-MM-DD hh:mm:ss) The time of the first epoch to process (all observations before this will be skipped) +
+ +
+
+ +
sleep_milliseconds: + # Time to sleep before checking for new data - lower numbers are associated with high idle cpu usage +
+ +
+
+ +
assign_closest_epoch: + # Assign observations to the closest epoch - don't skip observations that fall between epochs +
+ +
+
+ +
epoch_tolerance: + # Tolerance of times to add to an epoch (usually half of the original data's sample rate) +
+ +
+
+ +
max_rec_latency: + # Time to wait from the reception of the first data of an epoch before skipping receivers with data still unreceived +
+ +
+
+ +
require_obs: + # Exit the program if no observation sources are available +
+ +
+
+ +
simulate_real_time: + # For RTCM playback - delay processing to match original data rate +
+ +
+
+ +
wait_next_epoch: + # Time to wait for next epochs data before skipping the epoch (will default to epoch_interval as an appropriate minimum value for realtime) +
+ +
+
+
+
+ +
gnss_general: ⯆ + # Options to specify the processing of gnss observations +
+
+
+ +
sys_options: ⯆ +
+
+
+ +
bds: ⯆ + # Options for the BDS constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+ +
gal: ⯆ + # Options for the GAL constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+ +
glo: ⯆ + # Options for the GLO constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+ +
gps: ⯆ + # Options for the GPS constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+ +
leo: ⯆ + # Options for the LEO constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+ +
qzs: ⯆ + # Options for the QZS constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+ +
sbs: ⯆ + # Options for the SBS constellation +
+
+
+ +
process: + # Process this constellation +
+ +
+
+ +
code_priorities: + # List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
network_amb_pivot: + # Constrain: set of ambiguities, to eliminate network rank deficiencies +
+ +
+
+ +
receiver_amb_pivot: + # Constrain: set of ambiguities, to eliminate receiver rank deficiencies +
+ +
+
+ +
reject_eclipse: + # Exclude satellites that are in eclipsing region +
+ +
+
+ +
use_for_iono_model: + # Use this constellation as part of Ionospheric model +
+ +
+
+ +
use_iono_corrections: + # Use external ionosphere delay estimation for this constellation +
+ +
+
+ +
used_nav_type: + # {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} +
+ +
+
+ +
ambiguity_resolution: + # Solve carrier phase ambiguities for this constellation +
+ +
+
+
+
+
+
+ +
code_measurements: ⯆ +
+
+
+ +
process: + # Process code measurements +
+ +
+
+
+
+ +
phase_measurements: ⯆ +
+
+
+ +
process: + # Process phase measurements +
+ +
+
+
+
+ +
add_eop_component: + # Add eop adjustments as a component in residual chain (for adjusting frames to match ecef ephemeris) +
+ +
+
+ +
adjust_clocks_for_jumps_only: + # Round clock adjustments from SPP to half milliseconds +
+ +
+
+ +
adjust_rec_clocks_by_spp: + # Adjust receiver clocks by spp values to minimise prefit residuals +
+ +
+
+ +
auto_fill_pco: + # Use similar PCOs when requested values are not found +
+ +
+
+ +
common_rec_pco: + # Use L1 receiver PCO values for all signals +
+ +
+
+ +
common_sat_pco: + # Use L1 satellite PCO values for all signals +
+ +
+
+ +
delete_old_ephemerides: + # Remove old ephemerides that have accumulated over time from before far before the currently processing epoch +
+ +
+
+ +
equate_ionospheres: + # Use same STEC values for different receivers, useful for simulated rtk mode +
+ +
+
+ +
equate_tropospheres: + # Use same troposphere values for different receivers, useful for simulated rtk mode +
+ +
+
+ +
fixed_phase_bias_var: + # Variance of phase bias to be considered fixed/binded +
+ +
+
+ +
gpst_utc_leap_seconds: + # Difference between gps time and utc in leap seconds +
+ +
+
+ +
interpolate_rec_pco: + # Interpolate other known pco values to find pco for unknown frequencies +
+ +
+
+ +
minimise_ionosphere_offsets: + # Apply gauss-markov mu values to stec values to minimise offsets with respect to klobuchar values +
+ +
+
+ +
minimise_sat_clock_offsets: + # Apply gauss-markov mu values to satellite clocks to minimise offsets with respect to broadcast values +
+ +
+
+ +
minimise_sat_orbit_offsets: + # Apply gauss-markov mu values to satellite orbits to minimise offsets with respect to broadcast values +
+ +
+
+ +
pivot_receiver: + # Largely deprecated id of receiver to use for pivot constraints +
+ +
+
+ +
pivot_satellite: + # Largely deprecated id of satellite to use for pivot constraints +
+ +
+
+ +
require_antenna_details: + # Restrict processing to receivers that have antenna details +
+ +
+
+ +
require_apriori_positions: + # Restrict processing to receivers that have apriori positions available +
+ +
+
+ +
require_reflector_com: + # Restrict processing to SLR observations that have center of mass to laser retroreflector array offsets +
+ +
+
+ +
require_sinex_data: + # Restrict processing to receivers that have sinex data available +
+ +
+
+ +
require_site_eccentricity: + # Restrict processing to receivers that have site eccentricity information +
+ +
+
+ +
use_rtk_combo: + # Combine applicable observations to simulate an rtk solution +
+ +
+
+ +
use_tgd_bias: + # Use TGD/BGD bias from ephemeris, DO NOT turn on unless using Klobuchar/NeQuick Ionospheres +
+ +
+
+
+
+ +
process_modes: ⯆ + # Aspects of the processing flow may be enabled and disabled according to desired type of solutions +
+
+
+ +
ppp: + # Perform PPP network or end user mode +
+ +
+
+ +
preprocessor: + # Preprocessing and quality checks +
+ +
+
+ +
spp: + # Perform SPP on receiver data +
+ +
+
+ +
ionosphere: + # Compute Ionosphere models based on GNSS measurements +
+ +
+
+ +
slr: + # Process SLR observations +
+ +
+
+
+
+ +
spp: ⯆ + # Configurations for the kalman filter and its sub processes +
+
+
+ +
max_lsq_iterations: + # Maximum number of iterations of least squares allowed for convergence +
+ +
+
+ +
outlier_screening: ⯆ + # Statistical checks allow for detection of outliers that exceed their confidence intervals. +
+
+
+ +
chi_square: ⯆ +
+
+
+ +
enable: + # Enable Chi-square test +
+ +
+
+ +
mode: + # Chi-square test mode {innovation, measurement, state} +
+ +
+
+ +
sigma_threshold: + # Chi-square test threshold in terms of 'times of sigma' +
+ +
+
+
+
+ +
postfit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using postfit checks while iterating filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+ +
prefit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using prefit checks before attempting to filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
omega_test: + # Enable omega-test +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+ +
max_gdop: + # Maximum dilution of precision before error is flagged +
+ +
+
+ +
raim: + # Enable Receiver Autonomous Integrity Monitoring. When SPP fails further SPP solutions are calculated with subsets of observations with the aim of eliminating a problem satellite +
+ +
+
+
+
+ +
sigma_scaling: + # Scale applied to measurement noise for spp +
+ +
+
+ +
always_reinitialise: + # Reset SPP state to zero to avoid potential for lock-in of bad states +
+ +
+
+ +
iono_mode: + # {off, broadcast, sbas, iono_free_linear_combo, estimate, total_electron_content, qzs, lex, stec} +
+ +
+
+
+
+ +
preprocessor: ⯆ + # Configurations for the kalman filter and its sub processes +
+
+
+ +
cycle_slips: ⯆ + # Cycle slips may be detected by the preprocessor and measurements rejected or ambiguities reinitialised +
+
+
+ +
mw_process_noise: + # Process noise applied to filtered Melbourne-Wubenna measurements to detect cycle slips +
+ +
+
+ +
slip_threshold: + # Value used to determine when a slip has occurred +
+ +
+
+
+
+ +
preprocess_all_data: +
+ +
+
+
+
+ +
ppp_filter: ⯆ + # Configurations for the kalman filter and its sub processes +
+
+
+ +
ionospheric_components: ⯆ + # Slant ionospheric components +
+
+
+ +
common_ionosphere: + # Use the same ionosphere state for code and phase observations +
+ +
+
+ +
use_gf_combo: + # Combine 'uncombined' measurements to simulate a geometry-free solution +
+ +
+
+ +
use_if_combo: + # Combine 'uncombined' measurements to simulate an ionosphere-free solution +
+ +
+
+ +
corr_mode: + # {off, broadcast, sbas, iono_free_linear_combo, estimate, total_electron_content, qzs, lex, stec} +
+ +
+
+
+
+ +
outlier_screening: ⯆ + # Statistical checks allow for detection of outliers that exceed their confidence intervals. +
+
+
+ +
chi_square: ⯆ +
+
+
+ +
enable: + # Enable Chi-square test +
+ +
+
+ +
mode: + # Chi-square test mode {innovation, measurement, state} +
+ +
+
+ +
sigma_threshold: + # Chi-square test threshold in terms of 'times of sigma' +
+ +
+
+
+
+ +
postfit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using postfit checks while iterating filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+ +
prefit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using prefit checks before attempting to filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
omega_test: + # Enable omega-test +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+
+
+ +
advanced_postfits: + # Use alternate calculation method to determine postfit residuals +
+ +
+
+ +
assume_linearity: + # Residuals will be adjusted during measurement combination rather than performing 2 seperate state transitions +
+ +
+
+ +
chunking: ⯆ +
+
+
+ +
by_receiver: + # Split large filter and measurement matrices blockwise by receiver ID to improve processing speed +
+ +
+
+ +
by_satellite: + # Split large filter and measurement matrices blockwise by satellite ID to improve processing speed +
+ +
+
+ +
size: +
+ +
+
+
+
+ +
inverter: + # Inverter to be used within the Kalman filter update stage, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} +
+ +
+
+ +
joseph_stabilisation: +
+ +
+
+ +
periodic_reset: ⯆ +
+
+
+ +
enable: + # Enable periodic reset of filter states +
+ +
+
+ +
interval: + # Interval between reset of filter states +
+ +
+
+ +
states: + # States to remove for periodic reset [none, one, all, rec_pos, rec_vel, rec_pos_rate, rec_acc, strain_rate, pos, vel, acc, heading, orientation, ref_sys_bias, rec_clock, rec_sys_bias, rec_clock_rate, rec_sys_bias_rate, rec_clock_rate_gm, rec_sys_bias_rate_gm, sat_clock, sat_clock_rate, sat_clock_rate_gm, trop, trop_grad, trop_model, ionospheric, iono_stec, rec_pco_x, rec_pco_y, rec_pco_z, sat_pco_x, sat_pco_y, sat_pco_z, rec_pcv, ant_delta, eop, eop_rate, calc, slr_rec_range_bias, slr_rec_time_bias, xform_xlate, xform_rtate, xform_scale, xform_delay, ambiguity, code_bias, phase_bias, z_amb, reference, begin_meas_states, code_meas, phas_meas, laser_meas, pseudo_meas, orbit_meas, filter_meas, end_meas_states, begin_orbit_states, orbit, emp_d_0, emp_d_1, emp_d_2, emp_d_3, emp_d_4, emp_y_0, emp_y_1, emp_y_2, emp_y_3, emp_y_4, emp_b_0, emp_b_1, emp_b_2, emp_b_3, emp_b_4, emp_r_0, emp_r_1, emp_r_2, emp_r_3, emp_r_4, emp_t_0, emp_t_1, emp_t_2, emp_t_3, emp_t_4, emp_n_0, emp_n_1, emp_n_2, emp_n_3, emp_n_4, emp_p_0, emp_p_1, emp_p_2, emp_p_3, emp_p_4, emp_q_0, emp_q_1, emp_q_2, emp_q_3, emp_q_4, end_orbit_states, begin_inertial_states, gyro_bias, gyro_scale, accl_bias, accl_scale, imu_offset, end_inertial_states, range] +
+ +
+
+
+
+ +
rts: ⯆ + # RTS allows reverse smoothing of estimates such that early estimates can make use of later data. +
+
+
+ +
interval: + # Number of seconds to use between fixed lag in RTS smoothing. +
+ +
+
+ +
enable: + # Perform backward smoothing of states to improve precision of earlier states +
+ +
+
+ +
lag: + # Number of epochs to use in RTS smoothing. Negative numbers indicate full reverse smoothing. +
+ +
+
+ +
directory: + # Directory for rts intermediate files +
+ +
+
+ +
filename: + # Base filename for rts intermediate files +
+ +
+
+ +
inverter: + # Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} +
+ +
+
+ +
output_intermediates: + # Output best available smoothed states when performing fixed-lag rts (slow, use only when needed) +
+ +
+
+ +
queue_outputs: + # Queue rts outputs so that processing is not limited by IO bandwidth +
+ +
+
+ +
suffix: + # Suffix to be applied to smoothed versions of files +
+ +
+
+
+
+ +
simulate_filter_only: + # Residuals will be calculated, but no adjustments to state or covariances will be applied +
+ +
+
+
+
+ +
minimum_constraints: ⯆ + # Receiver coodinates may be aligned to reference frames with minimal external constraints +
+
+
+ +
outlier_screening: ⯆ + # Statistical checks allow for detection of outliers that exceed their confidence intervals. +
+
+
+ +
chi_square: ⯆ +
+
+
+ +
enable: + # Enable Chi-square test +
+ +
+
+ +
mode: + # Chi-square test mode {innovation, measurement, state} +
+ +
+
+ +
sigma_threshold: + # Chi-square test threshold in terms of 'times of sigma' +
+ +
+
+
+
+ +
postfit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using postfit checks while iterating filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+ +
prefit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using prefit checks before attempting to filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
omega_test: + # Enable omega-test +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+
+
+ +
advanced_postfits: + # Use alternate calculation method to determine postfit residuals +
+ +
+
+ +
enable: + # Transform states by minimal constraints to selected receiver coordinates +
+ +
+
+ +
delay: ⯆ + # Estimation and application of clock delay adjustment +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
rotation: ⯆ + # Estimation and application of angular offsets +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
scale: ⯆ + # Estimation and application of scaling factor +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
translation: ⯆ + # Estimation and application of CoG offsets +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
application_mode: + # Method of transforming positions {pseudo_obs, weight_matrix, variance_inverse, covariance_inverse} +
+ +
+
+ +
constrain_orbits: + # Enforce rigid transformations of orbital states +
+ +
+
+ +
full_vcv: + # ! experimental ! Use full VCV for measurement noise in minimum constraints filter +
+ +
+
+ +
once_per_epoch: + # Perform minimum constraints on a temporary filter and output results once per epoch +
+ +
+
+ +
transform_unweighted: + # Add design entries for transformation of positions without weighting +
+ +
+
+ +
inverter: + # Inverter to be used within the Kalman filter update stage, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} +
+ +
+
+ +
joseph_stabilisation: +
+ +
+
+ +
rts: ⯆ + # RTS allows reverse smoothing of estimates such that early estimates can make use of later data. +
+
+
+ +
interval: + # Number of seconds to use between fixed lag in RTS smoothing. +
+ +
+
+ +
enable: + # Perform backward smoothing of states to improve precision of earlier states +
+ +
+
+ +
lag: + # Number of epochs to use in RTS smoothing. Negative numbers indicate full reverse smoothing. +
+ +
+
+ +
directory: + # Directory for rts intermediate files +
+ +
+
+ +
filename: + # Base filename for rts intermediate files +
+ +
+
+ +
inverter: + # Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} +
+ +
+
+ +
output_intermediates: + # Output best available smoothed states when performing fixed-lag rts (slow, use only when needed) +
+ +
+
+ +
queue_outputs: + # Queue rts outputs so that processing is not limited by IO bandwidth +
+ +
+
+ +
suffix: + # Suffix to be applied to smoothed versions of files +
+ +
+
+
+
+
+
+ +
model_error_handling: ⯆ + # The kalman filter is capable of automatic statistical integrity modelling +
+
+
+ +
error_accumulation: ⯆ + # Any receivers that are consistently getting many measurement rejections may be reinitialiased +
+
+
+ +
enable: + # Enable reinitialisation of receivers upon many rejections +
+ +
+
+ +
receiver_error_count_threshold: + # Number of errors for a receiver to be considered in error for a single epoch +
+ +
+
+ +
receiver_error_epochs_threshold: + # Number of consecutive epochs with receiver in error before it is removed and reinitialised +
+ +
+
+
+
+ +
meas_deweighting: ⯆ + # Measurements that are outside the expected confidence bounds may be deweighted so that outliers do not contaminate the filtered solution +
+
+
+ +
deweight_factor: + # Factor to downweight the variance of measurements with statistically detected errors +
+ +
+
+ +
enable: + # Enable deweighting of all rejected measurement +
+ +
+
+
+
+ +
state_deweighting: ⯆ + # Any "state" errors cause deweighting of all measurements that reference the state +
+
+
+ +
deweight_factor: + # Factor to downweight the variance of measurements with statistically detected errors +
+ +
+
+ +
enable: + # Enable deweighting of all referencing measurements +
+ +
+
+
+
+ +
ambiguities: ⯆ + # Cycle slips in ambiguities are primary cause of incorrect gnss modelling and may be reinitialised +
+
+
+ +
outage_reset_limit: + # Maximum number of seconds without phase measurements before the ambiguity associated with the measurement is reset. +
+ +
+
+ +
phase_reject_limit: + # Maximum number of phase measurements to reject before the ambiguity associated with the measurement is reset. +
+ +
+
+ +
reset_on: ⯆ +
+
+
+ +
gf: + # Reset ambiguities if GF test is detecting a slip +
+ +
+
+ +
lli: + # Reset ambiguities if LLI test is detecting a slip +
+ +
+
+ +
mw: + # Reset ambiguities if MW test is detecting a slip +
+ +
+
+ +
scdia: + # Reset ambiguities if SCDIA test is detecting a slip +
+ +
+
+
+
+
+
+ +
ionospheric_components: ⯆ +
+
+
+ +
outage_reset_limit: + # Maximum number of seconds without measurements before the ionosphere associated with the measurement is reset. +
+ +
+
+
+
+ +
exclusions: ⯆ + # Cycle slips may be detected by the preprocessor and measurements rejected or ambiguities reinitialised +
+
+
+ +
bad_spp: + # Exclude measurements that were associated with failed SPP +
+ +
+
+ +
config: + # Exclude measurements that are configured as exclusions +
+ +
+
+ +
eclipse: + # Exclude measurements that are in eclipse +
+ +
+
+ +
elevation: + # Exclude measurements that fall below elevation mask +
+ +
+
+ +
gf: + # Exclude measurements that fail GF slip test in preprocessor +
+ +
+
+ +
lli: + # Exclude measurements that fail LLI slip test in preprocessor +
+ +
+
+ +
mw: + # Exclude measurements that fail MW slip test in preprocessor +
+ +
+
+ +
outlier: + # Exclude measurements that were rejected as SPP outliers +
+ +
+
+ +
scdia: + # Exclude measurements that fail SCDIA test in preprocessor +
+ +
+
+ +
svh: + # Exclude measurements that are not specified as healthy +
+ +
+
+ +
system: + # Exclude measurements that have been excluded by system configs +
+ +
+
+
+
+ +
orbit_errors: ⯆ + # Orbital states that are not consistent with measurements may be reinitialised to allow for dynamic maneuvers +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
pos_process_noise: + # Sigma to apply to orbital position states as reinitialisation +
+ +
+
+ +
vel_process_noise: + # Sigma to apply to orbital velocity states as reinitialisation +
+ +
+
+ +
vel_process_noise_trail: + # Initial sigma for exponentially decaying noise to apply for subsequent epochs as soft reinitialisation +
+ +
+
+ +
vel_process_noise_trail_tau: + # Time constant for exponentially decauing noise +
+ +
+
+
+
+
+
+ +
ambiguity_resolution: ⯆ +
+
+
+ +
elevation_mask: + # Minimum satellite elevation to perform ambiguity resolution +
+ +
+
+ +
fix_and_hold: + # Perform ambiguity resolution and commit results to the main processing filter +
+ +
+
+ +
lambda_set_size: + # Maximum numer of candidate sets to be used in lambda_alt2 and lambda_bie modes +
+ +
+
+ +
max_rounding_iterations: + # Maximum number of rounding iterations performed in iter_rnd and bootst modes +
+ +
+
+ +
mode: + # {off, round, iter_rnd, bootst, lambda, lambda_alt, lambda_al2, lambda_bie} +
+ +
+
+ +
once_per_epoch: + # Perform ambiguity resolution on a temporary filter and output results once per epoch +
+ +
+
+ +
solution_ratio_threshold: + # Thresold for integer validation, distance ratio test. +
+ +
+
+ +
success_rate_threshold: + # Thresold for integer validation, success rate test. +
+ +
+
+
+
+ +
ion_filter: ⯆ + # Configurations for the ionospheric model kalman filter and its sub processes +
+
+
+ +
outlier_screening: ⯆ + # Statistical checks allow for detection of outliers that exceed their confidence intervals. +
+
+
+ +
chi_square: ⯆ +
+
+
+ +
enable: + # Enable Chi-square test +
+ +
+
+ +
mode: + # Chi-square test mode {innovation, measurement, state} +
+ +
+
+ +
sigma_threshold: + # Chi-square test threshold in terms of 'times of sigma' +
+ +
+
+
+
+ +
postfit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using postfit checks while iterating filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+ +
prefit: ⯆ +
+
+
+ +
max_iterations: + # Maximum number of measurements to exclude using prefit checks before attempting to filter +
+ +
+
+ +
meas_sigma_threshold: + # Sigma threshold for measurements +
+ +
+
+ +
omega_test: + # Enable omega-test +
+ +
+
+ +
sigma_check: + # Enable sigma check +
+ +
+
+ +
sigma_threshold: + # Sigma threshold +
+ +
+
+ +
state_sigma_threshold: + # Sigma threshold for states +
+ +
+
+
+
+
+
+ +
advanced_postfits: + # Use alternate calculation method to determine postfit residuals +
+ +
+
+ +
estimate_sat_dcb: + # Estimate satellite dcb alongside Ionosphere models, should be false for local STEC +
+ +
+
+ +
function_degree: + # Maximum degree of Spherical harmonics for Ionospheric mapping +
+ +
+
+ +
function_order: + # Maximum order of Spherical harmonics for Ionospheric mapping +
+ +
+
+ +
inverter: + # Inverter to be used within the Kalman filter update stage, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} +
+ +
+
+ +
joseph_stabilisation: +
+ +
+
+ +
layer_heights: + # List of heights of ionosphere layers to estimate +
+ +
+
+ +
model: + # {none, meas_out, bspline, spherical_caps, spherical_harmonics, local} +
+ +
+
+ +
model_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
rts: ⯆ + # RTS allows reverse smoothing of estimates such that early estimates can make use of later data. +
+
+
+ +
interval: + # Number of seconds to use between fixed lag in RTS smoothing. +
+ +
+
+ +
enable: + # Perform backward smoothing of states to improve precision of earlier states +
+ +
+
+ +
lag: + # Number of epochs to use in RTS smoothing. Negative numbers indicate full reverse smoothing. +
+ +
+
+ +
directory: + # Directory for rts intermediate files +
+ +
+
+ +
filename: + # Base filename for rts intermediate files +
+ +
+
+ +
inverter: + # Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} +
+ +
+
+ +
output_intermediates: + # Output best available smoothed states when performing fixed-lag rts (slow, use only when needed) +
+ +
+
+ +
queue_outputs: + # Queue rts outputs so that processing is not limited by IO bandwidth +
+ +
+
+ +
suffix: + # Suffix to be applied to smoothed versions of files +
+ +
+
+
+
+ +
use_rotation_mtx: + # Use 3D rotation matrix for spherical harmonics to maintain orientation toward the sun +
+ +
+
+
+
+ +
orbit_propagation: ⯆ +
+
+
+ +
aod: + # Model Atmospheric and Oceanic non tidal accelerations +
+ +
+
+ +
atm_tide: + # Model accelerations due to atmospheric tides model +
+ +
+
+ +
central_force: + # Acceleration due to the central force +
+ +
+
+ +
egm_degree: + # Degree of spherical harmonics gravity model +
+ +
+
+ +
egm_field: + # Acceleration due to the high degree model of the Earth gravity model (exclude degree 0, made by central_force) +
+ +
+
+ +
general_relativity: + # Model acceleration due general relativisty +
+ +
+
+ +
indirect_j2: + # J2 acceleration perturbation due to the Sun and Moon +
+ +
+
+ +
integrator_time_step: + # Timestep for the integrator, must be smaller than the processing time step, might be adjusted if the processing time step isn't a integer number of time steps +
+ +
+
+ +
ocean_tide: + # Model accelerations due to ocean tides model +
+ +
+
+ +
pole_tide_ocean: + # Model accelerations due to ocean pole tide (degree 2 only) +
+ +
+
+ +
pole_tide_solid: + # Model accelerations due to solid pole tide (degree 2 only) +
+ +
+
+ +
solid_earth_tide: + # Model accelerations due to solid earth tides +
+ +
+
+
+
+ +
predictions: ⯆ +
+
+
+ +
forward_duration: +
+ +
+
+ +
interval: +
+ +
+
+ +
offset: +
+ +
+
+ +
reverse_duration: +
+ +
+
+ +
duration_units: + # {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
interval_units: + # {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+
+
+
+
+ +
receiver_options: ⯆ + # Options to configure individual satellites, systems, or global configs +
+
+
+ +
global: ⯆ +
+
+
+ +
elevation_mask: + # Minimum elevation for satellites to be processed +
+ +
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
kill: + # Remove receiver from future processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
zero_dcb_codes: + # [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
antenna_type: + # Antenna type and radome in 20 character string as per sinex +
+ +
+
+ +
apriori_position: + # Apriori position in XYZ ECEF frame +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
receiver_type: + # Type of gnss receiver hardware +
+ +
+
+ +
sat_id: + # Id for receivers that are also satellites +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
eccentricity: ⯆ +
+
+
+ +
enable: + # Enable antenna eccentrities +
+ +
+
+ +
offset: + # Antenna offset in ENU frame +
+ +
+
+
+
+ +
eop: ⯆ +
+
+
+ +
enable: + # Enable modelling of eops +
+ +
+
+
+
+ +
integer_ambiguity: ⯆ +
+
+
+ +
enable: + # Model ambiguities due to unknown integer number of cycles in phase measurements +
+ +
+
+
+
+ +
ionospheric_components: ⯆ + # Ionospheric models produce frequency-dependent effects +
+
+
+ +
geomagnetic_field_height: + # ionospheric pierce point layer height if not specified in the data or model (km) +
+ +
+
+ +
iono_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
mapping_function: + # Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} +
+ +
+
+ +
mapping_function_layer_height: + # mapping function layer height if not specified in the data or model (km) +
+ +
+
+ +
enable: + # Enable ionospheric modelling +
+ +
+
+ +
use_2nd_order: +
+ +
+
+ +
use_3rd_order: +
+ +
+
+
+
+ +
ionospheric_model: ⯆ + # Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers +
+
+
+ +
enable: + # Compute ionosphere maps from a network of receivers +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
range: ⯆ +
+
+
+ +
enable: + # Enable modelling of signal time of flight time due to range +
+ +
+
+
+
+ +
relativity2: ⯆ +
+
+
+ +
enable: + # Enable modelling of secondary relativistic effects +
+ +
+
+
+
+ +
relativity: ⯆ +
+
+
+ +
enable: + # Enable modelling of relativistic effects +
+ +
+
+
+
+ +
sagnac: ⯆ +
+
+
+ +
enable: + # Enable modelling of sagnac effect +
+ +
+
+
+
+ +
tides: ⯆ +
+
+
+ +
atl: + # Enable atmospheric tide loading +
+ +
+
+ +
enable: + # Enable modelling of tidal displacements +
+ +
+
+ +
opole: + # Enable ocean pole tides +
+ +
+
+ +
otl: + # Enable ocean tide loading +
+ +
+
+ +
solid: + # Enable solid Earth tides +
+ +
+
+ +
spole: + # Enable solid Earth pole tides +
+ +
+
+
+
+ +
troposphere: ⯆ + # Tropospheric modelling accounts for delays due to refraction of light in water vapour +
+
+
+ +
enable: + # Model tropospheric delays +
+ +
+
+ +
models: + # List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] +
+ +
+
+
+
+ +
tropospheric_map: ⯆ +
+
+
+ +
enable: + # Compute tropospheric maps from a network of receivers +
+ +
+
+
+
+
+
+ +
aliases: + # Aliases for this receiver +
+ +
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
rec_reference_system: + # Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} +
+ +
+
+ +
rinex2: ⯆ +
+
+
+ +
rnx_code_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+ +
rnx_phase_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+
+
+ +
gps: ⯆ +
+
+
+ +
elevation_mask: + # Minimum elevation for satellites to be processed +
+ +
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
kill: + # Remove receiver from future processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
zero_dcb_codes: + # [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
antenna_type: + # Antenna type and radome in 20 character string as per sinex +
+ +
+
+ +
apriori_position: + # Apriori position in XYZ ECEF frame +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
receiver_type: + # Type of gnss receiver hardware +
+ +
+
+ +
sat_id: + # Id for receivers that are also satellites +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
eccentricity: ⯆ +
+
+
+ +
enable: + # Enable antenna eccentrities +
+ +
+
+ +
offset: + # Antenna offset in ENU frame +
+ +
+
+
+
+ +
eop: ⯆ +
+
+
+ +
enable: + # Enable modelling of eops +
+ +
+
+
+
+ +
integer_ambiguity: ⯆ +
+
+
+ +
enable: + # Model ambiguities due to unknown integer number of cycles in phase measurements +
+ +
+
+
+
+ +
ionospheric_components: ⯆ + # Ionospheric models produce frequency-dependent effects +
+
+
+ +
geomagnetic_field_height: + # ionospheric pierce point layer height if not specified in the data or model (km) +
+ +
+
+ +
iono_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
mapping_function: + # Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} +
+ +
+
+ +
mapping_function_layer_height: + # mapping function layer height if not specified in the data or model (km) +
+ +
+
+ +
enable: + # Enable ionospheric modelling +
+ +
+
+ +
use_2nd_order: +
+ +
+
+ +
use_3rd_order: +
+ +
+
+
+
+ +
ionospheric_model: ⯆ + # Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers +
+
+
+ +
enable: + # Compute ionosphere maps from a network of receivers +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
range: ⯆ +
+
+
+ +
enable: + # Enable modelling of signal time of flight time due to range +
+ +
+
+
+
+ +
relativity2: ⯆ +
+
+
+ +
enable: + # Enable modelling of secondary relativistic effects +
+ +
+
+
+
+ +
relativity: ⯆ +
+
+
+ +
enable: + # Enable modelling of relativistic effects +
+ +
+
+
+
+ +
sagnac: ⯆ +
+
+
+ +
enable: + # Enable modelling of sagnac effect +
+ +
+
+
+
+ +
tides: ⯆ +
+
+
+ +
atl: + # Enable atmospheric tide loading +
+ +
+
+ +
enable: + # Enable modelling of tidal displacements +
+ +
+
+ +
opole: + # Enable ocean pole tides +
+ +
+
+ +
otl: + # Enable ocean tide loading +
+ +
+
+ +
solid: + # Enable solid Earth tides +
+ +
+
+ +
spole: + # Enable solid Earth pole tides +
+ +
+
+
+
+ +
troposphere: ⯆ + # Tropospheric modelling accounts for delays due to refraction of light in water vapour +
+
+
+ +
enable: + # Model tropospheric delays +
+ +
+
+ +
models: + # List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] +
+ +
+
+
+
+ +
tropospheric_map: ⯆ +
+
+
+ +
enable: + # Compute tropospheric maps from a network of receivers +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
l1w: ⯆ +
+
+
+ +
elevation_mask: + # Minimum elevation for satellites to be processed +
+ +
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
kill: + # Remove receiver from future processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
zero_dcb_codes: + # [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
antenna_type: + # Antenna type and radome in 20 character string as per sinex +
+ +
+
+ +
apriori_position: + # Apriori position in XYZ ECEF frame +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
receiver_type: + # Type of gnss receiver hardware +
+ +
+
+ +
sat_id: + # Id for receivers that are also satellites +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
eccentricity: ⯆ +
+
+
+ +
enable: + # Enable antenna eccentrities +
+ +
+
+ +
offset: + # Antenna offset in ENU frame +
+ +
+
+
+
+ +
eop: ⯆ +
+
+
+ +
enable: + # Enable modelling of eops +
+ +
+
+
+
+ +
integer_ambiguity: ⯆ +
+
+
+ +
enable: + # Model ambiguities due to unknown integer number of cycles in phase measurements +
+ +
+
+
+
+ +
ionospheric_components: ⯆ + # Ionospheric models produce frequency-dependent effects +
+
+
+ +
geomagnetic_field_height: + # ionospheric pierce point layer height if not specified in the data or model (km) +
+ +
+
+ +
iono_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
mapping_function: + # Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} +
+ +
+
+ +
mapping_function_layer_height: + # mapping function layer height if not specified in the data or model (km) +
+ +
+
+ +
enable: + # Enable ionospheric modelling +
+ +
+
+ +
use_2nd_order: +
+ +
+
+ +
use_3rd_order: +
+ +
+
+
+
+ +
ionospheric_model: ⯆ + # Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers +
+
+
+ +
enable: + # Compute ionosphere maps from a network of receivers +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
range: ⯆ +
+
+
+ +
enable: + # Enable modelling of signal time of flight time due to range +
+ +
+
+
+
+ +
relativity2: ⯆ +
+
+
+ +
enable: + # Enable modelling of secondary relativistic effects +
+ +
+
+
+
+ +
relativity: ⯆ +
+
+
+ +
enable: + # Enable modelling of relativistic effects +
+ +
+
+
+
+ +
sagnac: ⯆ +
+
+
+ +
enable: + # Enable modelling of sagnac effect +
+ +
+
+
+
+ +
tides: ⯆ +
+
+
+ +
atl: + # Enable atmospheric tide loading +
+ +
+
+ +
enable: + # Enable modelling of tidal displacements +
+ +
+
+ +
opole: + # Enable ocean pole tides +
+ +
+
+ +
otl: + # Enable ocean tide loading +
+ +
+
+ +
solid: + # Enable solid Earth tides +
+ +
+
+ +
spole: + # Enable solid Earth pole tides +
+ +
+
+
+
+ +
troposphere: ⯆ + # Tropospheric modelling accounts for delays due to refraction of light in water vapour +
+
+
+ +
enable: + # Model tropospheric delays +
+ +
+
+ +
models: + # List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] +
+ +
+
+
+
+ +
tropospheric_map: ⯆ +
+
+
+ +
enable: + # Compute tropospheric maps from a network of receivers +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
rec_reference_system: + # Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} +
+ +
+
+ +
rinex2: ⯆ +
+
+
+ +
rnx_code_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+ +
rnx_phase_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+
+
+
+
+ +
rec_reference_system: + # Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} +
+ +
+
+ +
rinex2: ⯆ +
+
+
+ +
rnx_code_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+ +
rnx_phase_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+
+
+
+
+
+
+ +
xmpl: ⯆ +
+
+
+ +
elevation_mask: + # Minimum elevation for satellites to be processed +
+ +
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
kill: + # Remove receiver from future processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
zero_dcb_codes: + # [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
antenna_type: + # Antenna type and radome in 20 character string as per sinex +
+ +
+
+ +
apriori_position: + # Apriori position in XYZ ECEF frame +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
receiver_type: + # Type of gnss receiver hardware +
+ +
+
+ +
sat_id: + # Id for receivers that are also satellites +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
eccentricity: ⯆ +
+
+
+ +
enable: + # Enable antenna eccentrities +
+ +
+
+ +
offset: + # Antenna offset in ENU frame +
+ +
+
+
+
+ +
eop: ⯆ +
+
+
+ +
enable: + # Enable modelling of eops +
+ +
+
+
+
+ +
integer_ambiguity: ⯆ +
+
+
+ +
enable: + # Model ambiguities due to unknown integer number of cycles in phase measurements +
+ +
+
+
+
+ +
ionospheric_components: ⯆ + # Ionospheric models produce frequency-dependent effects +
+
+
+ +
geomagnetic_field_height: + # ionospheric pierce point layer height if not specified in the data or model (km) +
+ +
+
+ +
iono_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
mapping_function: + # Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} +
+ +
+
+ +
mapping_function_layer_height: + # mapping function layer height if not specified in the data or model (km) +
+ +
+
+ +
enable: + # Enable ionospheric modelling +
+ +
+
+ +
use_2nd_order: +
+ +
+
+ +
use_3rd_order: +
+ +
+
+
+
+ +
ionospheric_model: ⯆ + # Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers +
+
+
+ +
enable: + # Compute ionosphere maps from a network of receivers +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
range: ⯆ +
+
+
+ +
enable: + # Enable modelling of signal time of flight time due to range +
+ +
+
+
+
+ +
relativity2: ⯆ +
+
+
+ +
enable: + # Enable modelling of secondary relativistic effects +
+ +
+
+
+
+ +
relativity: ⯆ +
+
+
+ +
enable: + # Enable modelling of relativistic effects +
+ +
+
+
+
+ +
sagnac: ⯆ +
+
+
+ +
enable: + # Enable modelling of sagnac effect +
+ +
+
+
+
+ +
tides: ⯆ +
+
+
+ +
atl: + # Enable atmospheric tide loading +
+ +
+
+ +
enable: + # Enable modelling of tidal displacements +
+ +
+
+ +
opole: + # Enable ocean pole tides +
+ +
+
+ +
otl: + # Enable ocean tide loading +
+ +
+
+ +
solid: + # Enable solid Earth tides +
+ +
+
+ +
spole: + # Enable solid Earth pole tides +
+ +
+
+
+
+ +
troposphere: ⯆ + # Tropospheric modelling accounts for delays due to refraction of light in water vapour +
+
+
+ +
enable: + # Model tropospheric delays +
+ +
+
+ +
models: + # List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] +
+ +
+
+
+
+ +
tropospheric_map: ⯆ +
+
+
+ +
enable: + # Compute tropospheric maps from a network of receivers +
+ +
+
+
+
+
+
+ +
aliases: + # Aliases for this receiver +
+ +
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
rec_reference_system: + # Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} +
+ +
+
+ +
rinex2: ⯆ +
+
+
+ +
rnx_code_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+ +
rnx_phase_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+
+
+ +
gps: ⯆ +
+
+
+ +
elevation_mask: + # Minimum elevation for satellites to be processed +
+ +
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
kill: + # Remove receiver from future processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
zero_dcb_codes: + # [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
antenna_type: + # Antenna type and radome in 20 character string as per sinex +
+ +
+
+ +
apriori_position: + # Apriori position in XYZ ECEF frame +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
receiver_type: + # Type of gnss receiver hardware +
+ +
+
+ +
sat_id: + # Id for receivers that are also satellites +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
eccentricity: ⯆ +
+
+
+ +
enable: + # Enable antenna eccentrities +
+ +
+
+ +
offset: + # Antenna offset in ENU frame +
+ +
+
+
+
+ +
eop: ⯆ +
+
+
+ +
enable: + # Enable modelling of eops +
+ +
+
+
+
+ +
integer_ambiguity: ⯆ +
+
+
+ +
enable: + # Model ambiguities due to unknown integer number of cycles in phase measurements +
+ +
+
+
+
+ +
ionospheric_components: ⯆ + # Ionospheric models produce frequency-dependent effects +
+
+
+ +
geomagnetic_field_height: + # ionospheric pierce point layer height if not specified in the data or model (km) +
+ +
+
+ +
iono_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
mapping_function: + # Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} +
+ +
+
+ +
mapping_function_layer_height: + # mapping function layer height if not specified in the data or model (km) +
+ +
+
+ +
enable: + # Enable ionospheric modelling +
+ +
+
+ +
use_2nd_order: +
+ +
+
+ +
use_3rd_order: +
+ +
+
+
+
+ +
ionospheric_model: ⯆ + # Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers +
+
+
+ +
enable: + # Compute ionosphere maps from a network of receivers +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
range: ⯆ +
+
+
+ +
enable: + # Enable modelling of signal time of flight time due to range +
+ +
+
+
+
+ +
relativity2: ⯆ +
+
+
+ +
enable: + # Enable modelling of secondary relativistic effects +
+ +
+
+
+
+ +
relativity: ⯆ +
+
+
+ +
enable: + # Enable modelling of relativistic effects +
+ +
+
+
+
+ +
sagnac: ⯆ +
+
+
+ +
enable: + # Enable modelling of sagnac effect +
+ +
+
+
+
+ +
tides: ⯆ +
+
+
+ +
atl: + # Enable atmospheric tide loading +
+ +
+
+ +
enable: + # Enable modelling of tidal displacements +
+ +
+
+ +
opole: + # Enable ocean pole tides +
+ +
+
+ +
otl: + # Enable ocean tide loading +
+ +
+
+ +
solid: + # Enable solid Earth tides +
+ +
+
+ +
spole: + # Enable solid Earth pole tides +
+ +
+
+
+
+ +
troposphere: ⯆ + # Tropospheric modelling accounts for delays due to refraction of light in water vapour +
+
+
+ +
enable: + # Model tropospheric delays +
+ +
+
+ +
models: + # List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] +
+ +
+
+
+
+ +
tropospheric_map: ⯆ +
+
+
+ +
enable: + # Compute tropospheric maps from a network of receivers +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
l1w: ⯆ +
+
+
+ +
elevation_mask: + # Minimum elevation for satellites to be processed +
+ +
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
kill: + # Remove receiver from future processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
zero_dcb_codes: + # [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
antenna_type: + # Antenna type and radome in 20 character string as per sinex +
+ +
+
+ +
apriori_position: + # Apriori position in XYZ ECEF frame +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
receiver_type: + # Type of gnss receiver hardware +
+ +
+
+ +
sat_id: + # Id for receivers that are also satellites +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
eccentricity: ⯆ +
+
+
+ +
enable: + # Enable antenna eccentrities +
+ +
+
+ +
offset: + # Antenna offset in ENU frame +
+ +
+
+
+
+ +
eop: ⯆ +
+
+
+ +
enable: + # Enable modelling of eops +
+ +
+
+
+
+ +
integer_ambiguity: ⯆ +
+
+
+ +
enable: + # Model ambiguities due to unknown integer number of cycles in phase measurements +
+ +
+
+
+
+ +
ionospheric_components: ⯆ + # Ionospheric models produce frequency-dependent effects +
+
+
+ +
geomagnetic_field_height: + # ionospheric pierce point layer height if not specified in the data or model (km) +
+ +
+
+ +
iono_sigma_limit: + # Ionosphere states are removed when their sigma exceeds this value +
+ +
+
+ +
mapping_function: + # Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} +
+ +
+
+ +
mapping_function_layer_height: + # mapping function layer height if not specified in the data or model (km) +
+ +
+
+ +
enable: + # Enable ionospheric modelling +
+ +
+
+ +
use_2nd_order: +
+ +
+
+ +
use_3rd_order: +
+ +
+
+
+
+ +
ionospheric_model: ⯆ + # Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers +
+
+
+ +
enable: + # Compute ionosphere maps from a network of receivers +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
range: ⯆ +
+
+
+ +
enable: + # Enable modelling of signal time of flight time due to range +
+ +
+
+
+
+ +
relativity2: ⯆ +
+
+
+ +
enable: + # Enable modelling of secondary relativistic effects +
+ +
+
+
+
+ +
relativity: ⯆ +
+
+
+ +
enable: + # Enable modelling of relativistic effects +
+ +
+
+
+
+ +
sagnac: ⯆ +
+
+
+ +
enable: + # Enable modelling of sagnac effect +
+ +
+
+
+
+ +
tides: ⯆ +
+
+
+ +
atl: + # Enable atmospheric tide loading +
+ +
+
+ +
enable: + # Enable modelling of tidal displacements +
+ +
+
+ +
opole: + # Enable ocean pole tides +
+ +
+
+ +
otl: + # Enable ocean tide loading +
+ +
+
+ +
solid: + # Enable solid Earth tides +
+ +
+
+ +
spole: + # Enable solid Earth pole tides +
+ +
+
+
+
+ +
troposphere: ⯆ + # Tropospheric modelling accounts for delays due to refraction of light in water vapour +
+
+
+ +
enable: + # Model tropospheric delays +
+ +
+
+ +
models: + # List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] +
+ +
+
+
+
+ +
tropospheric_map: ⯆ +
+
+
+ +
enable: + # Compute tropospheric maps from a network of receivers +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
rec_reference_system: + # Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} +
+ +
+
+ +
rinex2: ⯆ +
+
+
+ +
rnx_code_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+ +
rnx_phase_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+
+
+
+
+ +
rec_reference_system: + # Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} +
+ +
+
+ +
rinex2: ⯆ +
+
+
+ +
rnx_code_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+ +
rnx_phase_conversions: ⯆ +
+
+
+ +
c1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
c8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l3: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l4: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l5: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l6: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l7: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
l8: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
la: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
none: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p1: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+ +
p2: + # {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} +
+ +
+
+
+
+
+
+
+
+
+
+
+
+ +
satellite_options: ⯆ +
+
+
+ +
global: ⯆ +
+
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
surface_details: + # List of details for srp and drag surfaces +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
l1w: ⯆ +
+
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
surface_details: + # List of details for srp and drag surfaces +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
orbit_propagation: ⯆ + # Enable specific orbit propagation models +
+
+
+ +
area: + # Satellite area for use in solar radiation and albedo calculations +
+ +
+
+ +
mass: + # Satellite mass for use if not specified in the SINEX metadata file +
+ +
+
+ +
power: + # Transmission power use if not specified in the SINEX metadata file +
+ +
+
+ +
srp_cr: + # Coefficient of reflection of the satellite +
+ +
+
+ +
albedo: + # Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} +
+ +
+
+ +
antenna_thrust: + # Model accelerations due to the emitted signal from the antenna +
+ +
+
+ +
empirical: + # Model accelerations due to empirical accelerations +
+ +
+
+ +
empirical_dyb_eclipse: + # Turn on/off the eclipse on each axis (D, Y, B) +
+ +
+
+ +
empirical_rtn_eclipse: + # Turn on/off the eclipse on each axis (R, T, N) +
+ +
+
+ +
planetary_perturbations: + # Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] +
+ +
+
+ +
pseudo_pulses: ⯆ + # Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
interval: + # Interval between applying pseudo pulses +
+ +
+
+ +
pos_process_noise: + # Sigma to add to orbital position states +
+ +
+
+ +
vel_process_noise: + # Sigma to add to orbital velocity states +
+ +
+
+
+
+ +
solar_radiation_pressure: + # Model accelerations due to solar radiation pressure {none, cannonball, boxwing} +
+ +
+
+
+
+
+
+ +
orbit_propagation: ⯆ + # Enable specific orbit propagation models +
+
+
+ +
area: + # Satellite area for use in solar radiation and albedo calculations +
+ +
+
+ +
mass: + # Satellite mass for use if not specified in the SINEX metadata file +
+ +
+
+ +
power: + # Transmission power use if not specified in the SINEX metadata file +
+ +
+
+ +
srp_cr: + # Coefficient of reflection of the satellite +
+ +
+
+ +
albedo: + # Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} +
+ +
+
+ +
antenna_thrust: + # Model accelerations due to the emitted signal from the antenna +
+ +
+
+ +
empirical: + # Model accelerations due to empirical accelerations +
+ +
+
+ +
empirical_dyb_eclipse: + # Turn on/off the eclipse on each axis (D, Y, B) +
+ +
+
+ +
empirical_rtn_eclipse: + # Turn on/off the eclipse on each axis (R, T, N) +
+ +
+
+ +
planetary_perturbations: + # Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] +
+ +
+
+ +
pseudo_pulses: ⯆ + # Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
interval: + # Interval between applying pseudo pulses +
+ +
+
+ +
pos_process_noise: + # Sigma to add to orbital position states +
+ +
+
+ +
vel_process_noise: + # Sigma to add to orbital velocity states +
+ +
+
+
+
+ +
solar_radiation_pressure: + # Model accelerations due to solar radiation pressure {none, cannonball, boxwing} +
+ +
+
+
+
+
+
+ +
g--: ⯆ +
+
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
surface_details: + # List of details for srp and drag surfaces +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+
+
+ +
aliases: + # Aliases for this satellite +
+ +
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
l1w: ⯆ +
+
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
surface_details: + # List of details for srp and drag surfaces +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
orbit_propagation: ⯆ + # Enable specific orbit propagation models +
+
+
+ +
area: + # Satellite area for use in solar radiation and albedo calculations +
+ +
+
+ +
mass: + # Satellite mass for use if not specified in the SINEX metadata file +
+ +
+
+ +
power: + # Transmission power use if not specified in the SINEX metadata file +
+ +
+
+ +
srp_cr: + # Coefficient of reflection of the satellite +
+ +
+
+ +
albedo: + # Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} +
+ +
+
+ +
antenna_thrust: + # Model accelerations due to the emitted signal from the antenna +
+ +
+
+ +
empirical: + # Model accelerations due to empirical accelerations +
+ +
+
+ +
empirical_dyb_eclipse: + # Turn on/off the eclipse on each axis (D, Y, B) +
+ +
+
+ +
empirical_rtn_eclipse: + # Turn on/off the eclipse on each axis (R, T, N) +
+ +
+
+ +
planetary_perturbations: + # Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] +
+ +
+
+ +
pseudo_pulses: ⯆ + # Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
interval: + # Interval between applying pseudo pulses +
+ +
+
+ +
pos_process_noise: + # Sigma to add to orbital position states +
+ +
+
+ +
vel_process_noise: + # Sigma to add to orbital velocity states +
+ +
+
+
+
+ +
solar_radiation_pressure: + # Model accelerations due to solar radiation pressure {none, cannonball, boxwing} +
+ +
+
+
+
+
+
+ +
orbit_propagation: ⯆ + # Enable specific orbit propagation models +
+
+
+ +
area: + # Satellite area for use in solar radiation and albedo calculations +
+ +
+
+ +
mass: + # Satellite mass for use if not specified in the SINEX metadata file +
+ +
+
+ +
power: + # Transmission power use if not specified in the SINEX metadata file +
+ +
+
+ +
srp_cr: + # Coefficient of reflection of the satellite +
+ +
+
+ +
albedo: + # Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} +
+ +
+
+ +
antenna_thrust: + # Model accelerations due to the emitted signal from the antenna +
+ +
+
+ +
empirical: + # Model accelerations due to empirical accelerations +
+ +
+
+ +
empirical_dyb_eclipse: + # Turn on/off the eclipse on each axis (D, Y, B) +
+ +
+
+ +
empirical_rtn_eclipse: + # Turn on/off the eclipse on each axis (R, T, N) +
+ +
+
+ +
planetary_perturbations: + # Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] +
+ +
+
+ +
pseudo_pulses: ⯆ + # Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
interval: + # Interval between applying pseudo pulses +
+ +
+
+ +
pos_process_noise: + # Sigma to add to orbital position states +
+ +
+
+ +
vel_process_noise: + # Sigma to add to orbital velocity states +
+ +
+
+
+
+ +
solar_radiation_pressure: + # Model accelerations due to solar radiation pressure {none, cannonball, boxwing} +
+ +
+
+
+
+
+
+ +
gps: ⯆ +
+
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
surface_details: + # List of details for srp and drag surfaces +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
l1w: ⯆ +
+
+
+ +
exclude: + # Exclude receiver from processing +
+ +
+
+ +
laser_sigma: + # Standard deviation of SLR laser measurements +
+ +
+
+ +
pseudo_sigma: + # Standard deviation of pseudo measurmeents +
+ +
+
+ +
error_model: + # {uniform, elevation_dependent} +
+ +
+
+ +
code_sigma: + # Standard deviation of code measurements +
+ +
+
+ +
phase_sigma: + # Standard deviation of phase measurmeents +
+ +
+
+ +
clock_codes: + # Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] +
+ +
+
+ +
apriori_sigma_enu: + # Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) +
+ +
+
+ +
mincon_scale_apriori_sigma: + # Scale applied to apriori sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
mincon_scale_filter_sigma: + # Scale applied to filter sigmas while weighting in mincon transformation estimation +
+ +
+
+ +
surface_details: + # List of details for srp and drag surfaces +
+ +
+
+ +
models: ⯆ + # Enable specific models +
+
+
+ +
attitude: ⯆ +
+
+
+ +
enable: + # Enables non-nominal attitude types +
+ +
+
+ +
model_dt: + # Timestep used in modelling attitude +
+ +
+
+ +
sources: + # List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
clock: ⯆ +
+
+
+ +
enable: + # Enable modelling of clocks +
+ +
+
+ +
sources: + # List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+ +
code_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no code bias is found +
+ +
+
+ +
enable: + # Enable modelling of code biases +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default code biases +
+ +
+
+
+
+ +
pco: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center offsets +
+ +
+
+
+
+ +
pcv: ⯆ +
+
+
+ +
enable: + # Enable modelling of phase center variations +
+ +
+
+
+
+ +
phase_bias: ⯆ +
+
+
+ +
default_bias: + # Bias to use when no phase bias is found +
+ +
+
+ +
enable: + # Enable modelling of phase biases. Required for AR +
+ +
+
+ +
undefined_sigma: + # Uncertainty sigma to apply to default phase biases +
+ +
+
+
+
+ +
phase_windup: ⯆ +
+
+
+ +
enable: + # Model phase windup due to relative rotation of circularly polarised antennas +
+ +
+
+
+
+ +
pos: ⯆ +
+
+
+ +
enable: + # Enable modelling of position +
+ +
+
+ +
sources: + # Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] +
+ +
+
+
+
+
+
+ +
antenna_azimuth: + # Antenna azimuth (North) in satellite body-fixed frame +
+ +
+
+ +
antenna_boresight: + # Antenna boresight (Up) in satellite body-fixed frame +
+ +
+
+ +
ellipse_propagation_time_tolerance: + # Time gap tolerance under which the ellipse propagator can be used for orbit prediction +
+ +
+
+ +
orbit_propagation: ⯆ + # Enable specific orbit propagation models +
+
+
+ +
area: + # Satellite area for use in solar radiation and albedo calculations +
+ +
+
+ +
mass: + # Satellite mass for use if not specified in the SINEX metadata file +
+ +
+
+ +
power: + # Transmission power use if not specified in the SINEX metadata file +
+ +
+
+ +
srp_cr: + # Coefficient of reflection of the satellite +
+ +
+
+ +
albedo: + # Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} +
+ +
+
+ +
antenna_thrust: + # Model accelerations due to the emitted signal from the antenna +
+ +
+
+ +
empirical: + # Model accelerations due to empirical accelerations +
+ +
+
+ +
empirical_dyb_eclipse: + # Turn on/off the eclipse on each axis (D, Y, B) +
+ +
+
+ +
empirical_rtn_eclipse: + # Turn on/off the eclipse on each axis (R, T, N) +
+ +
+
+ +
planetary_perturbations: + # Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] +
+ +
+
+ +
pseudo_pulses: ⯆ + # Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
interval: + # Interval between applying pseudo pulses +
+ +
+
+ +
pos_process_noise: + # Sigma to add to orbital position states +
+ +
+
+ +
vel_process_noise: + # Sigma to add to orbital velocity states +
+ +
+
+
+
+ +
solar_radiation_pressure: + # Model accelerations due to solar radiation pressure {none, cannonball, boxwing} +
+ +
+
+
+
+
+
+ +
orbit_propagation: ⯆ + # Enable specific orbit propagation models +
+
+
+ +
area: + # Satellite area for use in solar radiation and albedo calculations +
+ +
+
+ +
mass: + # Satellite mass for use if not specified in the SINEX metadata file +
+ +
+
+ +
power: + # Transmission power use if not specified in the SINEX metadata file +
+ +
+
+ +
srp_cr: + # Coefficient of reflection of the satellite +
+ +
+
+ +
albedo: + # Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} +
+ +
+
+ +
antenna_thrust: + # Model accelerations due to the emitted signal from the antenna +
+ +
+
+ +
empirical: + # Model accelerations due to empirical accelerations +
+ +
+
+ +
empirical_dyb_eclipse: + # Turn on/off the eclipse on each axis (D, Y, B) +
+ +
+
+ +
empirical_rtn_eclipse: + # Turn on/off the eclipse on each axis (R, T, N) +
+ +
+
+ +
planetary_perturbations: + # Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] +
+ +
+
+ +
pseudo_pulses: ⯆ + # Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions +
+
+
+ +
enable: + # Enable applying process noise impulses to orbits upon state errors +
+ +
+
+ +
interval: + # Interval between applying pseudo pulses +
+ +
+
+ +
pos_process_noise: + # Sigma to add to orbital position states +
+ +
+
+ +
vel_process_noise: + # Sigma to add to orbital velocity states +
+ +
+
+
+
+ +
solar_radiation_pressure: + # Model accelerations due to solar radiation pressure {none, cannonball, boxwing} +
+ +
+
+
+
+
+
+
+
+ +
estimation_parameters: ⯆ +
+
+
+ +
receivers: ⯆ +
+
+
+ +
global: ⯆ +
+
+
+ +
ambiguities: ⯆ + # Integer phase ambiguities +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_stec: ⯆ + # Ionospheric slant delay +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop: ⯆ + # Troposphere corrections +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_grads: ⯆ + # Troposphere gradients +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_maps: ⯆ + # Troposphere ZWD mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pcv: ⯆ + # Antenna phase center variations (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_model: ⯆ + # Ionospheric mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
strain_rate: ⯆ + # Velocity (large gain, for geodetic timescales) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_range_bias: ⯆ + # Satellite Laser Ranging range bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_time_bias: ⯆ + # Satellite Laser Ranging time bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gps: ⯆ +
+
+
+ +
ambiguities: ⯆ + # Integer phase ambiguities +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_stec: ⯆ + # Ionospheric slant delay +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop: ⯆ + # Troposphere corrections +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_grads: ⯆ + # Troposphere gradients +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_maps: ⯆ + # Troposphere ZWD mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pcv: ⯆ + # Antenna phase center variations (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_model: ⯆ + # Ionospheric mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
strain_rate: ⯆ + # Velocity (large gain, for geodetic timescales) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_range_bias: ⯆ + # Satellite Laser Ranging range bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_time_bias: ⯆ + # Satellite Laser Ranging time bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
l1w: ⯆ +
+
+
+ +
ambiguities: ⯆ + # Integer phase ambiguities +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_stec: ⯆ + # Ionospheric slant delay +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop: ⯆ + # Troposphere corrections +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_grads: ⯆ + # Troposphere gradients +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_maps: ⯆ + # Troposphere ZWD mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pcv: ⯆ + # Antenna phase center variations (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_model: ⯆ + # Ionospheric mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
strain_rate: ⯆ + # Velocity (large gain, for geodetic timescales) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_range_bias: ⯆ + # Satellite Laser Ranging range bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_time_bias: ⯆ + # Satellite Laser Ranging time bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+
+
+
+
+
+
+ +
xmpl: ⯆ +
+
+
+ +
ambiguities: ⯆ + # Integer phase ambiguities +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_stec: ⯆ + # Ionospheric slant delay +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop: ⯆ + # Troposphere corrections +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_grads: ⯆ + # Troposphere gradients +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_maps: ⯆ + # Troposphere ZWD mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pcv: ⯆ + # Antenna phase center variations (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_model: ⯆ + # Ionospheric mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
strain_rate: ⯆ + # Velocity (large gain, for geodetic timescales) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_range_bias: ⯆ + # Satellite Laser Ranging range bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_time_bias: ⯆ + # Satellite Laser Ranging time bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gps: ⯆ +
+
+
+ +
ambiguities: ⯆ + # Integer phase ambiguities +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_stec: ⯆ + # Ionospheric slant delay +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop: ⯆ + # Troposphere corrections +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_grads: ⯆ + # Troposphere gradients +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_maps: ⯆ + # Troposphere ZWD mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pcv: ⯆ + # Antenna phase center variations (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_model: ⯆ + # Ionospheric mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
strain_rate: ⯆ + # Velocity (large gain, for geodetic timescales) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_range_bias: ⯆ + # Satellite Laser Ranging range bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_time_bias: ⯆ + # Satellite Laser Ranging time bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
l1w: ⯆ +
+
+
+ +
ambiguities: ⯆ + # Integer phase ambiguities +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_stec: ⯆ + # Ionospheric slant delay +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop: ⯆ + # Troposphere corrections +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_grads: ⯆ + # Troposphere gradients +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
trop_maps: ⯆ + # Troposphere ZWD mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pcv: ⯆ + # Antenna phase center variations (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion_model: ⯆ + # Ionospheric mapping +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
strain_rate: ⯆ + # Velocity (large gain, for geodetic timescales) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_range_bias: ⯆ + # Satellite Laser Ranging range bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
slr_time_bias: ⯆ + # Satellite Laser Ranging time bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+
+
+
+
+
+
+
+
+ +
satellites: ⯆ +
+
+
+ +
global: ⯆ +
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
l1w: ⯆ +
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+
+
+
+
+ +
g--: ⯆ +
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
l1w: ⯆ +
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+
+
+
+
+ +
gps: ⯆ +
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
l1w: ⯆ +
+
+
+ +
clock: ⯆ + # Clocks +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos: ⯆ + # Position +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pos_rate: ⯆ + # Velocity +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
clock_rate: ⯆ + # Clock rates +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orbit: ⯆ + # Orbital state +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
pco: ⯆ + # Phase Center Offsets (experimental) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ant_delta: ⯆ + # Antenna delta (body frame) +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
code_bias: ⯆ + # Code bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
phase_bias: ⯆ + # Phase bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_0: ⯆ + # Empirical accleration B bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_1: ⯆ + # Empirical accleration B 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_2: ⯆ + # Empirical accleration B 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_3: ⯆ + # Empirical accleration B 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_b_4: ⯆ + # Empirical accleration B 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_0: ⯆ + # Empirical accleration direct bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_1: ⯆ + # Empirical accleration direct 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_2: ⯆ + # Empirical accleration direct 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_3: ⯆ + # Empirical accleration direct 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_d_4: ⯆ + # Empirical accleration direct 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_0: ⯆ + # Empirical accleration normal bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_1: ⯆ + # Empirical accleration normal 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_2: ⯆ + # Empirical accleration normal 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_3: ⯆ + # Empirical accleration normal 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_n_4: ⯆ + # Empirical accleration normal 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_0: ⯆ + # Empirical accleration P bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_1: ⯆ + # Empirical accleration P 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_2: ⯆ + # Empirical accleration P 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_3: ⯆ + # Empirical accleration P 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_p_4: ⯆ + # Empirical accleration P 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_0: ⯆ + # Empirical accleration Q bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_1: ⯆ + # Empirical accleration Q 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_2: ⯆ + # Empirical accleration Q 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_3: ⯆ + # Empirical accleration Q 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_q_4: ⯆ + # Empirical accleration Q 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_0: ⯆ + # Empirical accleration radial bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_1: ⯆ + # Empirical accleration radial 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_2: ⯆ + # Empirical accleration radial 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_3: ⯆ + # Empirical accleration radial 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_r_4: ⯆ + # Empirical accleration radial 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_0: ⯆ + # Empirical accleration tangential bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_1: ⯆ + # Empirical accleration tangential 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_2: ⯆ + # Empirical accleration tangential 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_3: ⯆ + # Empirical accleration tangential 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_t_4: ⯆ + # Empirical accleration tangential 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_0: ⯆ + # Empirical accleration Y bias +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_1: ⯆ + # Empirical accleration Y 1 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_2: ⯆ + # Empirical accleration Y 2 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_3: ⯆ + # Empirical accleration Y 3 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
emp_y_4: ⯆ + # Empirical accleration Y 4 per rev +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
accelerometer_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_bias: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
gyro_scale: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
imu_offset: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
orientation: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+
+
+
+
+
+
+ +
global_models: ⯆ +
+
+
+ +
eop: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
eop_rates: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+ +
ion: ⯆ +
+
+
+ +
estimated: + # Estimate state in kalman filter +
+ +
+
+ +
sigma: + # Apriori sigma values - if zero, will be initialised using least squares +
+ +
+
+ +
process_noise: + # Process noise sigmas +
+ +
+
+ +
process_noise_dt: + # Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} +
+ +
+
+ +
apriori_value: + # Apriori state values +
+ +
+
+ +
use_remote_sigma: + # Use remote filter sigma for initial sigma +
+ +
+
+ +
comment: + # Comment to apply to the state +
+ +
+
+ +
mu: + # Desired mean value for gauss markov states +
+ +
+
+ +
tau: + # Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) +
+ +
+
+
+
+
+
+
+
+ +
mongo: ⯆ + # Mongo is a database used to store results and intermediate values for later analysis and inter-process communication +
+
+
+ +
enable: + # Enable and connect to mongo database {none, primary, secondary, both} +
+ +
+
+ +
delete_history: + # Drop the collection in the database at the beginning of the run to only show fresh data {none, primary, secondary, both} +
+ +
+
+ +
output_components: + # Output components of measurements {none, primary, secondary, both} +
+ +
+
+ +
output_cumulative: + # Output cumulative residuals of components of measurements {none, primary, secondary, both} +
+ +
+
+ +
output_measurements: + # Output measurements and their residuals {none, primary, secondary, both} +
+ +
+
+ +
output_state_covars: + # Output covariance values of related states {none, primary, secondary, both} +
+ +
+
+ +
output_states: + # Output states {none, primary, secondary, both} +
+ +
+
+ +
cull_history: + # Erase old database objects to limit the size and speed degredation over long runs {none, primary, secondary, both} +
+ +
+
+ +
min_cull_age: + # Age of which to cull history +
+ +
+
+ +
output_config: + # Output config {none, primary, secondary, both} +
+ +
+
+ +
output_logs: + # Output console trace and warnings to mongo with timestamps and other metadata {none, primary, secondary, both} +
+ +
+
+ +
output_predictions: + # {none, primary, secondary, both} +
+ +
+
+ +
output_ssr_precursors: + # Output orbits, clocks, and bias estimates to allow communication to ssr generating processes {none, primary, secondary, both} +
+ +
+
+ +
output_test_stats: + # Output test statistics {none, primary, secondary, both} +
+ +
+
+ +
output_trace: + # Output trace {none, primary, secondary, both} +
+ +
+
+ +
queue_outputs: + # Output data in a separate thread - may reduce latency +
+ +
+
+ +
use_predictions: + # {none, primary, secondary, both} +
+ +
+
+ +
primary_database: +
+ +
+
+ +
primary_suffix: + # Suffix to append to database elements to make distinctions between runs for comparison +
+ +
+
+ +
primary_uri: + # Location and port of the mongo database to connect to +
+ +
+
+ +
secondary_database: +
+ +
+
+ +
secondary_suffix: + # Suffix to append to database elements to make distinctions between runs for comparison +
+ +
+
+ +
secondary_uri: + # Location and port of the mongo database to connect to +
+ +
+
+ +
sent_predictions: + # Filter states to predict and send to mongo [none, one, all, rec_pos, rec_vel, rec_pos_rate, rec_acc, strain_rate, pos, vel, acc, heading, orientation, ref_sys_bias, rec_clock, rec_sys_bias, rec_clock_rate, rec_sys_bias_rate, rec_clock_rate_gm, rec_sys_bias_rate_gm, sat_clock, sat_clock_rate, sat_clock_rate_gm, trop, trop_grad, trop_model, ionospheric, iono_stec, rec_pco_x, rec_pco_y, rec_pco_z, sat_pco_x, sat_pco_y, sat_pco_z, rec_pcv, ant_delta, eop, eop_rate, calc, slr_rec_range_bias, slr_rec_time_bias, xform_xlate, xform_rtate, xform_scale, xform_delay, ambiguity, code_bias, phase_bias, z_amb, reference, begin_meas_states, code_meas, phas_meas, laser_meas, pseudo_meas, orbit_meas, filter_meas, end_meas_states, begin_orbit_states, orbit, emp_d_0, emp_d_1, emp_d_2, emp_d_3, emp_d_4, emp_y_0, emp_y_1, emp_y_2, emp_y_3, emp_y_4, emp_b_0, emp_b_1, emp_b_2, emp_b_3, emp_b_4, emp_r_0, emp_r_1, emp_r_2, emp_r_3, emp_r_4, emp_t_0, emp_t_1, emp_t_2, emp_t_3, emp_t_4, emp_n_0, emp_n_1, emp_n_2, emp_n_3, emp_n_4, emp_p_0, emp_p_1, emp_p_2, emp_p_3, emp_p_4, emp_q_0, emp_q_1, emp_q_2, emp_q_3, emp_q_4, end_orbit_states, begin_inertial_states, gyro_bias, gyro_scale, accl_bias, accl_scale, imu_offset, end_inertial_states, range] +
+ +
+
+ +
used_predictions: + # Filter states to retrieve from mongo [none, one, all, rec_pos, rec_vel, rec_pos_rate, rec_acc, strain_rate, pos, vel, acc, heading, orientation, ref_sys_bias, rec_clock, rec_sys_bias, rec_clock_rate, rec_sys_bias_rate, rec_clock_rate_gm, rec_sys_bias_rate_gm, sat_clock, sat_clock_rate, sat_clock_rate_gm, trop, trop_grad, trop_model, ionospheric, iono_stec, rec_pco_x, rec_pco_y, rec_pco_z, sat_pco_x, sat_pco_y, sat_pco_z, rec_pcv, ant_delta, eop, eop_rate, calc, slr_rec_range_bias, slr_rec_time_bias, xform_xlate, xform_rtate, xform_scale, xform_delay, ambiguity, code_bias, phase_bias, z_amb, reference, begin_meas_states, code_meas, phas_meas, laser_meas, pseudo_meas, orbit_meas, filter_meas, end_meas_states, begin_orbit_states, orbit, emp_d_0, emp_d_1, emp_d_2, emp_d_3, emp_d_4, emp_y_0, emp_y_1, emp_y_2, emp_y_3, emp_y_4, emp_b_0, emp_b_1, emp_b_2, emp_b_3, emp_b_4, emp_r_0, emp_r_1, emp_r_2, emp_r_3, emp_r_4, emp_t_0, emp_t_1, emp_t_2, emp_t_3, emp_t_4, emp_n_0, emp_n_1, emp_n_2, emp_n_3, emp_n_4, emp_p_0, emp_p_1, emp_p_2, emp_p_3, emp_p_4, emp_q_0, emp_q_1, emp_q_2, emp_q_3, emp_q_4, end_orbit_states, begin_inertial_states, gyro_bias, gyro_scale, accl_bias, accl_scale, imu_offset, end_inertial_states, range] +
+ +
+
+
+
+ +
debug: ⯆ + # Debug options are designed for developers and should probably not be used by normal users +
+
+
+ +
check_plumbing: + # Debugging option to show sizes of objects in memory to detect leaks +
+ +
+
+ +
explain_measurements: + # Debugging option to show verbose measurement coefficients +
+ +
+
+ +
fatal_message_level: + # Threshold level for exiting the program early (0-2) +
+ +
+
+ +
mincon_filename: + # Filename of pre-mincon filter state for backup/loading +
+ +
+
+ +
mincon_only: + # Debugging option to re-run minimum constraints code +
+ +
+
+ +
output_mincon: + # Debugging option to only save pre-minimum constraints filter state +
+ +
+
+ +
retain_rts_files: + # Debugging option to keep rts files for post processing +
+ +
+
+ +
rts_only: + # Debugging option to only re-run rts from previous run +
+ +
+
+ +
check_broadcast_differences: +
+ +
+
+ +
compare_attitudes: +
+ +
+
+ +
compare_clocks: +
+ +
+
+ +
compare_orbits: +
+ +
+
+
+ +

+ + +
+ + +
+ + + + + + + diff --git a/aboutGinan.html b/aboutGinan.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/aboutGinan.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/aboutGinan.md b/aboutGinan.md new file mode 100644 index 000000000..72144a0cf --- /dev/null +++ b/aboutGinan.md @@ -0,0 +1,53 @@ + +# Ginan: software toolkit and service + +![The Southern Cross in the night sky](images/SouthernCross.png) + +The Australian Government, through Geoscience Australia's Positioning Australia program, is funding the design, development and operational service of a Global Navigation Satellite System (GNSS) position correction system (the Ginan service and toolkit). + +This system will give individuals and organisations no-cost access to software and products that have the potential to greatly enhance the accuracy of positioning – to within a few centimetres – across Australia. + +The aims of the initiative are to: + +* Develop a software based GNSS analysis toolkit and make it available to the public through an open source licence. +* Use that toolkit to produce position correction messages that allow users with compatible GNSS receivers and an internet connection to get to a position accuracy of a few centimetres. This is the Ginan toolkit operating in its Network Platform mode. +* Provide the toolkit in its User Platform mode which can take GNSS observations and correction messages to calculate precise positions with an accuracy of a few centimetres. +* Encourage the development of innovative position dependent technology and services that will be of economic benefit to Australia – to grow the market for original equipment manufacturers (OEMs), technology integrators, service providers, the science community and end users, and realise the full benefits of GNSS. +* Enhance Geoscience Australia’s internal expertise in multi-GNSS so that Geoscience Australia can continue to provide expert advice on GNSS system performance to domestic and international GNSS users. +* Help Geoscience Australia generate the next generation of geodetic datums, keep track of multi-GNSS performance over Australia, and produce positioning products so that Geoscience Australia can realize the full benefit of the navigation systems that operate in our region. +* Provide a state-of-art GNSS analysis toolkit to our universities and research organisations to enable Australia to lead the development of geospatial technology. + +Geoscience Australia will support Ginan with ongoing maintenance and enhancements and will publish service level guarantees. + +## Product offering + +Ginan is being rolled out in a phased approach and will offer products in four distinct categories: + +1. **The software itself.** Ginan is open-source software that Geoscience Australia has hosted on this GitHub repository. Anybody who has access to GitHub will be able to download and use the software. Selected parts of the software or the whole application may be downloaded. This is the concept behind Ginan as a toolkit. If a person is only interested in precise orbit determination, they need only take that software. By making the software open-source Geoscience Australia is: + 1. Supporting GNSS education by allowing students and researchers to examine how the Ginan algorithms work to solve complex problems, + 1. Enabling researchers and commercial organisations to use the software to solve research or commercial problems, + 1. Allowing the software to become more robust over time by giving users the ability to report bugs and make suggestions to improve the software. +1. **Standard precise point positioning (PPP) product files.** An operational version of Ginan, maintained by Geoscience Australia, will produce a range of standard PPP product files including, for example, a precise orbits and clocks file in sp3 format. Users with a Geoscience Australia account will be able to log into the Geoscience repository and download the files they require. In time these files will also be submitted to the International GNSS Service (IGS) to become part of their data set. +1. **Precise point positioning correction messages.** An operational version of Ginan, maintained by Geoscience Australia, will stream over the internet on a 24 X 7 basis, a range of PPP correction messages in the [RTCM3](https://rtcm.myshopify.com/collections/differential-global-navigation-satellite-dgnss-standards) message format (and later possibly [SPARTN](https://www.spartnformat.org/) and [IGS-SSR](https://www.igs.org/formats-and-standards)) . Users with a Geoscience Australia account will be able to select and connect to the streams they require. The data will enable corrections to be applied in real-time to achieve position accuracies of under 5 cm in equipment capable of consuming the data. +1. **New PPP products and applications yet to be defined.** The Ginan toolkit gives Geoscience Australia the ability to offer new PPP products, yet to be defined but which, in collaboration with users, may spawn new applications and commercial opportunities. Within the PPP world there are well established conventions, but these do not need to constrain innovative thought. + + +## Users and Use Cases + +Ginan's users and use cases are summarised in the figure below: + +![Ginan's users and use cases](images/UseCasesv04.jpg) + +## Collaborate + +Geoscience Australia believes that Ginan is a compelling application to use for precise point positioning. Geoscience Australia is keen to hear from the positioning community regarding requirements around: + +* Types of application that need to be supported, +* Novel data formats or combinations for specific applications, +* Any other aspects related to PPP technology and operations. + +Contact Geoscience Australia via e-mail: clientservices@ga.gov.au - Include "Ginan" in the title. + +## Resources + +[![](images/GinanProjectOverviewFrontSlide20210902v01.png) The Ginan project overview presentation from March 2022](resources/GinanProjectOverview20220316v01.pdf) diff --git a/aboutGnss.md b/aboutGnss.md new file mode 100644 index 000000000..05569f2a7 --- /dev/null +++ b/aboutGnss.md @@ -0,0 +1,41 @@ + +# Global Navigation Satellite Systems (GNSS) + +> Global Navigation Satellite Systems `GNSS` have revolutionised the way we think about and use position information. But there is a lot more to GNSS than the phone in your hand. They are complex systems of systems. This section describes the major components that make up a GNSS. + +![Global Navigation Satellite System components](images/GNSSComponents1-75pc.png) +*Global Navigation Satellite System components* + +A global navigation satellite system consists of: + +1. A constellation of nominally 24 satellites moving around the Earth twice a day in three distinct orbits that are inclined to each other and at approximately 20,000 km above the Earth's surface (medium Earth orbit or MEO - the space segment), +1. A number of monitoring stations on the ground that listen to the satellite broadcasts and assess their quality, +1. A couple of control stations on the ground that can make adjustments to satellite orbits and configurations, +1. The receivers on the ground - in your phone or your car - that can pick up the satellite signals and decode them to give you a position. + +The clever part is that the satellites know where they are - their position in their orbit around the Earth - because the control segment uploads new computed orbits every time they pass over. The satellites continuously broadcast their orbital position along with a special timing or ranging signal. + +The speed at which the radio signal travels from the satellite to Earth is known - that is the speed of light. A receiver on the ground can pick up the ranging signal and calculate how far away the satellite is from the receiver. This is called ranging. Note: the speed of light is a known constant but unfortunately other effects become the source of some position uncertainties as we'll see later. + +Given that the satellite is also broadcasting its position, the receiver now has a distance and a position. If the receiver can see four satellites at one time it has enough information to use sophisticated trigonometry (trilateration) to calculate the position of the receiver. + +![The basic GNSS position calculation](images/GNSSPositions-75pc.png) +*The basic GNSS position calculation* + +## Active GNSS Constellations + +There are currently four full GNSS constellations in operation: + +1. Navstar Global Positioning System (GPS) - the original American system started in 1978 and achieved full operational capability in 1995. GPS orbits at 20,200 km above the Earth, +1. GLONASS from Russia - Global'naya Navigatsionnaya Sputnikovaya Sistema - since 1995. GLONASS orbits at 19,100 km above the Earth, +1. BeiDou from China since 2018. BeiDou orbits at 21,528 km above the Earth, +1. Galileo from the European Union since 2021. Galileo orbits at 23,222 km above the Earth, + +![GNSS Constellations](images/GNSSConstellations-75pc.png) +*GNSS Constellations* + +All of the constellations broadcast an open signal service (as opposed to an encrypted service for armed forces). It is the case that if you have a receiver that can pick up signals of different frequencies from more than one constellation, so the more confident and accurate will be your position. + +## Resources + +[![](images/GNSSFrontSlide20210618v01.png) Global Navigation Satellite Systems](resources/GNSS20211209v01.pdf) diff --git a/ambiguities.md b/ambiguities.md new file mode 100644 index 000000000..885c3a4fa --- /dev/null +++ b/ambiguities.md @@ -0,0 +1,158 @@ + +# Ambiguity Resolution + +Estimation and/or resolution of carrier phase ambiguities is central to precise point positioning. +Whereas standard precision positioning is performed using the unambiguous pseudorange measurement, these measurements are known to have an accuracy ranging from metres to decimetres. +Precise positioning thus rely on the use of carrier phase measurements which have an accuracy of millimetres to a few centimetres, but are ambiguous by an integer number of wavelengths. +Estimating these ambiguities to centimetre or millimetre level of accuracy is a requirement of precise positioning. +Integer ambiguity resolution offers the following advantages, over just real-valued ambiguity estimation. + +* Ambiguities resolved to integer ambiguities have no errors, which improves the accuracy of the solution, it also make the measurement model more robust to changes in environmental conditions. +* Ambiguity resolution can be attempted when estimates are of around 5cm of accuracy (one 4th of wavelength) reducing their errors to 0. This results in an acceleration of convergence of PPP solutions. +* Ambiguities are constant unless there are cycle slips eliminating the need to estimate then once resolved, this in turn will simplify/accelerate the estimation of other parameters in real time applications. + + +As with any integer estimation process the ambiguity resolution for GNSS signals in Ginan will follow the steps below + +* The ambiguities are estimated as real numbers (with the other parameters). +* Integer values of the ambiguities are resolved using the results of step 1 (the real-value ambiguities and the VCV matrix). +* The validity of integer ambiguities is tested using statistical tests. +* Ambiguity states are constrained to the resolved ambiguity + +Ginan can be set to solve ambiguities in GPS, Galileo, Beidou and QZSS measurements. Ambiguity resolution is not supported for the GLONASS FDMA signals. + + +## Real-valued ambiguity estimation + +Carrier phase ambiguities and phase biases are estimated as real numbers using carrier phase measurements +\begin{equation} +E(L_{r,c}^s) += \rho_{r}^s ++ c_{light}(dt_{r}^q - dt^s) ++ \tau_r^s +- I^s_r ++ b_{r,c}^q +- b_{c}^s ++ \lambda_{f} z_{r,c}^s ++ \phi^s_{r,f} +\end{equation} +and pseudorange measurements $P_{r,c}^s$. + +The range $\rho_{r}^s$, clock offsets $dt_{r}^q$ and $dt^s$, atmospheric delays $\tau_r^s $ and $I^s_r$, can be estimated to adequate accuracy using the pseudoranges, and $\phi^s_{r,f}$ can be corrected using deterministic models. +However this still leaves the rank deficiency produced by correlations between ambiguities $z_{r,c}^s$ and phase biases $b_{r,c}^q$ and $b_{c}^s$. +Thus, without using extra pseudo-observations, the real valued ambiguities are expected to be contaminated by these phase biases $A_{r,c}^s = \lambda_{f} z_{r,c}^s + b_{r,c}^q - b_{c}^s$ + +This make it difficult to solve the ambiguities directly. +Ginan chooses instead to make and solve combinations of ambiguities, e.g.: +\begin{equation} +A_{r1,r2, c}^{s1,s2} = A_{r1,c}^{s1} - A_{r1,c}^{s2} - A_{r2,c}^{s1} - A_{r2,c}^{s2} = \lambda_{f} (z_{r1,c}^{s1} - z_{r1,c}^{s2} - z_{r2,c}^{s1} - z_{r2,c}^{s2}). +\end{equation} +Ginan forms these combinations by using the LAMBDA Z-transform/decorrelation, thus only algorithms using the Z-transform are effective in ambiguity resolution without using pivots. + +For end user processing, where the satellite phase bias $b_{c}^{s1}$ is known, a **receiver ambiguity pivot** can be applied to separate the receiver phase bias from the ambiguities. +By setting the ambiguity for one satellite $s1$ to an arbitrary value $\tilde{z_{r,c}^{s1}}$ the receiver phase bias will be se to +$\tilde{b_{r,c}^q}=b_{r,c}^q+\lambda_{f} (\tilde{z_{r,c}^{s1}}-z_{r,c}^{s1})$. +This in turn will make other ambiguity estimate into solvable integers: +\begin{equation} +A_{r,c}^{s1} + b_{c}^{s1} - \tilde{b_{r,c}^q}= \lambda_{f} \tilde{z_{r,c}^{s1}} +\end{equation} +\begin{equation} +A_{r,c}^{s2} + b_{c}^{s2} - \tilde{b_{r,c}^q} = \lambda_{f} (z_{r,c}^{s2}-\tilde{z_{r,c}^{s1}}+z_{r,c}^{s1}) +\end{equation} +\begin{equation} +A_{r,c}^{s3} + b_{c}^{s3} - \tilde{b_{r,c}^q} = \lambda_{f} (z_{r,c}^{s3}-\tilde{z_{r,c}^{s1}}+z_{r,c}^{s1}) +\end{equation} + +The **network ambiguity pivot** performs a similar function for network processing, where both receiver and satellite biases are defined using a small set of arbitrarily set ambiguities: +1. Assign a station as anchor, and define the receiver bias $b_{r0,c}^q=0$ +1. At each epoch, scan all ambiguity estimates $z_{r,c}^{s}$ + 1. If the phase bias for receiver $b_{r,c}^q$ is defined but the satellite phase bias $b_{c}^{s}$ is not, define $b_{c}^{s}$ by setting $z_{r,c}^{s}$ to an arbitrary value + 1. If the phase bias for satellite $b_{c}^{s}$ is defined but the receiver phase bias $b_{r,c}^q$ is not, define $b_{r,c}^q$ by setting $z_{r,c}^{s}$ to an arbitrary value +1. Repeat until all phase biases are defined + +Using the ambiguity pivots allows real-value ambiguity estimates to become close to integer values and thus use ambiguity resolution techniques without Z-transform/decorrelation. + +## Integer ambiguity estimation and validation +Once the real-valued ambiguity estimates have been calculated, they can be solved into integers. Ginan implements various methods for to perform ambiguity resolution, namely: + +* Integer rounding (round) +* Iterative rounding (iter_rnd) +* Integer Bootstrap (bootst) +* Lambda Integer Least Squares (lambda) +* Lambda ILS with ratio test (lambda_alt) +* Lambda ILS with common ambiguity selection (lambda_al2) +* Lambda best integer Equivariant (lambda_bie) + +At its simplest, the `round` method, just rounds selected ambiguities $z(i)$ to their nearest integer $\hat{z}(i)$. Ambiguities are selected based on two criteria, the ratio test: +\begin{equation} +|z(i)-\hat{z}(i)|<\frac{1}{R_{thres}+1} +\end{equation} +and the success rate test: +\begin{equation} +\frac{1}{2}erfc(-\frac{1-|z(i)-\hat{z}(i)|}{\sqrt{2{\bf Q_{zz}}(i,i)}})>S_{thres} +\end{equation} +where $R_{thres}$ and $S_{thres}$ are user defined thresholds, $erfc$ is the complementary error function and $Q_{zz}$ is the covariance matrix of ambiguities. + +The `round` method consider the ambiguities to be independent of each other. +In reality the ambiguities are highly correlated with each other, even after eliminating rank deficiencies using ambiguity pivots. +The `iter_rnd` method attempts to mitigate the effect of these correlations by iterating the integer rounding process. +After solving the subset ${\bf j}\subset {\bf i}$ of ambiguities, the estimated ambiguities and its covariance are updated as: +\begin{equation} +{\bf K}={\bf Q_{zz}}({\bf i},{\bf j}) {\bf Q_{zz}}({\bf j},{\bf j}) +\end{equation} +\begin{equation} +{\bf z'}={\bf z} - {\bf K}({\bf z}({\bf j}) - {\bf \hat{z}}({\bf j})) +\end{equation} +\begin{equation} +{\bf Q_{z'z'}}={\bf Q_{zz}} - {\bf K} {\bf Q_{zz}}({\bf j},{\bf i}) +\end{equation} +and the process repeated with new set of ambiguities ${\bf z'}$. +This eliminates the influence of errors and uncertainty of ${\bf z}({\bf j})$ from ambiguities outside the ${\bf j}$ set, hopefully facilitating the resolution of the later ones. + +Alternatively, the `bootst` and lambda methods handle ambiguity correlations by performing a Z-transform based reduction process. +The substitutes the ambiguities ${\bf z}$ with a less correlated linear combination ${\bf z''}$. +The linear combination matrix is obtained by applying a series of unimodular transformations +\begin{equation} +{\bf z''}=(\coprod {\bf Z_{ij}}) {\bf z} +\end{equation} +where +\begin{equation} +{\bf Z_{ij}} = {\bf I} - n_{ij}{\bf e_i}{\bf e_j^{T}} +\end{equation} +with $n_{ij} \in \Bbb Z$ and ${\bf e_i}$ a column vector with 1 in position $i$ and 0 elsewhere. +The ${\bf Z_{ij}}$ transformation is equivalent to substituting $z(i)$ with $z(i)-n_{ij}z(j)$, and has the effect of changing the covariance matrix as: +\begin{equation} +{\bf L''} = {\bf L} - n_{ij}{\bf L}{\bf e_i}{\bf e_j^{T}} +\end{equation} +where ${\bf L}$ is lower triangular matrix product of the $L^TDL$ decomposition of $Q_{zz}$. +${\bf L''}$ s preserved by the transformation with the exception of: +\begin{equation} +l''_{kj} = l_{kj} - n_{ij}l_{ki} \forall k \ge i +\end{equation} +by choosing $n_{ij}$ such that $|l''_{kj}|<0.5$, the correlation between transformed ambiguities $z''$ are minimized +The `bootst` method applies the same process as `iter_rnd` on the transformed ambiguities $z''$. + +The lambda methods on the other hand use an iterative fix and adjust process to select a set of ambiguities with minimum distance to the real-valued estimates. +The $R_{thres}$ and $S_{thres}$ thresholds are used in different ways. First the success rate threshold $S_{thres}$ is used to discard ambiguities that has too high an uncertainty to resolve. +The reduction process used for lambda algorithms use a reordering process alongside the de-correlation which tends to order the $z''$ ambiguity in descending order of variance. +Relying on this, the last $J$ ambiguities are selected for resolutions, with $J$ selected in such a way as to fulfill +\begin{equation} +\coprod_{n-J}^n erf(sqrt{\frac{1}{8{\bf D''}(j)}}) \ge S_{thres} +\end{equation} +where ${\bf D''}$ is obtained from the $L^TDL$ decomposition of $Q_{z''z''}$. +The potential integer set candidates ${\bf \hat{z''}_k}$ candidates are selected among those that fulfill the criteria: +\begin{equation} +\|{\bf z''}-{\bf \hat{z''}_k}\| **2 Sept 2024** - the Ginan team is pleased to release v3.1.0 of the toolkit. +> +> The improvements delivered by this version include: +> +> * Boxwing model for the albedo +> * Sisnet (SouthPan) message support +> * SLR processing capability +> * PBO Position (.pos) format file output support +> * Apple silicon (M-chip) support +> * VMF3 file download python script (get_vmf3.py) +> * POS file visualisation python script (plot_pos.py) +> * EDA improvements +> * Improved documentation +> * Use case examples updated +> * Frequency dependent GLONASS receiver code bias estimation enabled +> * Improved missing/bad data handling +> * Bias rates from .BIA/BSX files parsed and used +> * Measurment and State error handling sigma_limit thresholds separated +> * Config file reorganisation (rec_reference_system: moved to receiver_options:) +> * Clock code handling modified +> * Many bug fixes. diff --git a/attitudes.md b/attitudes.md new file mode 100644 index 000000000..80be35e69 --- /dev/null +++ b/attitudes.md @@ -0,0 +1,43 @@ + + +# Attitude Modelling +A satellite's attitude is its orientation in space. Satellite attitude affects both the position and orientation of antenna arrays, as well as the spacecraft profile with respect to solar radiation or drag. + + +## Nominal Yaw +GNSS satellite attitudes are mainly dictated by their mission and operational requirements. In order to transmit GNSS signals, the antenna array (located on the satellite -Z axis) must point toward Earth. Secondly, in order to maximise solar power, satellites rotate around their Z axis (yaw) and rotate their solar panels around the Y axis to point toward the Sun. +The optimal yaw $\psi$ which allows solar panels to point directly at the Sun is given by: + +\begin{equation} + \psi = atan2(-tan(\beta), sin(\mu)) + \pi +\end{equation} + +where $\beta$ is the Sun elevation angle with respect to the orbital plane and $\mu$ is the angle of the satellite from orbital 'midnight' - i.e. when satellite is at the furthest point from the Sun in its orbit. + + +## Modelled Yaw +At low $\beta$ angles as the satellite passes through orbital noon or midnight, satellites experience 'gimbal lock' where the rate of yaw change required by the nominal yaw equation approaches $\pm\infty$ . Each constellation block has different modified yaw steering strategies to handle this problem, summarised below. + +| Block | Yaw steering strategy | +| - | - | +| GPS-IIA | Noon: catch up steering at max yaw rate; Midnight: max yaw rate steering during eclipse | +| GPS-IIF | Noon: catch up steering at max yaw rate; Midnight: constant yaw rate steering during eclipse | +| GPS-IIR | Catch up steering at max yaw rate | +| GPS-III | Smoothed yaw steering | +| GAL-IOV | Smoothed yaw steering via auxiliary Sun vector | +| GAL-FOC | Smoothed yaw steering | +| GLO | Noon: centered yaw steering at max yaw rate; Midnight: max yaw rate steering upon eclipse entry then stop | +| GLO-K | Unknown | +| QZSS-1 | Orbit-normal (yaw = 0) during specified periods | +| QZSS-2A/2I | Centered yaw steering at max yaw rate, with orbit-normal during specified periods | +| QZSS-2G | Orbit-normal | +| BDS-2I/2M | Orbit-normal at low beta angles | +| BDS-2G | Orbit normal | +| BDS-3I/3M | Smoothed yaw steering | +| BDS-3M-SECM | Smoothed yaw steering using auxiliary beta angle | + + +## Precise Attitudes + +Ginan is also able to use a-priori satellite attitudes, in place of the models above, in cases where GNSS satellite attitudes have already been precomputed or when a non-GNSS satellite has attitude data. + diff --git a/autoDownload.md b/autoDownload.md new file mode 100644 index 000000000..78afa2508 --- /dev/null +++ b/autoDownload.md @@ -0,0 +1,52 @@ + +# Auto Download Scripts + +The auto download script available in the `scripts` directory is a python tool that will automatically download various inputs needed to run Ginan + +The detailed features of each option can be found by changing to the `scripts` directory and running + + python3 auto_download_PPP.py --help + +however, some of the features include: +* the ability to download RINEX files from Geoscience Australia's `gnss-data` data repository, +* the ability to choose between final, rapid and ultra-rapid file types +* the ability to choose the analysis centre (apart from SNX coordinate and BIA bias files which come from IGS and COD, respectively) + +To get started try the following examples: + +Examples to run: + +## Download necessary real-time inputs: +``` +python3 auto_download_PPP.py \ + --target-dir="/data/tmp-dwn" \ + --preset="real-time" +``` + +## Download inputs for post-processed runs: + +Files for post-processing runs may be downloaded using most defaults: +``` +python3 auto_download_PPP.py \ + --target-dir="/data/tmp-dwn" \ + --preset="igs-station" \ + --station-list="ALIC,DARW" \ + --start-datetime="2023-02-24_00:00:00" \ + --end-datetime="2023-02-26_00:00:00" +``` + +or by choosing the solution type (ultra-rapid) and analysis centre (ESA): + +``` +python3 auto_download_PPP.py \ + --target-dir="/data/tmp-dwn" \ + --preset="igs-station" \ + --station-list="ALIC,DARW" \ + --start-datetime="2023-02-24_00:00:00" \ + --end-datetime="2023-02-26_00:00:00" \ + --solution-type="ULT" \ + --analysis-center="ESA" +``` + + + diff --git a/codingStandard.md b/codingStandard.md new file mode 100644 index 000000000..390593c04 --- /dev/null +++ b/codingStandard.md @@ -0,0 +1,389 @@ +# Coding Standards for C++ + +## Code style +Decades of experience has shown that codebases that are built with concise, clean code have fewer issues and are easier to maintain. If submitting a pull request for a patch to the software, please ensure your code meets the following standards. + +Overall we are aiming to + +* Write for clarity +* Write for clarity +* Write what you mean, not what is implied +* Write things once +* Use short, descriptive variable names +* Use aliases to reduce clutter. + +### Unconcise code - Not recommended + + //check first letter of satellite type against something + + if (obs.Sat.id().c_str()[0]) == 'G') + doSomething(); + else if (obs.Sat.id().c_str()[0]) == 'R') + doSomething(); + else if (obs.Sat.id().c_str()[0]) == 'E') + doSomething(); + else if (obs.Sat.id().c_str()[0]) == 'I') + doSomething(); + + +### Clear Code - Good + + char& sysChar = obs.Sat.id().c_str()[0]; + + switch (sysChar) + { + case 'G': doSomething(); break; + case 'R': doSomething(); break; + case 'E': doSomething(); break; + case 'I': doSomething(); break; + } + + +## Spacing, Indentation, and layout + +* Use tabs, with tab spacing set to 4. +* Use space or tabs before and after any ` + - * / = < > == != % ` etc.. +* Use space, tab or new line after any `, ;` +* Use a new line after if statements. +* Use tabs to keep things tidy - If the same function is called multiple times with different parameters, the parameters should line up. + +### Scattered Parameters - Bad + + trySetFromYaml(mongo_metadata,output_files,{"mongo_metadata" }); + trySetFromYaml(mongo_output_measurements,output_files,{"mongo_output_measurements" }); + trySetFromYaml(mongo_states,output_files,{"mongo_states" }); + +### Aligned Parameters - Good + + trySetFromYaml(mongo_metadata, output_files, {"mongo_metadata" }); + trySetFromYaml(mongo_output_measurements, output_files, {"mongo_output_measurements" }); + trySetFromYaml(mongo_states, output_files, {"mongo_states" }); + +## Statements + +One statement per line + +- `*`unless you have a very good reason + +### Multiple Statements per Line - Bad + + z[k]=ROUND(zb[k]); y=zb[k]-z[k]; step[k]=SGN(y); + +### Single Statement per Line - Good + + z[k] = ROUND(zb[k]); + y = zb[k]-z[k]; + step[k] = SGN(y); + +### Example of a good reason: + +* Multiple statements per line sometimes shows repetitive code more clearly, but put some spaces so the separation is clear. + +#### Normal + + switch (sysChar) + { + case ' ': + case 'G': + *sys = E_Sys::GPS; + *tsys = TSYS_GPS; + break; + case 'R': + *sys = E_Sys::GLO; + *tsys = TSYS_UTC; + break; + case 'E': + *sys = E_Sys::GAL; + *tsys = TSYS_GAL; + break; + //...continues + } + +#### Ok + + if (sys == SYS_GLO) fact = EFACT_GLO; + else if (sys == SYS_CMP) fact = EFACT_CMP; + else if (sys == SYS_GAL) fact = EFACT_GAL; + else if (sys == SYS_SBS) fact = EFACT_SBS; + else fact = EFACT_GPS; + +#### Ok + + switch (sysChar) + { + case ' ': + case 'G': *sys = E_Sys::GPS; *tsys = TSYS_GPS; break; + case 'R': *sys = E_Sys::GLO; *tsys = TSYS_UTC; break; + case 'E': *sys = E_Sys::GAL; *tsys = TSYS_GAL; break; + case 'S': *sys = E_Sys::SBS; *tsys = TSYS_GPS; break; + case 'J': *sys = E_Sys::QZS; *tsys = TSYS_QZS; break; + //...continues + } + +## Braces + +New line for braces. + + if (pass) + { + doSomething(); + } + +## Comments + +* Prefer `//` for comments within functions +* Use `/* */` only for temporary removal of blocks of code. +* Use `/** */` and `///<` for automatic documentation + +## Conditional checks + +* Put `&&` and `||` at the beginning of lines when using multiple conditionals. +* Always use curly braces when using multiple conditionals. + +``` +if ( ( testA > 10) + &&( testB == false + ||testC == false)) +{ + //do something +} +``` + +## Return Values + +* Use variables to name return values rather than using functions directly + +### Bad + + if (doSomeParsing(someObject)) + { + //code contingent on parsing success? failure? + } + +### Good + bool fail = doSomeParsing(someObject); + if (fail) + { + //This code is clearly a response to a failure + } + +## Variable declaration + +* Declare variables as late as possible - at point of first use. +* One declaration per line. +* Declare loop counters in loops where possible. +* Always initialise variables at declaration. + +``` +int type = 0; +bool found = false; //these have to be declared early so they can be used after the for loop + +for (int i = 0; i < 10; i++) +{ + bool pass = someTestFunction(); //this pass variable isn't declared until it's used - good + if (pass) + { + type = typeMap[i]; + found = true; + break; + } +} + +if (found) +{ + //... +} +``` + +## Function parameters + +* One per line. +* Add doxygen compatible documentation after parameters in the cpp file. +* Prefer references rather than pointers unless unavoidable. + +``` +void function( + bool runTests, ///< Run unit test while processing + MyStruct& myStruct, ///< Structure to modify + OtherStr* otherStr = nullptr) ///< Optional structure object to populate (cant use reference because its optional) +{ + //... +} +``` + +## Naming and Structure + +* Limit use of abbreviations +* For structs or classes, use `CamelCase` with capital start +* For member variables, use `camelCase` with lowercase start +* For config parameters, use `lowercase_with_underscores` +* For architectural documentation, use `__Camel_Case_With_Extra_Underscores__` +* Use suffixes (`_ptr`, `_arr`, `Map`, `List` etc.) to describe the type of container for complex types. +* Be sure to provide default values for member variables. +* Use hierarchical objects where applicable. + +``` +struct SubStruct +{ + int type = 0; + double val = 0; +}; + +struct MyStruct +{ + bool memberVariable = false; + double precision = 0.1; + + double offset_arr[10] = {}; + OtherStruct* refStruct_ptr = nullptr; + + map offsetMap; + list> variationMapList; + map subStructMap; +}; + +//... + +MyStruct myStruct = {}; + +if (acsConfig.some_parameter) +{ + //.. +} +``` + +## Undesirable Code + +* Do not use 'magic numbers', which require knowledge of other code fragments for comprehension. If a comment is required for explaining what a value means, the code should be rewritten with enums or defined constants. +* Do not append `.0` to integer valued doubles unless they are required. +* Never use `free()`, `malloc()`, or `new` unless it cannot be avoided. +* Threads create synchronisation issues; they should not be used unless manual synchronisation is never required. + +## Documentation + +* Use doxygen style documentation for function and struct headers and parameters +* `/** ` for headers. +* `///<` for parameters + +``` +/** Struct to demonstrate documentation. +* The first line automatically gets parsed as a brief description, but more detailed descriptions are possible too. +*/ +struct MyStruct +{ + bool dummyBool; ///< The thing to the left is documented here +}; + +/** Function to demonstrate documentation +*/ +void function( + bool runTests, ///< Run unit test while processing + MyStruct& myStruct, ///< Structure to modify + OtherStr* otherStr = nullptr) ///< Optional string to populate +{ + //... +} +``` + +## STL Templates + +* Prefer maps rather than fixed arrays. +* Prefer range-based loops rather than iterators or `i` loops, unless unavoidable. + +### Bad + + double double_arr[10] = {}; + + //..(Populate array) + + for (int i = 0; i < 10; i++) //Magic number 10 - bad. + { + + } + + + map doubleMap; + + //..(Populate Map) + + for (auto iter = doubleMap.begin(); iter != doubleMap.end(); iter++) //long, undescriptive - bad + { + if (iter->first == someVar) //'first' is undescriptive - bad + { + //.. + } + } + +### Good - Iterating Maps + + map offsetMap; + + //..(Populate Map) + + for (auto& [siteName, offset] : doubleMap) //give readable names to map keys and values + { + if (siteName.empty() == false) + { + + } + } + +### Good - Iterating Lists + + list obsList; + + //..(Populate list) + + for (auto& obs : obsList) //give readable names to list elements + { + doSomethingWithObs(obs); + } + +### Special Case - Deleting from maps/lists + +Use iterators when you need to delete from STL containers: + +``` +for (auto it = someMap.begin(); it != someMap.end(); ) +{ + KFKey key = it->first; //give some alias to the key/value so they're readable + + if (measuredStates[key] == false) + { + it = someMap.erase(it); + } + else + { + ++it; + } +} +``` + +## Namespaces + +Commonly used std containers may be included with `using` + + #include + #include + #include + #include + + using std::string; + using std::map; + using std::list + using std::unordered_map; + + +## Code sequencing + +The software is to be kept largely sequential - using threads sparingly to limit the overhead of collision avoidance. +Where possible tasks are completed in parallel using parallelisation libraries to take advantage of all CPU cores in multi-processor systems while still retaining a linear flow through the execution. + +Sections of the software that create and modify global objects, such as while reading ephemeris data, will be executed on a single core only. +This will ensure that collisions are avoided and the debugging of these functions is deterministic. + +For sections of the software that have clear delineation between objects, such as per-receiver calculations, these may be completed in parallel, provided they do not attempt to modify or create objects with more global scope. When globally accessible objects need to be created for individual receivers, they should be pre-initialised before the entry to parallel execution section. + + + + diff --git a/conventions.md b/conventions.md new file mode 100644 index 000000000..2a49b1ada --- /dev/null +++ b/conventions.md @@ -0,0 +1,81 @@ + +# Equation Conventions + +In this manual we will be adhering to the following conventions: + +## List of Symbols + +| Variable | Description | +| - | - | +|$i$ or $r$ | Receiver identification| +|$j$ or $s$ | Satellite identification | +|$k$ or $t$ | Epoch number | +|$q$ | GNSS type (GPS,GALILEO,GLONASS,QZSS)| +|$c$ | Speed of light [m/s]| +|$x$ | Vector of parameters to be estimated| +|$y$ | Vector of observations| +|$v$ | Vector of residuals| +|$H$ | Design matrix| +|$P$ | Covariance matrix| +|$R$ | Measurement noise matrix| +|$Q$ | Process noise matrix| +|$\sigma$ | Standard deviation of observable| +|$\Delta$ | Increment to a priori values [m]| +|$\lambda$ or $\lambda_1,\lambda_2,\lambda_5$ | Wavelength | +|$f_1,f_2,f_5$ | frequency| +|$N$ | Ambiguity or $N$} Real valued ambiguity and {$z$}} Integer part of real valued ambiguity| +|$\alpha$ | level of significance| +|$d$ | Code Biases| +|$b$ | Phase Biases| +|$z$ | (Integer) Carrier phase ambiguities| +|$dt$ | Clock error [s]| +|$\kappa$ | Correction - relativity| +|$\iota$ or $I$ | Ionosphere | +|$\tau$ or $T,T_h,T_w$ | Troposphere | +|$m_W$ | elevation dependent mapping function for the troposphere hydrostatic delay| +|$m_W$ | elevation dependent mapping function for the troposphere wet delay| +|$\xi$ | Phase wind-up error| +|$\epsilon$ | Error in observations and unmodelled effects [m]| +|$\rho_i^j$ | Geometric distance between satellite and receiver| +|$L_i^j$ | Carrier phase observable (times c) [m]| +|$P_i^j$ | Pseudo range observable [m]| +|$\psi$ | Satellite yaw [rad]| + + +Example: for an undifferenced, uncombined float solution, the linearized observation equations for pseudorange and phase observations from satellite $s$ to receiver $r$ can be described as: + +\begin{alignat}{2} +\label{eq:codeMeasurement} +\Delta P_{r,f}^{s} +&= u_r^{s} . \Delta x ++ c . (dt_r^q - dt^{s}) ++ M_r^{s} . T_r ++ \mu_f . I_{r}^{s} +&+ d_{r,f}^q +- d_f^{s} +&+ \epsilon_{P,f}^s +\\ +\label{eq:phasMeasurement} +\Delta L_{r,f}^{s} +&= u_r^{s} . \Delta x ++ c . (\delta t_r^q - \delta t^{s}) ++ M_r^{s} . T_r +- \mu_f . I_{r}^{s} ++ \lambda_f . N_{r,f}^{s} +&+ b_{r,f}^q +- b_f^{s} +&+ \epsilon_{L,f}^s +\end{alignat} + +where $\Delta P_{r,f}^{q,s}$ and $\Delta\phi_{r,f}^{q,s}$ are the respective pseudorange and phase measurements on the frequency $f$(f=1,2), from which the computed values are removed; +$u_r^{q,s}$ is the receiver-to-satellite unit vector; +$\Delta x$ is the vector of the receiver position corrections to its preliminary position; +$dt_r^q$ and $dt^{q,s}$ are the receiver and satellite clock errors respectively; +$c$ is the speed of light in a vacuum +$M_r^{q,s}$ is the elevation dependent mapping function for the troposphere wet delay from the corresponding zenith one $T_r$; +$I_{r,1}^{q,s}$ is the ionosphere delay along the line-of-sight from a receiver to a satellite at the first frequency and $mu_f^q = (\lambda_f^q / \lambda_1^q)^2$; +$\lambda_f^q$ is the wavelength for the frequency $f$ of a GNSS $q$; +$z_{r,f}^{q,s}$ is the phase ambiguity +$d_{r,f}^q$ and $b_{r,f}^q$ are the receiver hardware delays of code and phase observations respectively; +$d_f^{q,s}$ and $b_f^{q,s}$ are the satellite hardware delays of code and phase observations, respectively; +$\epsilon_{P,f}$ and $\epsilon_{L,f}$ are the code and phase measurement noises respectively. \ No newline at end of file diff --git a/css/faq.css b/css/faq.css new file mode 100644 index 000000000..ff66c3d54 --- /dev/null +++ b/css/faq.css @@ -0,0 +1,46 @@ +@charset "utf-8"; +/* CSS Document */ + +a{ +color: #282425!important; +} +ul.nav.nav-tabs > li{ + display: inline-block; + line-height: 50px; + height: 100%; + text-transform:uppercase; +} +ul.nav.nav-tabs > li a{ + display:block; + padding:15px; + color: #282425!important; + +} +ul.nav.nav-tabs > li a:hover, ul.nav.nav-tabs > li:hover{ + background: #FB282F; + color:#fff!important; + text-decoration: none!important; +} +ul.nav.nav-tabs > li a.active{ + background: #282425; + color:#fff!important; + text-decoration: none!important; +} +.card-header { + background-color: rgb(245,245,245,0.3)!important; + border-radius:0!important; +} +.card{ +border-radius:0!important; +} + +.card > .card-header a::before { + font-family: fontawesome; + content: "\f067 "; + color: #282425; + float: right; + margin-right: 15px; + font-weight: 400; + position: absolute; + right: 0; +} \ No newline at end of file diff --git a/css/general.css b/css/general.css new file mode 100644 index 000000000..4e45b1c18 --- /dev/null +++ b/css/general.css @@ -0,0 +1,94 @@ +body { + background-color: #fff; + font-family: 'Roboto', sans-serif; + } + +.container { + padding: 1rem; +} + +img.image-fluid { + margin: 20px 0px 0px 20px; +} + +.jumbotron{ + margin-top: 20px; + background-image: url("../images/JagXK3.jpg"); + background-origin: content-box; + background-position: center center; + color: white; +} + + pre { + width: 100%; + padding: 10px; + margin: 0; + overflow: auto; + overflow-y: hidden; + font-size: 12px; + line-height: 20px; + background: #efefef; + border: 1px solid #777; + } + code + { + color: #d63384; + } + .nav{ + display: revert; + padding-left: revert; + } + #myNavbar{ + max-width: 300px; + display: revert; + padding-left: revert; + font-size: small; + } + h2, h1, h3, h4, h5, h6{ + scroll-margin-top: 100px; + margin-top: 1rem; + } + + h6 + { + display:inline; + } + h6+p + { + display:inline; + } + img + { + + max-width: 100%; + } + blockquote + { + padding: 1em; + background-color: rgb(250, 229, 212); + } + + blockquote > p + { + margin-bottom: 0; + } + td, th + { + padding-left: 1em; + padding-right: 1em; + } + + img + em + { + display: block; + text-align: center; + } + + + +.fragment +{ + max-height: 60vh; + overflow: scroll; + background-color: #FFFAF1 !important +} diff --git a/defaultConfiguration.md b/defaultConfiguration.md new file mode 100644 index 000000000..6b0871b0c --- /dev/null +++ b/defaultConfiguration.md @@ -0,0 +1,75733 @@ + +# Default Configuration + +This document outlines the major configuration options available in ginan that are most applicable to general users. For more advanced configuration options and their defaults, use the `-Y ` option at the command line to view increasing levels of advanced configurations. +## inputs: + +###### **`inputs:`** + ` ` + + +> This section of the yaml file specifies the lists of files to be used for general metadata inputs, and inputs of external product data. + + +--- + +###### **`inputs:inputs_root:`** + `"." ` + + +Root path to be added to all other input files (unless they are absolute) + +--- + +###### **`inputs:include_yamls:`** + `[] ` + + +List of yaml files to include before this one + +--- + +###### **`inputs:gnss_observations:`** + ` ` + + +> Signal observation data from gnss receivers to be used as measurements + +--- + +###### **`inputs:gnss_observations:gnss_observations_root:`** + `"" ` + + +Root path to be added to all other gnss data inputs (unless they are absolute) + +--- + +###### **`inputs:gnss_observations:rnx_inputs:`** + ` ` + + +--- + +###### **`inputs:gnss_observations:rtcm_inputs:`** + ` ` + + +--- + +###### **`inputs:gnss_observations:custom_inputs:`** + ` ` + + +--- + +###### **`inputs:gnss_observations:ubx_inputs:`** + ` ` + + +--- + +###### **`inputs:satellite_data:`** + ` ` + + +--- + +###### **`inputs:satellite_data:rtcm_inputs:`** + ` ` + + +> This section specifies how State State Representation (SSR) corrections are applied after they are downloaded from an NTRIP caster. + +--- + +###### **`inputs:satellite_data:rtcm_inputs:rtcm_inputs_root:`** + `"" ` + + +Root path to be added to all other rtcm inputs (unless they are absolute) + +--- + +###### **`inputs:satellite_data:rtcm_inputs:rtcm_inputs:`** + `[] ` + + +List of rtcm inputs to use for corrections + +--- + +###### **`inputs:satellite_data:rtcm_inputs:ssr_antenna_offset:`** + [`E_OffsetType`](#e_offsettype) `UNSPECIFIED ` + + +Ephemeris type that is provided in the listed SSR stream, i.e. satellite antenna-phase-centre (APC) or centre-of-mass (COM). This information is listed in the NTRIP Caster's sourcetable {unspecified, apc, com} + +--- + +###### **`inputs:satellite_data:rtcm_inputs:qzl6_inputs:`** + `[] ` + + +List of qzss L6 inputs to use for corrections + +--- + +###### **`inputs:satellite_data:rtcm_inputs:code_bias_validity_time:`** + `3600 ` + + +Valid time period of SSR code biases + +--- + +###### **`inputs:satellite_data:rtcm_inputs:global_vtec_valid_time:`** + `300 ` + + +Valid time period of global VTEC maps + +--- + +###### **`inputs:satellite_data:rtcm_inputs:local_stec_valid_time:`** + `120 ` + + +Valid time period of local STEC corrections + +--- + +###### **`inputs:satellite_data:rtcm_inputs:local_trop_valid_time:`** + `120 ` + + +Valid time period of local Troposphere corrections + +--- + +###### **`inputs:satellite_data:rtcm_inputs:one_freq_phase_bias:`** + `false ` + + +Used stream have one SSR phase bias per frequency + +--- + +###### **`inputs:satellite_data:rtcm_inputs:phase_bias_validity_time:`** + `300 ` + + +Valid time period of SSR phase biases + +--- + +###### **`inputs:satellite_data:rtcm_inputs:validity_interval_factor:`** + `10 ` + + +--- + +###### **`inputs:satellite_data:sisnet_inputs:`** + ` ` + + +> Configuration for SiSNet stream input. SiSNet broadcast SBAS messages + +--- + +###### **`inputs:satellite_data:sisnet_inputs:sisnet_inputs:`** + `[] ` + + +List of sisnet inputs to use for corrections + +--- + +###### **`inputs:satellite_data:sisnet_inputs:sisnet_inputs_root:`** + `"" ` + + +Root path to be added to all other sisnet inputs (unless they are absolute) + +--- + +###### **`inputs:satellite_data:sisnet_inputs:sbas_carrier_frequency:`** + `0 ` + + +Carrier frequency of SBAS channel + +--- + +###### **`inputs:satellite_data:sisnet_inputs:sbas_prn:`** + `0 ` + + +PRN for SBAS satelite + +--- + +###### **`inputs:satellite_data:satellite_data_root:`** + `"" ` + + +Root path to be added to all other satellite data files (unless they are absolute) + +--- + +###### **`inputs:satellite_data:bsx_files:`** + `[] ` + + +List of biassinex files to use + +--- + +###### **`inputs:satellite_data:clk_files:`** + `[] ` + + +List of clock files to use + +--- + +###### **`inputs:satellite_data:dcb_files:`** + `[] ` + + +List of dcb files to use + +--- + +###### **`inputs:satellite_data:nav_files:`** + `[] ` + + +List of ephemeris files to use + +--- + +###### **`inputs:satellite_data:obx_files:`** + `[] ` + + +List of orbex files to use + +--- + +###### **`inputs:satellite_data:sp3_files:`** + `[] ` + + +List of sp3 files to use + +--- + +###### **`inputs:satellite_data:com_files:`** + `[] ` + + +List of com files to use - retroreflector offsets from centre-of-mass for spherical sats + +--- + +###### **`inputs:satellite_data:crd_files:`** + `[] ` + + +List of crd files to use - SLR observation data + +--- + +###### **`inputs:satellite_data:sid_files:`** + `[] ` + + +List of sat ID files to use - from https://cddis.nasa.gov/sp3c_satlist.html/ + +--- + +###### **`inputs:pseudo_observations:`** + ` ` + + +> Use data from pre-processed data products as observations. Useful for combining and comparing datasets + +--- + +###### **`inputs:pseudo_observations:pseudo_observations_root:`** + `"" ` + + +Root path to be added to all other pseudo obs data files (unless they are absolute) + +--- + +###### **`inputs:pseudo_observations:filter_files:`** + `[] ` + + +List of inputs to use for custom pseudoobservations + +--- + +###### **`inputs:pseudo_observations:snx_inputs:`** + ` ` + + +--- + +###### **`inputs:pseudo_observations:eci_pseudoobs:`** + `false ` + + +Pseudo observations are provided in eci frame rather than standard ECEF SP3 files + +--- + +###### **`inputs:pseudo_observations:sp3_inputs:`** + ` ` + + +--- + +###### **`inputs:tides:`** + ` ` + + +> Files specifying tidal loading and potential inputs + +--- + +###### **`inputs:tides:atl_blq_col_order:`** + [`[E_TidalConstituent]`](#e_tidalconstituent) `[S1, S2] ` + + +Column order for amplitude and phase components in ATL BLQ files [m2, s2, n2, k2, s1, k1, o1, p1, q1, mf, mm, ssa] + +--- + +###### **`inputs:tides:atl_blq_row_order:`** + [`[E_TidalComponent]`](#e_tidalcomponent) `[UP, EAST, NORTH] ` + + +Row order for amplitude and phase components in ATL BLQ files [east, west, north, south, up, down] + +--- + +###### **`inputs:tides:atmos_oceean_dealiasing_files:`** + `[] ` + + +List of tide files to use + +--- + +###### **`inputs:tides:atmos_tide_loading_blq_files:`** + `[] ` + + +List of atl blq files to use + +--- + +###### **`inputs:tides:atmos_tide_potential_files:`** + `[] ` + + +List of tide files to use + +--- + +###### **`inputs:tides:ocean_pole_tide_loading_files:`** + `[] ` + + +List of opole files to use + +--- + +###### **`inputs:tides:ocean_pole_tide_potential_files:`** + `[] ` + + +List of tide files to use + +--- + +###### **`inputs:tides:ocean_tide_loading_blq_files:`** + `[] ` + + +List of otl blq files to use + +--- + +###### **`inputs:tides:ocean_tide_potential_files:`** + `[] ` + + +List of tide files to use + +--- + +###### **`inputs:tides:otl_blq_col_order:`** + [`[E_TidalConstituent]`](#e_tidalconstituent) `[M2, S2, N2, K2, K1, O1, P1, Q1, MF, MM, SSA] ` + + +Column order for amplitude and phase components in OTL BLQ files [m2, s2, n2, k2, s1, k1, o1, p1, q1, mf, mm, ssa] + +--- + +###### **`inputs:tides:otl_blq_row_order:`** + [`[E_TidalComponent]`](#e_tidalcomponent) `[UP, WEST, SOUTH] ` + + +Row order for amplitude and phase components in OTL BLQ files [east, west, north, south, up, down] + +--- + +###### **`inputs:troposphere:`** + ` ` + + +> Files specifying tropospheric model inputs + +--- + +###### **`inputs:troposphere:gpt2grid_files:`** + `[] ` + + +List of gpt2 grid files to use + +--- + +###### **`inputs:troposphere:orography_files:`** + `[] ` + + +List of orography files to use + +--- + +###### **`inputs:troposphere:vmf_files:`** + `[] ` + + +List of vmf files to use + +--- + +###### **`inputs:ionosphere:`** + ` ` + + +> Files specifying ionospheric model inputs + +--- + +###### **`inputs:ionosphere:atm_reg_definitions:`** + `[] ` + + +List of files to define regions for compact SSR + +--- + +###### **`inputs:ionosphere:ion_files:`** + `[] ` + + +List of IONEX files for VTEC input + +--- + +###### **`inputs:atx_files:`** + `[] ` + + +List of atx files to use + +--- + +###### **`inputs:erp_files:`** + `[] ` + + +List of erp files to use + +--- + +###### **`inputs:cmc_files:`** + `[] ` + + +List of cmc files to use + +--- + +###### **`inputs:egm_files:`** + `[] ` + + +List of egm files to use + +--- + +###### **`inputs:hfeop_files:`** + `[] ` + + +List of hfeop files to use + +--- + +###### **`inputs:igrf_files:`** + `[] ` + + +List of igrf files to use + +--- + +###### **`inputs:planetary_ephemeris_files:`** + `[] ` + + +List of jpl files to use + +--- + +###### **`inputs:snx_files:`** + `[] ` + + +List of snx files to use + +--- + +## outputs: + +###### **`outputs:`** + ` ` + + +> Specifies options to enable outputs and specify file locations. + +Each section typically contains an option to `output` the filetype, and a `directory` to place the files named `filename`, along with any ancillary options. + + +--- + +###### **`outputs:outputs_root:`** + `"." ` + + +Directory that outputs will be placed in + +--- + +###### **`outputs:colourise_terminal:`** + `true ` + + +Use ascii command codes to highlight warnings and errors + +--- + +###### **`outputs:warn_once:`** + `true ` + + +Print warnings once only + +--- + +###### **`outputs:metadata:`** + ` ` + + +> Options for setting metadata for inputs and outputs + +--- + +###### **`outputs:metadata:config_description:`** + `"Pea" ` + + +ID for this config, used to replace tags in other options + +--- + +###### **`outputs:metadata:pass:`** + `"" ` + + +Password for connecting to NTRIP casters + +--- + +###### **`outputs:metadata:user:`** + `"" ` + + +Username for connecting to NTRIP casters + +--- + +###### **`outputs:metadata:ac_contact:`** + `"clientservices@ga.gov.au" ` + + +Contact person for output files headers + +--- + +###### **`outputs:metadata:analysis_agency:`** + `"GAA" ` + + +Agency for output files headers + +--- + +###### **`outputs:metadata:analysis_centre:`** + `"Geoscience Australia" ` + + +Analysis centre for output files headers + +--- + +###### **`outputs:metadata:analysis_software:`** + `"Ginan" ` + + +Program for output files headers + +--- + +###### **`outputs:metadata:analysis_software_version:`** + `"3.0" ` + + +Version for output files headers + +--- + +###### **`outputs:metadata:atmospheric_tide_loading_model:`** + `"---" ` + + +Atmospheric tide loading model applied + +--- + +###### **`outputs:metadata:config_details:`** + `"" ` + + +Comments and details specific to the config + +--- + +###### **`outputs:metadata:geoid_model:`** + `"EGM96" ` + + +Geoid model name for undulation values + +--- + +###### **`outputs:metadata:gradient_mapping_function:`** + `"Chen & Herring, 1992" ` + + +Name of mapping function used for mapping horizontal troposphere gradients + +--- + +###### **`outputs:metadata:ocean_tide_loading_model:`** + `"FES2004" ` + + +Ocean tide loading model applied + +--- + +###### **`outputs:metadata:reference_system:`** + `"igb14" ` + + +Terrestrial Reference System Code + +--- + +###### **`outputs:metadata:rinex_comment:`** + `"Daily 30-sec observations from IGS stations" ` + + +Comment for output files headers + +--- + +###### **`outputs:metadata:time_system:`** + `"G" ` + + +Time system - e.g. "G", "UTC" + +--- + +###### **`outputs:trace:`** + ` ` + + +> Trace files are used to document processing + +--- + +###### **`outputs:trace:directory:`** + `"" ` + + +Directory to output trace files to + +--- + +###### **`outputs:trace:level:`** + `0 ` + + +Threshold level for printing messages (0-6). Increasing this increases the amount of data stored in all trace files + +--- + +###### **`outputs:trace:output_config:`** + `false ` + + +Output configuration files to top of trace files + +--- + +###### **`outputs:trace:output_initialised_states:`** + `false ` + + +Output states after state transition 2 + +--- + +###### **`outputs:trace:output_predicted_states:`** + `false ` + + +Output states after state transition 1 + +--- + +###### **`outputs:trace:output_residual_chain:`** + `true ` + + +Output component-wise details for measurement residuals + +--- + +###### **`outputs:trace:output_residuals:`** + `false ` + + +Output measurements and residuals + +--- + +###### **`outputs:trace:output_network:`** + `false ` + + +Output trace files for complete network of receivers, inclucing kalman filter results and statistics + +--- + +###### **`outputs:trace:output_receivers:`** + `false ` + + +Output trace files for individual receivers processing + +--- + +###### **`outputs:trace:output_ionosphere:`** + `false ` + + +Output trace files for ionosphere processing, inclucing kalman filter results and statistics + +--- + +###### **`outputs:trace:output_satellites:`** + `false ` + + +Output trace files for individual satellites processing + +--- + +###### **`outputs:trace:network_filename:`** + `"/-.trace" ` + + +Template filename for network trace files + +--- + +###### **`outputs:trace:receiver_filename:`** + `"/-.trace" ` + + +Template filename for receiver trace files + +--- + +###### **`outputs:trace:ionosphere_filename:`** + `"/-.trace" ` + + +Template filename for ionosphere trace files + +--- + +###### **`outputs:trace:satellite_filename:`** + `"/-.trace" ` + + +Template filename for satellite trace files + +--- + +###### **`outputs:trace:output_json:`** + `false ` + + +Output json formatted trace files + +--- + +###### **`outputs:output_rotation:`** + ` ` + + +> Trace files can be rotated periodically by epoch interval. These options specify the period that applies to the template variables in filenames + +--- + +###### **`outputs:output_rotation:period:`** + `86400 ` + + +Period that times will be rounded by to generate template variables in filenames + +--- + +###### **`outputs:output_rotation:period_units:`** + [`E_Period`](#e_period) `SECOND ` + + + {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`outputs:ssr_outputs:`** + ` ` + + +> This section specifies how State State Representation (SSR) corrections are calculated before being published to an NTRIP caster. + +--- + +###### **`outputs:ssr_outputs:code_bias_sources:`** + [`[E_Source]`](#e_source) `[PRECISE] ` + + +Sources for SSR code biases [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:ssr_outputs:phase_bias_sources:`** + [`[E_Source]`](#e_source) `[NONE] ` + + +Sources for SSR phase biases [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:ssr_outputs:atmospheric:`** + ` ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:cmpssr_stec_format:`** + `3 ` + + +Format of STEC gridded corrections: 0:4bit(LSB=0.04) , 1:4bit(LSB=0.12), 2:5bit, 3:7bit, 4:16bit + +--- + +###### **`outputs:ssr_outputs:atmospheric:cmpssr_trop_format:`** + `1 ` + + +Format of Trop. ZWD corrections: 0:8bit, 1:6bit + +--- + +###### **`outputs:ssr_outputs:atmospheric:grid_type:`** + `-1 ` + + +Grid type for gridded atmospheric corrections + +--- + +###### **`outputs:ssr_outputs:atmospheric:lat_int:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:lat_max:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:lat_min:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:lon_int:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:lon_max:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:lon_min:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:npoly_iono:`** + `-1 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:npoly_trop:`** + `-1 ` + + +--- + +###### **`outputs:ssr_outputs:atmospheric:region_id:`** + `-1 ` + + +Region ID for atmospheric corrections + +--- + +###### **`outputs:ssr_outputs:atmospheric:region_iod:`** + `-1 ` + + +Region IOD for atmospheric corrections (default: -1 for undefined) + +--- + +###### **`outputs:ssr_outputs:atmospheric:sources:`** + [`[E_Source]`](#e_source) `[NONE] ` + + +Sources for SSR ionosphere [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:ssr_outputs:atmospheric:use_grid_iono:`** + `true ` + + +Grid type for gridded atmospheric corrections + +--- + +###### **`outputs:ssr_outputs:atmospheric:use_grid_trop:`** + `true ` + + +Grid type for gridded atmospheric corrections + +--- + +###### **`outputs:ssr_outputs:clock_sources:`** + [`[E_Source]`](#e_source) `[KALMAN] ` + + +Sources for SSR clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:ssr_outputs:cmpssr_cell_mask:`** + `false ` + + +--- + +###### **`outputs:ssr_outputs:ephemeris_sources:`** + [`[E_Source]`](#e_source) `[PRECISE] ` + + +Sources for SSR ephemeris [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:ssr_outputs:extrapolate_corrections:`** + `false ` + + +--- + +###### **`outputs:ssr_outputs:max_stec_sigma:`** + `1 ` + + +--- + +###### **`outputs:ssr_outputs:prediction_duration:`** + `0 ` + + +--- + +###### **`outputs:ssr_outputs:prediction_interval:`** + `30 ` + + +--- + +###### **`outputs:streams:`** + ` ` + + +--- + +###### **`outputs:streams:root_url:`** + `"" ` + + +Root url to be prepended to all other streams specified in this section. If the streams used have individually specified root urls, usernames, or passwords, this should not be used. + +--- + +###### **`outputs:streams:labels:`** + ` ` + + +List of output stream is with further information to be found in its own section, as per XMPL below + +--- + +###### **`outputs:streams:xmpl:`** + ` ` + + +--- + +###### **`outputs:streams:xmpl:messages:`** + ` ` + + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_0:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_0:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1019:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1019:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1020:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1020:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1042:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1042:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1044:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1044:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1045:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1045:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1046:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1046:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1057:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1057:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1058:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1058:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1059:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1059:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1060:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1060:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1061:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1061:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1062:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1062:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1063:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1063:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1064:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1064:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1065:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1065:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1066:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1066:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1067:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1067:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1068:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1068:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1074:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1074:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1075:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1075:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1076:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1076:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1077:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1077:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1084:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1084:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1085:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1085:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1086:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1086:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1087:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1087:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1094:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1094:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1095:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1095:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1096:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1096:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1097:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1097:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1114:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1114:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1115:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1115:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1116:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1116:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1117:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1117:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1124:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1124:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1125:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1125:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1126:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1126:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1127:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1127:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1240:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1240:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1241:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1241:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1242:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1242:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1243:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1243:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1244:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1244:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1245:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1245:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1246:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1246:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1247:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1247:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1248:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1248:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1249:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1249:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1250:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1250:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1251:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1251:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1252:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1252:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1253:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1253:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1254:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1254:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1255:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1255:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1256:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1256:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1257:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1257:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1258:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1258:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1259:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1259:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1260:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1260:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1261:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1261:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1262:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1262:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1263:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1263:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1265:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1265:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1266:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1266:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1267:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1267:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1268:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1268:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1269:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1269:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1270:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_1270:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_00:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_00:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_01:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_01:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_02:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_02:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_03:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_03:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_04:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_04:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_05:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_05:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_06:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_06:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_07:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_07:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_08:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_08:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_09:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_09:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_10:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_10:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_11:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_11:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_12:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4073_12:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_000:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_000:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_001:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_001:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_002:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_002:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_003:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_003:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_004:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_004:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_005:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_005:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_006:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_006:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_007:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_007:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_008:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_008:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_020:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_020:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_021:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_021:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_022:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_022:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_023:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_023:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_024:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_024:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_025:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_025:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_026:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_026:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_027:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_027:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_040:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_040:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_041:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_041:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_042:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_042:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_043:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_043:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_044:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_044:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_045:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_045:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_046:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_046:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_047:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_047:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_060:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_060:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_061:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_061:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_062:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_062:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_063:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_063:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_064:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_064:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_065:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_065:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_066:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_066:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_067:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_067:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_080:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_080:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_081:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_081:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_082:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_082:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_083:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_083:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_084:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_084:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_085:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_085:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_086:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_086:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_087:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_087:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_100:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_100:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_101:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_101:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_102:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_102:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_103:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_103:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_104:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_104:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_105:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_105:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_106:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_106:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_107:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_107:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_120:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_120:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_121:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_121:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_122:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_122:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_123:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_123:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_124:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_124:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_125:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_125:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_126:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_126:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_127:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_127:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_201:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4076_201:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4082:`** + ` ` + + +> Message type to output + +--- + +###### **`outputs:streams:xmpl:messages:rtcm_4082:udi:`** + `0 ` + + +Update interval + +--- + +###### **`outputs:streams:xmpl:url:`** + `"" ` + + +Url of caster to send messages to + +--- + +###### **`outputs:streams:xmpl:itrf_datum:`** + `true ` + + +--- + +###### **`outputs:streams:xmpl:provider_id:`** + `0 ` + + +--- + +###### **`outputs:streams:xmpl:solution_id:`** + `0 ` + + +--- + +###### **`outputs:clocks:`** + ` ` + + +> Rinex formatted clock files + +--- + +###### **`outputs:clocks:output:`** + `false ` + + +Output clock files + +--- + +###### **`outputs:clocks:directory:`** + `"" ` + + +Directory to output clock files to + +--- + +###### **`outputs:clocks:filename:`** + `"/-_.clk" ` + + +Template filename for clock files + +--- + +###### **`outputs:clocks:output_interval:`** + `1 ` + + +Update interval for clock records + +--- + +###### **`outputs:clocks:receiver_sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + + [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:clocks:satellite_sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + + [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:gpx:`** + ` ` + + +> GPX files contain point data that may be easily viewed in GIS mapping software + +--- + +###### **`outputs:gpx:output:`** + `false ` + + +--- + +###### **`outputs:gpx:directory:`** + `"" ` + + +--- + +###### **`outputs:gpx:filename:`** + `"/-.gpx" ` + + +--- + +###### **`outputs:log:`** + ` ` + + +> Log files store console output in files + +--- + +###### **`outputs:log:output:`** + `false ` + + +Enable console output logging + +--- + +###### **`outputs:log:directory:`** + `"" ` + + +Log output directory + +--- + +###### **`outputs:log:filename:`** + `"/log-.json" ` + + +Log output filename + +--- + +###### **`outputs:pos:`** + ` ` + + +> POS files contain point data that may be easily viewed in GIS mapping software + +--- + +###### **`outputs:pos:output:`** + `false ` + + +--- + +###### **`outputs:pos:directory:`** + `"" ` + + +--- + +###### **`outputs:pos:filename:`** + `"/-.pos" ` + + +--- + +###### **`outputs:bias_sinex:`** + ` ` + + +> Rinex formatted bias sinex files + +--- + +###### **`outputs:bias_sinex:output:`** + `false ` + + +Output bias sinex files + +--- + +###### **`outputs:bias_sinex:bias_time_system:`** + `"G" ` + + +Time system for bias SINEX "G", "C", "R", "UTC", "TAI" + +--- + +###### **`outputs:bias_sinex:code_output_interval:`** + `0 ` + + +Update interval for code biases + +--- + +###### **`outputs:bias_sinex:directory:`** + `"" ` + + +Directory to output bias sinex files to + +--- + +###### **`outputs:bias_sinex:filename:`** + `"/-.BIA" ` + + +Template filename for bias sinex files + +--- + +###### **`outputs:bias_sinex:output_rec_bias:`** + `false ` + + +output receiver biases + +--- + +###### **`outputs:bias_sinex:phase_output_interval:`** + `0 ` + + +Update interval for phase biases + +--- + +###### **`outputs:cost:`** + ` ` + + +> COST format files are used to export troposhere products, such as ZTD and delay gradients. + +--- + +###### **`outputs:cost:output:`** + `false ` + + +Enable data exporting to troposphere COST file + +--- + +###### **`outputs:cost:cost_centre:`** + `"GA__ Geoscience Aus" ` + + +Processing centre + +--- + +###### **`outputs:cost:cost_format:`** + `"COST-716 V2.2" ` + + +Format name & version number + +--- + +###### **`outputs:cost:cost_met_sources:`** + `"NONE" ` + + +Source of met. data + +--- + +###### **`outputs:cost:cost_method:`** + `"GINAN V2" ` + + +Processing method + +--- + +###### **`outputs:cost:cost_orbit_type:`** + `"IGSPRE" ` + + +Orbit type + +--- + +###### **`outputs:cost:cost_project:`** + `"GA-NRT" ` + + +Project name + +--- + +###### **`outputs:cost:cost_status:`** + `"TEST" ` + + +File status + +--- + +###### **`outputs:cost:directory:`** + `"" ` + + +Directory to export troposphere COST file + +--- + +###### **`outputs:cost:filename:`** + `"/cost_s_t___ga__.dat" ` + + +Troposphere COST filename + +--- + +###### **`outputs:cost:sources:`** + [`[E_Source]`](#e_source) `[KALMAN] ` + + +Source for troposphere delay data - KALMAN, etc. [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:cost:time_interval:`** + `900 ` + + +Time interval between entries in troposphere COST file (sec) + +--- + +###### **`outputs:erp:`** + ` ` + + +> Earth rotation parameters can be output to file + +--- + +###### **`outputs:erp:output:`** + `false ` + + +Enable exporting of erp data + +--- + +###### **`outputs:erp:directory:`** + `"" ` + + +Directory to export erp data files + +--- + +###### **`outputs:erp:filename:`** + `"/-.ERP" ` + + +ERP data output filename + +--- + +###### **`outputs:orbex:`** + ` ` + + +--- + +###### **`outputs:orbex:output:`** + `false ` + + +Output orbex file + +--- + +###### **`outputs:orbex:attitude_sources:`** + [`[E_Source]`](#e_source) `[NOMINAL] ` + + +Sources for orbex attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:orbex:clock_sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +Sources for orbex clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:orbex:directory:`** + `"" ` + + +Output orbex directory + +--- + +###### **`outputs:orbex:filename:`** + `"/-_.obx" ` + + +Output orbex filename + +--- + +###### **`outputs:orbex:orbit_sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +Sources for orbex orbits [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:orbex:output_interval:`** + `1 ` + + +Update interval for orbex records (irregular epoch interval is currently NOT supported) + +--- + +###### **`outputs:orbex:record_types:`** + [`[E_OrbexRecord]`](#e_orbexrecord) `[ATT] ` + + +List of record types to output to orbex file [pcs, vcs, cpc, cvc, pos, vel, clk, crt, att] + +--- + +###### **`outputs:sinex:`** + ` ` + + +--- + +###### **`outputs:sinex:output:`** + `false ` + + +--- + +###### **`outputs:sinex:directory:`** + `"" ` + + +--- + +###### **`outputs:sinex:filename:`** + `"/-.snx" ` + + +--- + +###### **`outputs:sp3:`** + ` ` + + +> SP3 files contain orbital and clock data of satellites and receivers + +--- + +###### **`outputs:sp3:output:`** + `false ` + + +Enable SP3 file outputs + +--- + +###### **`outputs:sp3:clock_sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources for clock data for SP3 outputs [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:sp3:directory:`** + `"" ` + + +Directory to store SP3 outputs + +--- + +###### **`outputs:sp3:filename:`** + `"/-_-Filt.sp3" ` + + +SP3 output filename + +--- + +###### **`outputs:sp3:orbit_sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources for orbit data for SP3 outputs [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:sp3:output_inertial:`** + `false ` + + +Output the entries using inertial positions and velocities + +--- + +###### **`outputs:sp3:output_interval:`** + `1 ` + + +Update interval for SP3 records + +--- + +###### **`outputs:sp3:output_velocities:`** + `false ` + + +Output velocity data to SP3 file + +--- + +###### **`outputs:sp3:predicted_filename:`** + `"/-_-Prop.sp3" ` + + +Filename for predicted SP3 outputs + +--- + +###### **`outputs:trop_sinex:`** + ` ` + + +> Troposphere SINEX files are used to export troposhere products, such as ZTD and delay gradients. + +--- + +###### **`outputs:trop_sinex:output:`** + `false ` + + +Enable data exporting to troposphere SINEX file + +--- + +###### **`outputs:trop_sinex:const_code:`** + ` ` + + +Troposphere SINEX const code + +--- + +###### **`outputs:trop_sinex:directory:`** + `"" ` + + +Directory to export troposphere SINEX file + +--- + +###### **`outputs:trop_sinex:filename:`** + `"/-.tro" ` + + +Troposphere SINEX filename + +--- + +###### **`outputs:trop_sinex:obs_code:`** + `P ` + + +Troposphere SINEX observation code + +--- + +###### **`outputs:trop_sinex:sol_type:`** + `"Solution parameters" ` + + +Troposphere SINEX solution type + +--- + +###### **`outputs:trop_sinex:sources:`** + [`[E_Source]`](#e_source) `[KALMAN] ` + + +Source for troposphere delay data - KALMAN, etc. [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`outputs:trop_sinex:version:`** + `2 ` + + +Troposphere SINEX version + +--- + +###### **`outputs:ionex:`** + ` ` + + +> IONEX formatted ionospheric mapping and modelling outputs + +--- + +###### **`outputs:ionex:output:`** + `false ` + + +Enable exporting ionospheric model data + +--- + +###### **`outputs:ionex:directory:`** + `"" ` + + +Directory to export ionex data + +--- + +###### **`outputs:ionex:filename:`** + `"/-.INX" ` + + +Ionex data filename + +--- + +###### **`outputs:ionex:grid:`** + ` ` + + +--- + +###### **`outputs:ionex:grid:lat_centre:`** + `0 ` + + +Center lattitude for models + +--- + +###### **`outputs:ionex:grid:lat_resolution:`** + `10 ` + + +Interval between lattitude outputs + +--- + +###### **`outputs:ionex:grid:lat_width:`** + `90 ` + + +Total lattitudinal width of model + +--- + +###### **`outputs:ionex:grid:lon_centre:`** + `0 ` + + +Center longitude for models + +--- + +###### **`outputs:ionex:grid:lon_resolution:`** + `10 ` + + +Interval between longitude outputs + +--- + +###### **`outputs:ionex:grid:lon_width:`** + `90 ` + + +Total longitudinal width of model + +--- + +###### **`outputs:ionex:grid:time_resolution:`** + `900 ` + + +Interval between output epochs + +--- + +###### **`outputs:ionstec:`** + ` ` + + +--- + +###### **`outputs:ionstec:output:`** + `false ` + + +--- + +###### **`outputs:ionstec:directory:`** + `"" ` + + +--- + +###### **`outputs:ionstec:filename:`** + `"/-.STEC" ` + + +--- + +###### **`outputs:orbit_ics:`** + ` ` + + +> Orbital parameters can be output in a yaml that Ginan can later use as an initial condition for futher processing. + +--- + +###### **`outputs:orbit_ics:directory:`** + `"" ` + + +Output orbital initial condition directory + +--- + +###### **`outputs:orbit_ics:filename:`** + `"/--orbits.yaml" ` + + +Output orbital initial condition filename + +--- + +###### **`outputs:orbit_ics:output:`** + `false ` + + +Output orbital initial condition file + +--- + +###### **`outputs:sbas_ems:`** + ` ` + + +--- + +###### **`outputs:sbas_ems:output:`** + `false ` + + +--- + +###### **`outputs:sbas_ems:directory:`** + `"" ` + + +--- + +###### **`outputs:sbas_ems:filename:`** + `"/y/d/h.ems" ` + + +--- + +###### **`outputs:network_statistics:`** + ` ` + + +--- + +###### **`outputs:network_statistics:output:`** + `false ` + + +Enable exporting network statistics data to file + +--- + +###### **`outputs:network_statistics:directory:`** + `"" ` + + +Directory to export network statistics data + +--- + +###### **`outputs:network_statistics:filename:`** + `"/-_network_statistics.json" ` + + +Network statistics data filename + +--- + +###### **`outputs:ntrip_log:`** + ` ` + + +--- + +###### **`outputs:ntrip_log:output:`** + `false ` + + +--- + +###### **`outputs:ntrip_log:directory:`** + `"" ` + + +--- + +###### **`outputs:ntrip_log:filename:`** + `"/ntrip_log-.json" ` + + +--- + +###### **`outputs:rinex_nav:`** + ` ` + + +--- + +###### **`outputs:rinex_nav:output:`** + `false ` + + +--- + +###### **`outputs:rinex_nav:directory:`** + `"" ` + + +--- + +###### **`outputs:rinex_nav:filename:`** + `"/-_nav_.rnx" ` + + +--- + +###### **`outputs:rinex_nav:version:`** + `3.05 ` + + +--- + +###### **`outputs:rinex_obs:`** + ` ` + + +--- + +###### **`outputs:rinex_obs:output:`** + `false ` + + +--- + +###### **`outputs:rinex_obs:directory:`** + `"" ` + + +--- + +###### **`outputs:rinex_obs:filename:`** + `"/-_.O" ` + + +--- + +###### **`outputs:rinex_obs:output_doppler:`** + `true ` + + +--- + +###### **`outputs:rinex_obs:output_phase_range:`** + `true ` + + +--- + +###### **`outputs:rinex_obs:output_pseudorange:`** + `true ` + + +--- + +###### **`outputs:rinex_obs:output_signal_to_noise:`** + `true ` + + +--- + +###### **`outputs:rinex_obs:version:`** + `3.05 ` + + +--- + +###### **`outputs:rtcm_nav:`** + ` ` + + +--- + +###### **`outputs:rtcm_nav:output:`** + `false ` + + +--- + +###### **`outputs:rtcm_nav:directory:`** + `"" ` + + +--- + +###### **`outputs:rtcm_nav:filename:`** + `"/--NAV.rtcm" ` + + +--- + +###### **`outputs:rtcm_obs:`** + ` ` + + +--- + +###### **`outputs:rtcm_obs:output:`** + `false ` + + +--- + +###### **`outputs:rtcm_obs:directory:`** + `"" ` + + +--- + +###### **`outputs:rtcm_obs:filename:`** + `"/--OBS.rtcm" ` + + +--- + +###### **`outputs:decoded_rtcm:`** + ` ` + + +> RTCM messages that are received may be recorded to human-readable json files + +--- + +###### **`outputs:decoded_rtcm:output:`** + `false ` + + +Enable exporting decoded RTCM data to file + +--- + +###### **`outputs:decoded_rtcm:directory:`** + `"" ` + + +Directory to export decoded RTCM data + +--- + +###### **`outputs:decoded_rtcm:filename:`** + `"/-_rtcm_decoded.json" ` + + +Decoded RTCM data filename + +--- + +###### **`outputs:encoded_rtcm:`** + ` ` + + +> RTCM messages that are encoded and transmitted may be recorded to human-readable json files + +--- + +###### **`outputs:encoded_rtcm:output:`** + `false ` + + +Enable exporting encoded RTCM data to file + +--- + +###### **`outputs:encoded_rtcm:directory:`** + `"" ` + + +Directory to export encoded RTCM data + +--- + +###### **`outputs:encoded_rtcm:filename:`** + `"/-_rtcm_encoded.json" ` + + +Encoded RTCM data filename + +--- + +###### **`outputs:raw_custom:`** + ` ` + + +--- + +###### **`outputs:raw_custom:output:`** + `false ` + + +--- + +###### **`outputs:raw_custom:directory:`** + `"" ` + + +--- + +###### **`outputs:raw_custom:filename:`** + `"/--OBS.custom" ` + + +--- + +###### **`outputs:raw_ubx:`** + ` ` + + +--- + +###### **`outputs:raw_ubx:output:`** + `false ` + + +--- + +###### **`outputs:raw_ubx:directory:`** + `"" ` + + +--- + +###### **`outputs:raw_ubx:filename:`** + `"/--OBS.rtcm" ` + + +--- + +###### **`outputs:slr_obs:`** + ` ` + + +> SLR_OBS files are used as temporary files to arrange SLR observations by time. SLR observations are taken from CRD files, which are not strictly in time-order). + +--- + +###### **`outputs:slr_obs:output:`** + `false ` + + +Enable data exporting to tabular SLR obs file + +--- + +###### **`outputs:slr_obs:directory:`** + `"" ` + + +Directory to export tabular SLR obs file + +--- + +###### **`outputs:slr_obs:filename:`** + `"/.slr_obs" ` + + +Tabular SLR obs filename + +--- + +## processing_options: + +###### **`processing_options:`** + ` ` + + +> Various sections and parameters to specify how the observations are processed + +--- + +###### **`processing_options:epoch_control:`** + ` ` + + +> Specifies the rate and duration of data processing + +--- + +###### **`processing_options:epoch_control:end_epoch:`** + `"" ` + + +(YYYY-MM-DD hh:mm:ss) The time of the last epoch to process (all observations after this will be skipped) + +--- + +###### **`processing_options:epoch_control:epoch_interval:`** + `1 ` + + +Desired time step between each processing epoch + +--- + +###### **`processing_options:epoch_control:max_epochs:`** + `0 ` + + +Maximum number of epochs to process + +--- + +###### **`processing_options:epoch_control:start_epoch:`** + `"" ` + + +(YYYY-MM-DD hh:mm:ss) The time of the first epoch to process (all observations before this will be skipped) + +--- + +###### **`processing_options:epoch_control:sleep_milliseconds:`** + `50 ` + + +Time to sleep before checking for new data - lower numbers are associated with high idle cpu usage + +--- + +###### **`processing_options:epoch_control:assign_closest_epoch:`** + `false ` + + +Assign observations to the closest epoch - don't skip observations that fall between epochs + +--- + +###### **`processing_options:epoch_control:epoch_tolerance:`** + `0.5 ` + + +Tolerance of times to add to an epoch (usually half of the original data's sample rate) + +--- + +###### **`processing_options:epoch_control:max_rec_latency:`** + `0 ` + + +Time to wait from the reception of the first data of an epoch before skipping receivers with data still unreceived + +--- + +###### **`processing_options:epoch_control:require_obs:`** + `true ` + + +Exit the program if no observation sources are available + +--- + +###### **`processing_options:epoch_control:simulate_real_time:`** + `false ` + + +For RTCM playback - delay processing to match original data rate + +--- + +###### **`processing_options:epoch_control:wait_next_epoch:`** + `0 ` + + +Time to wait for next epochs data before skipping the epoch (will default to epoch_interval as an appropriate minimum value for realtime) + +--- + +###### **`processing_options:gnss_general:`** + ` ` + + +> Options to specify the processing of gnss observations + +--- + +###### **`processing_options:gnss_general:sys_options:`** + ` ` + + +--- + +###### **`processing_options:gnss_general:sys_options:bds:`** + ` ` + + +> Options for the BDS constellation + +--- + +###### **`processing_options:gnss_general:sys_options:bds:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:bds:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:bds:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:bds:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:bds:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:bds:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:bds:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:bds:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `D1 ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:bds:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gal:`** + ` ` + + +> Options for the GAL constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gal:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gal:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:gal:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:gal:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:gal:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:gal:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:gal:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gal:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `INAV ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:gal:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:glo:`** + ` ` + + +> Options for the GLO constellation + +--- + +###### **`processing_options:gnss_general:sys_options:glo:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:glo:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:glo:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:glo:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:glo:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:glo:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:glo:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:glo:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `FDMA ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:glo:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gps:`** + ` ` + + +> Options for the GPS constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gps:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gps:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:gps:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:gps:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:gps:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:gps:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:gps:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:gps:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `LNAV ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:gps:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:leo:`** + ` ` + + +> Options for the LEO constellation + +--- + +###### **`processing_options:gnss_general:sys_options:leo:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:leo:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:leo:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:leo:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:leo:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:leo:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:leo:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:leo:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `NONE ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:leo:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:`** + ` ` + + +> Options for the QZS constellation + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `LNAV ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:qzs:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:`** + ` ` + + +> Options for the SBS constellation + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:process:`** + `false ` + + +Process this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:code_priorities:`** + [`[E_ObsCode]`](#e_obscode) `[L1C, L1P, L1Y, L1W, L1M, L1N, L1S, L1L, L1X, L2W, L2P, L2Y, L2C, L2M, L2N, L2D, L2S, L2L, L2X, L5I, L5Q, L5X] ` + + +List of observation codes to use in processing [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:network_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate network rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:receiver_amb_pivot:`** + `false ` + + +Constrain: set of ambiguities, to eliminate receiver rank deficiencies + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:reject_eclipse:`** + `false ` + + +Exclude satellites that are in eclipsing region + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:use_for_iono_model:`** + `false ` + + +Use this constellation as part of Ionospheric model + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:use_iono_corrections:`** + `false ` + + +Use external ionosphere delay estimation for this constellation + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:used_nav_type:`** + [`E_NavMsgType`](#e_navmsgtype) `NONE ` + + + {none, lnav, fdma, fnav, inav, ifnv, d1, d2, d1d2, sbas, cnav, cnv1, cnv2, cnv3, cnvx} + +--- + +###### **`processing_options:gnss_general:sys_options:sbs:ambiguity_resolution:`** + `false ` + + +Solve carrier phase ambiguities for this constellation + +--- + +###### **`processing_options:gnss_general:code_measurements:`** + ` ` + + +--- + +###### **`processing_options:gnss_general:code_measurements:process:`** + `true ` + + +Process code measurements + +--- + +###### **`processing_options:gnss_general:phase_measurements:`** + ` ` + + +--- + +###### **`processing_options:gnss_general:phase_measurements:process:`** + `true ` + + +Process phase measurements + +--- + +###### **`processing_options:gnss_general:add_eop_component:`** + `false ` + + +Add eop adjustments as a component in residual chain (for adjusting frames to match ecef ephemeris) + +--- + +###### **`processing_options:gnss_general:adjust_clocks_for_jumps_only:`** + `false ` + + +Round clock adjustments from SPP to half milliseconds + +--- + +###### **`processing_options:gnss_general:adjust_rec_clocks_by_spp:`** + `true ` + + +Adjust receiver clocks by spp values to minimise prefit residuals + +--- + +###### **`processing_options:gnss_general:auto_fill_pco:`** + `true ` + + +Use similar PCOs when requested values are not found + +--- + +###### **`processing_options:gnss_general:common_rec_pco:`** + `false ` + + +Use L1 receiver PCO values for all signals + +--- + +###### **`processing_options:gnss_general:common_sat_pco:`** + `false ` + + +Use L1 satellite PCO values for all signals + +--- + +###### **`processing_options:gnss_general:delete_old_ephemerides:`** + `true ` + + +Remove old ephemerides that have accumulated over time from before far before the currently processing epoch + +--- + +###### **`processing_options:gnss_general:equate_ionospheres:`** + `false ` + + +Use same STEC values for different receivers, useful for simulated rtk mode + +--- + +###### **`processing_options:gnss_general:equate_tropospheres:`** + `false ` + + +Use same troposphere values for different receivers, useful for simulated rtk mode + +--- + +###### **`processing_options:gnss_general:fixed_phase_bias_var:`** + `0.01 ` + + +Variance of phase bias to be considered fixed/binded + +--- + +###### **`processing_options:gnss_general:gpst_utc_leap_seconds:`** + `-1 ` + + +Difference between gps time and utc in leap seconds + +--- + +###### **`processing_options:gnss_general:interpolate_rec_pco:`** + `true ` + + +Interpolate other known pco values to find pco for unknown frequencies + +--- + +###### **`processing_options:gnss_general:minimise_ionosphere_offsets:`** + `false ` + + +Apply gauss-markov mu values to stec values to minimise offsets with respect to klobuchar values + +--- + +###### **`processing_options:gnss_general:minimise_sat_clock_offsets:`** + `false ` + + +Apply gauss-markov mu values to satellite clocks to minimise offsets with respect to broadcast values + +--- + +###### **`processing_options:gnss_general:minimise_sat_orbit_offsets:`** + `false ` + + +Apply gauss-markov mu values to satellite orbits to minimise offsets with respect to broadcast values + +--- + +###### **`processing_options:gnss_general:pivot_receiver:`** + `"NO_PIVOT" ` + + +Largely deprecated id of receiver to use for pivot constraints + +--- + +###### **`processing_options:gnss_general:pivot_satellite:`** + `"NO_PIVOT" ` + + +Largely deprecated id of satellite to use for pivot constraints + +--- + +###### **`processing_options:gnss_general:require_antenna_details:`** + `false ` + + +Restrict processing to receivers that have antenna details + +--- + +###### **`processing_options:gnss_general:require_apriori_positions:`** + `false ` + + +Restrict processing to receivers that have apriori positions available + +--- + +###### **`processing_options:gnss_general:require_reflector_com:`** + `false ` + + +Restrict processing to SLR observations that have center of mass to laser retroreflector array offsets + +--- + +###### **`processing_options:gnss_general:require_sinex_data:`** + `false ` + + +Restrict processing to receivers that have sinex data available + +--- + +###### **`processing_options:gnss_general:require_site_eccentricity:`** + `false ` + + +Restrict processing to receivers that have site eccentricity information + +--- + +###### **`processing_options:gnss_general:use_rtk_combo:`** + `false ` + + +Combine applicable observations to simulate an rtk solution + +--- + +###### **`processing_options:gnss_general:use_tgd_bias:`** + `false ` + + +Use TGD/BGD bias from ephemeris, DO NOT turn on unless using Klobuchar/NeQuick Ionospheres + +--- + +###### **`processing_options:process_modes:`** + ` ` + + +> Aspects of the processing flow may be enabled and disabled according to desired type of solutions + +--- + +###### **`processing_options:process_modes:ppp:`** + `false ` + + +Perform PPP network or end user mode + +--- + +###### **`processing_options:process_modes:preprocessor:`** + `true ` + + +Preprocessing and quality checks + +--- + +###### **`processing_options:process_modes:spp:`** + `true ` + + +Perform SPP on receiver data + +--- + +###### **`processing_options:process_modes:ionosphere:`** + `false ` + + +Compute Ionosphere models based on GNSS measurements + +--- + +###### **`processing_options:process_modes:slr:`** + `false ` + + +Process SLR observations + +--- + +###### **`processing_options:spp:`** + ` ` + + +> Configurations for the kalman filter and its sub processes + +--- + +###### **`processing_options:spp:max_lsq_iterations:`** + `12 ` + + +Maximum number of iterations of least squares allowed for convergence + +--- + +###### **`processing_options:spp:outlier_screening:`** + ` ` + + +> Statistical checks allow for detection of outliers that exceed their confidence intervals. + +--- + +###### **`processing_options:spp:outlier_screening:chi_square:`** + ` ` + + +--- + +###### **`processing_options:spp:outlier_screening:chi_square:enable:`** + `false ` + + +Enable Chi-square test + +--- + +###### **`processing_options:spp:outlier_screening:chi_square:mode:`** + [`E_ChiSqMode`](#e_chisqmode) `INNOVATION ` + + +Chi-square test mode {innovation, measurement, state} + +--- + +###### **`processing_options:spp:outlier_screening:chi_square:sigma_threshold:`** + `4 ` + + +Chi-square test threshold in terms of 'times of sigma' + +--- + +###### **`processing_options:spp:outlier_screening:postfit:`** + ` ` + + +--- + +###### **`processing_options:spp:outlier_screening:postfit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using postfit checks while iterating filter + +--- + +###### **`processing_options:spp:outlier_screening:postfit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:spp:outlier_screening:postfit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:spp:outlier_screening:postfit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:spp:outlier_screening:postfit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:spp:outlier_screening:prefit:`** + ` ` + + +--- + +###### **`processing_options:spp:outlier_screening:prefit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using prefit checks before attempting to filter + +--- + +###### **`processing_options:spp:outlier_screening:prefit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:spp:outlier_screening:prefit:omega_test:`** + `false ` + + +Enable omega-test + +--- + +###### **`processing_options:spp:outlier_screening:prefit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:spp:outlier_screening:prefit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:spp:outlier_screening:prefit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:spp:outlier_screening:max_gdop:`** + `30 ` + + +Maximum dilution of precision before error is flagged + +--- + +###### **`processing_options:spp:outlier_screening:raim:`** + `true ` + + +Enable Receiver Autonomous Integrity Monitoring. When SPP fails further SPP solutions are calculated with subsets of observations with the aim of eliminating a problem satellite + +--- + +###### **`processing_options:spp:sigma_scaling:`** + `1 ` + + +Scale applied to measurement noise for spp + +--- + +###### **`processing_options:spp:always_reinitialise:`** + `false ` + + +Reset SPP state to zero to avoid potential for lock-in of bad states + +--- + +###### **`processing_options:spp:iono_mode:`** + [`E_IonoMode`](#e_ionomode) `IONO_FREE_LINEAR_COMBO ` + + + {off, broadcast, sbas, iono_free_linear_combo, estimate, total_electron_content, qzs, lex, stec} + +--- + +###### **`processing_options:preprocessor:`** + ` ` + + +> Configurations for the kalman filter and its sub processes + +--- + +###### **`processing_options:preprocessor:cycle_slips:`** + ` ` + + +> Cycle slips may be detected by the preprocessor and measurements rejected or ambiguities reinitialised + +--- + +###### **`processing_options:preprocessor:cycle_slips:mw_process_noise:`** + `0 ` + + +Process noise applied to filtered Melbourne-Wubenna measurements to detect cycle slips + +--- + +###### **`processing_options:preprocessor:cycle_slips:slip_threshold:`** + `0.05 ` + + +Value used to determine when a slip has occurred + +--- + +###### **`processing_options:preprocessor:preprocess_all_data:`** + `true ` + + +--- + +###### **`processing_options:ppp_filter:`** + ` ` + + +> Configurations for the kalman filter and its sub processes + +--- + +###### **`processing_options:ppp_filter:ionospheric_components:`** + ` ` + + +> Slant ionospheric components + +--- + +###### **`processing_options:ppp_filter:ionospheric_components:common_ionosphere:`** + `true ` + + +Use the same ionosphere state for code and phase observations + +--- + +###### **`processing_options:ppp_filter:ionospheric_components:use_gf_combo:`** + `false ` + + +Combine 'uncombined' measurements to simulate a geometry-free solution + +--- + +###### **`processing_options:ppp_filter:ionospheric_components:use_if_combo:`** + `false ` + + +Combine 'uncombined' measurements to simulate an ionosphere-free solution + +--- + +###### **`processing_options:ppp_filter:ionospheric_components:corr_mode:`** + [`E_IonoMode`](#e_ionomode) `BROADCAST ` + + + {off, broadcast, sbas, iono_free_linear_combo, estimate, total_electron_content, qzs, lex, stec} + +--- + +###### **`processing_options:ppp_filter:outlier_screening:`** + ` ` + + +> Statistical checks allow for detection of outliers that exceed their confidence intervals. + +--- + +###### **`processing_options:ppp_filter:outlier_screening:chi_square:`** + ` ` + + +--- + +###### **`processing_options:ppp_filter:outlier_screening:chi_square:enable:`** + `false ` + + +Enable Chi-square test + +--- + +###### **`processing_options:ppp_filter:outlier_screening:chi_square:mode:`** + [`E_ChiSqMode`](#e_chisqmode) `INNOVATION ` + + +Chi-square test mode {innovation, measurement, state} + +--- + +###### **`processing_options:ppp_filter:outlier_screening:chi_square:sigma_threshold:`** + `4 ` + + +Chi-square test threshold in terms of 'times of sigma' + +--- + +###### **`processing_options:ppp_filter:outlier_screening:postfit:`** + ` ` + + +--- + +###### **`processing_options:ppp_filter:outlier_screening:postfit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using postfit checks while iterating filter + +--- + +###### **`processing_options:ppp_filter:outlier_screening:postfit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:ppp_filter:outlier_screening:postfit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:ppp_filter:outlier_screening:postfit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:ppp_filter:outlier_screening:postfit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:`** + ` ` + + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using prefit checks before attempting to filter + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:omega_test:`** + `false ` + + +Enable omega-test + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:ppp_filter:outlier_screening:prefit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:ppp_filter:advanced_postfits:`** + `false ` + + +Use alternate calculation method to determine postfit residuals + +--- + +###### **`processing_options:ppp_filter:assume_linearity:`** + `false ` + + +Residuals will be adjusted during measurement combination rather than performing 2 seperate state transitions + +--- + +###### **`processing_options:ppp_filter:chunking:`** + ` ` + + +--- + +###### **`processing_options:ppp_filter:chunking:by_receiver:`** + `false ` + + +Split large filter and measurement matrices blockwise by receiver ID to improve processing speed + +--- + +###### **`processing_options:ppp_filter:chunking:by_satellite:`** + `false ` + + +Split large filter and measurement matrices blockwise by satellite ID to improve processing speed + +--- + +###### **`processing_options:ppp_filter:chunking:size:`** + `0 ` + + +--- + +###### **`processing_options:ppp_filter:inverter:`** + [`E_Inverter`](#e_inverter) `LDLT ` + + +Inverter to be used within the Kalman filter update stage, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} + +--- + +###### **`processing_options:ppp_filter:joseph_stabilisation:`** + `false ` + + +--- + +###### **`processing_options:ppp_filter:periodic_reset:`** + ` ` + + +--- + +###### **`processing_options:ppp_filter:periodic_reset:enable:`** + `false ` + + +Enable periodic reset of filter states + +--- + +###### **`processing_options:ppp_filter:periodic_reset:interval:`** + `86400 ` + + +Interval between reset of filter states + +--- + +###### **`processing_options:ppp_filter:periodic_reset:states:`** + [`[KF]`](#kf) `[ALL] ` + + +States to remove for periodic reset [none, one, all, rec_pos, rec_vel, rec_pos_rate, rec_acc, strain_rate, pos, vel, acc, heading, orientation, ref_sys_bias, rec_clock, rec_sys_bias, rec_clock_rate, rec_sys_bias_rate, rec_clock_rate_gm, rec_sys_bias_rate_gm, sat_clock, sat_clock_rate, sat_clock_rate_gm, trop, trop_grad, trop_model, ionospheric, iono_stec, rec_pco_x, rec_pco_y, rec_pco_z, sat_pco_x, sat_pco_y, sat_pco_z, rec_pcv, ant_delta, eop, eop_rate, calc, slr_rec_range_bias, slr_rec_time_bias, xform_xlate, xform_rtate, xform_scale, xform_delay, ambiguity, code_bias, phase_bias, z_amb, reference, begin_meas_states, code_meas, phas_meas, laser_meas, pseudo_meas, orbit_meas, filter_meas, end_meas_states, begin_orbit_states, orbit, emp_d_0, emp_d_1, emp_d_2, emp_d_3, emp_d_4, emp_y_0, emp_y_1, emp_y_2, emp_y_3, emp_y_4, emp_b_0, emp_b_1, emp_b_2, emp_b_3, emp_b_4, emp_r_0, emp_r_1, emp_r_2, emp_r_3, emp_r_4, emp_t_0, emp_t_1, emp_t_2, emp_t_3, emp_t_4, emp_n_0, emp_n_1, emp_n_2, emp_n_3, emp_n_4, emp_p_0, emp_p_1, emp_p_2, emp_p_3, emp_p_4, emp_q_0, emp_q_1, emp_q_2, emp_q_3, emp_q_4, end_orbit_states, begin_inertial_states, gyro_bias, gyro_scale, accl_bias, accl_scale, imu_offset, end_inertial_states, range] + +--- + +###### **`processing_options:ppp_filter:rts:`** + ` ` + + +> RTS allows reverse smoothing of estimates such that early estimates can make use of later data. + +--- + +###### **`processing_options:ppp_filter:rts:interval:`** + `0 ` + + +Number of seconds to use between fixed lag in RTS smoothing. + +--- + +###### **`processing_options:ppp_filter:rts:enable:`** + `false ` + + +Perform backward smoothing of states to improve precision of earlier states + +--- + +###### **`processing_options:ppp_filter:rts:lag:`** + `-1 ` + + +Number of epochs to use in RTS smoothing. Negative numbers indicate full reverse smoothing. + +--- + +###### **`processing_options:ppp_filter:rts:directory:`** + `"" ` + + +Directory for rts intermediate files + +--- + +###### **`processing_options:ppp_filter:rts:filename:`** + `"Filter--.rts" ` + + +Base filename for rts intermediate files + +--- + +###### **`processing_options:ppp_filter:rts:inverter:`** + [`E_Inverter`](#e_inverter) `LDLT ` + + +Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} + +--- + +###### **`processing_options:ppp_filter:rts:output_intermediates:`** + `false ` + + +Output best available smoothed states when performing fixed-lag rts (slow, use only when needed) + +--- + +###### **`processing_options:ppp_filter:rts:queue_outputs:`** + `false ` + + +Queue rts outputs so that processing is not limited by IO bandwidth + +--- + +###### **`processing_options:ppp_filter:rts:suffix:`** + `"_smoothed" ` + + +Suffix to be applied to smoothed versions of files + +--- + +###### **`processing_options:ppp_filter:simulate_filter_only:`** + `false ` + + +Residuals will be calculated, but no adjustments to state or covariances will be applied + +--- + +###### **`processing_options:minimum_constraints:`** + ` ` + + +> Receiver coodinates may be aligned to reference frames with minimal external constraints + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:`** + ` ` + + +> Statistical checks allow for detection of outliers that exceed their confidence intervals. + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:chi_square:`** + ` ` + + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:chi_square:enable:`** + `false ` + + +Enable Chi-square test + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:chi_square:mode:`** + [`E_ChiSqMode`](#e_chisqmode) `INNOVATION ` + + +Chi-square test mode {innovation, measurement, state} + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:chi_square:sigma_threshold:`** + `4 ` + + +Chi-square test threshold in terms of 'times of sigma' + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:postfit:`** + ` ` + + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:postfit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using postfit checks while iterating filter + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:postfit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:postfit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:postfit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:postfit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:`** + ` ` + + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using prefit checks before attempting to filter + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:omega_test:`** + `false ` + + +Enable omega-test + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:minimum_constraints:outlier_screening:prefit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:minimum_constraints:advanced_postfits:`** + `false ` + + +Use alternate calculation method to determine postfit residuals + +--- + +###### **`processing_options:minimum_constraints:enable:`** + `false ` + + +Transform states by minimal constraints to selected receiver coordinates + +--- + +###### **`processing_options:minimum_constraints:delay:`** + ` ` + + +> Estimation and application of clock delay adjustment + +--- + +###### **`processing_options:minimum_constraints:delay:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`processing_options:minimum_constraints:delay:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`processing_options:minimum_constraints:delay:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`processing_options:minimum_constraints:delay:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`processing_options:minimum_constraints:delay:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`processing_options:minimum_constraints:delay:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`processing_options:minimum_constraints:delay:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`processing_options:minimum_constraints:delay:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`processing_options:minimum_constraints:delay:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`processing_options:minimum_constraints:rotation:`** + ` ` + + +> Estimation and application of angular offsets + +--- + +###### **`processing_options:minimum_constraints:rotation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`processing_options:minimum_constraints:rotation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`processing_options:minimum_constraints:rotation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`processing_options:minimum_constraints:rotation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`processing_options:minimum_constraints:rotation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`processing_options:minimum_constraints:rotation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`processing_options:minimum_constraints:rotation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`processing_options:minimum_constraints:rotation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`processing_options:minimum_constraints:rotation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`processing_options:minimum_constraints:scale:`** + ` ` + + +> Estimation and application of scaling factor + +--- + +###### **`processing_options:minimum_constraints:scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`processing_options:minimum_constraints:scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`processing_options:minimum_constraints:scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`processing_options:minimum_constraints:scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`processing_options:minimum_constraints:scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`processing_options:minimum_constraints:scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`processing_options:minimum_constraints:scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`processing_options:minimum_constraints:scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`processing_options:minimum_constraints:scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`processing_options:minimum_constraints:translation:`** + ` ` + + +> Estimation and application of CoG offsets + +--- + +###### **`processing_options:minimum_constraints:translation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`processing_options:minimum_constraints:translation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`processing_options:minimum_constraints:translation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`processing_options:minimum_constraints:translation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`processing_options:minimum_constraints:translation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`processing_options:minimum_constraints:translation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`processing_options:minimum_constraints:translation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`processing_options:minimum_constraints:translation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`processing_options:minimum_constraints:translation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`processing_options:minimum_constraints:application_mode:`** + [`E_Mincon`](#e_mincon) `COVARIANCE_INVERSE ` + + +Method of transforming positions {pseudo_obs, weight_matrix, variance_inverse, covariance_inverse} + +--- + +###### **`processing_options:minimum_constraints:constrain_orbits:`** + `true ` + + +Enforce rigid transformations of orbital states + +--- + +###### **`processing_options:minimum_constraints:full_vcv:`** + `false ` + + +! experimental ! Use full VCV for measurement noise in minimum constraints filter + +--- + +###### **`processing_options:minimum_constraints:once_per_epoch:`** + `false ` + + +Perform minimum constraints on a temporary filter and output results once per epoch + +--- + +###### **`processing_options:minimum_constraints:transform_unweighted:`** + `true ` + + +Add design entries for transformation of positions without weighting + +--- + +###### **`processing_options:minimum_constraints:inverter:`** + [`E_Inverter`](#e_inverter) `LDLT ` + + +Inverter to be used within the Kalman filter update stage, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} + +--- + +###### **`processing_options:minimum_constraints:joseph_stabilisation:`** + `false ` + + +--- + +###### **`processing_options:minimum_constraints:rts:`** + ` ` + + +> RTS allows reverse smoothing of estimates such that early estimates can make use of later data. + +--- + +###### **`processing_options:minimum_constraints:rts:interval:`** + `0 ` + + +Number of seconds to use between fixed lag in RTS smoothing. + +--- + +###### **`processing_options:minimum_constraints:rts:enable:`** + `false ` + + +Perform backward smoothing of states to improve precision of earlier states + +--- + +###### **`processing_options:minimum_constraints:rts:lag:`** + `-1 ` + + +Number of epochs to use in RTS smoothing. Negative numbers indicate full reverse smoothing. + +--- + +###### **`processing_options:minimum_constraints:rts:directory:`** + `"" ` + + +Directory for rts intermediate files + +--- + +###### **`processing_options:minimum_constraints:rts:filename:`** + `"Filter--.rts" ` + + +Base filename for rts intermediate files + +--- + +###### **`processing_options:minimum_constraints:rts:inverter:`** + [`E_Inverter`](#e_inverter) `LDLT ` + + +Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} + +--- + +###### **`processing_options:minimum_constraints:rts:output_intermediates:`** + `false ` + + +Output best available smoothed states when performing fixed-lag rts (slow, use only when needed) + +--- + +###### **`processing_options:minimum_constraints:rts:queue_outputs:`** + `false ` + + +Queue rts outputs so that processing is not limited by IO bandwidth + +--- + +###### **`processing_options:minimum_constraints:rts:suffix:`** + `"_smoothed" ` + + +Suffix to be applied to smoothed versions of files + +--- + +###### **`processing_options:model_error_handling:`** + ` ` + + +> The kalman filter is capable of automatic statistical integrity modelling + +--- + +###### **`processing_options:model_error_handling:error_accumulation:`** + ` ` + + +> Any receivers that are consistently getting many measurement rejections may be reinitialiased + +--- + +###### **`processing_options:model_error_handling:error_accumulation:enable:`** + `true ` + + +Enable reinitialisation of receivers upon many rejections + +--- + +###### **`processing_options:model_error_handling:error_accumulation:receiver_error_count_threshold:`** + `4 ` + + +Number of errors for a receiver to be considered in error for a single epoch + +--- + +###### **`processing_options:model_error_handling:error_accumulation:receiver_error_epochs_threshold:`** + `4 ` + + +Number of consecutive epochs with receiver in error before it is removed and reinitialised + +--- + +###### **`processing_options:model_error_handling:meas_deweighting:`** + ` ` + + +> Measurements that are outside the expected confidence bounds may be deweighted so that outliers do not contaminate the filtered solution + +--- + +###### **`processing_options:model_error_handling:meas_deweighting:deweight_factor:`** + `1000 ` + + +Factor to downweight the variance of measurements with statistically detected errors + +--- + +###### **`processing_options:model_error_handling:meas_deweighting:enable:`** + `true ` + + +Enable deweighting of all rejected measurement + +--- + +###### **`processing_options:model_error_handling:state_deweighting:`** + ` ` + + +> Any "state" errors cause deweighting of all measurements that reference the state + +--- + +###### **`processing_options:model_error_handling:state_deweighting:deweight_factor:`** + `1000 ` + + +Factor to downweight the variance of measurements with statistically detected errors + +--- + +###### **`processing_options:model_error_handling:state_deweighting:enable:`** + `true ` + + +Enable deweighting of all referencing measurements + +--- + +###### **`processing_options:model_error_handling:ambiguities:`** + ` ` + + +> Cycle slips in ambiguities are primary cause of incorrect gnss modelling and may be reinitialised + +--- + +###### **`processing_options:model_error_handling:ambiguities:outage_reset_limit:`** + `300 ` + + +Maximum number of seconds without phase measurements before the ambiguity associated with the measurement is reset. + +--- + +###### **`processing_options:model_error_handling:ambiguities:phase_reject_limit:`** + `10 ` + + +Maximum number of phase measurements to reject before the ambiguity associated with the measurement is reset. + +--- + +###### **`processing_options:model_error_handling:ambiguities:reset_on:`** + ` ` + + +--- + +###### **`processing_options:model_error_handling:ambiguities:reset_on:gf:`** + `true ` + + +Reset ambiguities if GF test is detecting a slip + +--- + +###### **`processing_options:model_error_handling:ambiguities:reset_on:lli:`** + `true ` + + +Reset ambiguities if LLI test is detecting a slip + +--- + +###### **`processing_options:model_error_handling:ambiguities:reset_on:mw:`** + `true ` + + +Reset ambiguities if MW test is detecting a slip + +--- + +###### **`processing_options:model_error_handling:ambiguities:reset_on:scdia:`** + `true ` + + +Reset ambiguities if SCDIA test is detecting a slip + +--- + +###### **`processing_options:model_error_handling:ionospheric_components:`** + ` ` + + +--- + +###### **`processing_options:model_error_handling:ionospheric_components:outage_reset_limit:`** + `300 ` + + +Maximum number of seconds without measurements before the ionosphere associated with the measurement is reset. + +--- + +###### **`processing_options:model_error_handling:exclusions:`** + ` ` + + +> Cycle slips may be detected by the preprocessor and measurements rejected or ambiguities reinitialised + +--- + +###### **`processing_options:model_error_handling:exclusions:bad_spp:`** + `true ` + + +Exclude measurements that were associated with failed SPP + +--- + +###### **`processing_options:model_error_handling:exclusions:config:`** + `true ` + + +Exclude measurements that are configured as exclusions + +--- + +###### **`processing_options:model_error_handling:exclusions:eclipse:`** + `true ` + + +Exclude measurements that are in eclipse + +--- + +###### **`processing_options:model_error_handling:exclusions:elevation:`** + `true ` + + +Exclude measurements that fall below elevation mask + +--- + +###### **`processing_options:model_error_handling:exclusions:gf:`** + `true ` + + +Exclude measurements that fail GF slip test in preprocessor + +--- + +###### **`processing_options:model_error_handling:exclusions:lli:`** + `true ` + + +Exclude measurements that fail LLI slip test in preprocessor + +--- + +###### **`processing_options:model_error_handling:exclusions:mw:`** + `true ` + + +Exclude measurements that fail MW slip test in preprocessor + +--- + +###### **`processing_options:model_error_handling:exclusions:outlier:`** + `true ` + + +Exclude measurements that were rejected as SPP outliers + +--- + +###### **`processing_options:model_error_handling:exclusions:scdia:`** + `true ` + + +Exclude measurements that fail SCDIA test in preprocessor + +--- + +###### **`processing_options:model_error_handling:exclusions:svh:`** + `true ` + + +Exclude measurements that are not specified as healthy + +--- + +###### **`processing_options:model_error_handling:exclusions:system:`** + `true ` + + +Exclude measurements that have been excluded by system configs + +--- + +###### **`processing_options:model_error_handling:orbit_errors:`** + ` ` + + +> Orbital states that are not consistent with measurements may be reinitialised to allow for dynamic maneuvers + +--- + +###### **`processing_options:model_error_handling:orbit_errors:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`processing_options:model_error_handling:orbit_errors:pos_process_noise:`** + `10 ` + + +Sigma to apply to orbital position states as reinitialisation + +--- + +###### **`processing_options:model_error_handling:orbit_errors:vel_process_noise:`** + `5 ` + + +Sigma to apply to orbital velocity states as reinitialisation + +--- + +###### **`processing_options:model_error_handling:orbit_errors:vel_process_noise_trail:`** + `1 ` + + +Initial sigma for exponentially decaying noise to apply for subsequent epochs as soft reinitialisation + +--- + +###### **`processing_options:model_error_handling:orbit_errors:vel_process_noise_trail_tau:`** + `0.05 ` + + +Time constant for exponentially decauing noise + +--- + +###### **`processing_options:ambiguity_resolution:`** + ` ` + + +--- + +###### **`processing_options:ambiguity_resolution:elevation_mask:`** + `15 ` + + +Minimum satellite elevation to perform ambiguity resolution + +--- + +###### **`processing_options:ambiguity_resolution:fix_and_hold:`** + `false ` + + +Perform ambiguity resolution and commit results to the main processing filter + +--- + +###### **`processing_options:ambiguity_resolution:lambda_set_size:`** + `2 ` + + +Maximum numer of candidate sets to be used in lambda_alt2 and lambda_bie modes + +--- + +###### **`processing_options:ambiguity_resolution:max_rounding_iterations:`** + `1 ` + + +Maximum number of rounding iterations performed in iter_rnd and bootst modes + +--- + +###### **`processing_options:ambiguity_resolution:mode:`** + [`E_ARmode`](#e_armode) `OFF ` + + + {off, round, iter_rnd, bootst, lambda, lambda_alt, lambda_al2, lambda_bie} + +--- + +###### **`processing_options:ambiguity_resolution:once_per_epoch:`** + `true ` + + +Perform ambiguity resolution on a temporary filter and output results once per epoch + +--- + +###### **`processing_options:ambiguity_resolution:solution_ratio_threshold:`** + `3 ` + + +Thresold for integer validation, distance ratio test. + +--- + +###### **`processing_options:ambiguity_resolution:success_rate_threshold:`** + `0.9999 ` + + +Thresold for integer validation, success rate test. + +--- + +###### **`processing_options:ion_filter:`** + ` ` + + +> Configurations for the ionospheric model kalman filter and its sub processes + +--- + +###### **`processing_options:ion_filter:outlier_screening:`** + ` ` + + +> Statistical checks allow for detection of outliers that exceed their confidence intervals. + +--- + +###### **`processing_options:ion_filter:outlier_screening:chi_square:`** + ` ` + + +--- + +###### **`processing_options:ion_filter:outlier_screening:chi_square:enable:`** + `false ` + + +Enable Chi-square test + +--- + +###### **`processing_options:ion_filter:outlier_screening:chi_square:mode:`** + [`E_ChiSqMode`](#e_chisqmode) `INNOVATION ` + + +Chi-square test mode {innovation, measurement, state} + +--- + +###### **`processing_options:ion_filter:outlier_screening:chi_square:sigma_threshold:`** + `4 ` + + +Chi-square test threshold in terms of 'times of sigma' + +--- + +###### **`processing_options:ion_filter:outlier_screening:postfit:`** + ` ` + + +--- + +###### **`processing_options:ion_filter:outlier_screening:postfit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using postfit checks while iterating filter + +--- + +###### **`processing_options:ion_filter:outlier_screening:postfit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:ion_filter:outlier_screening:postfit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:ion_filter:outlier_screening:postfit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:ion_filter:outlier_screening:postfit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:`** + ` ` + + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:max_iterations:`** + `2 ` + + +Maximum number of measurements to exclude using prefit checks before attempting to filter + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:meas_sigma_threshold:`** + `4 ` + + +Sigma threshold for measurements + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:omega_test:`** + `false ` + + +Enable omega-test + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:sigma_check:`** + `true ` + + +Enable sigma check + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:sigma_threshold:`** + `4 ` + + +Sigma threshold + +--- + +###### **`processing_options:ion_filter:outlier_screening:prefit:state_sigma_threshold:`** + `4 ` + + +Sigma threshold for states + +--- + +###### **`processing_options:ion_filter:advanced_postfits:`** + `false ` + + +Use alternate calculation method to determine postfit residuals + +--- + +###### **`processing_options:ion_filter:estimate_sat_dcb:`** + `true ` + + +Estimate satellite dcb alongside Ionosphere models, should be false for local STEC + +--- + +###### **`processing_options:ion_filter:function_degree:`** + `0 ` + + +Maximum degree of Spherical harmonics for Ionospheric mapping + +--- + +###### **`processing_options:ion_filter:function_order:`** + `0 ` + + +Maximum order of Spherical harmonics for Ionospheric mapping + +--- + +###### **`processing_options:ion_filter:inverter:`** + [`E_Inverter`](#e_inverter) `LDLT ` + + +Inverter to be used within the Kalman filter update stage, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} + +--- + +###### **`processing_options:ion_filter:joseph_stabilisation:`** + `false ` + + +--- + +###### **`processing_options:ion_filter:layer_heights:`** + `[] ` + + +List of heights of ionosphere layers to estimate + +--- + +###### **`processing_options:ion_filter:model:`** + [`E_IonoModel`](#e_ionomodel) `NONE ` + + + {none, meas_out, bspline, spherical_caps, spherical_harmonics, local} + +--- + +###### **`processing_options:ion_filter:model_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`processing_options:ion_filter:rts:`** + ` ` + + +> RTS allows reverse smoothing of estimates such that early estimates can make use of later data. + +--- + +###### **`processing_options:ion_filter:rts:interval:`** + `0 ` + + +Number of seconds to use between fixed lag in RTS smoothing. + +--- + +###### **`processing_options:ion_filter:rts:enable:`** + `false ` + + +Perform backward smoothing of states to improve precision of earlier states + +--- + +###### **`processing_options:ion_filter:rts:lag:`** + `-1 ` + + +Number of epochs to use in RTS smoothing. Negative numbers indicate full reverse smoothing. + +--- + +###### **`processing_options:ion_filter:rts:directory:`** + `"" ` + + +Directory for rts intermediate files + +--- + +###### **`processing_options:ion_filter:rts:filename:`** + `"Filter--.rts" ` + + +Base filename for rts intermediate files + +--- + +###### **`processing_options:ion_filter:rts:inverter:`** + [`E_Inverter`](#e_inverter) `LDLT ` + + +Inverter to be used within the rts processor, which may provide different performance outcomes in terms of processing time and accuracy and stability. {none, inv, llt, ldlt, colpivhqr, bdcsvd, jacobisvd, fullpivlu, first_unsupported, fullpivhqr} + +--- + +###### **`processing_options:ion_filter:rts:output_intermediates:`** + `false ` + + +Output best available smoothed states when performing fixed-lag rts (slow, use only when needed) + +--- + +###### **`processing_options:ion_filter:rts:queue_outputs:`** + `false ` + + +Queue rts outputs so that processing is not limited by IO bandwidth + +--- + +###### **`processing_options:ion_filter:rts:suffix:`** + `"_smoothed" ` + + +Suffix to be applied to smoothed versions of files + +--- + +###### **`processing_options:ion_filter:use_rotation_mtx:`** + `false ` + + +Use 3D rotation matrix for spherical harmonics to maintain orientation toward the sun + +--- + +###### **`processing_options:orbit_propagation:`** + ` ` + + +--- + +###### **`processing_options:orbit_propagation:aod:`** + `false ` + + +Model Atmospheric and Oceanic non tidal accelerations + +--- + +###### **`processing_options:orbit_propagation:atm_tide:`** + `false ` + + +Model accelerations due to atmospheric tides model + +--- + +###### **`processing_options:orbit_propagation:central_force:`** + `true ` + + +Acceleration due to the central force + +--- + +###### **`processing_options:orbit_propagation:egm_degree:`** + `12 ` + + +Degree of spherical harmonics gravity model + +--- + +###### **`processing_options:orbit_propagation:egm_field:`** + `true ` + + +Acceleration due to the high degree model of the Earth gravity model (exclude degree 0, made by central_force) + +--- + +###### **`processing_options:orbit_propagation:general_relativity:`** + `true ` + + +Model acceleration due general relativisty + +--- + +###### **`processing_options:orbit_propagation:indirect_j2:`** + `true ` + + +J2 acceleration perturbation due to the Sun and Moon + +--- + +###### **`processing_options:orbit_propagation:integrator_time_step:`** + `60 ` + + +Timestep for the integrator, must be smaller than the processing time step, might be adjusted if the processing time step isn't a integer number of time steps + +--- + +###### **`processing_options:orbit_propagation:ocean_tide:`** + `true ` + + +Model accelerations due to ocean tides model + +--- + +###### **`processing_options:orbit_propagation:pole_tide_ocean:`** + `true ` + + +Model accelerations due to ocean pole tide (degree 2 only) + +--- + +###### **`processing_options:orbit_propagation:pole_tide_solid:`** + `true ` + + +Model accelerations due to solid pole tide (degree 2 only) + +--- + +###### **`processing_options:orbit_propagation:solid_earth_tide:`** + `true ` + + +Model accelerations due to solid earth tides + +--- + +###### **`processing_options:predictions:`** + ` ` + + +--- + +###### **`processing_options:predictions:forward_duration:`** + `300 ` + + +--- + +###### **`processing_options:predictions:interval:`** + `30 ` + + +--- + +###### **`processing_options:predictions:offset:`** + `0 ` + + +--- + +###### **`processing_options:predictions:reverse_duration:`** + `-1 ` + + +--- + +###### **`processing_options:predictions:duration_units:`** + [`E_Period`](#e_period) `SECOND ` + + + {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`processing_options:predictions:interval_units:`** + [`E_Period`](#e_period) `SECOND ` + + + {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +## receiver_options: + +###### **`receiver_options:`** + ` ` + + +> Options to configure individual satellites, systems, or global configs + +--- + +###### **`receiver_options:global:`** + ` ` + + +--- + +###### **`receiver_options:global:elevation_mask:`** + `10 ` + + +Minimum elevation for satellites to be processed + +--- + +###### **`receiver_options:global:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`receiver_options:global:kill:`** + `false ` + + +Remove receiver from future processing + +--- + +###### **`receiver_options:global:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`receiver_options:global:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`receiver_options:global:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `ELEVATION_DEPENDENT ` + + + {uniform, elevation_dependent} + +--- + +###### **`receiver_options:global:code_sigma:`** + `1 ` + + +Standard deviation of code measurements + +--- + +###### **`receiver_options:global:phase_sigma:`** + `0.0015 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`receiver_options:global:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:global:zero_dcb_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + + [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:global:antenna_type:`** + `"" ` + + +Antenna type and radome in 20 character string as per sinex + +--- + +###### **`receiver_options:global:apriori_position:`** + `[] ` + + +Apriori position in XYZ ECEF frame + +--- + +###### **`receiver_options:global:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`receiver_options:global:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:global:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:global:receiver_type:`** + `"" ` + + +Type of gnss receiver hardware + +--- + +###### **`receiver_options:global:sat_id:`** + `"" ` + + +Id for receivers that are also satellites + +--- + +###### **`receiver_options:global:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`receiver_options:global:models:attitude:`** + ` ` + + +--- + +###### **`receiver_options:global:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`receiver_options:global:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`receiver_options:global:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:models:clock:`** + ` ` + + +--- + +###### **`receiver_options:global:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`receiver_options:global:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:models:code_bias:`** + ` ` + + +--- + +###### **`receiver_options:global:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`receiver_options:global:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`receiver_options:global:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`receiver_options:global:models:eccentricity:`** + ` ` + + +--- + +###### **`receiver_options:global:models:eccentricity:enable:`** + `true ` + + +Enable antenna eccentrities + +--- + +###### **`receiver_options:global:models:eccentricity:offset:`** + `[] ` + + +Antenna offset in ENU frame + +--- + +###### **`receiver_options:global:models:eop:`** + ` ` + + +--- + +###### **`receiver_options:global:models:eop:enable:`** + `false ` + + +Enable modelling of eops + +--- + +###### **`receiver_options:global:models:integer_ambiguity:`** + ` ` + + +--- + +###### **`receiver_options:global:models:integer_ambiguity:enable:`** + `true ` + + +Model ambiguities due to unknown integer number of cycles in phase measurements + +--- + +###### **`receiver_options:global:models:ionospheric_components:`** + ` ` + + +> Ionospheric models produce frequency-dependent effects + +--- + +###### **`receiver_options:global:models:ionospheric_components:geomagnetic_field_height:`** + `450 ` + + +ionospheric pierce point layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:global:models:ionospheric_components:iono_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`receiver_options:global:models:ionospheric_components:mapping_function:`** + [`E_IonoMapFn`](#e_ionomapfn) `MSLM ` + + +Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} + +--- + +###### **`receiver_options:global:models:ionospheric_components:mapping_function_layer_height:`** + `506.7 ` + + +mapping function layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:global:models:ionospheric_components:enable:`** + `true ` + + +Enable ionospheric modelling + +--- + +###### **`receiver_options:global:models:ionospheric_components:use_2nd_order:`** + `false ` + + +--- + +###### **`receiver_options:global:models:ionospheric_components:use_3rd_order:`** + `false ` + + +--- + +###### **`receiver_options:global:models:ionospheric_model:`** + ` ` + + +> Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers + +--- + +###### **`receiver_options:global:models:ionospheric_model:enable:`** + `false ` + + +Compute ionosphere maps from a network of receivers + +--- + +###### **`receiver_options:global:models:pco:`** + ` ` + + +--- + +###### **`receiver_options:global:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`receiver_options:global:models:pcv:`** + ` ` + + +--- + +###### **`receiver_options:global:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`receiver_options:global:models:phase_bias:`** + ` ` + + +--- + +###### **`receiver_options:global:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`receiver_options:global:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`receiver_options:global:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`receiver_options:global:models:phase_windup:`** + ` ` + + +--- + +###### **`receiver_options:global:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`receiver_options:global:models:pos:`** + ` ` + + +--- + +###### **`receiver_options:global:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`receiver_options:global:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:models:range:`** + ` ` + + +--- + +###### **`receiver_options:global:models:range:enable:`** + `true ` + + +Enable modelling of signal time of flight time due to range + +--- + +###### **`receiver_options:global:models:relativity2:`** + ` ` + + +--- + +###### **`receiver_options:global:models:relativity2:enable:`** + `true ` + + +Enable modelling of secondary relativistic effects + +--- + +###### **`receiver_options:global:models:relativity:`** + ` ` + + +--- + +###### **`receiver_options:global:models:relativity:enable:`** + `true ` + + +Enable modelling of relativistic effects + +--- + +###### **`receiver_options:global:models:sagnac:`** + ` ` + + +--- + +###### **`receiver_options:global:models:sagnac:enable:`** + `true ` + + +Enable modelling of sagnac effect + +--- + +###### **`receiver_options:global:models:tides:`** + ` ` + + +--- + +###### **`receiver_options:global:models:tides:atl:`** + `true ` + + +Enable atmospheric tide loading + +--- + +###### **`receiver_options:global:models:tides:enable:`** + `true ` + + +Enable modelling of tidal displacements + +--- + +###### **`receiver_options:global:models:tides:opole:`** + `true ` + + +Enable ocean pole tides + +--- + +###### **`receiver_options:global:models:tides:otl:`** + `true ` + + +Enable ocean tide loading + +--- + +###### **`receiver_options:global:models:tides:solid:`** + `true ` + + +Enable solid Earth tides + +--- + +###### **`receiver_options:global:models:tides:spole:`** + `true ` + + +Enable solid Earth pole tides + +--- + +###### **`receiver_options:global:models:troposphere:`** + ` ` + + +> Tropospheric modelling accounts for delays due to refraction of light in water vapour + +--- + +###### **`receiver_options:global:models:troposphere:enable:`** + `true ` + + +Model tropospheric delays + +--- + +###### **`receiver_options:global:models:troposphere:models:`** + [`[E_TropModel]`](#e_tropmodel) `[VMF3, GPT2, STANDARD] ` + + +List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] + +--- + +###### **`receiver_options:global:models:tropospheric_map:`** + ` ` + + +--- + +###### **`receiver_options:global:models:tropospheric_map:enable:`** + `false ` + + +Compute tropospheric maps from a network of receivers + +--- + +###### **`receiver_options:global:aliases:`** + `[] ` + + +Aliases for this receiver + +--- + +###### **`receiver_options:global:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`receiver_options:global:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`receiver_options:global:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`receiver_options:global:rec_reference_system:`** + [`E_Sys`](#e_sys) `NONE ` + + +Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} + +--- + +###### **`receiver_options:global:rinex2:`** + ` ` + + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:`** + ` ` + + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_code_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:`** + ` ` + + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:rinex2:rnx_phase_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:elevation_mask:`** + `10 ` + + +Minimum elevation for satellites to be processed + +--- + +###### **`receiver_options:global:gps:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`receiver_options:global:gps:kill:`** + `false ` + + +Remove receiver from future processing + +--- + +###### **`receiver_options:global:gps:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`receiver_options:global:gps:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`receiver_options:global:gps:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `ELEVATION_DEPENDENT ` + + + {uniform, elevation_dependent} + +--- + +###### **`receiver_options:global:gps:code_sigma:`** + `1 ` + + +Standard deviation of code measurements + +--- + +###### **`receiver_options:global:gps:phase_sigma:`** + `0.0015 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`receiver_options:global:gps:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:global:gps:zero_dcb_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + + [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:global:gps:antenna_type:`** + `"" ` + + +Antenna type and radome in 20 character string as per sinex + +--- + +###### **`receiver_options:global:gps:apriori_position:`** + `[] ` + + +Apriori position in XYZ ECEF frame + +--- + +###### **`receiver_options:global:gps:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`receiver_options:global:gps:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:global:gps:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:global:gps:receiver_type:`** + `"" ` + + +Type of gnss receiver hardware + +--- + +###### **`receiver_options:global:gps:sat_id:`** + `"" ` + + +Id for receivers that are also satellites + +--- + +###### **`receiver_options:global:gps:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`receiver_options:global:gps:models:attitude:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`receiver_options:global:gps:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`receiver_options:global:gps:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:gps:models:clock:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`receiver_options:global:gps:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:gps:models:code_bias:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`receiver_options:global:gps:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`receiver_options:global:gps:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`receiver_options:global:gps:models:eccentricity:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:eccentricity:enable:`** + `true ` + + +Enable antenna eccentrities + +--- + +###### **`receiver_options:global:gps:models:eccentricity:offset:`** + `[] ` + + +Antenna offset in ENU frame + +--- + +###### **`receiver_options:global:gps:models:eop:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:eop:enable:`** + `false ` + + +Enable modelling of eops + +--- + +###### **`receiver_options:global:gps:models:integer_ambiguity:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:integer_ambiguity:enable:`** + `true ` + + +Model ambiguities due to unknown integer number of cycles in phase measurements + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:`** + ` ` + + +> Ionospheric models produce frequency-dependent effects + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:geomagnetic_field_height:`** + `450 ` + + +ionospheric pierce point layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:iono_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:mapping_function:`** + [`E_IonoMapFn`](#e_ionomapfn) `MSLM ` + + +Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:mapping_function_layer_height:`** + `506.7 ` + + +mapping function layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:enable:`** + `true ` + + +Enable ionospheric modelling + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:use_2nd_order:`** + `false ` + + +--- + +###### **`receiver_options:global:gps:models:ionospheric_components:use_3rd_order:`** + `false ` + + +--- + +###### **`receiver_options:global:gps:models:ionospheric_model:`** + ` ` + + +> Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers + +--- + +###### **`receiver_options:global:gps:models:ionospheric_model:enable:`** + `false ` + + +Compute ionosphere maps from a network of receivers + +--- + +###### **`receiver_options:global:gps:models:pco:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`receiver_options:global:gps:models:pcv:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`receiver_options:global:gps:models:phase_bias:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`receiver_options:global:gps:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`receiver_options:global:gps:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`receiver_options:global:gps:models:phase_windup:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`receiver_options:global:gps:models:pos:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`receiver_options:global:gps:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:gps:models:range:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:range:enable:`** + `true ` + + +Enable modelling of signal time of flight time due to range + +--- + +###### **`receiver_options:global:gps:models:relativity2:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:relativity2:enable:`** + `true ` + + +Enable modelling of secondary relativistic effects + +--- + +###### **`receiver_options:global:gps:models:relativity:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:relativity:enable:`** + `true ` + + +Enable modelling of relativistic effects + +--- + +###### **`receiver_options:global:gps:models:sagnac:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:sagnac:enable:`** + `true ` + + +Enable modelling of sagnac effect + +--- + +###### **`receiver_options:global:gps:models:tides:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:tides:atl:`** + `true ` + + +Enable atmospheric tide loading + +--- + +###### **`receiver_options:global:gps:models:tides:enable:`** + `true ` + + +Enable modelling of tidal displacements + +--- + +###### **`receiver_options:global:gps:models:tides:opole:`** + `true ` + + +Enable ocean pole tides + +--- + +###### **`receiver_options:global:gps:models:tides:otl:`** + `true ` + + +Enable ocean tide loading + +--- + +###### **`receiver_options:global:gps:models:tides:solid:`** + `true ` + + +Enable solid Earth tides + +--- + +###### **`receiver_options:global:gps:models:tides:spole:`** + `true ` + + +Enable solid Earth pole tides + +--- + +###### **`receiver_options:global:gps:models:troposphere:`** + ` ` + + +> Tropospheric modelling accounts for delays due to refraction of light in water vapour + +--- + +###### **`receiver_options:global:gps:models:troposphere:enable:`** + `true ` + + +Model tropospheric delays + +--- + +###### **`receiver_options:global:gps:models:troposphere:models:`** + [`[E_TropModel]`](#e_tropmodel) `[VMF3, GPT2, STANDARD] ` + + +List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] + +--- + +###### **`receiver_options:global:gps:models:tropospheric_map:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:models:tropospheric_map:enable:`** + `false ` + + +Compute tropospheric maps from a network of receivers + +--- + +###### **`receiver_options:global:gps:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`receiver_options:global:gps:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`receiver_options:global:gps:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`receiver_options:global:gps:l1w:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:elevation_mask:`** + `10 ` + + +Minimum elevation for satellites to be processed + +--- + +###### **`receiver_options:global:gps:l1w:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`receiver_options:global:gps:l1w:kill:`** + `false ` + + +Remove receiver from future processing + +--- + +###### **`receiver_options:global:gps:l1w:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`receiver_options:global:gps:l1w:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`receiver_options:global:gps:l1w:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `ELEVATION_DEPENDENT ` + + + {uniform, elevation_dependent} + +--- + +###### **`receiver_options:global:gps:l1w:code_sigma:`** + `1 ` + + +Standard deviation of code measurements + +--- + +###### **`receiver_options:global:gps:l1w:phase_sigma:`** + `0.0015 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`receiver_options:global:gps:l1w:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:global:gps:l1w:zero_dcb_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + + [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:global:gps:l1w:antenna_type:`** + `"" ` + + +Antenna type and radome in 20 character string as per sinex + +--- + +###### **`receiver_options:global:gps:l1w:apriori_position:`** + `[] ` + + +Apriori position in XYZ ECEF frame + +--- + +###### **`receiver_options:global:gps:l1w:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`receiver_options:global:gps:l1w:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:global:gps:l1w:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:global:gps:l1w:receiver_type:`** + `"" ` + + +Type of gnss receiver hardware + +--- + +###### **`receiver_options:global:gps:l1w:sat_id:`** + `"" ` + + +Id for receivers that are also satellites + +--- + +###### **`receiver_options:global:gps:l1w:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`receiver_options:global:gps:l1w:models:attitude:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`receiver_options:global:gps:l1w:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`receiver_options:global:gps:l1w:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:gps:l1w:models:clock:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`receiver_options:global:gps:l1w:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:gps:l1w:models:code_bias:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`receiver_options:global:gps:l1w:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`receiver_options:global:gps:l1w:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`receiver_options:global:gps:l1w:models:eccentricity:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:eccentricity:enable:`** + `true ` + + +Enable antenna eccentrities + +--- + +###### **`receiver_options:global:gps:l1w:models:eccentricity:offset:`** + `[] ` + + +Antenna offset in ENU frame + +--- + +###### **`receiver_options:global:gps:l1w:models:eop:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:eop:enable:`** + `false ` + + +Enable modelling of eops + +--- + +###### **`receiver_options:global:gps:l1w:models:integer_ambiguity:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:integer_ambiguity:enable:`** + `true ` + + +Model ambiguities due to unknown integer number of cycles in phase measurements + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:`** + ` ` + + +> Ionospheric models produce frequency-dependent effects + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:geomagnetic_field_height:`** + `450 ` + + +ionospheric pierce point layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:iono_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:mapping_function:`** + [`E_IonoMapFn`](#e_ionomapfn) `MSLM ` + + +Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:mapping_function_layer_height:`** + `506.7 ` + + +mapping function layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:enable:`** + `true ` + + +Enable ionospheric modelling + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:use_2nd_order:`** + `false ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_components:use_3rd_order:`** + `false ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_model:`** + ` ` + + +> Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers + +--- + +###### **`receiver_options:global:gps:l1w:models:ionospheric_model:enable:`** + `false ` + + +Compute ionosphere maps from a network of receivers + +--- + +###### **`receiver_options:global:gps:l1w:models:pco:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`receiver_options:global:gps:l1w:models:pcv:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`receiver_options:global:gps:l1w:models:phase_bias:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`receiver_options:global:gps:l1w:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`receiver_options:global:gps:l1w:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`receiver_options:global:gps:l1w:models:phase_windup:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`receiver_options:global:gps:l1w:models:pos:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`receiver_options:global:gps:l1w:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:global:gps:l1w:models:range:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:range:enable:`** + `true ` + + +Enable modelling of signal time of flight time due to range + +--- + +###### **`receiver_options:global:gps:l1w:models:relativity2:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:relativity2:enable:`** + `true ` + + +Enable modelling of secondary relativistic effects + +--- + +###### **`receiver_options:global:gps:l1w:models:relativity:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:relativity:enable:`** + `true ` + + +Enable modelling of relativistic effects + +--- + +###### **`receiver_options:global:gps:l1w:models:sagnac:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:sagnac:enable:`** + `true ` + + +Enable modelling of sagnac effect + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:atl:`** + `true ` + + +Enable atmospheric tide loading + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:enable:`** + `true ` + + +Enable modelling of tidal displacements + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:opole:`** + `true ` + + +Enable ocean pole tides + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:otl:`** + `true ` + + +Enable ocean tide loading + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:solid:`** + `true ` + + +Enable solid Earth tides + +--- + +###### **`receiver_options:global:gps:l1w:models:tides:spole:`** + `true ` + + +Enable solid Earth pole tides + +--- + +###### **`receiver_options:global:gps:l1w:models:troposphere:`** + ` ` + + +> Tropospheric modelling accounts for delays due to refraction of light in water vapour + +--- + +###### **`receiver_options:global:gps:l1w:models:troposphere:enable:`** + `true ` + + +Model tropospheric delays + +--- + +###### **`receiver_options:global:gps:l1w:models:troposphere:models:`** + [`[E_TropModel]`](#e_tropmodel) `[VMF3, GPT2, STANDARD] ` + + +List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] + +--- + +###### **`receiver_options:global:gps:l1w:models:tropospheric_map:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:models:tropospheric_map:enable:`** + `false ` + + +Compute tropospheric maps from a network of receivers + +--- + +###### **`receiver_options:global:gps:l1w:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`receiver_options:global:gps:l1w:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`receiver_options:global:gps:l1w:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`receiver_options:global:gps:l1w:rec_reference_system:`** + [`E_Sys`](#e_sys) `NONE ` + + +Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rec_reference_system:`** + [`E_Sys`](#e_sys) `NONE ` + + +Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} + +--- + +###### **`receiver_options:global:gps:rinex2:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_code_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:`** + ` ` + + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:global:gps:rinex2:rnx_phase_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:elevation_mask:`** + `10 ` + + +Minimum elevation for satellites to be processed + +--- + +###### **`receiver_options:xmpl:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`receiver_options:xmpl:kill:`** + `false ` + + +Remove receiver from future processing + +--- + +###### **`receiver_options:xmpl:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`receiver_options:xmpl:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`receiver_options:xmpl:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `ELEVATION_DEPENDENT ` + + + {uniform, elevation_dependent} + +--- + +###### **`receiver_options:xmpl:code_sigma:`** + `1 ` + + +Standard deviation of code measurements + +--- + +###### **`receiver_options:xmpl:phase_sigma:`** + `0.0015 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`receiver_options:xmpl:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:xmpl:zero_dcb_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + + [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:xmpl:antenna_type:`** + `"" ` + + +Antenna type and radome in 20 character string as per sinex + +--- + +###### **`receiver_options:xmpl:apriori_position:`** + `[] ` + + +Apriori position in XYZ ECEF frame + +--- + +###### **`receiver_options:xmpl:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`receiver_options:xmpl:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:xmpl:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:xmpl:receiver_type:`** + `"" ` + + +Type of gnss receiver hardware + +--- + +###### **`receiver_options:xmpl:sat_id:`** + `"" ` + + +Id for receivers that are also satellites + +--- + +###### **`receiver_options:xmpl:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`receiver_options:xmpl:models:attitude:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`receiver_options:xmpl:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`receiver_options:xmpl:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:models:clock:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`receiver_options:xmpl:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:models:code_bias:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`receiver_options:xmpl:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`receiver_options:xmpl:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`receiver_options:xmpl:models:eccentricity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:eccentricity:enable:`** + `true ` + + +Enable antenna eccentrities + +--- + +###### **`receiver_options:xmpl:models:eccentricity:offset:`** + `[] ` + + +Antenna offset in ENU frame + +--- + +###### **`receiver_options:xmpl:models:eop:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:eop:enable:`** + `false ` + + +Enable modelling of eops + +--- + +###### **`receiver_options:xmpl:models:integer_ambiguity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:integer_ambiguity:enable:`** + `true ` + + +Model ambiguities due to unknown integer number of cycles in phase measurements + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:`** + ` ` + + +> Ionospheric models produce frequency-dependent effects + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:geomagnetic_field_height:`** + `450 ` + + +ionospheric pierce point layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:iono_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:mapping_function:`** + [`E_IonoMapFn`](#e_ionomapfn) `MSLM ` + + +Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:mapping_function_layer_height:`** + `506.7 ` + + +mapping function layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:enable:`** + `true ` + + +Enable ionospheric modelling + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:use_2nd_order:`** + `false ` + + +--- + +###### **`receiver_options:xmpl:models:ionospheric_components:use_3rd_order:`** + `false ` + + +--- + +###### **`receiver_options:xmpl:models:ionospheric_model:`** + ` ` + + +> Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers + +--- + +###### **`receiver_options:xmpl:models:ionospheric_model:enable:`** + `false ` + + +Compute ionosphere maps from a network of receivers + +--- + +###### **`receiver_options:xmpl:models:pco:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`receiver_options:xmpl:models:pcv:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`receiver_options:xmpl:models:phase_bias:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`receiver_options:xmpl:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`receiver_options:xmpl:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`receiver_options:xmpl:models:phase_windup:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`receiver_options:xmpl:models:pos:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`receiver_options:xmpl:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:models:range:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:range:enable:`** + `true ` + + +Enable modelling of signal time of flight time due to range + +--- + +###### **`receiver_options:xmpl:models:relativity2:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:relativity2:enable:`** + `true ` + + +Enable modelling of secondary relativistic effects + +--- + +###### **`receiver_options:xmpl:models:relativity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:relativity:enable:`** + `true ` + + +Enable modelling of relativistic effects + +--- + +###### **`receiver_options:xmpl:models:sagnac:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:sagnac:enable:`** + `true ` + + +Enable modelling of sagnac effect + +--- + +###### **`receiver_options:xmpl:models:tides:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:tides:atl:`** + `true ` + + +Enable atmospheric tide loading + +--- + +###### **`receiver_options:xmpl:models:tides:enable:`** + `true ` + + +Enable modelling of tidal displacements + +--- + +###### **`receiver_options:xmpl:models:tides:opole:`** + `true ` + + +Enable ocean pole tides + +--- + +###### **`receiver_options:xmpl:models:tides:otl:`** + `true ` + + +Enable ocean tide loading + +--- + +###### **`receiver_options:xmpl:models:tides:solid:`** + `true ` + + +Enable solid Earth tides + +--- + +###### **`receiver_options:xmpl:models:tides:spole:`** + `true ` + + +Enable solid Earth pole tides + +--- + +###### **`receiver_options:xmpl:models:troposphere:`** + ` ` + + +> Tropospheric modelling accounts for delays due to refraction of light in water vapour + +--- + +###### **`receiver_options:xmpl:models:troposphere:enable:`** + `true ` + + +Model tropospheric delays + +--- + +###### **`receiver_options:xmpl:models:troposphere:models:`** + [`[E_TropModel]`](#e_tropmodel) `[VMF3, GPT2, STANDARD] ` + + +List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] + +--- + +###### **`receiver_options:xmpl:models:tropospheric_map:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:models:tropospheric_map:enable:`** + `false ` + + +Compute tropospheric maps from a network of receivers + +--- + +###### **`receiver_options:xmpl:aliases:`** + `[] ` + + +Aliases for this receiver + +--- + +###### **`receiver_options:xmpl:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`receiver_options:xmpl:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`receiver_options:xmpl:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`receiver_options:xmpl:rec_reference_system:`** + [`E_Sys`](#e_sys) `NONE ` + + +Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} + +--- + +###### **`receiver_options:xmpl:rinex2:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_code_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:rinex2:rnx_phase_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:elevation_mask:`** + `10 ` + + +Minimum elevation for satellites to be processed + +--- + +###### **`receiver_options:xmpl:gps:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`receiver_options:xmpl:gps:kill:`** + `false ` + + +Remove receiver from future processing + +--- + +###### **`receiver_options:xmpl:gps:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`receiver_options:xmpl:gps:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`receiver_options:xmpl:gps:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `ELEVATION_DEPENDENT ` + + + {uniform, elevation_dependent} + +--- + +###### **`receiver_options:xmpl:gps:code_sigma:`** + `1 ` + + +Standard deviation of code measurements + +--- + +###### **`receiver_options:xmpl:gps:phase_sigma:`** + `0.0015 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`receiver_options:xmpl:gps:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:xmpl:gps:zero_dcb_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + + [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:xmpl:gps:antenna_type:`** + `"" ` + + +Antenna type and radome in 20 character string as per sinex + +--- + +###### **`receiver_options:xmpl:gps:apriori_position:`** + `[] ` + + +Apriori position in XYZ ECEF frame + +--- + +###### **`receiver_options:xmpl:gps:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`receiver_options:xmpl:gps:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:xmpl:gps:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:xmpl:gps:receiver_type:`** + `"" ` + + +Type of gnss receiver hardware + +--- + +###### **`receiver_options:xmpl:gps:sat_id:`** + `"" ` + + +Id for receivers that are also satellites + +--- + +###### **`receiver_options:xmpl:gps:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`receiver_options:xmpl:gps:models:attitude:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`receiver_options:xmpl:gps:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`receiver_options:xmpl:gps:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:gps:models:clock:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`receiver_options:xmpl:gps:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:gps:models:code_bias:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`receiver_options:xmpl:gps:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`receiver_options:xmpl:gps:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`receiver_options:xmpl:gps:models:eccentricity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:eccentricity:enable:`** + `true ` + + +Enable antenna eccentrities + +--- + +###### **`receiver_options:xmpl:gps:models:eccentricity:offset:`** + `[] ` + + +Antenna offset in ENU frame + +--- + +###### **`receiver_options:xmpl:gps:models:eop:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:eop:enable:`** + `false ` + + +Enable modelling of eops + +--- + +###### **`receiver_options:xmpl:gps:models:integer_ambiguity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:integer_ambiguity:enable:`** + `true ` + + +Model ambiguities due to unknown integer number of cycles in phase measurements + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:`** + ` ` + + +> Ionospheric models produce frequency-dependent effects + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:geomagnetic_field_height:`** + `450 ` + + +ionospheric pierce point layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:iono_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:mapping_function:`** + [`E_IonoMapFn`](#e_ionomapfn) `MSLM ` + + +Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:mapping_function_layer_height:`** + `506.7 ` + + +mapping function layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:enable:`** + `true ` + + +Enable ionospheric modelling + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:use_2nd_order:`** + `false ` + + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_components:use_3rd_order:`** + `false ` + + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_model:`** + ` ` + + +> Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers + +--- + +###### **`receiver_options:xmpl:gps:models:ionospheric_model:enable:`** + `false ` + + +Compute ionosphere maps from a network of receivers + +--- + +###### **`receiver_options:xmpl:gps:models:pco:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`receiver_options:xmpl:gps:models:pcv:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`receiver_options:xmpl:gps:models:phase_bias:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`receiver_options:xmpl:gps:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`receiver_options:xmpl:gps:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`receiver_options:xmpl:gps:models:phase_windup:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`receiver_options:xmpl:gps:models:pos:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`receiver_options:xmpl:gps:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:gps:models:range:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:range:enable:`** + `true ` + + +Enable modelling of signal time of flight time due to range + +--- + +###### **`receiver_options:xmpl:gps:models:relativity2:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:relativity2:enable:`** + `true ` + + +Enable modelling of secondary relativistic effects + +--- + +###### **`receiver_options:xmpl:gps:models:relativity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:relativity:enable:`** + `true ` + + +Enable modelling of relativistic effects + +--- + +###### **`receiver_options:xmpl:gps:models:sagnac:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:sagnac:enable:`** + `true ` + + +Enable modelling of sagnac effect + +--- + +###### **`receiver_options:xmpl:gps:models:tides:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:tides:atl:`** + `true ` + + +Enable atmospheric tide loading + +--- + +###### **`receiver_options:xmpl:gps:models:tides:enable:`** + `true ` + + +Enable modelling of tidal displacements + +--- + +###### **`receiver_options:xmpl:gps:models:tides:opole:`** + `true ` + + +Enable ocean pole tides + +--- + +###### **`receiver_options:xmpl:gps:models:tides:otl:`** + `true ` + + +Enable ocean tide loading + +--- + +###### **`receiver_options:xmpl:gps:models:tides:solid:`** + `true ` + + +Enable solid Earth tides + +--- + +###### **`receiver_options:xmpl:gps:models:tides:spole:`** + `true ` + + +Enable solid Earth pole tides + +--- + +###### **`receiver_options:xmpl:gps:models:troposphere:`** + ` ` + + +> Tropospheric modelling accounts for delays due to refraction of light in water vapour + +--- + +###### **`receiver_options:xmpl:gps:models:troposphere:enable:`** + `true ` + + +Model tropospheric delays + +--- + +###### **`receiver_options:xmpl:gps:models:troposphere:models:`** + [`[E_TropModel]`](#e_tropmodel) `[VMF3, GPT2, STANDARD] ` + + +List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] + +--- + +###### **`receiver_options:xmpl:gps:models:tropospheric_map:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:models:tropospheric_map:enable:`** + `false ` + + +Compute tropospheric maps from a network of receivers + +--- + +###### **`receiver_options:xmpl:gps:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`receiver_options:xmpl:gps:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`receiver_options:xmpl:gps:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`receiver_options:xmpl:gps:l1w:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:elevation_mask:`** + `10 ` + + +Minimum elevation for satellites to be processed + +--- + +###### **`receiver_options:xmpl:gps:l1w:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`receiver_options:xmpl:gps:l1w:kill:`** + `false ` + + +Remove receiver from future processing + +--- + +###### **`receiver_options:xmpl:gps:l1w:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`receiver_options:xmpl:gps:l1w:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`receiver_options:xmpl:gps:l1w:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `ELEVATION_DEPENDENT ` + + + {uniform, elevation_dependent} + +--- + +###### **`receiver_options:xmpl:gps:l1w:code_sigma:`** + `1 ` + + +Standard deviation of code measurements + +--- + +###### **`receiver_options:xmpl:gps:l1w:phase_sigma:`** + `0.0015 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`receiver_options:xmpl:gps:l1w:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:xmpl:gps:l1w:zero_dcb_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + + [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`receiver_options:xmpl:gps:l1w:antenna_type:`** + `"" ` + + +Antenna type and radome in 20 character string as per sinex + +--- + +###### **`receiver_options:xmpl:gps:l1w:apriori_position:`** + `[] ` + + +Apriori position in XYZ ECEF frame + +--- + +###### **`receiver_options:xmpl:gps:l1w:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`receiver_options:xmpl:gps:l1w:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:xmpl:gps:l1w:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`receiver_options:xmpl:gps:l1w:receiver_type:`** + `"" ` + + +Type of gnss receiver hardware + +--- + +###### **`receiver_options:xmpl:gps:l1w:sat_id:`** + `"" ` + + +Id for receivers that are also satellites + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:attitude:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:clock:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:code_bias:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:eccentricity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:eccentricity:enable:`** + `true ` + + +Enable antenna eccentrities + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:eccentricity:offset:`** + `[] ` + + +Antenna offset in ENU frame + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:eop:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:eop:enable:`** + `false ` + + +Enable modelling of eops + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:integer_ambiguity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:integer_ambiguity:enable:`** + `true ` + + +Model ambiguities due to unknown integer number of cycles in phase measurements + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:`** + ` ` + + +> Ionospheric models produce frequency-dependent effects + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:geomagnetic_field_height:`** + `450 ` + + +ionospheric pierce point layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:iono_sigma_limit:`** + `1000 ` + + +Ionosphere states are removed when their sigma exceeds this value + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:mapping_function:`** + [`E_IonoMapFn`](#e_ionomapfn) `MSLM ` + + +Mapping function if not specified in the data or model {slm, mslm, mlm, klobuchar} + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:mapping_function_layer_height:`** + `506.7 ` + + +mapping function layer height if not specified in the data or model (km) + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:enable:`** + `true ` + + +Enable ionospheric modelling + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:use_2nd_order:`** + `false ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_components:use_3rd_order:`** + `false ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_model:`** + ` ` + + +> Coherent ionosphere models can improve estimation of biases and allow use with single frequency receivers + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:ionospheric_model:enable:`** + `false ` + + +Compute ionosphere maps from a network of receivers + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pco:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pcv:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:phase_bias:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:phase_windup:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pos:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:range:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:range:enable:`** + `true ` + + +Enable modelling of signal time of flight time due to range + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:relativity2:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:relativity2:enable:`** + `true ` + + +Enable modelling of secondary relativistic effects + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:relativity:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:relativity:enable:`** + `true ` + + +Enable modelling of relativistic effects + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:sagnac:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:sagnac:enable:`** + `true ` + + +Enable modelling of sagnac effect + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:atl:`** + `true ` + + +Enable atmospheric tide loading + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:enable:`** + `true ` + + +Enable modelling of tidal displacements + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:opole:`** + `true ` + + +Enable ocean pole tides + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:otl:`** + `true ` + + +Enable ocean tide loading + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:solid:`** + `true ` + + +Enable solid Earth tides + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tides:spole:`** + `true ` + + +Enable solid Earth pole tides + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:troposphere:`** + ` ` + + +> Tropospheric modelling accounts for delays due to refraction of light in water vapour + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:troposphere:enable:`** + `true ` + + +Model tropospheric delays + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:troposphere:models:`** + [`[E_TropModel]`](#e_tropmodel) `[VMF3, GPT2, STANDARD] ` + + +List of models to use for troposphere [standard, sbas, vmf3, gpt2, cssr] + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tropospheric_map:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:models:tropospheric_map:enable:`** + `false ` + + +Compute tropospheric maps from a network of receivers + +--- + +###### **`receiver_options:xmpl:gps:l1w:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`receiver_options:xmpl:gps:l1w:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`receiver_options:xmpl:gps:l1w:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`receiver_options:xmpl:gps:l1w:rec_reference_system:`** + [`E_Sys`](#e_sys) `NONE ` + + +Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rec_reference_system:`** + [`E_Sys`](#e_sys) `NONE ` + + +Receiver will use this system as reference clock {none, gps, gal, glo, qzs, sbs, bds, leo, supported, irn, ims, comb} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:`** + ` ` + + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l1:`** + [`E_ObsCode`](#e_obscode) `L1C ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l2:`** + [`E_ObsCode`](#e_obscode) `L2W ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l3:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l4:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l5:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l6:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l7:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l8:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:la:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:none:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:p1:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +###### **`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:p2:`** + [`E_ObsCode`](#e_obscode) `NONE ` + + + {none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto} + +--- + +## satellite_options: + +###### **`satellite_options:`** + ` ` + + +--- + +###### **`satellite_options:global:`** + ` ` + + +--- + +###### **`satellite_options:global:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`satellite_options:global:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`satellite_options:global:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`satellite_options:global:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `UNIFORM ` + + + {uniform, elevation_dependent} + +--- + +###### **`satellite_options:global:code_sigma:`** + `0 ` + + +Standard deviation of code measurements + +--- + +###### **`satellite_options:global:phase_sigma:`** + `0 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`satellite_options:global:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`satellite_options:global:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`satellite_options:global:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:global:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:global:surface_details:`** + ` ` + + +List of details for srp and drag surfaces + +--- + +###### **`satellite_options:global:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`satellite_options:global:models:attitude:`** + ` ` + + +--- + +###### **`satellite_options:global:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`satellite_options:global:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`satellite_options:global:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:global:models:clock:`** + ` ` + + +--- + +###### **`satellite_options:global:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`satellite_options:global:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:global:models:code_bias:`** + ` ` + + +--- + +###### **`satellite_options:global:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`satellite_options:global:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`satellite_options:global:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`satellite_options:global:models:pco:`** + ` ` + + +--- + +###### **`satellite_options:global:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`satellite_options:global:models:pcv:`** + ` ` + + +--- + +###### **`satellite_options:global:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`satellite_options:global:models:phase_bias:`** + ` ` + + +--- + +###### **`satellite_options:global:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`satellite_options:global:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`satellite_options:global:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`satellite_options:global:models:phase_windup:`** + ` ` + + +--- + +###### **`satellite_options:global:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`satellite_options:global:models:pos:`** + ` ` + + +--- + +###### **`satellite_options:global:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`satellite_options:global:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:global:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`satellite_options:global:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`satellite_options:global:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`satellite_options:global:l1w:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`satellite_options:global:l1w:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`satellite_options:global:l1w:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`satellite_options:global:l1w:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `UNIFORM ` + + + {uniform, elevation_dependent} + +--- + +###### **`satellite_options:global:l1w:code_sigma:`** + `0 ` + + +Standard deviation of code measurements + +--- + +###### **`satellite_options:global:l1w:phase_sigma:`** + `0 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`satellite_options:global:l1w:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`satellite_options:global:l1w:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`satellite_options:global:l1w:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:global:l1w:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:global:l1w:surface_details:`** + ` ` + + +List of details for srp and drag surfaces + +--- + +###### **`satellite_options:global:l1w:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`satellite_options:global:l1w:models:attitude:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`satellite_options:global:l1w:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`satellite_options:global:l1w:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:global:l1w:models:clock:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`satellite_options:global:l1w:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:global:l1w:models:code_bias:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`satellite_options:global:l1w:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`satellite_options:global:l1w:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`satellite_options:global:l1w:models:pco:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`satellite_options:global:l1w:models:pcv:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`satellite_options:global:l1w:models:phase_bias:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`satellite_options:global:l1w:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`satellite_options:global:l1w:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`satellite_options:global:l1w:models:phase_windup:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`satellite_options:global:l1w:models:pos:`** + ` ` + + +--- + +###### **`satellite_options:global:l1w:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`satellite_options:global:l1w:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:global:l1w:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`satellite_options:global:l1w:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`satellite_options:global:l1w:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:`** + ` ` + + +> Enable specific orbit propagation models + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:area:`** + `20 ` + + +Satellite area for use in solar radiation and albedo calculations + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:mass:`** + `1000 ` + + +Satellite mass for use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:power:`** + `20 ` + + +Transmission power use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:srp_cr:`** + `1.25 ` + + +Coefficient of reflection of the satellite + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:albedo:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:antenna_thrust:`** + `true ` + + +Model accelerations due to the emitted signal from the antenna + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:empirical:`** + `true ` + + +Model accelerations due to empirical accelerations + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:empirical_dyb_eclipse:`** + `[true] ` + + +Turn on/off the eclipse on each axis (D, Y, B) + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:empirical_rtn_eclipse:`** + `[false] ` + + +Turn on/off the eclipse on each axis (R, T, N) + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:planetary_perturbations:`** + [`[E_ThirdBody]`](#e_thirdbody) `[SUN, MOON, JUPITER] ` + + +Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:pseudo_pulses:`** + ` ` + + +> Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:pseudo_pulses:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:pseudo_pulses:interval:`** + `1 ` + + +Interval between applying pseudo pulses + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:pseudo_pulses:pos_process_noise:`** + `10 ` + + +Sigma to add to orbital position states + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:pseudo_pulses:vel_process_noise:`** + `5 ` + + +Sigma to add to orbital velocity states + +--- + +###### **`satellite_options:global:l1w:orbit_propagation:solar_radiation_pressure:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to solar radiation pressure {none, cannonball, boxwing} + +--- + +###### **`satellite_options:global:orbit_propagation:`** + ` ` + + +> Enable specific orbit propagation models + +--- + +###### **`satellite_options:global:orbit_propagation:area:`** + `20 ` + + +Satellite area for use in solar radiation and albedo calculations + +--- + +###### **`satellite_options:global:orbit_propagation:mass:`** + `1000 ` + + +Satellite mass for use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:global:orbit_propagation:power:`** + `20 ` + + +Transmission power use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:global:orbit_propagation:srp_cr:`** + `1.25 ` + + +Coefficient of reflection of the satellite + +--- + +###### **`satellite_options:global:orbit_propagation:albedo:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} + +--- + +###### **`satellite_options:global:orbit_propagation:antenna_thrust:`** + `true ` + + +Model accelerations due to the emitted signal from the antenna + +--- + +###### **`satellite_options:global:orbit_propagation:empirical:`** + `true ` + + +Model accelerations due to empirical accelerations + +--- + +###### **`satellite_options:global:orbit_propagation:empirical_dyb_eclipse:`** + `[true] ` + + +Turn on/off the eclipse on each axis (D, Y, B) + +--- + +###### **`satellite_options:global:orbit_propagation:empirical_rtn_eclipse:`** + `[false] ` + + +Turn on/off the eclipse on each axis (R, T, N) + +--- + +###### **`satellite_options:global:orbit_propagation:planetary_perturbations:`** + [`[E_ThirdBody]`](#e_thirdbody) `[SUN, MOON, JUPITER] ` + + +Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] + +--- + +###### **`satellite_options:global:orbit_propagation:pseudo_pulses:`** + ` ` + + +> Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions + +--- + +###### **`satellite_options:global:orbit_propagation:pseudo_pulses:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`satellite_options:global:orbit_propagation:pseudo_pulses:interval:`** + `1 ` + + +Interval between applying pseudo pulses + +--- + +###### **`satellite_options:global:orbit_propagation:pseudo_pulses:pos_process_noise:`** + `10 ` + + +Sigma to add to orbital position states + +--- + +###### **`satellite_options:global:orbit_propagation:pseudo_pulses:vel_process_noise:`** + `5 ` + + +Sigma to add to orbital velocity states + +--- + +###### **`satellite_options:global:orbit_propagation:solar_radiation_pressure:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to solar radiation pressure {none, cannonball, boxwing} + +--- + +###### **`satellite_options:g--:`** + ` ` + + +--- + +###### **`satellite_options:g--:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`satellite_options:g--:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`satellite_options:g--:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`satellite_options:g--:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `UNIFORM ` + + + {uniform, elevation_dependent} + +--- + +###### **`satellite_options:g--:code_sigma:`** + `0 ` + + +Standard deviation of code measurements + +--- + +###### **`satellite_options:g--:phase_sigma:`** + `0 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`satellite_options:g--:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`satellite_options:g--:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`satellite_options:g--:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:g--:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:g--:surface_details:`** + ` ` + + +List of details for srp and drag surfaces + +--- + +###### **`satellite_options:g--:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`satellite_options:g--:models:attitude:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`satellite_options:g--:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`satellite_options:g--:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:g--:models:clock:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`satellite_options:g--:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:g--:models:code_bias:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`satellite_options:g--:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`satellite_options:g--:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`satellite_options:g--:models:pco:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`satellite_options:g--:models:pcv:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`satellite_options:g--:models:phase_bias:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`satellite_options:g--:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`satellite_options:g--:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`satellite_options:g--:models:phase_windup:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`satellite_options:g--:models:pos:`** + ` ` + + +--- + +###### **`satellite_options:g--:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`satellite_options:g--:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:g--:aliases:`** + `[] ` + + +Aliases for this satellite + +--- + +###### **`satellite_options:g--:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`satellite_options:g--:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`satellite_options:g--:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`satellite_options:g--:l1w:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`satellite_options:g--:l1w:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`satellite_options:g--:l1w:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`satellite_options:g--:l1w:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `UNIFORM ` + + + {uniform, elevation_dependent} + +--- + +###### **`satellite_options:g--:l1w:code_sigma:`** + `0 ` + + +Standard deviation of code measurements + +--- + +###### **`satellite_options:g--:l1w:phase_sigma:`** + `0 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`satellite_options:g--:l1w:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`satellite_options:g--:l1w:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`satellite_options:g--:l1w:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:g--:l1w:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:g--:l1w:surface_details:`** + ` ` + + +List of details for srp and drag surfaces + +--- + +###### **`satellite_options:g--:l1w:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`satellite_options:g--:l1w:models:attitude:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`satellite_options:g--:l1w:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`satellite_options:g--:l1w:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:g--:l1w:models:clock:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`satellite_options:g--:l1w:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:g--:l1w:models:code_bias:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`satellite_options:g--:l1w:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`satellite_options:g--:l1w:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`satellite_options:g--:l1w:models:pco:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`satellite_options:g--:l1w:models:pcv:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`satellite_options:g--:l1w:models:phase_bias:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`satellite_options:g--:l1w:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`satellite_options:g--:l1w:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`satellite_options:g--:l1w:models:phase_windup:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`satellite_options:g--:l1w:models:pos:`** + ` ` + + +--- + +###### **`satellite_options:g--:l1w:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`satellite_options:g--:l1w:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:g--:l1w:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`satellite_options:g--:l1w:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`satellite_options:g--:l1w:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:`** + ` ` + + +> Enable specific orbit propagation models + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:area:`** + `20 ` + + +Satellite area for use in solar radiation and albedo calculations + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:mass:`** + `1000 ` + + +Satellite mass for use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:power:`** + `20 ` + + +Transmission power use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:srp_cr:`** + `1.25 ` + + +Coefficient of reflection of the satellite + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:albedo:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:antenna_thrust:`** + `true ` + + +Model accelerations due to the emitted signal from the antenna + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:empirical:`** + `true ` + + +Model accelerations due to empirical accelerations + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:empirical_dyb_eclipse:`** + `[true] ` + + +Turn on/off the eclipse on each axis (D, Y, B) + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:empirical_rtn_eclipse:`** + `[false] ` + + +Turn on/off the eclipse on each axis (R, T, N) + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:planetary_perturbations:`** + [`[E_ThirdBody]`](#e_thirdbody) `[SUN, MOON, JUPITER] ` + + +Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:pseudo_pulses:`** + ` ` + + +> Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:pseudo_pulses:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:pseudo_pulses:interval:`** + `1 ` + + +Interval between applying pseudo pulses + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:pseudo_pulses:pos_process_noise:`** + `10 ` + + +Sigma to add to orbital position states + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:pseudo_pulses:vel_process_noise:`** + `5 ` + + +Sigma to add to orbital velocity states + +--- + +###### **`satellite_options:g--:l1w:orbit_propagation:solar_radiation_pressure:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to solar radiation pressure {none, cannonball, boxwing} + +--- + +###### **`satellite_options:g--:orbit_propagation:`** + ` ` + + +> Enable specific orbit propagation models + +--- + +###### **`satellite_options:g--:orbit_propagation:area:`** + `20 ` + + +Satellite area for use in solar radiation and albedo calculations + +--- + +###### **`satellite_options:g--:orbit_propagation:mass:`** + `1000 ` + + +Satellite mass for use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:g--:orbit_propagation:power:`** + `20 ` + + +Transmission power use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:g--:orbit_propagation:srp_cr:`** + `1.25 ` + + +Coefficient of reflection of the satellite + +--- + +###### **`satellite_options:g--:orbit_propagation:albedo:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} + +--- + +###### **`satellite_options:g--:orbit_propagation:antenna_thrust:`** + `true ` + + +Model accelerations due to the emitted signal from the antenna + +--- + +###### **`satellite_options:g--:orbit_propagation:empirical:`** + `true ` + + +Model accelerations due to empirical accelerations + +--- + +###### **`satellite_options:g--:orbit_propagation:empirical_dyb_eclipse:`** + `[true] ` + + +Turn on/off the eclipse on each axis (D, Y, B) + +--- + +###### **`satellite_options:g--:orbit_propagation:empirical_rtn_eclipse:`** + `[false] ` + + +Turn on/off the eclipse on each axis (R, T, N) + +--- + +###### **`satellite_options:g--:orbit_propagation:planetary_perturbations:`** + [`[E_ThirdBody]`](#e_thirdbody) `[SUN, MOON, JUPITER] ` + + +Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] + +--- + +###### **`satellite_options:g--:orbit_propagation:pseudo_pulses:`** + ` ` + + +> Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions + +--- + +###### **`satellite_options:g--:orbit_propagation:pseudo_pulses:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`satellite_options:g--:orbit_propagation:pseudo_pulses:interval:`** + `1 ` + + +Interval between applying pseudo pulses + +--- + +###### **`satellite_options:g--:orbit_propagation:pseudo_pulses:pos_process_noise:`** + `10 ` + + +Sigma to add to orbital position states + +--- + +###### **`satellite_options:g--:orbit_propagation:pseudo_pulses:vel_process_noise:`** + `5 ` + + +Sigma to add to orbital velocity states + +--- + +###### **`satellite_options:g--:orbit_propagation:solar_radiation_pressure:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to solar radiation pressure {none, cannonball, boxwing} + +--- + +###### **`satellite_options:gps:`** + ` ` + + +--- + +###### **`satellite_options:gps:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`satellite_options:gps:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`satellite_options:gps:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`satellite_options:gps:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `UNIFORM ` + + + {uniform, elevation_dependent} + +--- + +###### **`satellite_options:gps:code_sigma:`** + `0 ` + + +Standard deviation of code measurements + +--- + +###### **`satellite_options:gps:phase_sigma:`** + `0 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`satellite_options:gps:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`satellite_options:gps:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`satellite_options:gps:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:gps:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:gps:surface_details:`** + ` ` + + +List of details for srp and drag surfaces + +--- + +###### **`satellite_options:gps:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`satellite_options:gps:models:attitude:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`satellite_options:gps:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`satellite_options:gps:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:gps:models:clock:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`satellite_options:gps:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:gps:models:code_bias:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`satellite_options:gps:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`satellite_options:gps:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`satellite_options:gps:models:pco:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`satellite_options:gps:models:pcv:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`satellite_options:gps:models:phase_bias:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`satellite_options:gps:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`satellite_options:gps:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`satellite_options:gps:models:phase_windup:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`satellite_options:gps:models:pos:`** + ` ` + + +--- + +###### **`satellite_options:gps:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`satellite_options:gps:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:gps:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`satellite_options:gps:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`satellite_options:gps:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`satellite_options:gps:l1w:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:exclude:`** + `false ` + + +Exclude receiver from processing + +--- + +###### **`satellite_options:gps:l1w:laser_sigma:`** + `0.5 ` + + +Standard deviation of SLR laser measurements + +--- + +###### **`satellite_options:gps:l1w:pseudo_sigma:`** + `100000 ` + + +Standard deviation of pseudo measurmeents + +--- + +###### **`satellite_options:gps:l1w:error_model:`** + [`E_NoiseModel`](#e_noisemodel) `UNIFORM ` + + + {uniform, elevation_dependent} + +--- + +###### **`satellite_options:gps:l1w:code_sigma:`** + `0 ` + + +Standard deviation of code measurements + +--- + +###### **`satellite_options:gps:l1w:phase_sigma:`** + `0 ` + + +Standard deviation of phase measurmeents + +--- + +###### **`satellite_options:gps:l1w:clock_codes:`** + [`[E_ObsCode]`](#e_obscode) `[] ` + + +Codes for IF combination based clocks [none, l1c, l1p, l1w, l1y, l1m, l1n, l1s, l1l, l1e, l1a, l1b, l1x, l1z, l2c, l2d, l2s, l2l, l2x, l2p, l2w, l2y, l2m, l2n, l5i, l5q, l5x, l7i, l7q, l7x, l6a, l6b, l6c, l6x, l6z, l6s, l6l, l8i, l8q, l8x, l2i, l2q, l6i, l6q, l3i, l3q, l3x, l1i, l1q, l4a, l4b, l4x, l6e, l1d, l5d, l5p, l9a, l9b, l9c, l9x, l5a, l5b, l5c, l5z, l6d, l6p, l7d, l7p, l7z, l8d, l8p, l8z, auto] + +--- + +###### **`satellite_options:gps:l1w:apriori_sigma_enu:`** + `[] ` + + +Sigma applied for weighting in mincon transformation estimation. (Lower is stronger weighting, Negative is unweighted, ENU separation unsupported for satellites) + +--- + +###### **`satellite_options:gps:l1w:mincon_scale_apriori_sigma:`** + `1 ` + + +Scale applied to apriori sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:gps:l1w:mincon_scale_filter_sigma:`** + `0 ` + + +Scale applied to filter sigmas while weighting in mincon transformation estimation + +--- + +###### **`satellite_options:gps:l1w:surface_details:`** + ` ` + + +List of details for srp and drag surfaces + +--- + +###### **`satellite_options:gps:l1w:models:`** + ` ` + + +> Enable specific models + +--- + +###### **`satellite_options:gps:l1w:models:attitude:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:attitude:enable:`** + `true ` + + +Enables non-nominal attitude types + +--- + +###### **`satellite_options:gps:l1w:models:attitude:model_dt:`** + `1 ` + + +Timestep used in modelling attitude + +--- + +###### **`satellite_options:gps:l1w:models:attitude:sources:`** + [`[E_Source]`](#e_source) `[PRECISE, MODEL, NOMINAL] ` + + +List of sourecs to use for attitudes [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:gps:l1w:models:clock:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:clock:enable:`** + `true ` + + +Enable modelling of clocks + +--- + +###### **`satellite_options:gps:l1w:models:clock:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, PRECISE, BROADCAST] ` + + +List of sources to use for clocks [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:gps:l1w:models:code_bias:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:code_bias:default_bias:`** + `0 ` + + +Bias to use when no code bias is found + +--- + +###### **`satellite_options:gps:l1w:models:code_bias:enable:`** + `true ` + + +Enable modelling of code biases + +--- + +###### **`satellite_options:gps:l1w:models:code_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default code biases + +--- + +###### **`satellite_options:gps:l1w:models:pco:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:pco:enable:`** + `true ` + + +Enable modelling of phase center offsets + +--- + +###### **`satellite_options:gps:l1w:models:pcv:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:pcv:enable:`** + `true ` + + +Enable modelling of phase center variations + +--- + +###### **`satellite_options:gps:l1w:models:phase_bias:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:phase_bias:default_bias:`** + `0 ` + + +Bias to use when no phase bias is found + +--- + +###### **`satellite_options:gps:l1w:models:phase_bias:enable:`** + `false ` + + +Enable modelling of phase biases. Required for AR + +--- + +###### **`satellite_options:gps:l1w:models:phase_bias:undefined_sigma:`** + `0 ` + + +Uncertainty sigma to apply to default phase biases + +--- + +###### **`satellite_options:gps:l1w:models:phase_windup:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:phase_windup:enable:`** + `true ` + + +Model phase windup due to relative rotation of circularly polarised antennas + +--- + +###### **`satellite_options:gps:l1w:models:pos:`** + ` ` + + +--- + +###### **`satellite_options:gps:l1w:models:pos:enable:`** + `true ` + + +Enable modelling of position + +--- + +###### **`satellite_options:gps:l1w:models:pos:sources:`** + [`[E_Source]`](#e_source) `[KALMAN, CONFIG, PRECISE, SPP, BROADCAST] ` + + +Enable modelling of position [none, spp, config, precise, ssr, kalman, broadcast, nominal, model, remote] + +--- + +###### **`satellite_options:gps:l1w:antenna_azimuth:`** + `[] ` + + +Antenna azimuth (North) in satellite body-fixed frame + +--- + +###### **`satellite_options:gps:l1w:antenna_boresight:`** + `[] ` + + +Antenna boresight (Up) in satellite body-fixed frame + +--- + +###### **`satellite_options:gps:l1w:ellipse_propagation_time_tolerance:`** + `30 ` + + +Time gap tolerance under which the ellipse propagator can be used for orbit prediction + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:`** + ` ` + + +> Enable specific orbit propagation models + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:area:`** + `20 ` + + +Satellite area for use in solar radiation and albedo calculations + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:mass:`** + `1000 ` + + +Satellite mass for use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:power:`** + `20 ` + + +Transmission power use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:srp_cr:`** + `1.25 ` + + +Coefficient of reflection of the satellite + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:albedo:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:antenna_thrust:`** + `true ` + + +Model accelerations due to the emitted signal from the antenna + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:empirical:`** + `true ` + + +Model accelerations due to empirical accelerations + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:empirical_dyb_eclipse:`** + `[true] ` + + +Turn on/off the eclipse on each axis (D, Y, B) + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:empirical_rtn_eclipse:`** + `[false] ` + + +Turn on/off the eclipse on each axis (R, T, N) + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:planetary_perturbations:`** + [`[E_ThirdBody]`](#e_thirdbody) `[SUN, MOON, JUPITER] ` + + +Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:pseudo_pulses:`** + ` ` + + +> Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:pseudo_pulses:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:pseudo_pulses:interval:`** + `1 ` + + +Interval between applying pseudo pulses + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:pseudo_pulses:pos_process_noise:`** + `10 ` + + +Sigma to add to orbital position states + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:pseudo_pulses:vel_process_noise:`** + `5 ` + + +Sigma to add to orbital velocity states + +--- + +###### **`satellite_options:gps:l1w:orbit_propagation:solar_radiation_pressure:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to solar radiation pressure {none, cannonball, boxwing} + +--- + +###### **`satellite_options:gps:orbit_propagation:`** + ` ` + + +> Enable specific orbit propagation models + +--- + +###### **`satellite_options:gps:orbit_propagation:area:`** + `20 ` + + +Satellite area for use in solar radiation and albedo calculations + +--- + +###### **`satellite_options:gps:orbit_propagation:mass:`** + `1000 ` + + +Satellite mass for use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:gps:orbit_propagation:power:`** + `20 ` + + +Transmission power use if not specified in the SINEX metadata file + +--- + +###### **`satellite_options:gps:orbit_propagation:srp_cr:`** + `1.25 ` + + +Coefficient of reflection of the satellite + +--- + +###### **`satellite_options:gps:orbit_propagation:albedo:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to the albedo effect from Earth (Visible and Infra-red) {none, cannonball, boxwing} + +--- + +###### **`satellite_options:gps:orbit_propagation:antenna_thrust:`** + `true ` + + +Model accelerations due to the emitted signal from the antenna + +--- + +###### **`satellite_options:gps:orbit_propagation:empirical:`** + `true ` + + +Model accelerations due to empirical accelerations + +--- + +###### **`satellite_options:gps:orbit_propagation:empirical_dyb_eclipse:`** + `[true] ` + + +Turn on/off the eclipse on each axis (D, Y, B) + +--- + +###### **`satellite_options:gps:orbit_propagation:empirical_rtn_eclipse:`** + `[false] ` + + +Turn on/off the eclipse on each axis (R, T, N) + +--- + +###### **`satellite_options:gps:orbit_propagation:planetary_perturbations:`** + [`[E_ThirdBody]`](#e_thirdbody) `[SUN, MOON, JUPITER] ` + + +Acceleration due to third celestial bodies [mercury, venus, earth, mars, jupiter, saturn, uranus, neptune, pluto, moon, sun] + +--- + +###### **`satellite_options:gps:orbit_propagation:pseudo_pulses:`** + ` ` + + +> Apply process noise to simulate pseudo-stochastic pulses commonly applied in least squares solutions + +--- + +###### **`satellite_options:gps:orbit_propagation:pseudo_pulses:enable:`** + `false ` + + +Enable applying process noise impulses to orbits upon state errors + +--- + +###### **`satellite_options:gps:orbit_propagation:pseudo_pulses:interval:`** + `1 ` + + +Interval between applying pseudo pulses + +--- + +###### **`satellite_options:gps:orbit_propagation:pseudo_pulses:pos_process_noise:`** + `10 ` + + +Sigma to add to orbital position states + +--- + +###### **`satellite_options:gps:orbit_propagation:pseudo_pulses:vel_process_noise:`** + `5 ` + + +Sigma to add to orbital velocity states + +--- + +###### **`satellite_options:gps:orbit_propagation:solar_radiation_pressure:`** + [`E_SRPModel`](#e_srpmodel) `NONE ` + + +Model accelerations due to solar radiation pressure {none, cannonball, boxwing} + +--- + +## estimation_parameters: + +###### **`estimation_parameters:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:`** + ` ` + + +> Integer phase ambiguities + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:ambiguities:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:receivers:global:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:`** + ` ` + + +> Ionospheric slant delay + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:ion_stec:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:receivers:global:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:trop:`** + ` ` + + +> Troposphere corrections + +--- + +###### **`estimation_parameters:receivers:global:trop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:trop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:trop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:trop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:trop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:trop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:trop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:trop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:trop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:`** + ` ` + + +> Troposphere gradients + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:trop_grads:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:`** + ` ` + + +> Troposphere ZWD mapping + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:trop_maps:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:receivers:global:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:receivers:global:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:pcv:`** + ` ` + + +> Antenna phase center variations (experimental) + +--- + +###### **`estimation_parameters:receivers:global:pcv:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:pcv:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:pcv:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:pcv:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:pcv:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:pcv:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:pcv:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:pcv:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:pcv:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:ion_model:`** + ` ` + + +> Ionospheric mapping + +--- + +###### **`estimation_parameters:receivers:global:ion_model:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:ion_model:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:ion_model:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:ion_model:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:ion_model:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:ion_model:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:ion_model:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:ion_model:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:ion_model:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:receivers:global:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:`** + ` ` + + +> Velocity (large gain, for geodetic timescales) + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:strain_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:`** + ` ` + + +> Satellite Laser Ranging range bias + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:slr_range_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:`** + ` ` + + +> Satellite Laser Ranging time bias + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:slr_time_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:`** + ` ` + + +> Integer phase ambiguities + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:ambiguities:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:`** + ` ` + + +> Ionospheric slant delay + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_stec:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:`** + ` ` + + +> Troposphere corrections + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:trop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:`** + ` ` + + +> Troposphere gradients + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_grads:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:`** + ` ` + + +> Troposphere ZWD mapping + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:trop_maps:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:`** + ` ` + + +> Antenna phase center variations (experimental) + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:pcv:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:`** + ` ` + + +> Ionospheric mapping + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:ion_model:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:`** + ` ` + + +> Velocity (large gain, for geodetic timescales) + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:strain_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:`** + ` ` + + +> Satellite Laser Ranging range bias + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_range_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:`** + ` ` + + +> Satellite Laser Ranging time bias + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:slr_time_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:`** + ` ` + + +> Integer phase ambiguities + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ambiguities:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:`** + ` ` + + +> Ionospheric slant delay + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_stec:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:`** + ` ` + + +> Troposphere corrections + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:`** + ` ` + + +> Troposphere gradients + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_grads:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:`** + ` ` + + +> Troposphere ZWD mapping + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:trop_maps:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:`** + ` ` + + +> Antenna phase center variations (experimental) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:pcv:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:`** + ` ` + + +> Ionospheric mapping + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ion_model:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:`** + ` ` + + +> Velocity (large gain, for geodetic timescales) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:strain_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:`** + ` ` + + +> Satellite Laser Ranging range bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:`** + ` ` + + +> Satellite Laser Ranging time bias + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:`** + ` ` + + +> Integer phase ambiguities + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:ambiguities:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:`** + ` ` + + +> Ionospheric slant delay + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_stec:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:`** + ` ` + + +> Troposphere corrections + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:trop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:`** + ` ` + + +> Troposphere gradients + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_grads:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:`** + ` ` + + +> Troposphere ZWD mapping + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:trop_maps:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:`** + ` ` + + +> Antenna phase center variations (experimental) + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:pcv:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:`** + ` ` + + +> Ionospheric mapping + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:ion_model:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:`** + ` ` + + +> Velocity (large gain, for geodetic timescales) + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:strain_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:`** + ` ` + + +> Satellite Laser Ranging range bias + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_range_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:`** + ` ` + + +> Satellite Laser Ranging time bias + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:slr_time_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:`** + ` ` + + +> Integer phase ambiguities + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ambiguities:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:`** + ` ` + + +> Ionospheric slant delay + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_stec:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:`** + ` ` + + +> Troposphere corrections + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:`** + ` ` + + +> Troposphere gradients + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_grads:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:`** + ` ` + + +> Troposphere ZWD mapping + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:trop_maps:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:`** + ` ` + + +> Antenna phase center variations (experimental) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:pcv:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:`** + ` ` + + +> Ionospheric mapping + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ion_model:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:`** + ` ` + + +> Velocity (large gain, for geodetic timescales) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:strain_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:`** + ` ` + + +> Satellite Laser Ranging range bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_range_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:`** + ` ` + + +> Satellite Laser Ranging time bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:slr_time_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:`** + ` ` + + +> Integer phase ambiguities + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:`** + ` ` + + +> Ionospheric slant delay + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:`** + ` ` + + +> Troposphere corrections + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:`** + ` ` + + +> Troposphere gradients + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:`** + ` ` + + +> Troposphere ZWD mapping + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:`** + ` ` + + +> Antenna phase center variations (experimental) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:pcv:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:`** + ` ` + + +> Ionospheric mapping + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:`** + ` ` + + +> Velocity (large gain, for geodetic timescales) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:`** + ` ` + + +> Satellite Laser Ranging range bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:`** + ` ` + + +> Satellite Laser Ranging time bias + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:satellites:global:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:satellites:global:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:satellites:global:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:satellites:global:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:satellites:global:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:global:l1w:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:satellites:g--:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:satellites:g--:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:satellites:g--:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:satellites:g--:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:g--:l1w:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:satellites:gps:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:satellites:gps:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:satellites:gps:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:satellites:gps:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:`** + ` ` + + +> Clocks + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:`** + ` ` + + +> Position + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:`** + ` ` + + +> Velocity + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pos_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:`** + ` ` + + +> Clock rates + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:clock_rate:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:`** + ` ` + + +> Orbital state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orbit:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:`** + ` ` + + +> Phase Center Offsets (experimental) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:pco:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:`** + ` ` + + +> Antenna delta (body frame) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:ant_delta:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:`** + ` ` + + +> Code bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:code_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:`** + ` ` + + +> Phase bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:phase_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:`** + ` ` + + +> Empirical accleration B bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:`** + ` ` + + +> Empirical accleration B 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:`** + ` ` + + +> Empirical accleration B 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:`** + ` ` + + +> Empirical accleration B 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:`** + ` ` + + +> Empirical accleration B 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_b_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:`** + ` ` + + +> Empirical accleration direct bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:`** + ` ` + + +> Empirical accleration direct 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:`** + ` ` + + +> Empirical accleration direct 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:`** + ` ` + + +> Empirical accleration direct 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:`** + ` ` + + +> Empirical accleration direct 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_d_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:`** + ` ` + + +> Empirical accleration normal bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:`** + ` ` + + +> Empirical accleration normal 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:`** + ` ` + + +> Empirical accleration normal 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:`** + ` ` + + +> Empirical accleration normal 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:`** + ` ` + + +> Empirical accleration normal 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_n_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:`** + ` ` + + +> Empirical accleration P bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:`** + ` ` + + +> Empirical accleration P 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:`** + ` ` + + +> Empirical accleration P 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:`** + ` ` + + +> Empirical accleration P 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:`** + ` ` + + +> Empirical accleration P 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_p_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:`** + ` ` + + +> Empirical accleration Q bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:`** + ` ` + + +> Empirical accleration Q 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:`** + ` ` + + +> Empirical accleration Q 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:`** + ` ` + + +> Empirical accleration Q 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:`** + ` ` + + +> Empirical accleration Q 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_q_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:`** + ` ` + + +> Empirical accleration radial bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:`** + ` ` + + +> Empirical accleration radial 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:`** + ` ` + + +> Empirical accleration radial 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:`** + ` ` + + +> Empirical accleration radial 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:`** + ` ` + + +> Empirical accleration radial 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_r_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:`** + ` ` + + +> Empirical accleration tangential bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:`** + ` ` + + +> Empirical accleration tangential 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:`** + ` ` + + +> Empirical accleration tangential 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:`** + ` ` + + +> Empirical accleration tangential 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:`** + ` ` + + +> Empirical accleration tangential 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_t_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:`** + ` ` + + +> Empirical accleration Y bias + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_0:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:`** + ` ` + + +> Empirical accleration Y 1 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_1:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:`** + ` ` + + +> Empirical accleration Y 2 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_2:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:`** + ` ` + + +> Empirical accleration Y 3 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_3:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:`** + ` ` + + +> Empirical accleration Y 4 per rev + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:emp_y_4:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:accelerometer_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_bias:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:gyro_scale:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:imu_offset:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:`** + ` ` + + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:satellites:gps:l1w:orientation:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:global_models:`** + ` ` + + +--- + +###### **`estimation_parameters:global_models:eop:`** + ` ` + + +--- + +###### **`estimation_parameters:global_models:eop:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:global_models:eop:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:global_models:eop:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:global_models:eop:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:global_models:eop:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:global_models:eop:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:global_models:eop:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:global_models:eop:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:global_models:eop:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:global_models:eop_rates:`** + ` ` + + +--- + +###### **`estimation_parameters:global_models:eop_rates:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:global_models:eop_rates:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:global_models:eop_rates:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:global_models:eop_rates:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:global_models:eop_rates:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:global_models:eop_rates:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:global_models:eop_rates:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:global_models:eop_rates:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:global_models:eop_rates:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +###### **`estimation_parameters:global_models:ion:`** + ` ` + + +--- + +###### **`estimation_parameters:global_models:ion:estimated:`** + `[false] ` + + +Estimate state in kalman filter + +--- + +###### **`estimation_parameters:global_models:ion:sigma:`** + `[-1] ` + + +Apriori sigma values - if zero, will be initialised using least squares + +--- + +###### **`estimation_parameters:global_models:ion:process_noise:`** + `[0] ` + + +Process noise sigmas + +--- + +###### **`estimation_parameters:global_models:ion:process_noise_dt:`** + [`E_Period`](#e_period) `SECOND ` + + +Time unit for process noise {second, minute, hour, day, week, year, seconds, minutes, hours, days, weeks, years, sec, min, hr, dy, wk, yr, secs, mins, hrs, dys, wks, yrs, sqrt_sec, sqrt_min, sqrt_hr, sqrt_dy, sqrt_wk, sqrt_yr, sqrt_secs, sqrt_mins, sqrt_hrs, sqrt_dys, sqrt_wks, sqrt_yrs, sqrt_second, sqrt_minute, sqrt_hour, sqrt_day, sqrt_week, sqrt_year, sqrt_seconds, sqrt_minutes, sqrt_hours, sqrt_days, sqrt_weeks, sqrt_years} + +--- + +###### **`estimation_parameters:global_models:ion:apriori_value:`** + `[0] ` + + +Apriori state values + +--- + +###### **`estimation_parameters:global_models:ion:use_remote_sigma:`** + `[false] ` + + +Use remote filter sigma for initial sigma + +--- + +###### **`estimation_parameters:global_models:ion:comment:`** + `[""] ` + + +Comment to apply to the state + +--- + +###### **`estimation_parameters:global_models:ion:mu:`** + `[0] ` + + +Desired mean value for gauss markov states + +--- + +###### **`estimation_parameters:global_models:ion:tau:`** + `[-1] ` + + +Correlation times for gauss markov noise, defaults to -1 -> inf (Random Walk) + +--- + +## mongo: + +###### **`mongo:`** + ` ` + + +> Mongo is a database used to store results and intermediate values for later analysis and inter-process communication + +--- + +###### **`mongo:enable:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Enable and connect to mongo database {none, primary, secondary, both} + +--- + +###### **`mongo:delete_history:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Drop the collection in the database at the beginning of the run to only show fresh data {none, primary, secondary, both} + +--- + +###### **`mongo:output_components:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output components of measurements {none, primary, secondary, both} + +--- + +###### **`mongo:output_cumulative:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output cumulative residuals of components of measurements {none, primary, secondary, both} + +--- + +###### **`mongo:output_measurements:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output measurements and their residuals {none, primary, secondary, both} + +--- + +###### **`mongo:output_state_covars:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output covariance values of related states {none, primary, secondary, both} + +--- + +###### **`mongo:output_states:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output states {none, primary, secondary, both} + +--- + +###### **`mongo:cull_history:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Erase old database objects to limit the size and speed degredation over long runs {none, primary, secondary, both} + +--- + +###### **`mongo:min_cull_age:`** + `300 ` + + +Age of which to cull history + +--- + +###### **`mongo:output_config:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output config {none, primary, secondary, both} + +--- + +###### **`mongo:output_logs:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output console trace and warnings to mongo with timestamps and other metadata {none, primary, secondary, both} + +--- + +###### **`mongo:output_predictions:`** + [`E_Mongo`](#e_mongo) `NONE ` + + + {none, primary, secondary, both} + +--- + +###### **`mongo:output_ssr_precursors:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output orbits, clocks, and bias estimates to allow communication to ssr generating processes {none, primary, secondary, both} + +--- + +###### **`mongo:output_test_stats:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output test statistics {none, primary, secondary, both} + +--- + +###### **`mongo:output_trace:`** + [`E_Mongo`](#e_mongo) `NONE ` + + +Output trace {none, primary, secondary, both} + +--- + +###### **`mongo:queue_outputs:`** + `false ` + + +Output data in a separate thread - may reduce latency + +--- + +###### **`mongo:use_predictions:`** + [`E_Mongo`](#e_mongo) `NONE ` + + + {none, primary, secondary, both} + +--- + +###### **`mongo:primary_database:`** + `"" ` + + +--- + +###### **`mongo:primary_suffix:`** + `"" ` + + +Suffix to append to database elements to make distinctions between runs for comparison + +--- + +###### **`mongo:primary_uri:`** + `"mongodb://localhost:27017" ` + + +Location and port of the mongo database to connect to + +--- + +###### **`mongo:secondary_database:`** + `"" ` + + +--- + +###### **`mongo:secondary_suffix:`** + `"" ` + + +Suffix to append to database elements to make distinctions between runs for comparison + +--- + +###### **`mongo:secondary_uri:`** + `"mongodb://localhost:27017" ` + + +Location and port of the mongo database to connect to + +--- + +###### **`mongo:sent_predictions:`** + [`[KF]`](#kf) `[ORBIT, REC_POS, SAT_CLOCK, CODE_BIAS, PHASE_BIAS, EOP, EOP_RATE] ` + + +Filter states to predict and send to mongo [none, one, all, rec_pos, rec_vel, rec_pos_rate, rec_acc, strain_rate, pos, vel, acc, heading, orientation, ref_sys_bias, rec_clock, rec_sys_bias, rec_clock_rate, rec_sys_bias_rate, rec_clock_rate_gm, rec_sys_bias_rate_gm, sat_clock, sat_clock_rate, sat_clock_rate_gm, trop, trop_grad, trop_model, ionospheric, iono_stec, rec_pco_x, rec_pco_y, rec_pco_z, sat_pco_x, sat_pco_y, sat_pco_z, rec_pcv, ant_delta, eop, eop_rate, calc, slr_rec_range_bias, slr_rec_time_bias, xform_xlate, xform_rtate, xform_scale, xform_delay, ambiguity, code_bias, phase_bias, z_amb, reference, begin_meas_states, code_meas, phas_meas, laser_meas, pseudo_meas, orbit_meas, filter_meas, end_meas_states, begin_orbit_states, orbit, emp_d_0, emp_d_1, emp_d_2, emp_d_3, emp_d_4, emp_y_0, emp_y_1, emp_y_2, emp_y_3, emp_y_4, emp_b_0, emp_b_1, emp_b_2, emp_b_3, emp_b_4, emp_r_0, emp_r_1, emp_r_2, emp_r_3, emp_r_4, emp_t_0, emp_t_1, emp_t_2, emp_t_3, emp_t_4, emp_n_0, emp_n_1, emp_n_2, emp_n_3, emp_n_4, emp_p_0, emp_p_1, emp_p_2, emp_p_3, emp_p_4, emp_q_0, emp_q_1, emp_q_2, emp_q_3, emp_q_4, end_orbit_states, begin_inertial_states, gyro_bias, gyro_scale, accl_bias, accl_scale, imu_offset, end_inertial_states, range] + +--- + +###### **`mongo:used_predictions:`** + [`[KF]`](#kf) `[ORBIT, REC_POS, SAT_CLOCK, CODE_BIAS, PHASE_BIAS, EOP, EOP_RATE] ` + + +Filter states to retrieve from mongo [none, one, all, rec_pos, rec_vel, rec_pos_rate, rec_acc, strain_rate, pos, vel, acc, heading, orientation, ref_sys_bias, rec_clock, rec_sys_bias, rec_clock_rate, rec_sys_bias_rate, rec_clock_rate_gm, rec_sys_bias_rate_gm, sat_clock, sat_clock_rate, sat_clock_rate_gm, trop, trop_grad, trop_model, ionospheric, iono_stec, rec_pco_x, rec_pco_y, rec_pco_z, sat_pco_x, sat_pco_y, sat_pco_z, rec_pcv, ant_delta, eop, eop_rate, calc, slr_rec_range_bias, slr_rec_time_bias, xform_xlate, xform_rtate, xform_scale, xform_delay, ambiguity, code_bias, phase_bias, z_amb, reference, begin_meas_states, code_meas, phas_meas, laser_meas, pseudo_meas, orbit_meas, filter_meas, end_meas_states, begin_orbit_states, orbit, emp_d_0, emp_d_1, emp_d_2, emp_d_3, emp_d_4, emp_y_0, emp_y_1, emp_y_2, emp_y_3, emp_y_4, emp_b_0, emp_b_1, emp_b_2, emp_b_3, emp_b_4, emp_r_0, emp_r_1, emp_r_2, emp_r_3, emp_r_4, emp_t_0, emp_t_1, emp_t_2, emp_t_3, emp_t_4, emp_n_0, emp_n_1, emp_n_2, emp_n_3, emp_n_4, emp_p_0, emp_p_1, emp_p_2, emp_p_3, emp_p_4, emp_q_0, emp_q_1, emp_q_2, emp_q_3, emp_q_4, end_orbit_states, begin_inertial_states, gyro_bias, gyro_scale, accl_bias, accl_scale, imu_offset, end_inertial_states, range] + +--- + +## debug: + +###### **`debug:`** + ` ` + + +> Debug options are designed for developers and should probably not be used by normal users + +--- + +###### **`debug:check_plumbing:`** + `false ` + + +Debugging option to show sizes of objects in memory to detect leaks + +--- + +###### **`debug:explain_measurements:`** + `false ` + + +Debugging option to show verbose measurement coefficients + +--- + +###### **`debug:fatal_message_level:`** + `0 ` + + +Threshold level for exiting the program early (0-2) + +--- + +###### **`debug:mincon_filename:`** + `"preMinconState.bin" ` + + +Filename of pre-mincon filter state for backup/loading + +--- + +###### **`debug:mincon_only:`** + `false ` + + +Debugging option to re-run minimum constraints code + +--- + +###### **`debug:output_mincon:`** + `false ` + + +Debugging option to only save pre-minimum constraints filter state + +--- + +###### **`debug:retain_rts_files:`** + `false ` + + +Debugging option to keep rts files for post processing + +--- + +###### **`debug:rts_only:`** + `false ` + + +Debugging option to only re-run rts from previous run + +--- + +###### **`debug:check_broadcast_differences:`** + `false ` + + +--- + +###### **`debug:compare_attitudes:`** + `false ` + + +--- + +###### **`debug:compare_clocks:`** + `false ` + + +--- + +###### **`debug:compare_orbits:`** + `false ` + + +--- + +# Enum Details + +--- + +### E_ARmode + +Valid enum values are: +- `off` +- `round` +- `iter_rnd` +- `bootst` +- `lambda` +- `lambda_alt` +- `lambda_al2` +- `lambda_bie` + +For options: + +- [`processing_options:ambiguity_resolution:mode:`](#processing_optionsambiguity_resolutionmode) +--- + +### E_ChiSqMode + +Valid enum values are: +- `innovation` +- `measurement` +- `state` + +For options: + +- [`processing_options:minimum_constraints:outlier_screening:chi_square:mode:`](#processing_optionsminimum_constraintsoutlier_screeningchi_squaremode) +- [`processing_options:ppp_filter:outlier_screening:chi_square:mode:`](#processing_optionsppp_filteroutlier_screeningchi_squaremode) +- [`processing_options:ion_filter:outlier_screening:chi_square:mode:`](#processing_optionsion_filteroutlier_screeningchi_squaremode) +- [`processing_options:spp:outlier_screening:chi_square:mode:`](#processing_optionssppoutlier_screeningchi_squaremode) +--- + +### E_Inverter + +Valid enum values are: +- `none` +- `inv` +- `llt` +- `ldlt` +- `colpivhqr` +- `bdcsvd` +- `jacobisvd` +- `fullpivlu` +- `first_unsupported` +- `fullpivhqr` + +For options: + +- [`processing_options:minimum_constraints:inverter:`](#processing_optionsminimum_constraintsinverter) +- [`processing_options:minimum_constraints:rts:inverter:`](#processing_optionsminimum_constraintsrtsinverter) +- [`processing_options:ppp_filter:inverter:`](#processing_optionsppp_filterinverter) +- [`processing_options:ppp_filter:rts:inverter:`](#processing_optionsppp_filterrtsinverter) +- [`processing_options:ion_filter:inverter:`](#processing_optionsion_filterinverter) +- [`processing_options:ion_filter:rts:inverter:`](#processing_optionsion_filterrtsinverter) +--- + +### E_IonoMapFn + +Valid enum values are: +- `slm` +- `mslm` +- `mlm` +- `klobuchar` + +For options: + +- [`receiver_options:global:models:ionospheric_components:mapping_function:`](#receiver_optionsglobalmodelsionospheric_componentsmapping_function) +- [`receiver_options:global:gps:models:ionospheric_components:mapping_function:`](#receiver_optionsglobalgpsmodelsionospheric_componentsmapping_function) +- [`receiver_options:global:gps:l1w:models:ionospheric_components:mapping_function:`](#receiver_optionsglobalgpsl1wmodelsionospheric_componentsmapping_function) +- [`receiver_options:xmpl:models:ionospheric_components:mapping_function:`](#receiver_optionsxmplmodelsionospheric_componentsmapping_function) +- [`receiver_options:xmpl:gps:models:ionospheric_components:mapping_function:`](#receiver_optionsxmplgpsmodelsionospheric_componentsmapping_function) +- [`receiver_options:xmpl:gps:l1w:models:ionospheric_components:mapping_function:`](#receiver_optionsxmplgpsl1wmodelsionospheric_componentsmapping_function) +--- + +### E_IonoMode + +Valid enum values are: +- `off` +- `broadcast` : Values derived from broadcast ephemeris streams/files +- `sbas` +- `iono_free_linear_combo` +- `estimate` +- `total_electron_content` +- `qzs` +- `lex` +- `stec` + +For options: + +- [`processing_options:ppp_filter:ionospheric_components:corr_mode:`](#processing_optionsppp_filterionospheric_componentscorr_mode) +- [`processing_options:spp:iono_mode:`](#processing_optionssppiono_mode) +--- + +### E_IonoModel + +Valid enum values are: +- `none` +- `meas_out` +- `bspline` +- `spherical_caps` +- `spherical_harmonics` +- `local` + +For options: + +- [`processing_options:ion_filter:model:`](#processing_optionsion_filtermodel) +--- + +### E_Mincon + +Valid enum values are: +- `pseudo_obs` +- `weight_matrix` +- `variance_inverse` +- `covariance_inverse` + +For options: + +- [`processing_options:minimum_constraints:application_mode:`](#processing_optionsminimum_constraintsapplication_mode) +--- + +### E_Mongo + +Valid enum values are: +- `none` +- `primary` +- `secondary` +- `both` + +For options: + +- [`mongo:enable:`](#mongoenable) +- [`mongo:output_measurements:`](#mongooutput_measurements) +- [`mongo:output_components:`](#mongooutput_components) +- [`mongo:output_cumulative:`](#mongooutput_cumulative) +- [`mongo:output_states:`](#mongooutput_states) +- [`mongo:output_state_covars:`](#mongooutput_state_covars) +- [`mongo:output_config:`](#mongooutput_config) +- [`mongo:output_trace:`](#mongooutput_trace) +- [`mongo:output_test_stats:`](#mongooutput_test_stats) +- [`mongo:output_logs:`](#mongooutput_logs) +- [`mongo:output_ssr_precursors:`](#mongooutput_ssr_precursors) +- [`mongo:delete_history:`](#mongodelete_history) +- [`mongo:cull_history:`](#mongocull_history) +- [`mongo:use_predictions:`](#mongouse_predictions) +- [`mongo:output_predictions:`](#mongooutput_predictions) +--- + +### E_NavMsgType + +Valid enum values are: +- `none` +- `lnav` +- `fdma` +- `fnav` +- `inav` +- `ifnv` +- `d1` +- `d2` +- `d1d2` +- `sbas` +- `cnav` +- `cnv1` +- `cnv2` +- `cnv3` +- `cnvx` + +For options: + +- [`processing_options:gnss_general:sys_options:gps:used_nav_type:`](#processing_optionsgnss_generalsys_optionsgpsused_nav_type) +- [`processing_options:gnss_general:sys_options:gal:used_nav_type:`](#processing_optionsgnss_generalsys_optionsgalused_nav_type) +- [`processing_options:gnss_general:sys_options:glo:used_nav_type:`](#processing_optionsgnss_generalsys_optionsgloused_nav_type) +- [`processing_options:gnss_general:sys_options:qzs:used_nav_type:`](#processing_optionsgnss_generalsys_optionsqzsused_nav_type) +- [`processing_options:gnss_general:sys_options:sbs:used_nav_type:`](#processing_optionsgnss_generalsys_optionssbsused_nav_type) +- [`processing_options:gnss_general:sys_options:bds:used_nav_type:`](#processing_optionsgnss_generalsys_optionsbdsused_nav_type) +- [`processing_options:gnss_general:sys_options:leo:used_nav_type:`](#processing_optionsgnss_generalsys_optionsleoused_nav_type) +--- + +### E_NoiseModel + +Valid enum values are: +- `uniform` +- `elevation_dependent` + +For options: + +- [`satellite_options:global:error_model:`](#satellite_optionsglobalerror_model) +- [`satellite_options:global:l1w:error_model:`](#satellite_optionsgloball1werror_model) +- [`satellite_options:gps:error_model:`](#satellite_optionsgpserror_model) +- [`satellite_options:gps:l1w:error_model:`](#satellite_optionsgpsl1werror_model) +- [`satellite_options:g--:error_model:`](#satellite_optionsg--error_model) +- [`satellite_options:g--:l1w:error_model:`](#satellite_optionsg--l1werror_model) +- [`receiver_options:global:error_model:`](#receiver_optionsglobalerror_model) +- [`receiver_options:global:gps:error_model:`](#receiver_optionsglobalgpserror_model) +- [`receiver_options:global:gps:l1w:error_model:`](#receiver_optionsglobalgpsl1werror_model) +- [`receiver_options:xmpl:error_model:`](#receiver_optionsxmplerror_model) +- [`receiver_options:xmpl:gps:error_model:`](#receiver_optionsxmplgpserror_model) +- [`receiver_options:xmpl:gps:l1w:error_model:`](#receiver_optionsxmplgpsl1werror_model) +--- + +### E_ObsCode + +Valid enum values are: +- `none` +- `l1c` +- `l1p` +- `l1w` +- `l1y` +- `l1m` +- `l1n` +- `l1s` +- `l1l` +- `l1e` +- `l1a` +- `l1b` +- `l1x` +- `l1z` +- `l2c` +- `l2d` +- `l2s` +- `l2l` +- `l2x` +- `l2p` +- `l2w` +- `l2y` +- `l2m` +- `l2n` +- `l5i` +- `l5q` +- `l5x` +- `l7i` +- `l7q` +- `l7x` +- `l6a` +- `l6b` +- `l6c` +- `l6x` +- `l6z` +- `l6s` +- `l6l` +- `l8i` +- `l8q` +- `l8x` +- `l2i` +- `l2q` +- `l6i` +- `l6q` +- `l3i` +- `l3q` +- `l3x` +- `l1i` +- `l1q` +- `l4a` +- `l4b` +- `l4x` +- `l6e` +- `l1d` +- `l5d` +- `l5p` +- `l9a` +- `l9b` +- `l9c` +- `l9x` +- `l5a` +- `l5b` +- `l5c` +- `l5z` +- `l6d` +- `l6p` +- `l7d` +- `l7p` +- `l7z` +- `l8d` +- `l8p` +- `l8z` +- `auto` + +For options: + +- [`processing_options:gnss_general:sys_options:gps:code_priorities:`](#processing_optionsgnss_generalsys_optionsgpscode_priorities) +- [`processing_options:gnss_general:sys_options:gal:code_priorities:`](#processing_optionsgnss_generalsys_optionsgalcode_priorities) +- [`processing_options:gnss_general:sys_options:glo:code_priorities:`](#processing_optionsgnss_generalsys_optionsglocode_priorities) +- [`processing_options:gnss_general:sys_options:qzs:code_priorities:`](#processing_optionsgnss_generalsys_optionsqzscode_priorities) +- [`processing_options:gnss_general:sys_options:sbs:code_priorities:`](#processing_optionsgnss_generalsys_optionssbscode_priorities) +- [`processing_options:gnss_general:sys_options:bds:code_priorities:`](#processing_optionsgnss_generalsys_optionsbdscode_priorities) +- [`processing_options:gnss_general:sys_options:leo:code_priorities:`](#processing_optionsgnss_generalsys_optionsleocode_priorities) +- [`satellite_options:global:clock_codes:`](#satellite_optionsglobalclock_codes) +- [`satellite_options:global:l1w:clock_codes:`](#satellite_optionsgloball1wclock_codes) +- [`satellite_options:gps:clock_codes:`](#satellite_optionsgpsclock_codes) +- [`satellite_options:gps:l1w:clock_codes:`](#satellite_optionsgpsl1wclock_codes) +- [`satellite_options:g--:clock_codes:`](#satellite_optionsg--clock_codes) +- [`satellite_options:g--:l1w:clock_codes:`](#satellite_optionsg--l1wclock_codes) +- [`receiver_options:global:clock_codes:`](#receiver_optionsglobalclock_codes) +- [`receiver_options:global:zero_dcb_codes:`](#receiver_optionsglobalzero_dcb_codes) +- [`receiver_options:global:rinex2:rnx_code_conversions:none:`](#receiver_optionsglobalrinex2rnx_code_conversionsnone) +- [`receiver_options:global:rinex2:rnx_phase_conversions:none:`](#receiver_optionsglobalrinex2rnx_phase_conversionsnone) +- [`receiver_options:global:rinex2:rnx_code_conversions:p1:`](#receiver_optionsglobalrinex2rnx_code_conversionsp1) +- [`receiver_options:global:rinex2:rnx_phase_conversions:p1:`](#receiver_optionsglobalrinex2rnx_phase_conversionsp1) +- [`receiver_options:global:rinex2:rnx_code_conversions:p2:`](#receiver_optionsglobalrinex2rnx_code_conversionsp2) +- [`receiver_options:global:rinex2:rnx_phase_conversions:p2:`](#receiver_optionsglobalrinex2rnx_phase_conversionsp2) +- [`receiver_options:global:rinex2:rnx_code_conversions:c1:`](#receiver_optionsglobalrinex2rnx_code_conversionsc1) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c1:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc1) +- [`receiver_options:global:rinex2:rnx_code_conversions:c2:`](#receiver_optionsglobalrinex2rnx_code_conversionsc2) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c2:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc2) +- [`receiver_options:global:rinex2:rnx_code_conversions:c3:`](#receiver_optionsglobalrinex2rnx_code_conversionsc3) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c3:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc3) +- [`receiver_options:global:rinex2:rnx_code_conversions:c4:`](#receiver_optionsglobalrinex2rnx_code_conversionsc4) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c4:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc4) +- [`receiver_options:global:rinex2:rnx_code_conversions:c5:`](#receiver_optionsglobalrinex2rnx_code_conversionsc5) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c5:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc5) +- [`receiver_options:global:rinex2:rnx_code_conversions:c6:`](#receiver_optionsglobalrinex2rnx_code_conversionsc6) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c6:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc6) +- [`receiver_options:global:rinex2:rnx_code_conversions:c7:`](#receiver_optionsglobalrinex2rnx_code_conversionsc7) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c7:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc7) +- [`receiver_options:global:rinex2:rnx_code_conversions:c8:`](#receiver_optionsglobalrinex2rnx_code_conversionsc8) +- [`receiver_options:global:rinex2:rnx_phase_conversions:c8:`](#receiver_optionsglobalrinex2rnx_phase_conversionsc8) +- [`receiver_options:global:rinex2:rnx_code_conversions:l1:`](#receiver_optionsglobalrinex2rnx_code_conversionsl1) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l1:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl1) +- [`receiver_options:global:rinex2:rnx_code_conversions:l2:`](#receiver_optionsglobalrinex2rnx_code_conversionsl2) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l2:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl2) +- [`receiver_options:global:rinex2:rnx_code_conversions:l3:`](#receiver_optionsglobalrinex2rnx_code_conversionsl3) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l3:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl3) +- [`receiver_options:global:rinex2:rnx_code_conversions:l4:`](#receiver_optionsglobalrinex2rnx_code_conversionsl4) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l4:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl4) +- [`receiver_options:global:rinex2:rnx_code_conversions:l5:`](#receiver_optionsglobalrinex2rnx_code_conversionsl5) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l5:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl5) +- [`receiver_options:global:rinex2:rnx_code_conversions:l6:`](#receiver_optionsglobalrinex2rnx_code_conversionsl6) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l6:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl6) +- [`receiver_options:global:rinex2:rnx_code_conversions:l7:`](#receiver_optionsglobalrinex2rnx_code_conversionsl7) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l7:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl7) +- [`receiver_options:global:rinex2:rnx_code_conversions:l8:`](#receiver_optionsglobalrinex2rnx_code_conversionsl8) +- [`receiver_options:global:rinex2:rnx_phase_conversions:l8:`](#receiver_optionsglobalrinex2rnx_phase_conversionsl8) +- [`receiver_options:global:rinex2:rnx_code_conversions:la:`](#receiver_optionsglobalrinex2rnx_code_conversionsla) +- [`receiver_options:global:rinex2:rnx_phase_conversions:la:`](#receiver_optionsglobalrinex2rnx_phase_conversionsla) +- [`receiver_options:global:gps:clock_codes:`](#receiver_optionsglobalgpsclock_codes) +- [`receiver_options:global:gps:zero_dcb_codes:`](#receiver_optionsglobalgpszero_dcb_codes) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:none:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsnone) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:none:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsnone) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:p1:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsp1) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:p1:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsp1) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:p2:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsp2) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:p2:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsp2) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c1:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc1) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c1:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc1) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c2:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc2) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c2:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc2) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c3:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc3) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c3:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc3) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c4:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc4) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c4:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc4) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c5:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc5) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c5:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc5) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c6:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc6) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c6:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc6) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c7:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc7) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c7:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc7) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:c8:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsc8) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:c8:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsc8) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l1:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl1) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l1:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl1) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l2:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl2) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l2:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl2) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l3:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl3) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l3:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl3) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l4:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl4) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l4:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl4) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l5:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl5) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l5:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl5) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l6:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl6) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l6:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl6) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l7:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl7) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l7:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl7) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:l8:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsl8) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:l8:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsl8) +- [`receiver_options:global:gps:rinex2:rnx_code_conversions:la:`](#receiver_optionsglobalgpsrinex2rnx_code_conversionsla) +- [`receiver_options:global:gps:rinex2:rnx_phase_conversions:la:`](#receiver_optionsglobalgpsrinex2rnx_phase_conversionsla) +- [`receiver_options:global:gps:l1w:clock_codes:`](#receiver_optionsglobalgpsl1wclock_codes) +- [`receiver_options:global:gps:l1w:zero_dcb_codes:`](#receiver_optionsglobalgpsl1wzero_dcb_codes) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:none:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsnone) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:none:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsnone) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:p1:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsp1) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:p1:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsp1) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:p2:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsp2) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:p2:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsp2) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c1:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc1) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c1:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc1) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c2:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc2) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c2:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc2) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c3:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc3) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c3:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc3) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c4:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc4) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c4:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc4) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c5:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc5) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c5:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc5) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c6:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc6) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c6:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc6) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c7:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc7) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c7:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc7) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:c8:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsc8) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:c8:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsc8) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l1:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl1) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l1:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl1) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l2:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl2) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l2:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl2) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l3:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl3) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l3:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl3) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l4:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl4) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l4:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl4) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l5:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl5) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l5:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl5) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l6:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl6) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l6:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl6) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l7:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl7) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l7:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl7) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:l8:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsl8) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:l8:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsl8) +- [`receiver_options:global:gps:l1w:rinex2:rnx_code_conversions:la:`](#receiver_optionsglobalgpsl1wrinex2rnx_code_conversionsla) +- [`receiver_options:global:gps:l1w:rinex2:rnx_phase_conversions:la:`](#receiver_optionsglobalgpsl1wrinex2rnx_phase_conversionsla) +- [`receiver_options:xmpl:clock_codes:`](#receiver_optionsxmplclock_codes) +- [`receiver_options:xmpl:zero_dcb_codes:`](#receiver_optionsxmplzero_dcb_codes) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:none:`](#receiver_optionsxmplrinex2rnx_code_conversionsnone) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:none:`](#receiver_optionsxmplrinex2rnx_phase_conversionsnone) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:p1:`](#receiver_optionsxmplrinex2rnx_code_conversionsp1) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:p1:`](#receiver_optionsxmplrinex2rnx_phase_conversionsp1) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:p2:`](#receiver_optionsxmplrinex2rnx_code_conversionsp2) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:p2:`](#receiver_optionsxmplrinex2rnx_phase_conversionsp2) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c1:`](#receiver_optionsxmplrinex2rnx_code_conversionsc1) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c1:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc1) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c2:`](#receiver_optionsxmplrinex2rnx_code_conversionsc2) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c2:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc2) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c3:`](#receiver_optionsxmplrinex2rnx_code_conversionsc3) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c3:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc3) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c4:`](#receiver_optionsxmplrinex2rnx_code_conversionsc4) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c4:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc4) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c5:`](#receiver_optionsxmplrinex2rnx_code_conversionsc5) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c5:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc5) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c6:`](#receiver_optionsxmplrinex2rnx_code_conversionsc6) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c6:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc6) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c7:`](#receiver_optionsxmplrinex2rnx_code_conversionsc7) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c7:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc7) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:c8:`](#receiver_optionsxmplrinex2rnx_code_conversionsc8) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:c8:`](#receiver_optionsxmplrinex2rnx_phase_conversionsc8) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l1:`](#receiver_optionsxmplrinex2rnx_code_conversionsl1) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l1:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl1) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l2:`](#receiver_optionsxmplrinex2rnx_code_conversionsl2) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l2:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl2) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l3:`](#receiver_optionsxmplrinex2rnx_code_conversionsl3) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l3:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl3) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l4:`](#receiver_optionsxmplrinex2rnx_code_conversionsl4) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l4:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl4) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l5:`](#receiver_optionsxmplrinex2rnx_code_conversionsl5) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l5:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl5) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l6:`](#receiver_optionsxmplrinex2rnx_code_conversionsl6) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l6:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl6) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l7:`](#receiver_optionsxmplrinex2rnx_code_conversionsl7) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l7:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl7) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:l8:`](#receiver_optionsxmplrinex2rnx_code_conversionsl8) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:l8:`](#receiver_optionsxmplrinex2rnx_phase_conversionsl8) +- [`receiver_options:xmpl:rinex2:rnx_code_conversions:la:`](#receiver_optionsxmplrinex2rnx_code_conversionsla) +- [`receiver_options:xmpl:rinex2:rnx_phase_conversions:la:`](#receiver_optionsxmplrinex2rnx_phase_conversionsla) +- [`receiver_options:xmpl:gps:clock_codes:`](#receiver_optionsxmplgpsclock_codes) +- [`receiver_options:xmpl:gps:zero_dcb_codes:`](#receiver_optionsxmplgpszero_dcb_codes) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:none:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsnone) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:none:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsnone) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:p1:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsp1) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:p1:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsp1) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:p2:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsp2) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:p2:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsp2) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c1:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc1) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c1:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc1) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c2:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc2) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c2:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc2) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c3:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc3) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c3:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc3) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c4:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc4) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c4:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc4) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c5:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc5) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c5:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc5) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c6:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc6) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c6:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc6) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c7:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc7) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c7:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc7) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:c8:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsc8) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:c8:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsc8) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l1:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl1) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l1:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl1) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l2:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl2) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l2:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl2) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l3:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl3) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l3:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl3) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l4:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl4) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l4:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl4) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l5:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl5) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l5:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl5) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l6:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl6) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l6:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl6) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l7:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl7) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l7:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl7) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:l8:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsl8) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:l8:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsl8) +- [`receiver_options:xmpl:gps:rinex2:rnx_code_conversions:la:`](#receiver_optionsxmplgpsrinex2rnx_code_conversionsla) +- [`receiver_options:xmpl:gps:rinex2:rnx_phase_conversions:la:`](#receiver_optionsxmplgpsrinex2rnx_phase_conversionsla) +- [`receiver_options:xmpl:gps:l1w:clock_codes:`](#receiver_optionsxmplgpsl1wclock_codes) +- [`receiver_options:xmpl:gps:l1w:zero_dcb_codes:`](#receiver_optionsxmplgpsl1wzero_dcb_codes) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:none:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsnone) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:none:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsnone) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:p1:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsp1) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:p1:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsp1) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:p2:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsp2) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:p2:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsp2) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c1:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc1) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c1:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc1) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c2:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc2) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c2:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc2) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c3:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc3) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c3:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc3) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c4:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc4) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c4:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc4) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c5:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc5) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c5:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc5) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c6:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc6) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c6:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc6) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c7:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc7) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c7:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc7) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:c8:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsc8) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:c8:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsc8) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l1:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl1) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l1:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl1) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l2:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl2) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l2:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl2) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l3:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl3) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l3:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl3) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l4:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl4) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l4:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl4) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l5:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl5) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l5:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl5) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l6:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl6) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l6:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl6) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l7:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl7) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l7:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl7) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:l8:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsl8) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:l8:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsl8) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_code_conversions:la:`](#receiver_optionsxmplgpsl1wrinex2rnx_code_conversionsla) +- [`receiver_options:xmpl:gps:l1w:rinex2:rnx_phase_conversions:la:`](#receiver_optionsxmplgpsl1wrinex2rnx_phase_conversionsla) +--- + +### E_OffsetType + +Valid enum values are: +- `unspecified` +- `apc` +- `com` + +For options: + +- [`inputs:satellite_data:rtcm_inputs:ssr_antenna_offset:`](#inputssatellite_datartcm_inputsssr_antenna_offset) +--- + +### E_OrbexRecord + +Valid enum values are: +- `pcs` +- `vcs` +- `cpc` +- `cvc` +- `pos` +- `vel` +- `clk` +- `crt` +- `att` + +For options: + +- [`outputs:orbex:record_types:`](#outputsorbexrecord_types) +--- + +### E_Period + +Valid enum values are: +- `second` +- `minute` +- `hour` +- `day` +- `week` +- `year` +- `seconds` +- `minutes` +- `hours` +- `days` +- `weeks` +- `years` +- `sec` +- `min` +- `hr` +- `dy` +- `wk` +- `yr` +- `secs` +- `mins` +- `hrs` +- `dys` +- `wks` +- `yrs` +- `sqrt_sec` +- `sqrt_min` +- `sqrt_hr` +- `sqrt_dy` +- `sqrt_wk` +- `sqrt_yr` +- `sqrt_secs` +- `sqrt_mins` +- `sqrt_hrs` +- `sqrt_dys` +- `sqrt_wks` +- `sqrt_yrs` +- `sqrt_second` +- `sqrt_minute` +- `sqrt_hour` +- `sqrt_day` +- `sqrt_week` +- `sqrt_year` +- `sqrt_seconds` +- `sqrt_minutes` +- `sqrt_hours` +- `sqrt_days` +- `sqrt_weeks` +- `sqrt_years` + +For options: + +- [`outputs:output_rotation:period_units:`](#outputsoutput_rotationperiod_units) +- [`processing_options:minimum_constraints:delay:process_noise_dt:`](#processing_optionsminimum_constraintsdelayprocess_noise_dt) +- [`processing_options:minimum_constraints:scale:process_noise_dt:`](#processing_optionsminimum_constraintsscaleprocess_noise_dt) +- [`processing_options:minimum_constraints:rotation:process_noise_dt:`](#processing_optionsminimum_constraintsrotationprocess_noise_dt) +- [`processing_options:minimum_constraints:translation:process_noise_dt:`](#processing_optionsminimum_constraintstranslationprocess_noise_dt) +- [`processing_options:predictions:interval_units:`](#processing_optionspredictionsinterval_units) +- [`processing_options:predictions:interval_units:`](#processing_optionspredictionsinterval_units) +- [`processing_options:predictions:duration_units:`](#processing_optionspredictionsduration_units) +- [`processing_options:predictions:duration_units:`](#processing_optionspredictionsduration_units) +- [`estimation_parameters:global_models:eop:process_noise_dt:`](#estimation_parametersglobal_modelseopprocess_noise_dt) +- [`estimation_parameters:global_models:eop_rates:process_noise_dt:`](#estimation_parametersglobal_modelseop_ratesprocess_noise_dt) +- [`estimation_parameters:global_models:ion:process_noise_dt:`](#estimation_parametersglobal_modelsionprocess_noise_dt) +- [`estimation_parameters:satellites:global:orientation:process_noise_dt:`](#estimation_parameterssatellitesglobalorientationprocess_noise_dt) +- [`estimation_parameters:satellites:global:gyro_bias:process_noise_dt:`](#estimation_parameterssatellitesglobalgyro_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:accelerometer_bias:process_noise_dt:`](#estimation_parameterssatellitesglobalaccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:gyro_scale:process_noise_dt:`](#estimation_parameterssatellitesglobalgyro_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:global:accelerometer_scale:process_noise_dt:`](#estimation_parameterssatellitesglobalaccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:global:imu_offset:process_noise_dt:`](#estimation_parameterssatellitesglobalimu_offsetprocess_noise_dt) +- [`estimation_parameters:satellites:global:clock:process_noise_dt:`](#estimation_parameterssatellitesglobalclockprocess_noise_dt) +- [`estimation_parameters:satellites:global:clock_rate:process_noise_dt:`](#estimation_parameterssatellitesglobalclock_rateprocess_noise_dt) +- [`estimation_parameters:satellites:global:pos:process_noise_dt:`](#estimation_parameterssatellitesglobalposprocess_noise_dt) +- [`estimation_parameters:satellites:global:pos_rate:process_noise_dt:`](#estimation_parameterssatellitesglobalpos_rateprocess_noise_dt) +- [`estimation_parameters:satellites:global:orbit:process_noise_dt:`](#estimation_parameterssatellitesglobalorbitprocess_noise_dt) +- [`estimation_parameters:satellites:global:pco:process_noise_dt:`](#estimation_parameterssatellitesglobalpcoprocess_noise_dt) +- [`estimation_parameters:satellites:global:code_bias:process_noise_dt:`](#estimation_parameterssatellitesglobalcode_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:phase_bias:process_noise_dt:`](#estimation_parameterssatellitesglobalphase_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:ant_delta:process_noise_dt:`](#estimation_parameterssatellitesglobalant_deltaprocess_noise_dt) +- [`estimation_parameters:satellites:global:emp_d_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_d_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_d_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_d_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_d_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_d_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_d_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_d_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_d_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_d_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_y_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_y_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_y_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_y_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_y_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_y_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_y_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_y_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_y_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_y_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_b_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_b_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_b_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_b_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_b_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_b_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_b_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_b_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_b_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_b_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_r_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_r_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_r_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_r_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_r_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_r_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_r_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_r_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_r_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_r_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_t_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_t_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_t_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_t_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_t_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_t_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_t_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_t_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_t_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_t_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_n_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_n_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_n_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_n_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_n_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_n_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_n_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_n_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_n_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_n_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_p_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_p_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_p_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_p_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_p_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_p_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_p_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_p_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_p_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_p_4process_noise_dt) +- [`estimation_parameters:satellites:global:emp_q_0:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_q_0process_noise_dt) +- [`estimation_parameters:satellites:global:emp_q_1:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_q_1process_noise_dt) +- [`estimation_parameters:satellites:global:emp_q_2:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_q_2process_noise_dt) +- [`estimation_parameters:satellites:global:emp_q_3:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_q_3process_noise_dt) +- [`estimation_parameters:satellites:global:emp_q_4:process_noise_dt:`](#estimation_parameterssatellitesglobalemp_q_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:orientation:process_noise_dt:`](#estimation_parameterssatellitesgloball1worientationprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:gyro_bias:process_noise_dt:`](#estimation_parameterssatellitesgloball1wgyro_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:accelerometer_bias:process_noise_dt:`](#estimation_parameterssatellitesgloball1waccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:gyro_scale:process_noise_dt:`](#estimation_parameterssatellitesgloball1wgyro_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:accelerometer_scale:process_noise_dt:`](#estimation_parameterssatellitesgloball1waccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:imu_offset:process_noise_dt:`](#estimation_parameterssatellitesgloball1wimu_offsetprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:clock:process_noise_dt:`](#estimation_parameterssatellitesgloball1wclockprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:clock_rate:process_noise_dt:`](#estimation_parameterssatellitesgloball1wclock_rateprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:pos:process_noise_dt:`](#estimation_parameterssatellitesgloball1wposprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:pos_rate:process_noise_dt:`](#estimation_parameterssatellitesgloball1wpos_rateprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:orbit:process_noise_dt:`](#estimation_parameterssatellitesgloball1worbitprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:pco:process_noise_dt:`](#estimation_parameterssatellitesgloball1wpcoprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:code_bias:process_noise_dt:`](#estimation_parameterssatellitesgloball1wcode_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:phase_bias:process_noise_dt:`](#estimation_parameterssatellitesgloball1wphase_biasprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:ant_delta:process_noise_dt:`](#estimation_parameterssatellitesgloball1want_deltaprocess_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_d_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_d_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_d_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_d_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_d_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_d_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_d_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_d_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_d_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_d_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_y_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_y_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_y_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_y_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_y_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_y_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_y_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_y_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_y_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_y_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_b_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_b_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_b_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_b_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_b_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_b_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_b_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_b_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_b_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_b_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_r_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_r_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_r_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_r_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_r_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_r_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_r_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_r_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_r_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_r_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_t_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_t_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_t_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_t_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_t_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_t_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_t_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_t_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_t_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_t_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_n_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_n_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_n_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_n_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_n_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_n_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_n_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_n_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_n_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_n_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_p_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_p_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_p_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_p_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_p_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_p_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_p_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_p_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_p_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_p_4process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_q_0:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_q_0process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_q_1:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_q_1process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_q_2:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_q_2process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_q_3:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_q_3process_noise_dt) +- [`estimation_parameters:satellites:global:l1w:emp_q_4:process_noise_dt:`](#estimation_parameterssatellitesgloball1wemp_q_4process_noise_dt) +- [`estimation_parameters:satellites:gps:orientation:process_noise_dt:`](#estimation_parameterssatellitesgpsorientationprocess_noise_dt) +- [`estimation_parameters:satellites:gps:gyro_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsgyro_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:accelerometer_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsaccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:gyro_scale:process_noise_dt:`](#estimation_parameterssatellitesgpsgyro_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:gps:accelerometer_scale:process_noise_dt:`](#estimation_parameterssatellitesgpsaccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:gps:imu_offset:process_noise_dt:`](#estimation_parameterssatellitesgpsimu_offsetprocess_noise_dt) +- [`estimation_parameters:satellites:gps:clock:process_noise_dt:`](#estimation_parameterssatellitesgpsclockprocess_noise_dt) +- [`estimation_parameters:satellites:gps:clock_rate:process_noise_dt:`](#estimation_parameterssatellitesgpsclock_rateprocess_noise_dt) +- [`estimation_parameters:satellites:gps:pos:process_noise_dt:`](#estimation_parameterssatellitesgpsposprocess_noise_dt) +- [`estimation_parameters:satellites:gps:pos_rate:process_noise_dt:`](#estimation_parameterssatellitesgpspos_rateprocess_noise_dt) +- [`estimation_parameters:satellites:gps:orbit:process_noise_dt:`](#estimation_parameterssatellitesgpsorbitprocess_noise_dt) +- [`estimation_parameters:satellites:gps:pco:process_noise_dt:`](#estimation_parameterssatellitesgpspcoprocess_noise_dt) +- [`estimation_parameters:satellites:gps:code_bias:process_noise_dt:`](#estimation_parameterssatellitesgpscode_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:phase_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsphase_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:ant_delta:process_noise_dt:`](#estimation_parameterssatellitesgpsant_deltaprocess_noise_dt) +- [`estimation_parameters:satellites:gps:emp_d_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_d_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_d_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_d_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_d_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_d_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_d_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_d_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_d_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_d_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_y_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_y_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_y_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_y_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_y_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_y_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_y_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_y_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_y_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_y_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_b_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_b_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_b_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_b_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_b_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_b_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_b_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_b_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_b_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_b_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_r_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_r_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_r_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_r_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_r_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_r_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_r_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_r_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_r_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_r_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_t_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_t_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_t_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_t_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_t_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_t_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_t_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_t_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_t_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_t_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_n_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_n_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_n_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_n_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_n_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_n_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_n_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_n_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_n_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_n_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_p_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_p_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_p_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_p_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_p_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_p_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_p_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_p_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_p_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_p_4process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_q_0:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_q_0process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_q_1:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_q_1process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_q_2:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_q_2process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_q_3:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_q_3process_noise_dt) +- [`estimation_parameters:satellites:gps:emp_q_4:process_noise_dt:`](#estimation_parameterssatellitesgpsemp_q_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:orientation:process_noise_dt:`](#estimation_parameterssatellitesgpsl1worientationprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:gyro_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wgyro_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:accelerometer_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsl1waccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:gyro_scale:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wgyro_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:accelerometer_scale:process_noise_dt:`](#estimation_parameterssatellitesgpsl1waccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:imu_offset:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wimu_offsetprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:clock:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wclockprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:clock_rate:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wclock_rateprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:pos:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wposprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:pos_rate:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wpos_rateprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:orbit:process_noise_dt:`](#estimation_parameterssatellitesgpsl1worbitprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:pco:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wpcoprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:code_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wcode_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:phase_bias:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wphase_biasprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:ant_delta:process_noise_dt:`](#estimation_parameterssatellitesgpsl1want_deltaprocess_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_d_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_d_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_d_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_d_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_d_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_d_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_d_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_d_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_d_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_d_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_y_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_y_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_y_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_y_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_y_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_y_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_y_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_y_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_y_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_y_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_b_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_b_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_b_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_b_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_b_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_b_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_b_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_b_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_b_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_b_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_r_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_r_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_r_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_r_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_r_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_r_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_r_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_r_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_r_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_r_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_t_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_t_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_t_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_t_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_t_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_t_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_t_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_t_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_t_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_t_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_n_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_n_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_n_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_n_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_n_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_n_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_n_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_n_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_n_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_n_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_p_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_p_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_p_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_p_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_p_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_p_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_p_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_p_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_p_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_p_4process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_q_0:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_q_0process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_q_1:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_q_1process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_q_2:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_q_2process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_q_3:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_q_3process_noise_dt) +- [`estimation_parameters:satellites:gps:l1w:emp_q_4:process_noise_dt:`](#estimation_parameterssatellitesgpsl1wemp_q_4process_noise_dt) +- [`estimation_parameters:satellites:g--:orientation:process_noise_dt:`](#estimation_parameterssatellitesg--orientationprocess_noise_dt) +- [`estimation_parameters:satellites:g--:gyro_bias:process_noise_dt:`](#estimation_parameterssatellitesg--gyro_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:accelerometer_bias:process_noise_dt:`](#estimation_parameterssatellitesg--accelerometer_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:gyro_scale:process_noise_dt:`](#estimation_parameterssatellitesg--gyro_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:g--:accelerometer_scale:process_noise_dt:`](#estimation_parameterssatellitesg--accelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:g--:imu_offset:process_noise_dt:`](#estimation_parameterssatellitesg--imu_offsetprocess_noise_dt) +- [`estimation_parameters:satellites:g--:clock:process_noise_dt:`](#estimation_parameterssatellitesg--clockprocess_noise_dt) +- [`estimation_parameters:satellites:g--:clock_rate:process_noise_dt:`](#estimation_parameterssatellitesg--clock_rateprocess_noise_dt) +- [`estimation_parameters:satellites:g--:pos:process_noise_dt:`](#estimation_parameterssatellitesg--posprocess_noise_dt) +- [`estimation_parameters:satellites:g--:pos_rate:process_noise_dt:`](#estimation_parameterssatellitesg--pos_rateprocess_noise_dt) +- [`estimation_parameters:satellites:g--:orbit:process_noise_dt:`](#estimation_parameterssatellitesg--orbitprocess_noise_dt) +- [`estimation_parameters:satellites:g--:pco:process_noise_dt:`](#estimation_parameterssatellitesg--pcoprocess_noise_dt) +- [`estimation_parameters:satellites:g--:code_bias:process_noise_dt:`](#estimation_parameterssatellitesg--code_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:phase_bias:process_noise_dt:`](#estimation_parameterssatellitesg--phase_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:ant_delta:process_noise_dt:`](#estimation_parameterssatellitesg--ant_deltaprocess_noise_dt) +- [`estimation_parameters:satellites:g--:emp_d_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_d_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_d_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_d_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_d_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_d_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_d_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_d_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_d_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_d_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_y_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_y_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_y_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_y_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_y_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_y_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_y_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_y_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_y_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_y_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_b_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_b_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_b_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_b_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_b_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_b_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_b_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_b_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_b_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_b_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_r_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_r_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_r_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_r_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_r_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_r_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_r_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_r_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_r_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_r_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_t_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_t_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_t_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_t_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_t_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_t_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_t_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_t_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_t_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_t_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_n_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_n_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_n_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_n_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_n_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_n_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_n_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_n_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_n_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_n_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_p_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_p_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_p_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_p_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_p_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_p_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_p_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_p_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_p_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_p_4process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_q_0:process_noise_dt:`](#estimation_parameterssatellitesg--emp_q_0process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_q_1:process_noise_dt:`](#estimation_parameterssatellitesg--emp_q_1process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_q_2:process_noise_dt:`](#estimation_parameterssatellitesg--emp_q_2process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_q_3:process_noise_dt:`](#estimation_parameterssatellitesg--emp_q_3process_noise_dt) +- [`estimation_parameters:satellites:g--:emp_q_4:process_noise_dt:`](#estimation_parameterssatellitesg--emp_q_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:orientation:process_noise_dt:`](#estimation_parameterssatellitesg--l1worientationprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:gyro_bias:process_noise_dt:`](#estimation_parameterssatellitesg--l1wgyro_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:accelerometer_bias:process_noise_dt:`](#estimation_parameterssatellitesg--l1waccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:gyro_scale:process_noise_dt:`](#estimation_parameterssatellitesg--l1wgyro_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:accelerometer_scale:process_noise_dt:`](#estimation_parameterssatellitesg--l1waccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:imu_offset:process_noise_dt:`](#estimation_parameterssatellitesg--l1wimu_offsetprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:clock:process_noise_dt:`](#estimation_parameterssatellitesg--l1wclockprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:clock_rate:process_noise_dt:`](#estimation_parameterssatellitesg--l1wclock_rateprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:pos:process_noise_dt:`](#estimation_parameterssatellitesg--l1wposprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:pos_rate:process_noise_dt:`](#estimation_parameterssatellitesg--l1wpos_rateprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:orbit:process_noise_dt:`](#estimation_parameterssatellitesg--l1worbitprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:pco:process_noise_dt:`](#estimation_parameterssatellitesg--l1wpcoprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:code_bias:process_noise_dt:`](#estimation_parameterssatellitesg--l1wcode_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:phase_bias:process_noise_dt:`](#estimation_parameterssatellitesg--l1wphase_biasprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:ant_delta:process_noise_dt:`](#estimation_parameterssatellitesg--l1want_deltaprocess_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_d_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_d_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_d_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_d_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_d_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_d_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_d_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_d_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_d_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_d_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_y_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_y_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_y_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_y_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_y_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_y_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_y_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_y_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_y_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_y_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_b_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_b_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_b_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_b_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_b_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_b_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_b_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_b_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_b_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_b_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_r_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_r_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_r_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_r_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_r_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_r_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_r_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_r_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_r_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_r_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_t_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_t_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_t_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_t_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_t_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_t_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_t_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_t_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_t_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_t_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_n_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_n_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_n_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_n_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_n_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_n_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_n_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_n_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_n_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_n_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_p_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_p_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_p_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_p_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_p_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_p_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_p_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_p_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_p_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_p_4process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_q_0:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_q_0process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_q_1:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_q_1process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_q_2:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_q_2process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_q_3:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_q_3process_noise_dt) +- [`estimation_parameters:satellites:g--:l1w:emp_q_4:process_noise_dt:`](#estimation_parameterssatellitesg--l1wemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:global:orientation:process_noise_dt:`](#estimation_parametersreceiversglobalorientationprocess_noise_dt) +- [`estimation_parameters:receivers:global:gyro_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgyro_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:accelerometer_bias:process_noise_dt:`](#estimation_parametersreceiversglobalaccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gyro_scale:process_noise_dt:`](#estimation_parametersreceiversglobalgyro_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:global:accelerometer_scale:process_noise_dt:`](#estimation_parametersreceiversglobalaccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:global:imu_offset:process_noise_dt:`](#estimation_parametersreceiversglobalimu_offsetprocess_noise_dt) +- [`estimation_parameters:receivers:global:clock:process_noise_dt:`](#estimation_parametersreceiversglobalclockprocess_noise_dt) +- [`estimation_parameters:receivers:global:clock_rate:process_noise_dt:`](#estimation_parametersreceiversglobalclock_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:pos:process_noise_dt:`](#estimation_parametersreceiversglobalposprocess_noise_dt) +- [`estimation_parameters:receivers:global:pos_rate:process_noise_dt:`](#estimation_parametersreceiversglobalpos_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:orbit:process_noise_dt:`](#estimation_parametersreceiversglobalorbitprocess_noise_dt) +- [`estimation_parameters:receivers:global:pco:process_noise_dt:`](#estimation_parametersreceiversglobalpcoprocess_noise_dt) +- [`estimation_parameters:receivers:global:code_bias:process_noise_dt:`](#estimation_parametersreceiversglobalcode_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:phase_bias:process_noise_dt:`](#estimation_parametersreceiversglobalphase_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:ant_delta:process_noise_dt:`](#estimation_parametersreceiversglobalant_deltaprocess_noise_dt) +- [`estimation_parameters:receivers:global:emp_d_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_d_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_d_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_d_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_d_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_d_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_d_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_d_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_d_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_d_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_y_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_y_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_y_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_y_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_y_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_y_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_y_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_y_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_y_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_y_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_b_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_b_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_b_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_b_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_b_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_b_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_b_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_b_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_b_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_b_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_r_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_r_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_r_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_r_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_r_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_r_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_r_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_r_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_r_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_r_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_t_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_t_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_t_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_t_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_t_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_t_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_t_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_t_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_t_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_t_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_n_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_n_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_n_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_n_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_n_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_n_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_n_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_n_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_n_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_n_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_p_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_p_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_p_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_p_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_p_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_p_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_p_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_p_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_p_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_p_4process_noise_dt) +- [`estimation_parameters:receivers:global:emp_q_0:process_noise_dt:`](#estimation_parametersreceiversglobalemp_q_0process_noise_dt) +- [`estimation_parameters:receivers:global:emp_q_1:process_noise_dt:`](#estimation_parametersreceiversglobalemp_q_1process_noise_dt) +- [`estimation_parameters:receivers:global:emp_q_2:process_noise_dt:`](#estimation_parametersreceiversglobalemp_q_2process_noise_dt) +- [`estimation_parameters:receivers:global:emp_q_3:process_noise_dt:`](#estimation_parametersreceiversglobalemp_q_3process_noise_dt) +- [`estimation_parameters:receivers:global:emp_q_4:process_noise_dt:`](#estimation_parametersreceiversglobalemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:global:strain_rate:process_noise_dt:`](#estimation_parametersreceiversglobalstrain_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:ambiguities:process_noise_dt:`](#estimation_parametersreceiversglobalambiguitiesprocess_noise_dt) +- [`estimation_parameters:receivers:global:pcv:process_noise_dt:`](#estimation_parametersreceiversglobalpcvprocess_noise_dt) +- [`estimation_parameters:receivers:global:ion_stec:process_noise_dt:`](#estimation_parametersreceiversglobalion_stecprocess_noise_dt) +- [`estimation_parameters:receivers:global:ion_model:process_noise_dt:`](#estimation_parametersreceiversglobalion_modelprocess_noise_dt) +- [`estimation_parameters:receivers:global:slr_range_bias:process_noise_dt:`](#estimation_parametersreceiversglobalslr_range_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:slr_time_bias:process_noise_dt:`](#estimation_parametersreceiversglobalslr_time_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:trop:process_noise_dt:`](#estimation_parametersreceiversglobaltropprocess_noise_dt) +- [`estimation_parameters:receivers:global:trop_grads:process_noise_dt:`](#estimation_parametersreceiversglobaltrop_gradsprocess_noise_dt) +- [`estimation_parameters:receivers:global:trop_maps:process_noise_dt:`](#estimation_parametersreceiversglobaltrop_mapsprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:orientation:process_noise_dt:`](#estimation_parametersreceiversglobalgpsorientationprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:gyro_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsgyro_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:accelerometer_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsaccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:gyro_scale:process_noise_dt:`](#estimation_parametersreceiversglobalgpsgyro_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:accelerometer_scale:process_noise_dt:`](#estimation_parametersreceiversglobalgpsaccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:imu_offset:process_noise_dt:`](#estimation_parametersreceiversglobalgpsimu_offsetprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:clock:process_noise_dt:`](#estimation_parametersreceiversglobalgpsclockprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:clock_rate:process_noise_dt:`](#estimation_parametersreceiversglobalgpsclock_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:pos:process_noise_dt:`](#estimation_parametersreceiversglobalgpsposprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:pos_rate:process_noise_dt:`](#estimation_parametersreceiversglobalgpspos_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:orbit:process_noise_dt:`](#estimation_parametersreceiversglobalgpsorbitprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:pco:process_noise_dt:`](#estimation_parametersreceiversglobalgpspcoprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:code_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpscode_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:phase_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsphase_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:ant_delta:process_noise_dt:`](#estimation_parametersreceiversglobalgpsant_deltaprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_d_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_d_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_d_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_d_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_d_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_d_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_d_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_d_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_d_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_d_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_y_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_y_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_y_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_y_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_y_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_y_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_y_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_y_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_y_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_y_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_b_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_b_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_b_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_b_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_b_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_b_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_b_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_b_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_b_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_b_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_r_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_r_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_r_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_r_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_r_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_r_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_r_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_r_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_r_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_r_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_t_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_t_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_t_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_t_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_t_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_t_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_t_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_t_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_t_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_t_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_n_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_n_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_n_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_n_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_n_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_n_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_n_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_n_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_n_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_n_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_p_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_p_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_p_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_p_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_p_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_p_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_p_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_p_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_p_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_p_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_q_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_q_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_q_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_q_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_q_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_q_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_q_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_q_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:emp_q_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:strain_rate:process_noise_dt:`](#estimation_parametersreceiversglobalgpsstrain_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:ambiguities:process_noise_dt:`](#estimation_parametersreceiversglobalgpsambiguitiesprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:pcv:process_noise_dt:`](#estimation_parametersreceiversglobalgpspcvprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:ion_stec:process_noise_dt:`](#estimation_parametersreceiversglobalgpsion_stecprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:ion_model:process_noise_dt:`](#estimation_parametersreceiversglobalgpsion_modelprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:slr_range_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsslr_range_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:slr_time_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsslr_time_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:trop:process_noise_dt:`](#estimation_parametersreceiversglobalgpstropprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:trop_grads:process_noise_dt:`](#estimation_parametersreceiversglobalgpstrop_gradsprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:trop_maps:process_noise_dt:`](#estimation_parametersreceiversglobalgpstrop_mapsprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:orientation:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1worientationprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:gyro_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wgyro_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:accelerometer_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1waccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:gyro_scale:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wgyro_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:accelerometer_scale:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1waccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:imu_offset:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wimu_offsetprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:clock:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wclockprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:clock_rate:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wclock_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:pos:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wposprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:pos_rate:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wpos_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:orbit:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1worbitprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:pco:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wpcoprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:code_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wcode_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:phase_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wphase_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:ant_delta:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1want_deltaprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_d_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_d_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_d_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_d_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_d_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_d_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_d_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_d_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_d_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_d_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_y_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_y_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_y_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_y_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_y_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_y_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_y_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_y_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_y_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_y_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_b_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_b_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_b_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_b_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_b_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_b_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_b_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_b_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_b_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_b_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_r_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_r_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_r_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_r_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_r_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_r_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_r_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_r_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_r_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_r_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_t_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_t_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_t_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_t_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_t_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_t_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_t_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_t_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_t_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_t_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_n_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_n_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_n_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_n_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_n_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_n_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_n_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_n_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_n_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_n_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_p_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_p_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_p_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_p_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_p_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_p_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_p_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_p_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_p_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_p_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_q_0:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_q_0process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_q_1:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_q_1process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_q_2:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_q_2process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_q_3:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_q_3process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:emp_q_4:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:strain_rate:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wstrain_rateprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:ambiguities:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wambiguitiesprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:pcv:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wpcvprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:ion_stec:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wion_stecprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:ion_model:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wion_modelprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:slr_range_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wslr_range_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:slr_time_bias:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wslr_time_biasprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:trop:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wtropprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:trop_grads:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wtrop_gradsprocess_noise_dt) +- [`estimation_parameters:receivers:global:gps:l1w:trop_maps:process_noise_dt:`](#estimation_parametersreceiversglobalgpsl1wtrop_mapsprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:orientation:process_noise_dt:`](#estimation_parametersreceiversxmplorientationprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gyro_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgyro_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:accelerometer_bias:process_noise_dt:`](#estimation_parametersreceiversxmplaccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gyro_scale:process_noise_dt:`](#estimation_parametersreceiversxmplgyro_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:accelerometer_scale:process_noise_dt:`](#estimation_parametersreceiversxmplaccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:imu_offset:process_noise_dt:`](#estimation_parametersreceiversxmplimu_offsetprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:clock:process_noise_dt:`](#estimation_parametersreceiversxmplclockprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:clock_rate:process_noise_dt:`](#estimation_parametersreceiversxmplclock_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:pos:process_noise_dt:`](#estimation_parametersreceiversxmplposprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:pos_rate:process_noise_dt:`](#estimation_parametersreceiversxmplpos_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:orbit:process_noise_dt:`](#estimation_parametersreceiversxmplorbitprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:pco:process_noise_dt:`](#estimation_parametersreceiversxmplpcoprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:code_bias:process_noise_dt:`](#estimation_parametersreceiversxmplcode_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:phase_bias:process_noise_dt:`](#estimation_parametersreceiversxmplphase_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:ant_delta:process_noise_dt:`](#estimation_parametersreceiversxmplant_deltaprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_d_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_d_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_d_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_d_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_d_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_d_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_d_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_d_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_d_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_d_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_y_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_y_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_y_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_y_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_y_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_y_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_y_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_y_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_y_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_y_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_b_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_b_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_b_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_b_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_b_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_b_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_b_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_b_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_b_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_b_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_r_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_r_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_r_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_r_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_r_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_r_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_r_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_r_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_r_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_r_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_t_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_t_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_t_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_t_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_t_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_t_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_t_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_t_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_t_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_t_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_n_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_n_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_n_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_n_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_n_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_n_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_n_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_n_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_n_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_n_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_p_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_p_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_p_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_p_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_p_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_p_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_p_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_p_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_p_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_p_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_q_0:process_noise_dt:`](#estimation_parametersreceiversxmplemp_q_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_q_1:process_noise_dt:`](#estimation_parametersreceiversxmplemp_q_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_q_2:process_noise_dt:`](#estimation_parametersreceiversxmplemp_q_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_q_3:process_noise_dt:`](#estimation_parametersreceiversxmplemp_q_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:emp_q_4:process_noise_dt:`](#estimation_parametersreceiversxmplemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:strain_rate:process_noise_dt:`](#estimation_parametersreceiversxmplstrain_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:ambiguities:process_noise_dt:`](#estimation_parametersreceiversxmplambiguitiesprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:pcv:process_noise_dt:`](#estimation_parametersreceiversxmplpcvprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:ion_stec:process_noise_dt:`](#estimation_parametersreceiversxmplion_stecprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:ion_model:process_noise_dt:`](#estimation_parametersreceiversxmplion_modelprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:slr_range_bias:process_noise_dt:`](#estimation_parametersreceiversxmplslr_range_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:slr_time_bias:process_noise_dt:`](#estimation_parametersreceiversxmplslr_time_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:trop:process_noise_dt:`](#estimation_parametersreceiversxmpltropprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:trop_grads:process_noise_dt:`](#estimation_parametersreceiversxmpltrop_gradsprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:trop_maps:process_noise_dt:`](#estimation_parametersreceiversxmpltrop_mapsprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:orientation:process_noise_dt:`](#estimation_parametersreceiversxmplgpsorientationprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:gyro_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsgyro_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:accelerometer_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsaccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:gyro_scale:process_noise_dt:`](#estimation_parametersreceiversxmplgpsgyro_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:accelerometer_scale:process_noise_dt:`](#estimation_parametersreceiversxmplgpsaccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:imu_offset:process_noise_dt:`](#estimation_parametersreceiversxmplgpsimu_offsetprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:clock:process_noise_dt:`](#estimation_parametersreceiversxmplgpsclockprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:clock_rate:process_noise_dt:`](#estimation_parametersreceiversxmplgpsclock_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:pos:process_noise_dt:`](#estimation_parametersreceiversxmplgpsposprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:pos_rate:process_noise_dt:`](#estimation_parametersreceiversxmplgpspos_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:orbit:process_noise_dt:`](#estimation_parametersreceiversxmplgpsorbitprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:pco:process_noise_dt:`](#estimation_parametersreceiversxmplgpspcoprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:code_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpscode_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:phase_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsphase_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:ant_delta:process_noise_dt:`](#estimation_parametersreceiversxmplgpsant_deltaprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_d_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_d_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_d_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_d_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_d_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_d_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_d_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_d_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_d_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_d_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_y_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_y_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_y_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_y_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_y_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_y_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_y_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_y_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_y_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_y_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_b_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_b_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_b_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_b_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_b_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_b_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_b_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_b_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_b_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_b_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_r_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_r_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_r_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_r_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_r_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_r_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_r_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_r_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_r_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_r_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_t_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_t_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_t_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_t_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_t_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_t_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_t_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_t_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_t_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_t_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_n_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_n_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_n_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_n_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_n_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_n_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_n_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_n_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_n_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_n_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_p_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_p_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_p_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_p_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_p_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_p_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_p_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_p_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_p_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_p_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_q_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_q_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_q_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_q_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_q_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_q_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_q_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_q_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:emp_q_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:strain_rate:process_noise_dt:`](#estimation_parametersreceiversxmplgpsstrain_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:ambiguities:process_noise_dt:`](#estimation_parametersreceiversxmplgpsambiguitiesprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:pcv:process_noise_dt:`](#estimation_parametersreceiversxmplgpspcvprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:ion_stec:process_noise_dt:`](#estimation_parametersreceiversxmplgpsion_stecprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:ion_model:process_noise_dt:`](#estimation_parametersreceiversxmplgpsion_modelprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:slr_range_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsslr_range_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:slr_time_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsslr_time_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:trop:process_noise_dt:`](#estimation_parametersreceiversxmplgpstropprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:trop_grads:process_noise_dt:`](#estimation_parametersreceiversxmplgpstrop_gradsprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:trop_maps:process_noise_dt:`](#estimation_parametersreceiversxmplgpstrop_mapsprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:orientation:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1worientationprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:gyro_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wgyro_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1waccelerometer_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:gyro_scale:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wgyro_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:accelerometer_scale:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1waccelerometer_scaleprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:imu_offset:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wimu_offsetprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:clock:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wclockprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:clock_rate:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wclock_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:pos:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wposprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:pos_rate:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wpos_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:orbit:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1worbitprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:pco:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wpcoprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:code_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wcode_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:phase_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wphase_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:ant_delta:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1want_deltaprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_d_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_d_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_d_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_d_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_d_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_d_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_y_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_y_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_y_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_y_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_y_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_y_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_b_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_b_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_b_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_b_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_b_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_b_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_r_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_r_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_r_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_r_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_r_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_r_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_t_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_t_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_t_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_t_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_t_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_t_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_n_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_n_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_n_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_n_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_n_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_n_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_p_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_p_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_p_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_p_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_p_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_p_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_0:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_q_0process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_1:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_q_1process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_2:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_q_2process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_3:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_q_3process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:emp_q_4:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wemp_q_4process_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:strain_rate:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wstrain_rateprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:ambiguities:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wambiguitiesprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:pcv:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wpcvprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:ion_stec:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wion_stecprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:ion_model:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wion_modelprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:slr_range_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wslr_range_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:slr_time_bias:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wslr_time_biasprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:trop:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wtropprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:trop_grads:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wtrop_gradsprocess_noise_dt) +- [`estimation_parameters:receivers:xmpl:gps:l1w:trop_maps:process_noise_dt:`](#estimation_parametersreceiversxmplgpsl1wtrop_mapsprocess_noise_dt) +--- + +### E_SRPModel + +Valid enum values are: +- `none` +- `cannonball` +- `boxwing` + +For options: + +- [`satellite_options:global:orbit_propagation:solar_radiation_pressure:`](#satellite_optionsglobalorbit_propagationsolar_radiation_pressure) +- [`satellite_options:global:orbit_propagation:albedo:`](#satellite_optionsglobalorbit_propagationalbedo) +- [`satellite_options:global:l1w:orbit_propagation:solar_radiation_pressure:`](#satellite_optionsgloball1worbit_propagationsolar_radiation_pressure) +- [`satellite_options:global:l1w:orbit_propagation:albedo:`](#satellite_optionsgloball1worbit_propagationalbedo) +- [`satellite_options:gps:orbit_propagation:solar_radiation_pressure:`](#satellite_optionsgpsorbit_propagationsolar_radiation_pressure) +- [`satellite_options:gps:orbit_propagation:albedo:`](#satellite_optionsgpsorbit_propagationalbedo) +- [`satellite_options:gps:l1w:orbit_propagation:solar_radiation_pressure:`](#satellite_optionsgpsl1worbit_propagationsolar_radiation_pressure) +- [`satellite_options:gps:l1w:orbit_propagation:albedo:`](#satellite_optionsgpsl1worbit_propagationalbedo) +- [`satellite_options:g--:orbit_propagation:solar_radiation_pressure:`](#satellite_optionsg--orbit_propagationsolar_radiation_pressure) +- [`satellite_options:g--:orbit_propagation:albedo:`](#satellite_optionsg--orbit_propagationalbedo) +- [`satellite_options:g--:l1w:orbit_propagation:solar_radiation_pressure:`](#satellite_optionsg--l1worbit_propagationsolar_radiation_pressure) +- [`satellite_options:g--:l1w:orbit_propagation:albedo:`](#satellite_optionsg--l1worbit_propagationalbedo) +--- + +### E_Source + +Valid enum values are: +- `none` +- `spp` +- `config` +- `precise` : Values derived from file-based products such as SP3/CLK/OBX +- `ssr` : Values derived from applying received corrections to broadcast ephemeris +- `kalman` : Values estimated internally by the kalman filter +- `broadcast` : Values derived from broadcast ephemeris streams/files +- `nominal` +- `model` +- `remote` + +For options: + +- [`outputs:clocks:receiver_sources:`](#outputsclocksreceiver_sources) +- [`outputs:clocks:satellite_sources:`](#outputsclockssatellite_sources) +- [`outputs:sp3:clock_sources:`](#outputssp3clock_sources) +- [`outputs:sp3:orbit_sources:`](#outputssp3orbit_sources) +- [`outputs:orbex:orbit_sources:`](#outputsorbexorbit_sources) +- [`outputs:orbex:clock_sources:`](#outputsorbexclock_sources) +- [`outputs:orbex:attitude_sources:`](#outputsorbexattitude_sources) +- [`outputs:cost:sources:`](#outputscostsources) +- [`outputs:trop_sinex:sources:`](#outputstrop_sinexsources) +- [`outputs:ssr_outputs:ephemeris_sources:`](#outputsssr_outputsephemeris_sources) +- [`outputs:ssr_outputs:clock_sources:`](#outputsssr_outputsclock_sources) +- [`outputs:ssr_outputs:code_bias_sources:`](#outputsssr_outputscode_bias_sources) +- [`outputs:ssr_outputs:phase_bias_sources:`](#outputsssr_outputsphase_bias_sources) +- [`outputs:ssr_outputs:atmospheric:sources:`](#outputsssr_outputsatmosphericsources) +- [`satellite_options:global:models:pos:sources:`](#satellite_optionsglobalmodelspossources) +- [`satellite_options:global:models:clock:sources:`](#satellite_optionsglobalmodelsclocksources) +- [`satellite_options:global:models:attitude:sources:`](#satellite_optionsglobalmodelsattitudesources) +- [`satellite_options:global:l1w:models:pos:sources:`](#satellite_optionsgloball1wmodelspossources) +- [`satellite_options:global:l1w:models:clock:sources:`](#satellite_optionsgloball1wmodelsclocksources) +- [`satellite_options:global:l1w:models:attitude:sources:`](#satellite_optionsgloball1wmodelsattitudesources) +- [`satellite_options:gps:models:pos:sources:`](#satellite_optionsgpsmodelspossources) +- [`satellite_options:gps:models:clock:sources:`](#satellite_optionsgpsmodelsclocksources) +- [`satellite_options:gps:models:attitude:sources:`](#satellite_optionsgpsmodelsattitudesources) +- [`satellite_options:gps:l1w:models:pos:sources:`](#satellite_optionsgpsl1wmodelspossources) +- [`satellite_options:gps:l1w:models:clock:sources:`](#satellite_optionsgpsl1wmodelsclocksources) +- [`satellite_options:gps:l1w:models:attitude:sources:`](#satellite_optionsgpsl1wmodelsattitudesources) +- [`satellite_options:g--:models:pos:sources:`](#satellite_optionsg--modelspossources) +- [`satellite_options:g--:models:clock:sources:`](#satellite_optionsg--modelsclocksources) +- [`satellite_options:g--:models:attitude:sources:`](#satellite_optionsg--modelsattitudesources) +- [`satellite_options:g--:l1w:models:pos:sources:`](#satellite_optionsg--l1wmodelspossources) +- [`satellite_options:g--:l1w:models:clock:sources:`](#satellite_optionsg--l1wmodelsclocksources) +- [`satellite_options:g--:l1w:models:attitude:sources:`](#satellite_optionsg--l1wmodelsattitudesources) +- [`receiver_options:global:models:pos:sources:`](#receiver_optionsglobalmodelspossources) +- [`receiver_options:global:models:clock:sources:`](#receiver_optionsglobalmodelsclocksources) +- [`receiver_options:global:models:attitude:sources:`](#receiver_optionsglobalmodelsattitudesources) +- [`receiver_options:global:gps:models:pos:sources:`](#receiver_optionsglobalgpsmodelspossources) +- [`receiver_options:global:gps:models:clock:sources:`](#receiver_optionsglobalgpsmodelsclocksources) +- [`receiver_options:global:gps:models:attitude:sources:`](#receiver_optionsglobalgpsmodelsattitudesources) +- [`receiver_options:global:gps:l1w:models:pos:sources:`](#receiver_optionsglobalgpsl1wmodelspossources) +- [`receiver_options:global:gps:l1w:models:clock:sources:`](#receiver_optionsglobalgpsl1wmodelsclocksources) +- [`receiver_options:global:gps:l1w:models:attitude:sources:`](#receiver_optionsglobalgpsl1wmodelsattitudesources) +- [`receiver_options:xmpl:models:pos:sources:`](#receiver_optionsxmplmodelspossources) +- [`receiver_options:xmpl:models:clock:sources:`](#receiver_optionsxmplmodelsclocksources) +- [`receiver_options:xmpl:models:attitude:sources:`](#receiver_optionsxmplmodelsattitudesources) +- [`receiver_options:xmpl:gps:models:pos:sources:`](#receiver_optionsxmplgpsmodelspossources) +- [`receiver_options:xmpl:gps:models:clock:sources:`](#receiver_optionsxmplgpsmodelsclocksources) +- [`receiver_options:xmpl:gps:models:attitude:sources:`](#receiver_optionsxmplgpsmodelsattitudesources) +- [`receiver_options:xmpl:gps:l1w:models:pos:sources:`](#receiver_optionsxmplgpsl1wmodelspossources) +- [`receiver_options:xmpl:gps:l1w:models:clock:sources:`](#receiver_optionsxmplgpsl1wmodelsclocksources) +- [`receiver_options:xmpl:gps:l1w:models:attitude:sources:`](#receiver_optionsxmplgpsl1wmodelsattitudesources) +--- + +### E_Sys + +Valid enum values are: +- `none` +- `gps` +- `gal` +- `glo` +- `qzs` +- `sbs` +- `bds` +- `leo` +- `supported` +- `irn` +- `ims` +- `comb` + +For options: + +- [`receiver_options:global:rec_reference_system:`](#receiver_optionsglobalrec_reference_system) +- [`receiver_options:global:gps:rec_reference_system:`](#receiver_optionsglobalgpsrec_reference_system) +- [`receiver_options:global:gps:l1w:rec_reference_system:`](#receiver_optionsglobalgpsl1wrec_reference_system) +- [`receiver_options:xmpl:rec_reference_system:`](#receiver_optionsxmplrec_reference_system) +- [`receiver_options:xmpl:gps:rec_reference_system:`](#receiver_optionsxmplgpsrec_reference_system) +- [`receiver_options:xmpl:gps:l1w:rec_reference_system:`](#receiver_optionsxmplgpsl1wrec_reference_system) +--- + +### E_ThirdBody + +Valid enum values are: +- `mercury` +- `venus` +- `earth` +- `mars` +- `jupiter` +- `saturn` +- `uranus` +- `neptune` +- `pluto` +- `moon` +- `sun` + +For options: + +- [`satellite_options:global:orbit_propagation:planetary_perturbations:`](#satellite_optionsglobalorbit_propagationplanetary_perturbations) +- [`satellite_options:global:l1w:orbit_propagation:planetary_perturbations:`](#satellite_optionsgloball1worbit_propagationplanetary_perturbations) +- [`satellite_options:gps:orbit_propagation:planetary_perturbations:`](#satellite_optionsgpsorbit_propagationplanetary_perturbations) +- [`satellite_options:gps:l1w:orbit_propagation:planetary_perturbations:`](#satellite_optionsgpsl1worbit_propagationplanetary_perturbations) +- [`satellite_options:g--:orbit_propagation:planetary_perturbations:`](#satellite_optionsg--orbit_propagationplanetary_perturbations) +- [`satellite_options:g--:l1w:orbit_propagation:planetary_perturbations:`](#satellite_optionsg--l1worbit_propagationplanetary_perturbations) +--- + +### E_TidalComponent + +Valid enum values are: +- `east` +- `west` +- `north` +- `south` +- `up` +- `down` + +For options: + +- [`inputs:tides:atl_blq_row_order:`](#inputstidesatl_blq_row_order) +- [`inputs:tides:otl_blq_row_order:`](#inputstidesotl_blq_row_order) +--- + +### E_TidalConstituent + +Valid enum values are: +- `m2` +- `s2` +- `n2` +- `k2` +- `s1` +- `k1` +- `o1` +- `p1` +- `q1` +- `mf` +- `mm` +- `ssa` + +For options: + +- [`inputs:tides:atl_blq_col_order:`](#inputstidesatl_blq_col_order) +- [`inputs:tides:otl_blq_col_order:`](#inputstidesotl_blq_col_order) +--- + +### E_TropModel + +Valid enum values are: +- `standard` +- `sbas` +- `vmf3` +- `gpt2` +- `cssr` + +For options: + +- [`receiver_options:global:models:troposphere:models:`](#receiver_optionsglobalmodelstropospheremodels) +- [`receiver_options:global:gps:models:troposphere:models:`](#receiver_optionsglobalgpsmodelstropospheremodels) +- [`receiver_options:global:gps:l1w:models:troposphere:models:`](#receiver_optionsglobalgpsl1wmodelstropospheremodels) +- [`receiver_options:xmpl:models:troposphere:models:`](#receiver_optionsxmplmodelstropospheremodels) +- [`receiver_options:xmpl:gps:models:troposphere:models:`](#receiver_optionsxmplgpsmodelstropospheremodels) +- [`receiver_options:xmpl:gps:l1w:models:troposphere:models:`](#receiver_optionsxmplgpsl1wmodelstropospheremodels) +--- + +### KF + +Valid enum values are: +- `none` +- `one` +- `all` +- `rec_pos` +- `rec_vel` +- `rec_pos_rate` +- `rec_acc` +- `strain_rate` +- `pos` +- `vel` +- `acc` +- `heading` +- `orientation` +- `ref_sys_bias` +- `rec_clock` +- `rec_sys_bias` +- `rec_clock_rate` +- `rec_sys_bias_rate` +- `rec_clock_rate_gm` +- `rec_sys_bias_rate_gm` +- `sat_clock` +- `sat_clock_rate` +- `sat_clock_rate_gm` +- `trop` +- `trop_grad` +- `trop_model` +- `ionospheric` +- `iono_stec` +- `rec_pco_x` +- `rec_pco_y` +- `rec_pco_z` +- `sat_pco_x` +- `sat_pco_y` +- `sat_pco_z` +- `rec_pcv` +- `ant_delta` +- `eop` +- `eop_rate` +- `calc` +- `slr_rec_range_bias` +- `slr_rec_time_bias` +- `xform_xlate` +- `xform_rtate` +- `xform_scale` +- `xform_delay` +- `ambiguity` +- `code_bias` +- `phase_bias` +- `z_amb` +- `reference` +- `begin_meas_states` +- `code_meas` +- `phas_meas` +- `laser_meas` +- `pseudo_meas` +- `orbit_meas` +- `filter_meas` +- `end_meas_states` +- `begin_orbit_states` +- `orbit` +- `emp_d_0` +- `emp_d_1` +- `emp_d_2` +- `emp_d_3` +- `emp_d_4` +- `emp_y_0` +- `emp_y_1` +- `emp_y_2` +- `emp_y_3` +- `emp_y_4` +- `emp_b_0` +- `emp_b_1` +- `emp_b_2` +- `emp_b_3` +- `emp_b_4` +- `emp_r_0` +- `emp_r_1` +- `emp_r_2` +- `emp_r_3` +- `emp_r_4` +- `emp_t_0` +- `emp_t_1` +- `emp_t_2` +- `emp_t_3` +- `emp_t_4` +- `emp_n_0` +- `emp_n_1` +- `emp_n_2` +- `emp_n_3` +- `emp_n_4` +- `emp_p_0` +- `emp_p_1` +- `emp_p_2` +- `emp_p_3` +- `emp_p_4` +- `emp_q_0` +- `emp_q_1` +- `emp_q_2` +- `emp_q_3` +- `emp_q_4` +- `end_orbit_states` +- `begin_inertial_states` +- `gyro_bias` +- `gyro_scale` +- `accl_bias` +- `accl_scale` +- `imu_offset` +- `end_inertial_states` +- `range` + +For options: + +- [`processing_options:ppp_filter:periodic_reset:states:`](#processing_optionsppp_filterperiodic_resetstates) +- [`mongo:used_predictions:`](#mongoused_predictions) +- [`mongo:sent_predictions:`](#mongosent_predictions) \ No newline at end of file diff --git a/docsReadme.md b/docsReadme.md new file mode 100644 index 000000000..4feef1a0e --- /dev/null +++ b/docsReadme.md @@ -0,0 +1,77 @@ + +# Documentation + +The html documentation is set up to use client-side processes to simulate a more extensive server. +What this means is that the source for pages is separated and spread across multiple files to enable consistent styling and ease of editing. + +## URLS + +Pages are all accessed through one URL, with a parameter passed to the page to indicate which content is desired. + + page.html?p=home.md + +This will load the `home.md` page into the browser. Other pages are accessible by changing the parameter value after the `?p=` + +## File Structure + +The content is spread across different types of files, which are individually simple and serve a single purpose each. + +### The HTML layout - page.html + +This file contains the html layout to be used for all pages in the site. +Things such as the header and footer, dropdown links and all of the scripts and CSS includes are placed in this file. + +### Markdown Content ----.md + +The content for pages is written in markdown, with the ability to add inline mathematical equations using MathJax. + +### HTML Content ----.html + +Html fragments may be used in place of markdown, but is not recommended due to otherwise enforced commonality between structures and formatting. + +Html content files should ~not~ contain ` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

+ + +

+ +
+

Contents

+
+ +
+ + \ No newline at end of file diff --git a/peaConfig.md b/peaConfig.md new file mode 100644 index 000000000..85271e120 --- /dev/null +++ b/peaConfig.md @@ -0,0 +1,8 @@ + +# Pea Config Examples + +Example configurations for the different `pea` use-cases are included in the git repository in the `exampleConfigs` directory. +These examples utilise a reference dataset from 2019, which demonstrate the majority of the features that are currently supported by Ginan. + +For descriptions of the specifics of those examples, refer to the [Configuring Ginan](page.html?c=on&p=ginanConfiguration.md) page. + diff --git a/peaNetwork.md b/peaNetwork.md new file mode 100644 index 000000000..e8716478c --- /dev/null +++ b/peaNetwork.md @@ -0,0 +1,20 @@ + + + +# Using PEA in network mode + +PEA is designed to estimate the GNSS error parameters that cannot be precisely determined by a single receiver. The PEA will estimate the following parameters: + +* Correction to satellite initial conditions estimated by the POD component +* Satellite clock offset and drift +* Satellite hardware bias for two signal carriers +* Satellite differential bias for two signal pseudoranges +* Ionospheric propagation delay +* Tropospheric propagation delay +* Receiver/station position and velocity +* Receiver/station clock offset and drift +* Receiver/station hardware bias for signal carriers +* Receiver/station differential bias for two signal pseudoranges +* Relative carrier phase ambiguities + +In order to estimate the full range of parameters, the PEA will need to ingest GNSS observation data from a Global network of sufficient density. diff --git a/peaUser.md b/peaUser.md new file mode 100644 index 000000000..e8b9e1a86 --- /dev/null +++ b/peaUser.md @@ -0,0 +1,87 @@ + + +# Using PEA in user mode + +When set to end user mode, the PEA component of Ginan will process each station separately. This mode will allow the estimation of parameters available to users with single receivers. + +* Receiver position +* Receiver clock offset +* Tropospheric delay at receiver location +* Ionospheric delay at the receiver location (not yet available) +* Carrier phase ambiguities + +The results of PEA run in end user mode are printed in the trace files. +Station trace file outputs can be activated by setting the `outputs: trace: output_stations: true` +The most commonly used outputs from the PEA used in end-user mode are expected to be: the receiver position, receiver velocity, receiver clocks and tropospheric delays. + +### Receiver position + +Receiver position results are preceded by the `$POS` label and thus, in Linux, can be extracted using the command: + + grep "$POS" + +the output line for the receiver position will have comma separated fields with the following format: + + $POS, 2166, 278015.000, -4052053.0060, 4212836.8682, -2545105.0796, 0.0245227, 0.0231919, 0.0163678 + +the fields represent, from left to right: + + * `$POS` label + * GPS week + * GPS TOW in seconds + * Receiver ECEF X position in meters + * Receiver ECEF Y position in meters + * Receiver ECEF Z position in meters + * Standard deviation of ECEF X positions in meters + * Standard deviation of ECEF X positions in meters + * Standard deviation of ECEF X positions in meters + + +### Receiver clock + +Receiver clock offset results are preceded by the `$CLK` label and thus, in Linux, can be extracted using the command: + + grep "$CLK" + +the output line for the for receiver position will have comma separated fields with the following format: + + $CLK, 2166, 278015.000, 3.1902, 0.0000, 1.1924, 0.0000, 0.0860, 0.0000, 0.0953, 0.0000 + +the fields represent, from left to right: + +1. `$CLK` label +1. GPS week +1. GPS TOW in seconds +1. Receiver clock offset for with respect to GPS clock, in nanoseconds +1. Receiver clock offset for with respect to GLONASS clock, in nanoseconds +1. Receiver clock offset for with respect to Galileo clock, in nanoseconds +1. Receiver clock offset for with respect to Beidou clock, in nanoseconds +1. Standard deviation of clock offset wrt. GPS, in nanoseconds +1. Standard deviation of clock offset wrt. GLONASS, in nanoseconds +1. Standard deviation of clock offset wrt. Galileo, in nanoseconds +1. Standard deviation of clock offset wrt. Beidou, in nanoseconds + +If clock offsets for a particular constellation are not available both the offset and its variance will be set to 0. + +### Tropospheric delays + +Tropospheric delays at the receiver position are preceded by the `$TROP` label and thus, in Linux, can be extracted using the command: + + grep "$TROP" + +the tropospheric delay solutions will be represented to either a single line, with the `$TROP` or three lines, as follows: + +``` +$TROP, 2166, 278015.000, 14 ,2.294950, 0.0030977 +$TROP_N, 2166, 278015.000, 14, -0.174797, 0.0181385 +$TROP_E, 2166, 278015.000, 14, -0.223868, 0.0250276 +``` + +each of the troposphere output line will contain comma separated fields, of which the first are: + +* Label, `$TROP`, `$TROP_N` or `$TROP_E` +* GPS week +* GPS TOW in seconds +* Number of satellites used in the solution + +The line starting with `$TROP` contain the Zenith Tropospheric Delay (ZTD) and its standards deviation, both in meters, as their last two fields. The line starting with `$TROP_N` contains the tropospheric delay gradient in north-south direction, and the line starting with `$TROP_E` contains the tropospheric delay gradient in east-west direction. diff --git a/positioningProgram.md b/positioningProgram.md new file mode 100644 index 000000000..dd816ebf3 --- /dev/null +++ b/positioningProgram.md @@ -0,0 +1,14 @@ + +# Positioning program +![The Positioning Australia logo](images/PALogoB.png) + +The Australian Government is making a significant investment in the Positioning Australia program through Geoscience Australia. The program contains three major projects: + +1. The commercial procurement and operation of a Satellite Based Augmentation System (SBAS) called SouthPAN which will enhance positioning across the region through the provision of extra Global Navigation Satellite System (GNSS) signals and data delivered from a geostationary satellite. +1. The enhancement of the National Positioning Infrastructure Capability (NPIC) which will see upgrades to and an expansion of the GNSS Continuously Operating Reference Station (CORS) network across the South Pacific and Antarctica. +1. Ginan is an open source Precise Point Positioning (PPP) toolkit. It can produce PPP position correction products and, operating in another mode, use GNSS observations and those correction products to determine positions with an accuracy in the centimetre range. + +The program is summarised in figure below. +![The Positioning Australia Program in a diagram](images/PositioningOZExplainerv02.jpg) + +For more information on the positioning program please visit the [program website.](https://www.ga.gov.au/scientific-topics/positioning-navigation/positioning-australia/about-the-program) \ No newline at end of file diff --git a/ppp.html b/ppp.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/ppp.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/ppp.md b/ppp.md new file mode 100644 index 000000000..957c6203c --- /dev/null +++ b/ppp.md @@ -0,0 +1,131 @@ + +# Precise Point Positioning + +> Precise Point Positioning (PPP) is a way of determining very precise positions using GNSS observations and position correction data - and of calculating that position correction data. Ginan can be used to both produce position correction data and determine precise positions. + +There are several distinct parts to the process that allows us to determine a position using a GNSS. These parts include: + +* The GNSS signal being created within and broadcast by the satellite, +* The passage of that signal through space and the Earth's atmosphere, and +* Its reception by a receiver on the Earth's surface. + +Each one of these parts is capable of introducing elements into the process which ultimately reduces the accuracy of the position that is calculated. Precise Point Positioning (PPP) aims to understand what those elements are and build models to create corrections such that the final position is as accurate as is possible. + +## Satellites in the Space Environment + +![Space environment for a GNSS satellite](images/GNSSSatelliteInSpace-75pc.png) + +*The space environment for a GNSS satellite.* + +Knowing exactly where a GNSS satellite is at an instance in time is crucial for the position calculation. Because the signals travel at the speed of light (which is huge), even tiny inaccuracies in satellite position and onboard clock time can have a big impact on the final position. Unfortunately there are always some inaccuracies in satellite position and time: + +* The clocks carried by GNSS satellites are incredibly accurate but even they have a tendency to drift and need to be corrected. +* Satellite orbits are shaped and perturbed by: + * Variations in the Earth's gravity. Gravity around the globe is not uniform but rather a bit "lumpy". This lumpiness can alter the orbit of satellites. + * The gravitational forces on the satellite from the Sun, Moon and other bodies in the solar system. + * Light from the Sun creates a force as it strikes the satellite. This force changes as the satellite moves in and out of the light. + * The satellite's own radio transmissions can create a pushing force which can vary depending on the power used by the transmitter. +* The electronic systems and antennas on the satellite introduce "biases" or delays between when a signal is created and actually transmitted. +* The gravitational force in space creates tides in the surface of the Earth. These tides can physically alter the height of the surface of the Earth. +* The speed at which the satellite moves means that the signal is subject to the doppler effect. + +PPP software like Ginan seeks to build models that create correction data to provide very precise satellite orbits and clocks, bias and Earth tide adjustments. + +## The Atmosphere + +![Ionosphere and troposphere](images/Atmosphere-75pc.png) + +*The nature of the Ionosphere and Troposphere.* + +The Ionosphere and Troposphere are quite different in their composition but both delay GNSS radio signals. That delay makes the transmitting satellite appear further away than it actually is and so reduces the accuracy of the final position. The delay adds error. + +The Ionosphere is a shell of electrons and electrically charged atoms and molecules that surrounds the Earth. It is considered to start at an altitude of 85km and extend to about 2,000 km above the Earth’s surface. The Ionosphere: + +* Changes the refractive index of the atmosphere and bends (thus extends) the path the signal takes, +* The presence of ions actually slows down the signal. + +The effect of the Ionosphere is different for different frequencies. GNSS receivers that can decode two signals (e.g. GPS L1 and L2) can use an algorithm to remove much of the Ionosphere effect. The use of this algorithm is referred to as deriving a position which is Ionosphere-free. + +PPP uses an Ionosphere model to make an adjustment for the effect of the Ionosphere. The more sophisticated the model the longer it takes to make the adjustment but the more accurate it will be. Ionosphere models typically describe four main parameters: + +1. Electron density, +1. Electron temperature, +1. Ion temperature, +1. Ion composition. + +The value of parameters vary by time of day, time period of the current Solar Cycle, Sunspot activity, latitude, longitude and height. + +The Troposphere contains the bulk of the Earth’s atmosphere and all its weather. It starts at the Earth’s surface and extends upwards to an altitude of 18 km. + +Delays to the GNSS signal caused by the Troposphere differ to the Ionosphere in one very important aspect – they are uniform across the GNSS frequencies. This means that the techniques used to create Ionosphere-free observations cannot be applied to the Troposphere. Troposphere models have to be used to adjust for delays. Models make a clear distinction between the dry and wet components of the Troposphere. The dry component, typically 90% of the delay, can be modelled accurately using temperature and pressure (gas laws). Thankfully the wet component (water vapour) contributes a fraction of the delay as it is unpredictable and complex to model accurately. + +Conversely, GNSS signals can be used to make readings of the Troposphere and specifically the wet component for use in weather forecasting applications. Using very accurate satellite orbit and clock details, an Ionosphere-free model and models for the dry (hydrostatic) part of the Troposphere, it is possible to determine the effect of the wet part of the Troposphere by comparing the actual measured GNSS signal against a calculated signal. + +Stars twinkle or scintillate in the sky because of dynamic changes in the Troposphere – changes which cause continuous variations to the refractive index of the atmosphere. These scintillations affect GNSS signals and are observable by receivers. + +## At the Receiver + +![Multipath and no line of sight](images/Multipath-780px.png) + +*Multipath and No Line of Sight.* + +Much like the satellites that broadcast the GNSS signal, receivers also have biases. This time the delay is between the receipt of the signal at the antenna and the processing of that signal by the receiver's electronics. It is also important for the receiver to know the location of its antenna. Any calculated position will be that of the antenna. + +Another phenomenon that can occur is the idea of multipath and no line-of-sight signals. GNSS signals can be reflected off the ground, bodies of water and the side of large buildings. The reflected signal has travelled further than the line-of-sight signal and so arrives at a slightly later time. This kind of interference can cause the measured position to drift or jump around as the multipath signals reach the receiver. + +High quality antennas will mitigate the effects of multi-path signals. + +## Creating PPP + +With PPP there are two main activities: + +1. The construction and operation of the correction models to produce position correction data, +1. The combination of that correction data with GNSS observable signals to calculate a position - typically with an accuracy of a few centimetres. + +The trick to being able to create high quality corrections is having access to reliable, sometimes independently sourced data that supports the use of algorithms which can deliver answers to our questions. For example, we have a GNSS receiver fixed to a point on the Earth. We know very accurately the position of that receiver because we have verified its position using GNSS-independent means. We know the receiver's physical dimensions and we have good data on its biases (electronics). Co-located with the receiver is a barometer that gives us an indication of the air pressure at the site which can be used to estimate the dry component of the Troposphere. The site is free from obstructions that could cause multipath interference. When that receiver records signals from a GNSS satellite we can look up a lot of data on that satellite. Also we are not constrained to the C/A code signals. Our receiver lets us observe the actual carrier wave signal. Suddenly we have a lot of data to answer questions like: + +* Is the satellite where it says it is? +* Does it look like its clock is drifting? +* What effect does the Troposphere seem to be having? + +![CORS Network](images/CORSNetwork-75pc.png) + +*A network of continuously operating reference stations.* + +One reference station can only tell us so much. A whole network of reference stations providing many observations from many satellites gives us a rich source of data with which to work to produce correction messages. A complete PPP solution would use the results of the analysis of signal observations with other reference data to: + +* Derive corrections for satellite orbital eccentricities and clock drifts, +* Remove the effects of ionospheric refraction, +* Remove signal delays caused by the troposphere, +* Use precise locations for satellite and receiver antenna phase centres - see Notes below, +* Allow for the satellite signal carrier phase wind up effect, +* Make corrections for satellite transmission power changes, +* Compensate for Earth solid tides, +* Use undifferenced and uncombined raw observations. + +PPP doesn't require all of these corrections to improve accuracy. For example, just using precise satellite orbit and clock corrections will improve accuracy on their own. + +These corrections are made available as file products which can be used by PPP applications for post-processing GNSS observations. Corrections are also available as streams to be consumed for the real-time application of PPP. + +Notes: + +* The phase centre is defined as the apparent source of signal radiation. The phase centre of an antenna is not only angle dependant (elevation and azimuth) but also depends on the signal frequency. A simple model is to assume that the phase centre differs only in the vertical axis of the antenna. Antenna manufacturers include technical sheets indicating the phase centre offsets. +* For a receiver with fixed coordinates, the wind-up effect is due to the satellite's orbital motion. As the satellite moves along its orbital path it must rotate to keep its solar panels pointing at the sun to maintain the maximum energy while the satellite antenna keeps pointing to the earth's centre. This rotation causes a phase variation that the receiver misunderstands as a range variation and which needs to be corrected. +* Occasionally GNSS constellation operators will increase or decrease the transmission power of a satellite. This can cause a slight perturbation in the satellite's orbit. + +### The Benefits of PPP + +PPP brings with it some valuable advantages compared to a technique like RTK: +1. PPP can provide an absolute precise position with respect to a global reference frame, like the International Terrestrial Reference Frame (ITRF), using a single receiver i.e. it does not measure position relative to another point, which itself could be moving, +1. The fact that PPP does not rely on another receiver (undifferenced) potentially makes it easier and cheaper to use, +1. Taking an undifferenced, uncombined approach reduces the amount of signal noise potentially improving accuracy, +1. PPP using carrier wave ambiguity resolution is able to achieve position accuracy on the level of few centimetres, +1. PPP produces other products of value such as Zenith Troposphere Delay (ZTD) data water vapour in the atmosphere. + +Those terms undifferenced, uncombined and ambiguity resolution are discussed as part of the documentation for Ginan. + +One of the challenges and opportunities faced by Ginan is to minimise the time taken to converge on a position, something that can be problematic with PPP given the complexity of the processing. + +## Resources + +[![](images/PPPFrontSlide20210625v01.png) Precise Point Positioning](resources/PPP20211215v01.pdf) diff --git a/products.html b/products.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/products.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/products.md b/products.md new file mode 100644 index 000000000..6e47ca7ab --- /dev/null +++ b/products.md @@ -0,0 +1,38 @@ + + +# File and stream products + +> This page provides information on the precise point positioning file and stream products provided by Ginan through Geoscience Australia. + + +## Ginan products + +The Ginan software is still under active development. As the software becomes more capable and robust, Geoscience Australia will release new products to serve the needs of the positioning community in Australia and overseas. + +--- + +## Product access + +Ginan data files and live streams may be accessed via the Geoscience Australia data portal. Please read [this document](resources/GinanProductsStreamsAccess20220422.pdf) for detailed instructions. + +--- + +## Orbits and Clocks - SP3 + +To access the orbits and clocks SP3 file, please follow the access instructions above. Details on the SP3 file product can be found in this [datasheet](resources/GA-SP3datasheet20230616v03.pdf). + +## Clocks - CLK + +To access the clocks CLK file, please follow the access instructions above. Details on the CLK file product can be found in this [datasheet](resources/GA-CLKdatasheet20230616v02.pdf). + +## Earth Rotation Parameters - ERP + +To access the Earth rotation parameters ERP file, please follow the access instructions above. Details on the ERP file product can be found in this [datasheet](resources/GA-ERPdatasheet20230616v03.pdf). + +## CORS Position - SINEX + +To access the CORS position SNX file, please follow the access instructions above. Details on the SNX file product can be found in this [datasheet](resources/GA-SNXdatasheet20230616v02.pdf). + +## RTCM SSR Correction Stream - NTRIP (1059, 1060) + +To access the correction streams, please follow the access instructions above. Details on the stream product can be found in this [datasheet](resources/GA-STREAMdatasheet20220615v01.pdf). \ No newline at end of file diff --git a/program.html b/program.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/program.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/redirect.html b/redirect.html new file mode 100644 index 000000000..159680324 --- /dev/null +++ b/redirect.html @@ -0,0 +1,9 @@ + + + + + + +

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+ + diff --git a/resources.md b/resources.md new file mode 100644 index 000000000..a892979d1 --- /dev/null +++ b/resources.md @@ -0,0 +1,69 @@ + +# Resources - documents and presentations + +![A library of information](images/LibraryBooksStrip.png) + + +*** + +## Ginan Workshop Tutorial - IGNSS 2024 + +> [![](images/GinanWorkshopS.png) Slides from the Ginan Workshop hosted at the IGNSS 2024 conference.](resources/Ginan_Workshop_Slides_-_IGNSS_2024.pdf) + +> [![](images/GinanWorkshop1.png) Set Up Guide for the Ginan Workshop.](resources/Ginan_Workshop_1_Set-up_Guide_-_IGNSS_2024_-_6_Feb.pdf) + +> [![](images/GinanWorkshop2.png) Guide outlining how to run Ginan in the Workshop Tutorial.](resources/Ginan_Workshop_2_Running_Ginan_-_IGNSS_2024_-_6_Feb.pdf) + +> [![](images/GinanWorkshopD.png) Guide for those using Docker to run Ginan.](resources/Ginan_Workshop_Docker_Guide_-_IGNSS_2024_-_6_Feb.pdf) + + +*** + +## Ginan presentations + +> [![](images/GinanProjectOverviewFrontSlide20210902v01.png) The Ginan project overview presentation from September 2022.](resources/GinanProjectOverview202209v01.pdf) + +> [![](images/GinanTechnologyFrontSlide20210902v01.png) The Ginan project technical review from March 2022.](resources/GinanTechnology20220318v01.pdf) + + +*** + +## Ginan user stories + + +> [![](images/ginan-csiro-case-study.png) Report on using Ginan to measure the water level of Googong dam.
Partners: CSIRO, FroniterSI
August 2024](https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/149667) + +> [![](images/ginan-bom-case-study.png) Report on the results of taking "Ginan-in-a-box" to the edge of space on a weather balloon.
Partners: Bureau of Metereology, FroniterSI
June 2024](https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/149656) + +> [![](images/AIMSThumb.png) Report on a demonstration showing Ginan on air and sea drones at AIMS Reefworks.
Partners: Australian Institute of Marine Science, FrontierSI
August 2023](https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/148622) + +> [![](images/Locate23_S_McClusky_frontpage101X57.jpg) Open-source Precise Point Positioning (PPP) with Ginan v2 - Simon McClusky, from Locate 23
11 May 2023](resources/Locate23_S_McClusky_final.pdf) + +> [![](images/McClusky202301FrontPage101X57.jpg) Australian perspectives on the use of GNSS for tsunami warning - Simon McClusky, Adrienne Moseley, Phil Cummins, Shin-Chan Han, John Dawson,
Partners: University of Newcastle
February 2023](resources/TourDelIGS5_04_McClusky.pdf) + +> [![](images/TamDaoIonoPaperFrontPage101X57.jpg) Modelling of Ionospheric Corrections for High Accuracy GNSS Positioning using the GINAN toolkit - Tam Dao, Ken Harima, Brett Carter, Julie Currie, Simon McClusky, Rupert Brown, Eldar Rubinov, John Barassi, Suelynn Choy
Partners: RMIT, FrontierSI
December 2022](resources/TamDaoIonosphere.pdf) + +> [![](images/IonosphereFrontPage101X69.jpg) Using Ginan to analyse the ionosphere
December 2022](resources/GinanIonosphere20221218v05.pdf) + + +*** + + +## Reference + +> [![](images/ReferenceFramesFrontSlide20210618v01.png) Reference Frames from December 2021.](resources/ReferenceFrames20211209v01.pdf) + +> [![](images/GNSSFrontSlide20210618v01.png) Global Navigation Satellite Systems from July 2021.](resources/GNSS20211209v01.pdf) + +> [![](images/SPSFrontSlide20210623v01.png) Standard Positioning Service from December 2021.](resources/SPS20211216v01.pdf) + +> [![](images/PPPFrontSlide20210625v01.png) Precise Point Positioning from September 2021.](resources/PPP20211215v01.pdf) + +> [![](images/SP3-dQuickReferenceFrontSlidev01.png) Precise Orbits and Clocks File (SP3) from July 2021.](resources/SP3-dQuickReferencev01.pdf) + + +*** + +## Market + +> [![](images/GNSSLandscapeMiniv05.png) Precise Positioning Landscape from May 2021.](resources/GNSSLandscapev06.pdf) \ No newline at end of file diff --git a/resources/GA-CLKdatasheet20230616v02.pdf 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+> Real Time Kinematic (RTK) and Differential GNSS (DGNSS) positioning are quite distinct from Precise Point Positioning (PPP) which is the technique employed in Ginan. However RTK, and to an extent DGNSS, are very successful and widely used technologies. It is important to know the difference between RTK, DGNSS and PPP. + +RTK and DGNSS are similar techniques in that they rely on one, or a network of receivers (base stations) whose positions are very accurately known, to calculate data that allows another receiver (the rover) to determine its position with high accuracy. + +The “differencing” between the base receiver’s known position and its computed position using GNSS, allows for errors to be eliminated and thus position accuracy for the rover to be improved. Those errors are local in nature. The closer the rover receiver is to a base receiver the better i.e. tens of kilometres rather than hundreds. + +The key difference is that with RTK, the base stations are sending to the rover the GNSS carrier wave measurements it is observing – carrier observations. The rover knows the true positions of the base stations. With DGNSS, the base station is sending the difference between observed and calculated pseudoranges – pseudorange differences. + +RTK, and to an extent DGNSS, are very successful and widely used techniques. They have good accuracy and converge on a position quickly, but have some downsides: + +* Both rely on having at least two GNSS receivers (base station and rover) which increases cost. You can buy what is in effect a "base station service" so you don't have to have the physical equipment, but that service still costs money. +* You need radio or some other form of communications to transmit the difference data. +* If you lose the difference data signal, you can lose accuracy. +* The rover has to stay within a few tens of kilometres of the base station. The further away, the less reliable the correction becomes. + +![Basic principles of real time kinematic and differential GNSS positioning](images/RTKDGNSS-75pc.png) + +*The basic principles of real time kinematic and differential GNSS positioning* + +Ginan is not an RTK or DGNSS based software application. Ginan will achieve high accuracy positioning using the precise point positioning (PPP) technique. \ No newline at end of file diff --git a/rts.md b/rts.md new file mode 100644 index 000000000..8c03e93e0 --- /dev/null +++ b/rts.md @@ -0,0 +1,28 @@ + +# Rauch–Tung–Striebel (RTS) Smoothing + +While the Kalman filter is an optimal solution to computing state estimates from all previous data, better estimates could be obtained if all future data were also incorporated. + +The RTS Smoothing algorithm is an approach to determine estimates of states and uncertainties by considering the state transition between two Kalman filtered estimates, smoothing the transition between prior and 'future' data. + +All Kalman filters in the toolkit are capable of having RTS Smoothing applied. If configured appropriately with an RTS\_lag and output files, intermediate filter results will be stored to file for reverse smoothing. + +For real-time processing, a small lag may be applied to improve short-term accuracy. After each filtering stage, the new result is propagated backward through time to correct the previous N epochs. Each epoch worth of lag however requires a comparable processing time to an Kalman filter processing stage - a lag of N epochs may slow processing by up to a multiple of N. + +For post-processing, the optimal lag is to use all future and past data. This is achieved by first computing the forward solution, before propagating the final results backward through to the first epoch. The processing time required for a complete backward smoothed filter may be less than 2x a non-smoothed filter - considerably faster than a finite lag in real-time. + +## Example + +Consider the system of a single particle moving in one dimension. At time t=0, the particle's position is measured to be x=0. The system then evolves with a random walk, with no more measurements until the time t=100. + +At t=99, the particles position has a large uncertainty - it has likely moved from its original position, however, with no more data available, its mean expected value remains as x=0. + +At t=100, the particles position is again measured, this time as x=10. If this system were monitored using a Kalman filter, the expected position of the particle would be a constant x=0 for the first 99 seconds, before an abrupt change in location at t=100. During the 100 seconds, the variance would increase steadily, before abruptly returning to a low value when the second measurement is taken. + +If the Kalman filter measurements were taken in reverse order, with the first measurement at t=100, the variance of the particle would steadily increase going backward in time until t=0, before the second measurement again reduced the variance, this time at t=0. + +Using an RTS Smoother effectively combines both forward and backward filtering. At t=1, the variance is low due to the measurement at t=0. Likewise, at t=99, the variance is low due to the measurement at t=100. In this example, in addition to the measurements at t=0 and t=100, the expected mean value at t=50 can be expected to be the midpoint between the two measurements - a result that can not be obtained using Kalman filtering alone. + +In order to accurately calculate the expected position and variance at t=50 however, knowledge of the measurement at t=100 was required (50 seconds later). RTS smoothed estimates necessarily lag behind the primary Kalman filter to allow some time for future data to be obtained. The length of this lag determines the effectiveness of the smoothing. + + diff --git a/s3_filehandler.md b/s3_filehandler.md new file mode 100644 index 000000000..2e61a5d6b --- /dev/null +++ b/s3_filehandler.md @@ -0,0 +1,37 @@ + +# s3_filehandler Scripts + +The s3 file handler script available in the `scripts` directory is a python tool that will download the input data required to run the example as well as important file of solution + +The detailed features of each option can be found by changing to the `scripts` directory and running +``` +python3 s3_filehandler.py --help +``` + +* It is designed to be run at the root location of the Ginan software but all paths can be customised. +* It has the capability to download (default) or upload data into a Amazon s3 bucket, however the upload requires special authorisation (access key) + +To get started try the following examples: + +Examples to run: +git +## Download input file: +``` +python3 s3_filehandler.py -p -l -d +``` +will download all products, loading and data file + +## Download results of some of the examples: + +``` +python3 s3_filehandler.py -s +``` + +to download them all, or by choosing the specific solution (for example ex02) + +``` +python3 s3_filehandler.py -s ex02 +``` + + + diff --git a/science.index b/science.index new file mode 100644 index 000000000..e216cbddf --- /dev/null +++ b/science.index @@ -0,0 +1,10 @@ +observations.md +kalmanFilter.md +rts.md +orbits.md +ionosphere.md +ambiguities.md +minimumConstraints.md +attitudes.md +slrObservations.md +conventions.md \ No newline at end of file diff --git a/scripts.index b/scripts.index new file mode 100644 index 000000000..8d961183a --- /dev/null +++ b/scripts.index @@ -0,0 +1,4 @@ + ginanEDA.md + autoDownload.md + s3_filehandler.md + flexPower.md \ No newline at end of file diff --git a/scripts/indexer.js b/scripts/indexer.js new file mode 100644 index 000000000..626dd73ed --- /dev/null +++ b/scripts/indexer.js @@ -0,0 +1,322 @@ + + +// The MIT License (MIT) +// +// Copyright (c) 2016 Stack Exchange +// +// Permission is hereby granted, free of charge, to any person obtaining a copy +// of this software and associated documentation files (the "Software"), to deal +// in the Software without restriction, including without limitation the rights +// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +// copies of the Software, and to permit persons to whom the Software is +// furnished to do so, subject to the following conditions: +// +// The above copyright notice and this permission notice shall be included in all +// copies or substantial portions of the Software. +// +// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +// SOFTWARE. +// +// =============================================== +"use strict"; + +var StackExchangemathjaxEditing; +var ready = false; // true after initial typeset is complete +var pending = false; // true when MathJax has been requested +var preview = null; // the preview container +var inline = "$"; // the inline math delimiter +var blocks, start, end, last, braces; // used in searching for math +var math; // stores math until markdone is done + +// +// The pattern for math delimiters and special symbols +// needed for searching for math in the page. +// +var SPLIT = /(\$\$?|\\(?:begin|end)\{[a-z]*\*?\}|\\[\\{}$]|[{}]|(?:\n\s*)+|@@\d+@@)/i; + +// +// The math is in blocks i through j, so +// collect it into one block and clear the others. +// Replace &, <, and > by named entities. +// For IE, put
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This technology involves the transmission of laser beams from a ground station to a satellite equipped with retroreflectors, which then reflect the laser pulses back to Earth. By measuring the round-trip travel time of the laser pulses, the distance between the ground station and the satellite can be accurately determined. + +SLR plays a significant role contributing to geodetic products, including the definition and scale of the International Terrestrial Reference Frame (ITRF), monitoring Earth rotation and polar motion to provide the relationship with the International Celestial Reference Frame (CRF), and modelling the temporal and spatial variation of the Earth's gravity field. SLR observations also provide an independent data source to verify the accuracy of GNSS-formed orbits. + +The Ginan toolkit has the capability to process SLR observations to produce geodetic products - either alone or alongside GNSS observations. Unlike GNSS observations, SLR utilises a simpler two-way time-of-flight observation, and several GNSS-specific components (e.g. satellite clock biases, ambiguities) do not need to be considered. + +In Ginan, SLR measurements are modelled as normally distributed random variables with mean: + +\begin{equation} +\label{eq:slr_mea} +E(S_r^s) += 2(\rho_{r}^s ++ \tau_r^s ++ \kappa) ++ d_r ++ c_{light}(dt_r) +\end{equation} + +with a constant variance. In this equation: + +| Variable | Description | +| - | - | +| $S_r^s$ | represents the SLR measurement (m) between satellite $s$ and receiver $r$ | +| $E()$ | expected (mean) value | +| $\rho_{r}^s$ | geometric distance between satellite $s$ and receiver $r$ (m) | +| $\tau_r^s $ | slant troposphere delay between satellite $s$ and receiver $r$ (m) | +| $\kappa $ | relativistic (Shapiro) effect (m) | +| $d_{r,c}^q$ | receiver range bias (m) | +| $c_{light}$ | speed of light (m/s) | +| $dt_r^q$ | receiver time bias (s) | + +Note that SLR observations are 2-way measurements, hence the leading coefficient in the observation equation above. Otherwise, most of the components - including satellite and receiver positions - are modelled and estimated in the same way as for GNSS observations. + +## Troposphere modelling (SLR) +SLR tropospheric delays are composed of both hydrostatic and wet components. However, water vapor only contributes a small amount to atmospheric refraction at visible wavelengths, thus only a single mapping function is used for SLR modelling: +\begin{equation} + \tau_r^s = m(\theta_{el,r}^s) \tau_{ZTD,r} +\end{equation} + +The total tropospheric delay $\tau_{ZTD,r}$ and (total) mapping function $m(\theta_{el,r}^s)$ are assumed to be deterministic, and estimate both hydrostatic and wet components. They are estimated using the Mendes and Pavlis (2004) and Mendes et al. (2002) models respectively. + + +## Hardware biases (SLR) +SLR stations have hardware biases that affect both range and time measurements. Range biases affect the measured range of the total observation, whereas time biases affect the time-stamp associated with each measurement. Ginan estimates these biases within the Kalman filter, and applies a-priori values when known. + +(Note that time biases do not affect the range measurement on a 1:1 basis as with GNSS observations, as SLR uses a two-way observation which cancels out the direct effect of this component. Rather, time biases affect the assumed time of reflection off of the satellite, and thus affect the calculated position of satellite at the time of observation.) + diff --git a/spp.md b/spp.md new file mode 100644 index 000000000..e48382d84 --- /dev/null +++ b/spp.md @@ -0,0 +1,130 @@ + +# Standard Positioning Service + +> Our experience of positions from satellites will almost certainly be thanks to the `Standard Positioning Service`. This brilliant concept was pioneered by the US Global Positioning System (GPS) and provides free positions across the globe with an accuracy of a few meters. This section describes how that service works. + +The GNSS constellations offer a number of different services. The one that will be familiar to most people is the Standard Positioning Service (SPS). This is the service that is open, free and used by smartphones and car navigation devices. Other GNSS services offer higher position accuracy but are usually encrypted and reserved for special purposes such as the military. This page describes the SPS and its accuracy. + +The GPS SPS [Performance Standard](https://www.gps.gov/technical/ps/) defines the SPS as: + +> The SPS is a positioning and timing service that is available for peaceful civil, commercial, and scientific use. It includes the C/A-code signal, the CM/CL-code signals, and the I5-code/Q5-code signals. The C/A-code signal is transmitted by all satellites and comprises an L1 carrier modulated by a coarse/acquisition (C/A) code ranging signal with a legacy navigation (LNAV) data message. The ... + +The definition goes on to describe the CM/CL-code and I5-code/Q5-code signals, but for this purpose an exploration of the coarse/acquisition (C/A) code is sufficient. + + +## C/A-codes and modulation + +To make sense of the Standard Positioning Service (SPS), it is important to understand the C/A-code concept and how it is used to transmit the information required for ranging, and thus determining a position. + +Like any other radio message, GNSS signals are transmitted by the satellites at certain frequencies. The best known of these is called L1 which is a frequency of 1575.42 Mhz. It is also referred to as a carrier wave frequency - "carrier" because it is used to carry other information to a receiver. + +A carrier wave can be used to carry information by modulating its frequency - modulation gives the carrier wave a shape that represents the information. The shape is understood by the receiver and recovers the information. + +Every GNSS satellite is allocated a unique Pseudo Random Noise (PRN) code (C/A-code) which is modulated onto the satellite's carrier wave frequency. + +The position of the satellite in its orbit around the Earth is contained within a navigation message. The data in this message is overlaid on the C/A-code. A GNSS receiver can identify the satellite through the PRN code and decode the navigation message. Timestamps informing the receiver when the satellite sent the message, are embedded as part of the modulation process. + +Thus the receiver can determine where the satellite is, and how far it is from the satellite. If a receiver can see four or more satellites and has at least four sets of satellite positions and distances, it can calculate its position. + +![The time it takes for a GNSS signal to reach Earth](images/GPS_signal_modulation_scheme.png) + +*Representing the navigation message and C/A-code being modulated on to the carrier wave. +By P. F. Lammertsma, converted to vector by Denelson83 - Satellite Navigation, P. F. Lammertsma, p. 9, CC BY-SA 3.0, +https://commons.wikimedia.org/w/index.php?curid=1383669* + + +## The SPS Process + +The basic process stages for the Standard Positioning Service (SPS) are: + +* The systems on the ground - the monitoring and ground control stations - maintain a very close watch on the GNSS satellites in orbit. Central processing systems calculate very precise satellite orbits and adjustments to satellite clocks which are broadcast to the satellites as they pass over ground control stations. +* The satellites use the data from the ground control stations and create their GNSS signal. They modulate the carrier wave with their PRN (C/A-code) and the navigation message, and broadcast to Earth on a continuous basis. +* A receiver picks up the GNSS signals. A receiver has a number of channels. Each channel can process the data from one satellite. +* The receiver decodes the GNSS signals. The receiver identifies the satellite by decoding its PRN code and matches it to a list of known satellites. It determines the position of that satellite, and how far it is from the satellite, from the navigation message and timestamp information. +* Algorithms are used to turn these satellite positions and distances into a series of X, Y and Z coordinates. +* Trigonometry, specifically a technique called trilateration, turns the X, Y and Z coordinates and distances of several satellites into the X, Y and Z position of the receiver. +* Finally the receiver can translate its own X, Y and Z coordinates into latitude, longitude and height (using reference frames). + +Note there is a difference between the PRN code - which is lots of ones and zeros - and the PRN number - which is a regular integer. A GNSS satellite is typically referred to by its PRN number and that satellite will broadcast its signals encoding them using its PRN code. + + +## Signals and the Speed of Light + +![The time it takes for a GNSS signal to reach Earth](images/SpeedOfLight-75pc.png) + +*The time it takes for a GNSS signal to reach Earth's surface.* + +A signal from a GNSS satellite, in a 20,000 km orbit passing directly over us, takes around 0.0667 seconds (66.7 mS) to reach Earth's surface. A signal from that satellite as it appears over the horizon takes approximately 0.0854 seconds (85.4 mS) to reach the same spot. The difference between the two is a mere 0.0187 seconds (18.7 mS) but that difference is crucial when it comes to computing the distance between our GNSS receiver and the satellite. The receiver has to be able to calculate that distance to work out its position. + + +## Distance - Pseudorange +![Pseudorange components](images/Pseudorange-75pc.png) + +*Pseudorange components.* + +Up to this point the term "distance" has been used when talking about the space between the GNSS satellite and the receiver. There is a "true distance" between the satellite and receiver that could be measured in meters but in practice it doesn't work quite that way. + +The distance between the satellite and the receiver is calculated by multiplying the speed of light by the time it takes for the GNSS signal to travel from the satellite to the receiver. This distance calculation is pretty good but isn't the whole story. Other effects cause the distance to appear larger than it actually is. + +For this reason the distance between satellite and receiver is called the pseudorange. "Pseudo" because it isn't a simple value of distance. The figure above shows the most significant components that go to make the complete pseudorange value. + +The greatest part of the pseudorange is the true distance between the satellite and the receiver. But the Ionosphere, the Troposphere and delays (biases) in the electronic equipment itself contribute to making the pseudorange appear longer than the true distance - sometimes by hundreds of meters. This can have an adverse effect on the calculated position of the receiver. + + +## The Navigation Message +![Defining a satellite's orbital position](images/DefiningOrbitPosition-75pc.png) + +Defining a satellite's orbital position. + +A satellite's position in its orbit is defined by the values associated with a number of key parameters as shown in the figure above. This orbital position is broadcast by the satellite as part of its navigation message. As has been discussed, the satellite's position is important data in allowing a receiver to calculate a position. + + +## Carrier waves and Codes + +The SPS relies on a receiver being able to receive, interpret and measure the C/A-code signals along with the navigation message. As we'll see in the discussion around Precise Point Positioning (PPP) later, the carrier wave itself can also be used as a means of determining the distance between a satellite and the receiver. + +For this reason the C/A-code and carrier wave are known as the two main observables in GNSS positioning. Both the C/A-codes and the carrier wave can be used for ranging, even though original GNSS systems were never designed to exploit the carrier wave for positioning. Inexpensive GNSS receivers can measure the codes. More expensive and sophisticated devices are needed to measure the carrier wave. + +A question for you: if all the GNSS satellites are broadcasting on the same frequencies, how come the signals don’t get mixed up? How does a receiver know which signal comes from which satellite? + +The answer to this puzzle lies in understanding how Code Division Multiple Access (CDMA) works. Every GNSS satellite is allocated the entire transmission band all of the time. The trick is that each satellite’s message is coded using their unique PRN code. The key to CDMA is the receiver's ability to extract the desired signal while rejecting everything else as random noise. + +PRN codes are designed to be very orthogonal to one another. That means that codes only correlate (can be matched) when they are almost exactly aligned. A receiver knows all the codes and identifies satellites when comparisons it performs as part of its processing result in strong correlations. The [allocation of PRN codes](https://www.gps.gov/technical/prn-codes/) is controlled by the US Space Force. + +In CDMA, each message bit (like a bit of the navigation message) is subdivided into a number of short intervals called chips. Each satellite is assigned a unique 1,023 bit chip sequence which is its PRN code. To transmit 1 bit (of the navigation message), a satellite sends its chip sequence. To transmit a 0 bit, it sends the one's complement of its chip sequence. For example, if satellite A is assigned the chip sequence 00011011, it sends a 1 bit by sending 00011011 and a 0 bit by sending 11100100. + +For GPS, the navigation message is sent at the very sedate rate of 50 bits per second. The rate at which the chips are sent (the chipping rate) is 1.023 megabits per second. This means that a chip (PRN code) is transmitted in a millisecond. + +Putting it another way, the PRN code is like a key. Receivers have all the keys and compare incoming messages with locally generated codes (keys). There is a timestamp on each chip of the PRN code. So PRN codes from the satellite have satellite atomic clock generated time stamps and the receiver have internally generated time stamps. + + +## Calculating a position +![Calculating a GNSS position](images/CalculateAPosition-75pc.png) + +*Calculating a GNSS position.* + +The situation: our receiver can see four or more satellites in the sky and can decode their signals. It has calculated four sets of distances and orbital positions. It has a rough idea as to where it is - perhaps the receiver remembers where it was last turned on. The receiver uses the mathematical techniques of trilateration, linear approximation and a least squares best fit to nudge from the initial position to its actual position. It is able to do this in a dynamic way as the satellites move across the sky and the receiver moves across the Earth. This basic technique represents the Standard Positioning Service. + + +## How accurate is the Standard Positioning Service? + +A [report](https://www.nstb.tc.faa.gov/reports/PAN96_0117.pdf#page=22) produced by the US William J. Hughes Technical Center for the US Federal Aviation Administration in 2017 states that the Standard Position Service gives a position that is: + +* Within 3.9 m of the actual vertical position 95% of the time, and +* Within 1.9 m of the actual horizontal position 95% of the time. + +That sounds pretty good. However, the actual performance you experience depends on many things including, but not limited to: + +* The quality of your receiver. The quality of your GNSS antenna and the electronics behind it can have significant impacts on performance, +* The number of satellites your receiver can see. Generally the more satellites, the more data, the better the position, +* Multi-path effects. If the satellite signals are bouncing around nearby structures, the reflected signals can confuse the receiver, +* The accuracy of the navigation message transmitted by the satellite. If, for whatever reason, the satellite clock is a little bit off, or the satellite is a little out of its orbit then the calculated position can be thrown out too. +* The atmosphere. Both the ionosphere and troposphere can have effects on the signals which can add errors to a position. + +The other signals and codes broadcast by GNSS satellites can improve that accuracy. Now there are also augmentation systems available which send additional signals that greatly improve accuracy and often carry signal integrity information. Some of these are available to the general public and some are not. + +Ginan is concerned with a technique called Precise Point Positioning (PPP). PPP aims to be able to compensate for many sources of error and so greatly increase position accuracy - from metres to a few centimetres. + +## Resources + +[![](images/SPSFrontSlide20210623v01.png) GNSS Standard Positioning Service.](resources/SPS20211216v01.pdf) diff --git a/sps.html b/sps.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/sps.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/tech.html b/tech.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/tech.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/test.html b/test.html new file mode 100644 index 000000000..2259e100d --- /dev/null +++ b/test.html @@ -0,0 +1,5 @@ +

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    Here are some words + + \ No newline at end of file diff --git a/theory.html b/theory.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/theory.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file diff --git a/theory.md b/theory.md new file mode 100644 index 000000000..b7a55c597 --- /dev/null +++ b/theory.md @@ -0,0 +1,50 @@ + + +# A Position on Earth + +> We take positions on Earth for granted but they rely on a series of well-defined and maintained reference frames. This section introduces the reference frames that let us define a point on Earth in terms of latitude, longitude and height. + +![Position in an ever-moving, ever-changing Universe](images/PositionOnEarth-75pc.png) + +*Position in an ever-moving, ever-changing Universe.* + +Our Universe is expanding in all directions from the point of the big bang. Our solar system sits in a spiral arm that rotates around the centre of our galaxy. The Earth orbits the Sun and rotates around its own axis. The truth is, in galactic terms, you have never been in the same place twice and never will be. Given all of that how do we work out where we are? + +Well fortunately for the vast majority of applications we only need to know where we are with reference to the surface of the Earth. But that too is a little problematic because the surface of the Earth doesn't stay still - it actually slides around a bit. Australia is moving north north-east at the rate of 7 centimetres each year. This whole problem becomes manageable thanks to our use of reference frames. + +## The International Celestial Reference Frame (ICRF) + +![The International Celestial Reference Frame (ICRF)](images/ICRF-75pc.png) + +*The International Celestial Reference Frame (ICRF). J2000.0 is a standard Julian equinox and epoch - January 1, 2000 at 12:00 TT.* + +The International Earth Rotation and Reference Systems Service (IERS) was created in 1988 to establish and maintain a Celestial Reference Frame, the ICRF. The ICRF is defined by the position of significant celestial objects. Perhaps the most important of these are the so-called radio-loud quasars. These are super massive black holes at the centre of galaxies that radiate huge amounts of energy. A quasar typically emits radiation with a unique signature - a pattern across the radiation spectrum. These quasars, despite all the movement, appear as fixed points in the sky and thus as fixed reference points in the ICRF. + + +## The International Terrestrial Reference Frame (ITRF) + +![The International Terrestrial Reference Frame (ITRF)](images/ITRF-75pc.png) + +*The International Terestrial Reference Frame (ICRF).* + +The IERS also maintains the International Terrestrial Reference Frame, the ITRF. The ITRF is based on three axes, X, Y and Z with the origin placed at the Earth's centre of mass. The Z axis points up following the axis of the Earth's rotation (through the North Pole). The X axis passes through the point at the intersection of the International Reference Meridian (lying about 100m to the west of the original Greenwich Mean Meridian) and the Equator. The Y axis is orthogonal to both of them. The ITRF rotates with and as the Earth rotates across a day. + +The relationship between the ICRF and ITRF is defined by Earth Observation Parameters (EOP). + +The Earth is not a perfect sphere. Its radius is bigger at the equator than it is at the poles. It also has lumpy gravity. If you ran an altimeter over Earth and plotted out all the points of equal gravity, the picture would look a bit like a potato. That said, a position in X, Y and Z coordinates can be converted to geographical coordinates (Longitude, Latitude and Height) using a geocentric datum. + +Given that Australia does move approximately 7 centimetres a year north north-east, it is important that Australia keeps track of where it is in the context of the ITRF. To this end Geoscience Australia maintains the geocentric datum GDA2020 and a suite of tools, models and resources as part of the Australian Geospatial Reference System. + + +## Latitude, Longitude, Height + +![Latitude, Longitude, Altitude](images/LatLongH-75pc.png) + +*Points on the Earth defined by Latitude, Longitude and Height.* + +We usually talk about our position on the Earth as being defined by latitude, longitude and height (in the context of a geodetic datum like GDA2020). Finding where we are on Earth in terms of latitude, longitude and height has been made much simpler and more accurate thanks to Global Navigation Satellite Systems (GNSS). + + +## Resources + +[![](images/ReferenceFramesFrontSlide20210618v01.png) Reference Frames from September 2021](resources/ReferenceFrames20211209v01.pdf) \ No newline at end of file diff --git a/usingThePea.md b/usingThePea.md new file mode 100644 index 000000000..853426816 --- /dev/null +++ b/usingThePea.md @@ -0,0 +1,297 @@ + +# Overview of the PEA + +The `pea` is in essence a configurable, robust, application-specific Kalman filter. + +* Kalman filters are known for being the optimal method for estimating parameters - in linear systems, and provided an accurate system model is available. +* The `pea` contains accurate system models and linearisation routines for satellite positioning. +* It performs statistical monitoring and error checking, to ensure the robustness of results that is required for operational use, and +* It has an intuitive configuration, using hierarchical config files that allow you to tell the software precisely what and how to process GNSS data. + +The flow through the software is largely sequential, ensuring simplicity of understanding for developers and users alike. The major components of this flow are outlined below: + +## Data Input and Synchronisation + +Before the processing of data from an epoch is initiated, all other relevant data is accumulated. As this code affects global objects that have effects in multiple places, this code is run in a single thread until data processing is ready to begin. + +#### Config + +Configurations are defined in YAML files. At the beginning of each epoch the timestamp of the configuration file is read, and if there has been a modification, new parameters in the configuration will be loaded into memory. + +#### Product Input + +Various external products may be required for operation of the software, as defined in the configuration file. At the beginning of each epoch, if any product input files have been added to the config, or if the inputs are detected to have been modified, they will be re-read into memory. + +#### Metadata Input + +Metadata such as GNSS ephemerides are available from external sources to augment the capability of the software. This data is ingested at the beginning of each epoch before processing begins. + +#### Observation Data Input + +Observation data forms the basis for operation of the software. Observations from various sources are synchronised and collated at the beginning of each epoch before processing begins. The software uses class inheritance and polymorphism such that all data type inputs are retrieved using a single common instruction, with backend functions performing any retrieval and parsing required. + +Observation data is synchronised by timestamp - when the main function requests data of a specific timestamp all data until that point is parsed (but may be discarded), before the observation data corresponding to that timestamp being used in processing. + +#### SSR Data Input + +State Space Representation (SSR) messages contain the values of different GNSS error components, such as satellite clocks & orbits, hardware biases and ionosphere delays. These SSR components can be applied to GNSS observations to correct their error components. Streams containing SSR messages are available via NTRIP casters, which enable performing PPP in real-time. +Note that Ginan will allow the mixing of SSR streams, but users should not use SSR messages from inconsistent sources (e.g. orbits and clocks should be obtained from the same analysis centre). + +The software can decode SSR messages for the following constellations: +* GPS +* GALILEO +* GLONASS +* BEIDOU +* QZSS +* SBS + +For each constellation, the following GNSS error components can be decoded and applied: +* Satellite clocks +* High-rate satellite clocks +* Satellite orbits +* Code & phase biases +* User Range Accuracy (URA) + + +#### Initialisation of Objects + +During the following stages of processing many receiver-specific objects may be created within global objects. To prevent thread collision in the global objects, the receiver-specific objects are created here sequentially. + +## Preprocessor + +The preprocessor is run on input data to detect the anomalies and other metrics that are available before complete processing of the data is performed. This enables low-latency reporting of issues, and prepares data for more efficient processing in the later stages of operation. + +* Cycle Slip Detection +* Low Latency Anomaly Detection +* Missing Data +* Output / Reporting + +## Precise Point Positioning + +The largest component of the software, the PPP module ingests all data available, and applies scientific models to estimate and predict current and future parameters of interest. + +Version 1 of the GINAN toolkit satisfies many of the requirements for GNSS modelling, but has been achieved by incrementally adding features as they became available and as scientific models have been developed. Many of the components make assumptions about the outputs of previous computations performed in the software, and require care before adding or making changes to the code, or even setting configuration options. + +It is tempting for researchers to apply heuristics or corrections that may have been historically used to assist in computation, but these must be limited to effects that can be modelled and applied through the Kalman filter, in order to maintain the efficiency and robustness that it provides. + +As the models required for ‘user’, ‘network’, and even ‘ionosphere’ modes are equivalent, the only distinction between the modes is the extent of modelling to be applied, which can be reduced to a simple configuration change. As such the parallel streams within the software will be eliminated and reduced to a single unified model, with example configurations for common use-cases. + +It is intended that the software will be reorganised with the benefit of hindsight, to remove interactions between modules and explicitly execute each processing step in a manner similar to an algebraic formulation used by experts in the field. + + +#### Force and Dynamic Models + +At the beginning of processing of an epoch, parameters with time-dependent models are updated to reflect the time increment since the previous epoch. Simple models will be well defined when initialised, but more complex models will require updating at every epoch. + +Ultimate positioning performance largely depends on accurate dynamic models, with development of these models improving predictive capability, and reducing uncertainty and adjustments at every point in time. + +* Gravity +* Solar Radiation Pressure +* Other + +#### Orbit and State Prediction + +Before the available observations for an epoch are utilised, a prediction is made of the parameters of interest by utilising the previous estimates and applying dynamic models through the Kalman filter’s state transition. + +#### Phenomena Modelling + Estimation + +In order to accurately estimate and predict parameters of interest, all phenomena that affect GNSS/SLR observations must be isolated and modelled, as being components comprising the available measurements. + +Where the values of parameters are well known they may be used directly to extract other parameters of interest from the data - such as using published corrections to precisely determine a user’s position. + +When data is unavailable, or when it is desired to compute these products for subsequent publication and use, estimates of the values are derived from the available data. + +It is the sophistication of the models available and applied that determines the ultimate performance of the software. + +The software will be developed to allow for all applicable phenomena to be modelled, estimated, such that user’s desired constraints may be applied and parameters of interest extracted. + +#### Initialisation of Parameters + +Estimation parameters are initialised on the point of first use, automatically by the Kalman filter module. Their initial value may be selected to be user-defined, extracted from a model or input file, or established using a least-squares estimation. + +#### Robust Kalman Filter + +It is well known that the Kalman filter is the optimal technique for estimating parameters of interest from sets of noisy data - provided the model is appropriate. + +In addition, statistical techniques may be used to detect defects in models or the parameters used to characterise the data, providing opportunities to intervene and make corrections to the model according to the nature of the anomaly. + +By incorporating these features into a single generic module, the robustness that was previously available only under certain circumstances may now be automatically applied to all systems to which it is applied. These benefits extend automatically to all related modules (such as RTS), and often perform better than modules designed specifically to address isolated issues. + +For further details about the software's robust Kalman filter see the (Ginan Science Manual)[]. + +#### RTS Smoothing + +The intermediate outputs of a Kalman filter are of use for other algorithms such as RTS smoothers. All intermediate values required for such algorithms are to be recorded in a consistent manner, suitable for later processing. + +For further details about the software's RTS smoothing algorithm see the Ginan Science Manual. + +#### Integer Ambiguity Resolution + +GNSS phase measurements allow for very precise measurements of biases but require extra processing steps to disambiguate between cycles. Techniques have been demonstrated that perform acceptably under certain conditions and measurement types, but require substantial bookkeeping and may not easily transfer to different measurement applications. + +For further details about the software's ambiguity resolution algorithms see the Ginan Science Manual. + +#### Product calculation + +In order for estimated and predicted values to be of use to end-users, they must be prepared and distributed in an appropriate format. + +Some parameters of interest are not directly estimated by the filter, but may be derived from estimates by secondary operations, which are performed in this section of the code. + +In this section, data is written to files or pushed to NTRIP casters and other data sinks. + +#### SSR message generation + +State Space Representation (SSR) messages contain data on different GNSS error components, such as satellite clocks and orbits. +To generate an SSR message, error components are retrieved from a selection of several sources - such as the Kalman filter (estimated), precise product files, or even other input SSR streams. +Then, messages are formed according to the RTCM 3 standard. +Once ready, the SSR messages are then published to an NTRIP caster to be broadcast to multiple end-users. + +The software can generate SSR messages for the following constellations: +* GPS +* GALILEO +* GLONASS +* BEIDOU +* QZSS +* SBS + +For each constellation, the following GNSS error components can be generated: +* Satellite clocks +* High-rate satellite clocks +* Satellite orbits +* Code & phase biases +* User Range Accuracy (URA) + +For further details on how SSR messages are used on the end-user side, see section `SSR Data Input`. + + +## Post-processing + + +#### Smoothing + +The RTS Smoothing algorithm is capable of using intermediate states, covariances, and state transition matrices stored during the Kalman filter stage to calculate reverse smoothed estimates of parameters. + +The intermediate data is stored in binary files with messages that contain tail blocks containing the length of the message. This allows for the file to be efficiently traversed in reverse; seeking to the beginning of each message as defined by the tail block. + +For further details about the software's RTS Smoothing algorithm see the Ginan Science Manual. + + +#### Minimum Constraints + +The minimum constraints algorithm is capable of aligning a network of stations to a reference system without introducing any bias to the positions of the stations. + +A subset of stations positions are selected and weighted to create pseudo-observations to determine the optimal rigid transformation between the coordinates and the reference frame. The transformation takes the same algebraic form as a Kalman filter stage and is implemented as such in the software. + +For further details about the software's minimum constraints algorithm see the Ginan Science Manual. + + +#### Unit Testing + +The nature of GNSS processing means that well-defined unit tests are difficult to write from first-principles. The software however, is capable of comparing results between runs to determine if the results have changed unexpectedly. + +Intermediate variables are tagged throughout the code, and auxiliary files specify which variables should be tested as they are obtained, and the expected values from previous runs. + +## Logging and outputs + +Details of processing are logged to trace files according to the processing mode in use. + +Per-station trace files may be created with intermediate processing values and information, and a single network summary file is generated for the unified filter and combined processing. + +In addition to trace files, the `pea` is capable of outputting most of the file-types that it can read, and includes: + +* RINEX Clock files +* RINEX Navigation files +* RINEX Observation files +* RTCM Observation files/streams +* RTCM Correction files/streams +* SINEX files +* SINEX Bias files +* SINEX Troposphere files +* SP3 files +* YAML files +* GPX files - an XML format for interchange of GPS data (waypoints, routes, and tracks) used by Google Earth among other software. (https://www.topografix.com/GPX/1/1/) +* JSON files + +### Station Trace files + +The station trace files will contain outputs relevant and limited to a single station. +It will, for example, contain the observed-minus predicted estimation for individual signals observed by the residuals. + +``` +... +---------------------------------------------------- +Measurement for CODE_MEAS G31 NNOR 20 L2W + + OBSERVED +23129117.0340 -> 23129117.0340 + RANGE -23214116.5012 -> -84999.4672 + REC_CLOCK +78026.0567 -> -6973.4105 + SAT_CLOCK +6944.3768 -> -29.0337 + REC_ANTENNA_DELTA +0.0504 -> -28.9833 + REC_PCO +0.0347 -> -28.9486 + SAT_PCO +0.7339 -> -28.2147 + REC_PCV +0.0037 -> -28.2110 + SAT_PCV -0.0022 -> -28.2131 + TIDES_SOLID -0.0599 -> -28.2731 + TIDES_OTL -0.0085 -> -28.2815 + TIDES_POLE -0.0008 -> -28.2823 + RELATIVITY1 +5.4878 -> -22.7946 + RELATIVITY2 -0.0155 -> -22.8100 + SAGNAC +22.5172 -> -0.2928 + IONOSPHERIC_COMPONENT +3.8763 -> 3.5835 + IONOSPHERIC_COMPONENT1 -0.0030 -> 3.5805 + IONOSPHERIC_COMPONENT2 +0.0000 -> 3.5805 + TROPOSPHERE -5.1548 -> -1.5743 + EOP -0.0011 -> -1.5754 + REC_CODE_BIAS +0.0000 -> -1.5754 + SAT_CODE_BIAS -0.0000 -> -1.5754 + NET_RESIDUAL -0.0000 -> -1.5754 + ... + ``` + +In this example the pre-fit residual is calculated for L2W code measurement of satellite G31 in station NNOR. +The modelled/estimated value of various effects (geometric range, clock offsets, antenna characteristics, tide and relativistic effects, atmospheric delays, etc) are presented. +This allows to look for anomalous values on modelled/estimated parameters applied to the GNSS observation model. + +### Network Trace files + +The network trace files contain outputs relevant to the whole network. For example it will contain the state of parameters estimated by Ginan Processing +``` +... +* 2019-07-18 00:05:30 PHASE_BIAS G31 20 -0.2396864 88.58950070 L2W +* 2019-07-18 00:05:30 SAT_CLOCK G32 0 303.8257442 33.42697170 +* 2019-07-18 00:05:30 SAT_CLOCK_RATE G32 0 0.0045856 0.00333322 +* 2019-07-18 00:05:30 CODE_BIAS G32 1 0.0307764 0.01959992 L1C +* 2019-07-18 00:05:30 CODE_BIAS G32 3 -3.216e-17 1.0000e-16 L1W +* 2019-07-18 00:05:30 CODE_BIAS G32 20 3.101e-17 1.0000e-16 L2W +* 2019-07-18 00:05:30 CODE_BIAS G32 25 -0.7453901 0.14406117 L5Q +* 2019-07-18 00:05:30 PHASE_BIAS G32 1 0.6058104 90.18690487 L1C +* 2019-07-18 00:05:30 PHASE_BIAS G32 3 0.3273932 94.38893807 L1W +* 2019-07-18 00:05:30 PHASE_BIAS G32 20 0.9557970 90.18794887 L2W +* 2019-07-18 00:05:30 PHASE_BIAS G32 25 -0.0154065 93.53419260 L5Q +* 2019-07-18 00:05:30 REC_POS AREG 0 1942816.6390803 0.11138497 +* 2019-07-18 00:05:30 REC_POS AREG 1 -5804077.1997447 0.31250347 +* 2019-07-18 00:05:30 REC_POS AREG 2 -1796884.3863768 0.07612933 +* 2019-07-18 00:05:30 REC_CLOCK AREG 0 -8133.8558767 3000.65388827 +* 2019-07-18 00:05:30 TROP AREG 0 1.8534086 0.01375931 +* 2019-07-18 00:05:30 TROP_GRAD AREG 0 -0.0062538 0.00027328 +* 2019-07-18 00:05:30 TROP_GRAD AREG 1 -0.0022097 0.00072508 +* 2019-07-18 00:05:30 CODE_BIAS AREG G-- 1 0.0077985 0.01470148 L1C +* 2019-07-18 00:05:30 CODE_BIAS AREG G-- 3 -3.533e-10 3.0034e-07 L1W +* 2019-07-18 00:05:30 CODE_BIAS AREG G-- 20 -5.338e-10 3.0075e-07 L2W +* 2019-07-18 00:05:30 CODE_BIAS AREG G-- 25 0.8660053 0.12206356 L5Q +* 2019-07-18 00:05:30 PHASE_BIAS AREG G-- 1 0.4674732 93.48961365 L1C +* 2019-07-18 00:05:30 PHASE_BIAS AREG G-- 3 0.4936798 93.49109304 L1W +* 2019-07-18 00:05:30 PHASE_BIAS AREG G-- 20 0.7138144 93.49006419 L2W +* 2019-07-18 00:05:30 PHASE_BIAS AREG G-- 25 0.6556864 97.10528922 L5Q +* 2019-07-18 00:05:30 IONO_STEC AREG G02 0 -36.2661645 121.59989594 +* 2019-07-18 00:05:30 AMBIGUITY AREG G02 1 -9.2027480 4988.17927778 L1C +* 2019-07-18 00:05:30 AMBIGUITY AREG G02 3 -6.5010596 5121.40868346 L1W +* 2019-07-18 00:05:30 AMBIGUITY AREG G02 20 -11.3644227 3043.48150056 L2W +* 2019-07-18 00:05:30 IONO_STEC AREG G12 0 -21.3198438 121.60048193 +* 2019-07-18 00:05:30 AMBIGUITY AREG G12 1 19.4419675 4988.28296914 L1C +* 2019-07-18 00:05:30 AMBIGUITY AREG G12 3 22.5097301 5121.65630355 L1W +... +``` + +The example above contains (from left to right) the epoch (GPS time), the state name, the station and satellite/constellation if relevant, an index number, the value of the estimated state and its variance. +On the top of the section are the estimates for satellite clock offset, code bias and phase bias for GPS satellites. At the bottom the estimated station parameters: positions, clock offsets, troposphere, hardware biases, ionosphere delays and carrier phase ambiguities for the AREG station. diff --git a/weblinks.html b/weblinks.html new file mode 120000 index 000000000..b1224550e --- /dev/null +++ b/weblinks.html @@ -0,0 +1 @@ +redirect.html \ No newline at end of file