The Sequential Monte Carlo Multi-Bernoulli Filter for Extended Targets

被引：0
|
作者：
Liu, Meiqin [1 ,2 ]
Jiang, Tongyang [1 ,2 ]
Zhang, Senlin [2 ]
机构：
[1] Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China
来源：
2015 18TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) | 2015年
关键词：
Random finite set; multi-Bernoulli filter; extended targets; sequential Monte Carlo;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The multi-Bernoulli (MB) filter for extended targets has been derived recently. However, the implementation of the extended target (ET) MB filter for nonlinear non-Gaussian models has not been presented. In this paper, we propose the sequential Monte Carlo (SMC) implementation of the ET-MB filter for estimating multiple extended targets by using the SMC technique and measurement partitioning algorithm. Simulation results demonstrate that the estimation performance of the SMC-ET-MB filter is superior to that of the standard SMC-MB filter for extended target measurement models.
引用
收藏
页码：984 / 990
页数：7
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