An Improved GMPHD High-Maneuverability Multi-Target Tracking Algorithm
Due to the unknown number of targets and complex motion patterns in the high-maneuvering multi-tar-get tracking scene,the traditional GMPHD filtering algorithm is prone to large tracking errors,inaccurate target number estimation and difficult to distinguish target tracks.To solve the above problems,based on GMPHD filtering algorithm,a labeling GMPHD filtering algorithm for adaptive CS model is proposed.By means of labeling,the target track is explicitly distinguished and the missing target track is extrapolated.Meanwhile,the adaptive CS model suitable for single target is extended to maneuvering multi-target scenarios.The maneuverability change of the target is fed back to the target state estimation in real time.Compared with extended GMPHD,square root cubature GMPHD and adaptive CS-GMPHD,the simulation results show that the proposed algorithm has the advantages of low computation time and high tracking accu-racy in high maneuvering multi-target scenarios.
improved GMPHD filterhigh maneuverability multi-target trackinglabelingadaptive CS model
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