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PHD,CPHD,和CBMeMBer滤波器的实现

于 2023-08-08 发布 文件大小:16.67 kB
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应用背景在杂波环境下,传统的多目标跟踪算法需要进行数据关联,若杂波密度或目标数较大时,关联算法变得非常复杂,会出现组会爆炸等问题。随后,Mahler提出来基于随机有限集的多目标跟踪算法,其无需进行数据关联,就可以对杂波环境下多个目标进行有效地跟踪。关键技术给出了三种基于随机有限集的多目标跟踪算法,概率假设密度(PHD)滤波器、势概率假设密度(CPHD)滤波器和势平衡多目标多伯努利(CBMeMBer)滤波器。在线性高斯条件下给出上述滤波器的高斯混合实现,并对其进行比较。

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