Stability of nonlinear filters in nonmixing case

The nonlinear filtering equation is said to be stable if it ``forgets'' the initial condition. It is known that the filter might be unstable even if the signal is an ergodic Markov chain. In general, the filtering stability requires stronger signal ergodicity provided by the, so called, mixing condition. The latter is formulated in terms of the transition probability density of the signal. The most restrictive requirement of the mixing condition is the uniform positiveness of this density. We show that it might be relaxed regardless of an observation process structure.

[1]  Thomas Kaijser A Limit Theorem for Partially Observed Markov Chains , 1975 .

[2]  V. Benes,et al.  Estimation and control for linear, partially observable systems with non-gaussian initial distribution☆☆☆ , 1983 .

[3]  A. Makowski Filtering formulae for partially observed linear systems with non-gaussian initial conditions , 1986 .

[4]  Decision Systems.,et al.  Lyapunov Exponents for Filtering Problems , 1988 .

[5]  A. Makowski,et al.  Discrete-time filtering for linear systems with non-Gaussian initial conditions: asymptotic behavior of the difference between the MMSE and LMSE estimates , 1992 .

[6]  D. Ocone,et al.  Asymptotic Stability of the Optimal Filter with Respect toIts Initial Condition , 1996 .

[7]  A. Budhiraja,et al.  Exponential stability of discrete-time filters for bounded observation noise , 1997 .

[8]  R. Atar,et al.  Exponential stability for nonlinear filtering , 1997 .

[9]  Laurent Mevel,et al.  Exponential Forgetting and Geometric Ergodicity in Hidden Markov Models , 2000, Math. Control. Signals Syst..

[10]  F. LeGland,et al.  Stability and approximation of nonlinear filters in the Hilbert metric, and application to particle filters , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[11]  P. Moral,et al.  On the stability of interacting processes with applications to filtering and genetic algorithms , 2001 .

[12]  Pavel Chigansky,et al.  Asymptotic Stability of the Wonham Filter: Ergodic and Nonergodic Signals , 2002, SIAM J. Control. Optim..

[13]  N. Oudjane,et al.  Stability and Uniform Particle Approximation of Nonlinear Filters in Case of Non Ergodic Signals , 2005 .