Typing Instructions For FUSION 2001 Documents

Hongshe Dang Institute of Synthetic Automation Xi’an Jiaotong University Xi’an, Shaan xi 710049, P. R. China [email protected] Chongzhao Han Institute of Synthetic Automation Xi’an Jiaotong University Xi’an, Shaan xi 710049, P. R. China [email protected] Zhansheng Duan Institute of Synthetic Automation Xi’an Jiaotong University Xi’an, Shaan xi 710049, P. R. China [email protected] Abstract -Data association was an important content in Multi-target tracking. Typical algorithms to deal with 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 update the track. In this paper, a new weight assignment method based on fuzzy c-means methodology was proposed, and the general methodology of JPDAF remains unchanged. This leads to a fruitful combination between fuzzy and probability approaches. It is proved that the method is simple and fast by simulation, and suits for automotive radar multi-target tracking.