A group target tracking algorithm based on topology
Yingjing Zhang, Mingyang Liu, Xin Liu, Tianhao Wu · Journal of Physics Conference Series · 2020
Abstract For dense individual targets, their close distances may cause gates overlap, which impairs the tracking performance. To solve this problem, this paper proposes a group target tracking algorithm based on topology. Firstly, the targets are grouped based on their positions and velocities. Note that group targets have more stable tracks compared with individual targets. Then, for the targets in the group, data association based on topology for dense individual targets is achieved, considering relative positions of targets are stable. Finally, the simulation experiments are conducted to evaluate the proposed algorithm. The simulation results show that the group target tracking algorithm based on topology improves the association performance compared with the traditional Hungarian algorithm.