中文摘要：

提出了一种未知杂波环境下的多目标跟踪算法.该算法通过有限混合模型（Finite mixtrue model,FMM）建立多目标似然函数,其中混合模型参数可通过期望极大化（Expectation maximum,EM）算法及模型合并与删除技术得到.由估计的混合模型参数可进一步得到杂波模型估计、目标个数估计以及多目标状态估计.类似基于随机有限集（Random finite set,RFS）的多目标跟踪算法,该算法也可避免目标与测量的关联过程.仿真实验表明,当杂波分布未知并且较复杂时,本文算法的估计效果要明显优于未进行杂波拟合时的多目标跟踪算法.

英文摘要：

A novel multitarget tracking algorithm in unknown clutter is proposed in this paper. In the proposed algorithm, the multitarget likelihood function is described based on the finite mixture model （FMM）, whose parameters are estimated according to the algorithm of expectation maximum （EM） and the technology of model merging and pruning. The estimation of clutter model, target number, and multitarget states can be derived based on the estimated parameters. Similar to the multitarget tracking algorithms based on random finite set （RFS）, the association process between the targets and measurements can be avoided in the algorithm proposed. The simulation shows that the estimation results of the proposed algorithm are much better than those of the multitarget tracking algorithms without the fitting of clutter model, especially when the clutter models are complicated and unknown.