Joint probability data association algorithm with fusing multi-feature information
Li Juan Zhou · Computer Engineering and Applications Journal · 2012
Joint Probability Data Association (JPDA) algorithm only uses the newest status measurements.As for this shortcoming,this paper proposes an improved JPDA algorithm which fuses multiple feature information.The new algorithm calculates the association matrix between each feature information and targets.According to D-S theory of evidence,this paper fuses status measurements with the other feature information to get fused association probability.Then the fused association probability will be used to modify the original association probability gotten by using JPDA algorithm.And the modified association probability will be used to update the state of targets.Compared to JPDA algorithm,simulations show that the tracking error of the new algorithm can be decreased from 27 to 60 percent.