Distributed Fusion with Multi-Bernoulli Filter based on Generalized Covariance Intersection

被引:0
|
作者
Wang, Bailu [1 ]
Yi, Wei [1 ]
Li, Suqi [1 ]
Kong, Lingjiang [1 ]
Yang, Xiaobo [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Elect Engn, Chengdu, Peoples R China
来源
2015 IEEE INTERNATIONAL RADAR CONFERENCE (RADARCON) | 2015年
关键词
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
In this letter, we consider the distributed multitarget tracking through the use of multi-Bernoulli based on generalized Covariance Intersection (G-CI). However, the G-CI fusion of two multi-Bernoulli posterior distributions does not admit an closed-form expression. To solve this problem, we firstly approximate the fused posterior as an unlabeled version of delta-generalized labelled multi-Bernoulli (delta-GLMB) distribution, referred to as delta-GMB. To allow the subsequent fusion with another multi-Bernoulli distribution, e.g., fusion with a third sensor node in the sensor network, or feedback working mode, we further approximate the fused delta-GMB posterior using a multi-Bernoulli formed distribution which matches its first-order statistical moment. We implement the proposed method using sequential Monte Carlo techniques and demonstrate its performance in two challenging tracking scenarios.
引用
收藏
页码:958 / 962
页数:5
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