Chapter 7 of my book discusses the Kalman filter.
Buy from Amazon: https://a.co/d/1zUEkNQ
The goal of a state space model is to infer information about the state variables of a dynamic system, given the observations. The algorithm for carrying out this procedure is the Kalman Filter.
An excerpt from my book:
The state space representation of a timeseries problem is a sequential analysis framework that typically includes tasks like filtering and smoothing. Refer to the code directory of this repo to find out more.
Find out more from another book: https://bookdown.org/rdpeng/timeseriesbook/state-space-models-and-the-kalman-filter.html