中文说明：
在杂波环境下，传统的多目标跟踪算法需要与数据相关联。如果杂波密度非常大，或者杂波密度非常大。随后，Mahler提出了一种基于随机有限集的多目标跟踪算法，该算法不需要进行数据关联，可以在杂波环境下跟踪多个目标。
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，潜在概率假设密度（CPHD）滤波器和势平衡多目标跟踪算法。
English Description：
Application background In the clutter environment, the traditional multi target tracking algorithm needs to be associated with the data. If the clutter density or the target number is large, the algorithm becomes very complex. Subsequently, Mahler proposed a multi object tracking algorithm based on the random finite set, which has no need to carry out the data association, it can track multiple targets in clutter environment. Key Technology Three kinds of multi object tracking algorithm based on random finite set, probability hypothesis density (PHD) filter, potential probability hypothesis density (CPHD) filter, and potential balanced multi