期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 65, 期 1, 页码 242-255出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2016.2617825
关键词
Multi-Bernoulli filter; multi-target tracking; distributed fusion; sensor network
资金
- Australian Research Council [DP130104404, DP160104662]
- National Natural Science Foundation of China [61301266]
- Chinese Postdoctoral Science Foundation [2014M550465, 2016T90845]
In this paper, we propose a distributed multiobject tracking algorithm through the use of multi-Bernoulli (MB) filter based on generalized covariance intersection (G-CI). Our analyses show that the G-CI fusion with two MB posterior distributions does not admit an accurate closed-form expression. To solve this problem, we first approximate the fused posterior as the unlabeled version of delta-generalized labeled MB distribution, referred to as generalizedMB(GMB) distribution. Then, to allow the subsequent fusion with another MB posterior distribution, e.g., fusion with a third sensor node in the sensor network, or fusion in the feedback working mode, we further approximate the fused GMB posterior distribution as an MB distribution which matches its first-order statistical moment. The proposed fusion algorithm is implemented using sequential Monte Carlo technique and its performance is highlighted by numerical results.
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