Improved particle filter based on differential evolution

被引：29
|
作者：
Li, H-W. [1 ]
Wang, J. [1 ]
Su, H-T. [1 ]
机构：
[1] Xidian Univ, Natl Lab Radar Signal Proc, Xian 710071, Peoples R China
来源：
ELECTRONICS LETTERS | 2011年 / 47卷 / 19期
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1049/el.2011.1825
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Resampling schemes for a particle filter based on the differential evolution (DE) algorithm are presented. By using these schemes, several types of differential evolution particle filters (DEPFs) are proposed. In the proposed filters, the unscented Kalman filter is utilised to generate the importance proposal distribution and the different DE algorithms are used as the resampling scheme. Simulation results demonstrate that the proposed DEPFs outperform the sequential importance resampling algorithm, the regularised particle filter, and the unscented particle filter.
引用
收藏
页码：1078 / U41
页数：2
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