A Possibilistic Data Association Based Algorithm for Multi-target Tracking

The reasons for fuzzy data association in a densely cluttered environment are analyzed in this paper, and a possibilistic data association based algorithm for multi-target tracking is proposed. This paper fully analyses the shortcomings of the conventional fuzzy approaches and proposes the possibilistic data association based algorithm which can improve the performance of the multiple targets tracking. It can reduce the association errors caused by clutters greatly. The simulation results show that the algorithm has superiority over the conventional fuzzy approaches, and can track multiple targets in real time.