A robust D–S fusion algorithm for multi-target multi-sensor with higher reliability

This paper addresses the problem of track fusion for unordered distributed sensors with unknown measurement noise. A robust Dempster–Shafer (D–S) fusion algorithm is proposed, which includes three parts, namely, the local track estimation, the track association, and the state fusion. First, a labeling VB-PHD filter is derived to present target states with track labels and the unknown measurement noises of local sensors. Next, a heuristic D–S method is proposed to determine the relationship of local tracks and fused tracks, where the accumulated information is taken into account. Finally, a fusion method is given to show the state fusion results, which can fully utilize local state estimates and measurement noise information. Simulation results are provided to illustrate the high precision of tracking and good robustness, comparing with the traditional methods.