chapter  4
106 Pages

Advanced Topics in Sequential State Estimation

In this chapter we present some advanced topics used in sequential state estima-tion that have been found relevant for modern applications. We selectively present detailed formulations, however, as in previous chapters, we encourage the interested reader to pursue these topics further in the references provided. These topics include factorization methods, colored-noise Kalman filtering, consistency of the Kalman filter, consider Kalman filtering, decentralized filtering, adaptive filtering, ensemble filtering, nonlinear stochastic filtering theory, Gaussian sum filtering, particle filtering, error analysis, and robust filtering.