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A new improved firefly clustering algorithm for SMC-PHD filter
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DOI：10.1016/j.asoc.2019.105840.png)
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Aiming at the difficulty of extracting multi-target states in SMC-PHD filter, this paper proposes a SMC-PHD multi-target tracking method based on the improved firefly clustering algorithm. This method uses the improved firefly clustering algorithm to extract the peaks of the updated PHD function. Firstly, select the particles equal to the number of targets to form firefly individuals, introduce attraction and movement mechanism of the firefly algorithm, use the optimal firefly guiding other fireflies' movement, and undergo combination and mutation operation for the optimal firefly. Search the optimal solution in the whole solution space and obtain multi-target states. The experimental results show that the improved algorithm has more stable peak extraction ability than K-Means clustering algorithm in SMC-PHD filter. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Multi-target tracking
SMC-PHD
Firefly algorithm
State extraction
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IF:
6.6
论文数:
1.4W
被引数:
4.8W
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