Feature-Aided Tracking Algorithm for Radar Target

In traditional radar target tracking, only angle and range measurement data are used, and the tracking precision can not be further improved because of insufficient target information. In this paper, utilizing the high range resolution profile (HRRP) information of modern radar, a highperformance target tracking algorithm referred to as FAT-UKF is proposed. The algorithm is based on HRRP extentaided tracking model, and is implemented via advanced nonlinear filtering technology. The performance improvement of tracking comes from extra measurement information of target extent, which is inherently related with target motion state. Simulation results for typical application example show that the presented method not only has a high convergence speed, but also can effectively break through the tracking error lower bounds of traditional methods, thus to significantly improve the total performance of tracking system.