一种交叉多目标跟踪算法

为了解决多目标跟踪过程中由目标轨迹交叉引起的跟踪算法复杂度增加以及跟踪精度降低的问题，提出了一种改进的基于随机有限集的交叉多目标跟踪算法。该算法以高斯混合参数代替概率密度假设来降低算法复杂度和减小跟踪误差。最后在线性高斯条件下进行了MATLAB仿真实验，模拟多目标的运动过程，应用本文提出的改进算法和传统的基于数据关联的算法对多目标进行跟踪，对比试验结果表明所提出的改进算法对交叉多目标具有更加良好的跟踪性能。

Algorithm forcross-multi-target tracking

In order to solve the problem that the crossover of target trajectory would make the algorithm more complex and make the tracing accuracy lower in the process of multi target tracking. This paper proposed a cross multi target tracking algorithm based on random finite sets. The proposed algorithm substituted the Gaussian mixture probability parameter for the probability hypothesis density in order to decrease the complexity and educe the tracing error. The MATLAB simulation is implemented under linear Gaussian assumptions, this paper simulated the moving process of multiple targets, and used the improved algorithm proposed in this paper and the traditional data association algorithm for tracking multiple targets, the experimental results show that the proposed algorithm has better performance for the cross multi target tracking.