Kalman filter

This page contains resources about Kalman filters and Linear Gaussian State Space Model.

Subfields and Concepts

 * Bayesian Recursive Estimation / Bayes filter (generalization of the Kalman filter)
 * Extended Kalman filter (EKF)
 * Unscented Kalman filter (UKF)
 * Iterated EKF
 * Information filter

Lecture Notes

 * Estimation by Ian Reid

Books and Book Chapters

 * Murphy, K. P. (2012). "Chapter 18: State space models". Machine Learning: A Probabilistic Perspective. MIT Press.
 * Koller, D., & Friedman, N. (2009). "Section 6.2.3.2: Linear Dynamical Systems". Probabilistic Graphical Models. MIT Press.
 * Bishop, C. M. (2006). "Chapter 13: Sequential Data". Pattern Recognition and Machine Learning. Springer.
 * Grover, R., & Hwang, P. Y. (1996). Introduction to random signals and applied Kalman filtering. 3rd Ed. John Wiley & Sons.

Software

 * filterpy - Python
 * pykalman - Python
 * Kalman filter and Linear Dynamical System - MATLAB

Other resources

 * Kalman Filter book using Jupyter Notebook - Github
 * The Kalman filter - Some tutorials, references, and research related to the Kalman filter