Maneuvering Multi-target Tracking Using the Multi-model Cardinalized Probability Hypothesis Density Filter

被引：0
|
作者：
Fu Yaowen [1 ]
Long Jianqian [1 ]
Yang Wei [1 ]
机构：
[1] Natl Univ Def Technol, Sch Elect Sci & Engn, Changsha 410073, Hunan, Peoples R China
来源：
CHINESE JOURNAL OF ELECTRONICS | 2013年 / 22卷 / 03期
关键词：
Multi-target tracking; Maneuvering target tracking; Multi-model method; Cardinalized probability hypothesis density (CPHD) filter;
D O I：
暂无
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：
Tracking an unknown and time-varying number of maneuvering targets is a challenging problem in the presence of noise, clutter, uncertainties in target maneuvers, data association, and detection. To account for this problem, a multi-model extension of the Cardinalized probability hypothesis density (CPHD) filter is proposed in this paper. Additionally, a particle implementation and a Gaussian mixture implementation of the proposed extension are given for generic models and linear Gaussian models, respectively. The effectiveness of the extension is illustrated through Monte Carlo simulation.
引用
收藏
页码：634 / 640
页数：7
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