Particle filter based on PSO

Gongyuan Zhang, Yongmei Cheng, Feng Yang, Quan Pan

科研成果: 书/报告/会议事项章节会议稿件同行评审

33 引用 (Scopus)

摘要

The main challenge in using particle filter (PF) to nonlinear state estimation problem is the particle degeneracy. Resampling operation solves degeneracy to some extent, but it results in the phenomenon of sample impoverishment. Therefore, it cannot achieve the satisfactory accuracy generally with certain number particles by using generic PF algorithm because of the serious impoverishment problem. Here we aim for decreasing the impoverishment of samples set after resampling step. The principle of PF together with its particle degeneracy and sample impoverishment problems are introduced in this paper. Based on the analysis of the causes of sample impoverishment, particle swarm optimization (PSO) which is one of the swarm intelligence algorithms is introduced to PF to ameliorate the diversity of samples set after resampling step. Thus a new algorithm which is called PSO-PF is proposed. From a theoretical analysis, the PSO operation on particles set can overcome sample impoverishment problem largely. And finally, a generic numerical example shows that PSO-PF presents better than generic PF algorithm regarding to accuracy.

源语言英语
主期刊名Proceedings - International Conference on Intelligent Computation Technology and Automation, ICICTA 2008
121-124
页数4
DOI
出版状态已出版 - 2008
活动International Conference on Intelligent Computation Technology and Automation, ICICTA 2008 - Changsha, Hunan, 中国
期限: 20 10月 200822 10月 2008

出版系列

姓名Proceedings - International Conference on Intelligent Computation Technology and Automation, ICICTA 2008
1

会议

会议International Conference on Intelligent Computation Technology and Automation, ICICTA 2008
国家/地区中国
Changsha, Hunan
时期20/10/0822/10/08

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