Multipath Generalized Labeled Multi-Bernoulli Filter

被引:0
|
作者
Yang, Bin [1 ]
Wang, Jun [1 ]
Wang, Wenguang [1 ]
Wei, Shaoming [1 ]
机构
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
RANDOM FINITE SETS; TRACKING; FUSION; ORDER;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traditional multitarget tracking algorithms assume that each target can generate at most one detection per scan. However, in the over-the-horizon radar (OTHR), a target may produce multiple detections because of multipath propagation. In this paper, we propose a new algorithm, called multipath generalized labeled multi-Bernoulli (MP-GLMB) filter, to effectively track multiple targets in such multiple-detection systems. The proposed technique is based on the labeled random finite set (RFS), which estimates the number of targets and the trajectories of their states. The proposed MP-GLMB filter is compared with the multipath version of the probability hypothesis density (PHD) filter and the multi-target multi-Bernoulli (MeMber) filter, and simulation results show that our algorithm has improved tracking performance.
引用
收藏
页码:1423 / 1429
页数:7
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