Convergence Analysis of a Family of Robust Kalman Filters Based on the Contraction Principle

Mattia Zorzi
2017 SIAM Journal of Control and Optimization  
In this paper we analyze the convergence of a family of robust Kalman filters. For each filter of this family the model uncertainty is tuned according to the so called tolerance parameter. Assuming that the corresponding state-space model is reachable and observable, we show that the corresponding Riccati-like mapping is strictly contractive provided that the tolerance is sufficiently small, accordingly the filter converges.
doi:10.1137/16m1099078 fatcat:czpzo45x3zhjhoafa5etmjphz4