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A Possibilistic Data Association Based Algorithm for Multi-target Tracking

机译:基于多目标跟踪的可能基于数据关联的算法

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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.
机译:在本文中分析了浓密杂有环境中的模糊数据关联的原因,提出了一种用于多目标跟踪的可能基于多目标跟踪的可能基于多目标跟踪的算法。 本文充分分析了传统模糊方法的缺点,提出了基于可能的数据关联算法,可以提高多个目标跟踪的性能。 它可以大大减少由丛丛引起的关联错误。 仿真结果表明,该算法对传统的模糊方法具有优势,并且可以实时跟踪多个目标。

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