Update EKF2 overview #3533
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Update EKF2 overview #3533
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bresch
commented
Jan 6, 2025
•
bresch
commented
- add terrain state
- mention error-state formulation
- mention Joseph covariance update
- change position state to global position
- update derivation link
| Reducing the 'fusion time horizon' delay reduces errors in the complementary filter used to propagate states forward to current time. | ||
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| The EKF uses the IMU data for state prediction only. IMU data is not used as an observation in the EKF derivation. | ||
| The algebraic equations for the covariance prediction and measurement jacobians are derived using [SymForce](https://symforce.org/) and can be found here: [Symbolic Derivation](https://github.com/PX4/PX4-Autopilot/blob/main/src/modules/ekf2/EKF/python/ekf_derivation/derivation.py). | ||
| Covariance update is done using the Joseph Stabilized form to improve numerical stability and allow conditional update of independent states. |
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Would a link be helpful or will all readers know what this is or be able to search? https://en.wikipedia.org/wiki/Kalman_filter#Deriving_the_posteriori_estimate_covariance_matrix
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Yes, good idea, we could link that wikipedia section. Like this: https://github.com/PX4/PX4-user_guide/pull/3533/files#r1926992602 ?
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bresch
commented
Jan 23, 2025
hamishwillee
approved these changes
Jan 23, 2025
- add terrain state - mention error-state formulation - mention Joseph covariance update - change position state to global position
Co-authored-by: Mathieu Bresciani <[email protected]>
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