Abstract
The probability hypothesis density (PHD) filter as an efficient, practical and robust approach to solve the multi-target tracking problem has been successfully implemented. In this paper, a study on multi-target tracking problem and the PHD filter with 1œlateral and vertical thinking1 is proposed. Firstly we list several difficulties (data association, time-varying number, and inaccessible control signal) for multi-target tracking; and then come up with the particle PHD filter as an alternative, while summarizing the algorithm with clarity and perception; finally simulation and analysis further prove the strengthens of PHD filter.
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