Distributed System Target Tracking Algorithm Based On Track Comparability Degree

Track association and track fusion are the key problems of tracking target in distributed target tracking system,a dynamic weighted fusion tracking algorithm based on track comparability degree is proposed in this paper.By integrating the track character vector provided by track estimation of each local sensor and the performance of sensor resolution,track fuzzy membership comparability degree matrix and systemic track association decision matrix at every measurement time are established on the basis of Fuzzy Clustering Method,and the problem of track association in fusion center is solved.Combining with the idea of weighted fusion algorithm and track fuzzy membership comparability degree matrix at every measurement time,real time and dynamic weighting factors of all local tracks in fusion center track aggregation are alloted,then the problem of track fusion in fusion center is solved.Monte Carlo simulation shows that with the proposed algorithm track association and track fusion in fusion center can be correctly processed,thus the system can track all targets in the observation area effectively,and obtain the systemic fusion tracks of targets that have smaller tracking errors than individual local sensor tracks,simulation results also show that the algorithm proposed in this paper is an effective tracking method for distributed target tracking system.