Abstract:The probability hypothesis density (PHD) filter only provides the state estimates of targets at each time step, but the individual tracks for targets were not involved. In this paper, an algorithm to maintain the track continuity for the extended targets is proposed for the extended target Gaussianmixture probability hypothesis density (GMPHD) filter. First, each individual Gaussian term of the mixture representing the posterior intensity function will be assigned a label, which is evolved through time. Then a track management scheme is developed to form the tracks for the extended targets. Furthermore, to improve the performance of the extended target GMPHD filter we also propose an adaptive measurement set partitioning algorithm for resolving the identities of the extended targets in close proximity. The simulation results show that the proposed tracker can achieve good tracking performance.