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		Ling WU,Faxing LU.[en_title][J].Control Theory and Technology,2011,9(4):584~588.[Copy]

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LingWU,FaxingLU
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(Electronic Engineering College, Naval University of Engineering)

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Received:December 31, 2009Revised:April 16, 2010

基金项目:This work was supported by the National Natural Science Foundation of Hubei Province (Nos. 2009CDB098, 2009CDB274).

Dynamic resampling particle filter adaptive to changes in system model

Ling WU,Faxing LU

(Electronic Engineering College, Naval University of Engineering)

Abstract:

A dynamic resampling particle filter (DRPF), integrated with scattering and migrating operations, is proposed for the flexibility in nonlinear systems subject to changes in the system model without a considerable increase in computational cost. Under the change detection with the tracking error, the scattering and migration are alternatively adopted where the scattering can boost the diversity in the particle population when no change, or slow change occurs, while the migrating updates particles with new observations if the change comes abruptly. Simulation results validate the proposed PF as a promising alternative to the existing PFs.

Key words: Particle filter Bayesian estimation Change detection Resampling