Fuzzy JPDAF approach for vehicle tracldng in road situation
H. Dang, Chongzhao Han, Zhansheng Duan · 2003
Data association was an important content in Multi-target tracking. Typical algorithms to deal with probability in JPDAF method was substituted by the fuzzy membership, but the general methodology of JPDAF such problems are the joint probabilities data association filter (JPDAF) proposed by Bar-Shalom and his team. The basis of JPDAF is the calculus of the joint probabilities between the measurements and the tracks. The algorithm assigns weights for reasonable measurements and uses a weighted centroid of those measurements to updaie the track. In this paper. a new weight assignment method based on fuzv c-means methodology was proposed, and the general methodology of JPDAF remains unchanged. This leads to a fiitjid combination between firzry and probability approaches. It is proved that the method is simple andfast by simulation. and suits for automotive radar multi-iarget tracking.