Research on Multi-Sensor Multi-Target Tracking Algorithm

Abstract

The tracking performance of JPDA-based algorithms will be decreased with the increase of sensors amount and clutter density. Thus it is necessary to find out a multi-sensor data fusion tracking algorithm which has lower computation and higher tracking accuracy. Since the motion direction of the targer is viewed as a key factor in data correlation, the pseudodirection tracking gate can be improved. The feature of location and speed are combined to reduce the amount of the related affairs, which can reduce the computation of JPDA algorithm. This idea is adopted to improve the FDA algorithm and a sequenced fast algorithm for data association based on double-gate tracking. The simulations proved that this method has legitimately limited the effective number of echoes, which ensures the accuracy of correlation and tracking. Its computation is less than original FDA algorithm with keeping and it has good performance for maneuvering target tracking