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Application of particle swarm optimization in multi-sensor multi-target tracking

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4 Author(s)
Lei Yang ; Sch. of Inf. & Commun. Eng., Harbin Eng. Univ. ; Weiwei Hu ; Shenyuan Yang ; Shujin Pu

For the multi-sensor multi-target data association problem, a novel particle swarm optimization (PSO) algorithm based S-dimensional (S-D) assignment method is proposed in this paper. By a combinational optimal way, it could find the minimum objective cost to be the best solution. Furthermore, the best solution could be searched soon through reducing the search region. The reason is that the validity of the candidate measurements is considered in particle swarm initialization, cross-over rules, and mutation rules. The PSO using different rules and GA are simulated for data association in the presence of fault alarms, and missed detections. The comparison testifies the proposed approach is effective

Published in:

Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on

Date of Conference:

19-21 Jan. 2006