具有形状信息的多个群目标跟踪算法OA北大核心CSTPCD

Aiming at the problem of low shape estimation accuracy under the condition of miss detection and clutter measurements in multiple group-target tracking,a novel multiple group-target tracking algorithm with shape information is proposed in this paper.Firstly,the algorithm divides the measurement set for track initiation.Then,the method improves the conventional group-target Bayesian recursive estimation,and fuses the group-target track association algorithm.Based on the improved method,the kinematic state and shape information of group-target can be estimated simultaneously,and high shape estimation accuracy is achieved.Simulation results show that the algorithm can not only track multiple group-targets simultaneously,but also achieve the shape information of each group-target with high shape estimation accuracy.