SIAM Journal on Control and Optimization, Vol.55, No.5, 3116-3131, 2017
CONVERGENCE ANALYSIS OF A FAMILY OF ROBUST KALMAN FILTERS BASED ON THE CONTRACTION PRINCIPLE
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 N-fold composition of the corresponding Riccati-like mapping is strictly contractive provided that the tolerance is sufficiently small and, accordingly, the filter converges.
Keywords:block update;contraction mapping;Kalman filter;Riccati equation;Thompson's art metric;risk-sensitive filtering