Weight over-estimation problem in GMP-PHD filter

被引：4

作者：

Ouyang, C. ^{[1
]}

Ji, H. B. ^{[1
]}

机构：

[1] Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China

来源：

ELECTRONICS LETTERS | 2011年 / 47卷 / 02期

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1049/el.2010.7410

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：

The Gaussian mixture particle probability hypothesis density (GMP-PHD) filter is a promising nonlinear multi-target tracking algorithm. However, when the variance of measurement noise is small, and if there are some particles nearby clutters, the average weight of the particles will be much greater than the clutter density, because the peak value of the likelihood function is much greater than the number of particles. Therefore, the weights of Gaussian components updated by the clutter will be greater than the actual values. The present authors call this phenomenon the weight over-estimation problem, which can be solved by some modifications of the weight updating formula. Simulation results show that the proposed algorithm has better performance than the GMP-PHD filter, implying good application prospects.

引用

页码：139 / +

页数：2

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