Abstract:In this paper,a new association method is proposed to tackle the data association problem of multi-target tracking.In this algorithm, building the associative matrix with the Euclidean distance and the 1-Norm of state vector between tracks and points firstly.And using the associative matrix find the most suitable(Maximum matching success rate)points for every track. If the points just marked by one track, update this track directly; if the points marked by many tracks, choose the track with highest probability to update. Monte-Carlo Simulation experiments show that this algorithm guarantees the updating points for every tracks are the best points among all present points.
