A track extraction method based on target topology for PHD filter
Feng Ping Yang, Yazhe Su, Wanying Zhang, Yao Xuanzheng · 2016
Probability Hypothesis Density (PHD) filter has proven to be a valid algorithm for jointly estimating the time-varying number of targets and their states. However, the filter can only provide the estimates of the set of targets states but not the complete tracks of individual targets. To solve this problem, we present a track extraction method based on the targets' topology information. Simulation results indicate that the proposed method has a better performance than that of the methods proposed in recent years.