Continuous and discrete time filters for Markov jump linear systems with Gaussian observations

Author

Krishnamurthy, Vikram ; Evans, Jamie

Author_Institution

Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia

fYear

1996

fDate

24-26 Jun 1996

Firstpage

402

Lastpage

405

Abstract

We present new finite dimensional filters for estimating the state of Markov jump linear systems, given noisy measurements of the Markov chain. Discrete time as well as continuous time models are considered. A robust version of the continuous time filters is used to derive a discretization which links the continuous and discrete time results. Simulations compare the robust discretization with direct numerical solutions of the filtering equations. The new filters have applications in the passive tracking of maneuvering targets and speech coding

Keywords

Gaussian noise; Markov processes; continuous time filters; discrete time filters; filtering theory; linear systems; speech coding; state estimation; target tracking; tracking filters; Gaussian observations; Markov chain; Markov jump linear systems; continuous time filters; direct numerical solutions; discrete time approximate model; discrete time filters; filtering equations; finite dimensional filters; maneuvering targets; noisy measurements; passive tracking; robust discretization; simulations; speech coding; state estimation; Continuous time systems; Equations; Filtering; Linear systems; Nonlinear filters; Passive filters; Robustness; Speech coding; State estimation; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004

Conference_Location

Corfu

Print_ISBN

0-8186-7576-4

Type

conf

DOI

10.1109/SSAP.1996.534901

Filename

534901