Optimal stationary linear filtering for systems with Markov switching parameters

Author

Costa, O.L.V.

Author_Institution

Dept. de Engenharia Eletronica, Sao Paulo Univ., Brazil

fYear

1993

fDate

15-17 Dec 1993

Firstpage

837

Abstract

The stationary minimum mean square error estimator for discrete time linear systems with Markov switching parameters is considered for the case when the output sequence and mode of operation of the system are directly observable. It is shown that the solution of this problem is associated to a set of coupled algebraic Riccati-like equations. Conditions for the existence and uniqueness of a positive semi-definite solution are obtained via the convergence of a sequence of solutions of Lyapunov-like equations

Keywords

Lyapunov methods; Markov processes; difference equations; discrete time systems; filtering and prediction theory; least squares approximations; linear systems; nonlinear differential equations; optimisation; Lyapunov-like equations; Markov switching parameters; coupled algebraic Riccati-like equations; discrete time linear systems; optimal stationary linear filtering; positive semi-definite solution; stationary minimum mean square error estimator; Hilbert space; Linear systems; Maximum likelihood detection; Mean square error methods; Nonlinear filters; Riccati equations; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-1298-8

Type

conf

DOI

10.1109/CDC.1993.325031

Filename

325031