Robust GM-PHD Filter with Adaptive Target Birth

Due to electromagnetic silence, passive tracking systems for emitter targets usually produce track segments (i.e., tracklets) rather than an entire trajectory of the target. Therefore, a multistage method for emitter target tracking is proposed in this paper. In the stage of tracklet generation, the Gaussian mixture-probability hypothesis density tracker with adaptive estimation of target birth intensity is applied to generate reliable tracklets of the emitter targets. After that, in the stage of tracklet association, the multipoint motion information and emitter signal information are integrated to compute the similarities between the tracklets. The affinity propagation algorithm, which does not impose the constraint of one-to-one correspondence, is then used to cluster the tracklets. In the stage of association refining, the clustering result is adjusted to refine the final trajectories according to the spatial-temporal constraint of the tracklets. The simulation results show that the proposed method is robust and performs well.