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中文摘要：
针对多传感器多目标跟踪问题,提出了基于随机有限集的概率假设密度（PHD）滤波算法。该算法通过选取与各传感器相关的重要性密度函数,层层更新各传感器的采样粒子,达到多传感器多目标有序PHD跟踪。给出了应用该算法的具体步骤,通过仿真实例证明该算法的有效性。
英文摘要：
In order to solve multi-sensor multi-target tracking problem,a probability hypothesis density（PHD） filter algorithm based on random finite sets is proposed.The algorithm chooses the importance density function with regard to every sensor,layer-by-layer updates sample particle of every sensor,finally realizes the multi-sensor multi-target sequential PHD tracking.The approach of using this algorithm is introduced.Simulation examples show the validity and rationality of this algorithm.
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