Estimation of parameters in a linear state space model using a Rao-Blackwellised particle filter

P. Li, R. Goodall, V. Kadirkamanathan

Research output: Contribution to journalArticle

84 Citations (Scopus)

Abstract

A Rao-Blackwellised particle filter is used in the estimation of the parameters of a linear stochastic state space model. The proposed method combines the particle filtering technique with a Kalman filter using marginalisation so as to make full use of the analytically tractable structure of the model. Simulation studies are performed on a simple illustrative example and the results demonstrate the effectiveness of the proposed method in comparison with the conventional extended-Kalman-filler-based method. The proposed method is then applied in the estimation of the parameters in a railway vehicle dynamic model for condition monitoring and the desired results have been obtained.

Original languageEnglish
Pages (from-to)727-738
Number of pages12
JournalIEE Proceedings: Control Theory and Applications
Volume151
Issue number6
DOIs
Publication statusPublished - 22 Nov 2004
Externally publishedYes

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