Abstract:

In traditional radar target tracking, only azimuth and range measurement data are used, and the tracking precision can not be further improved because of insufficient target information. For this problem, utilizing the ability of high resolution sensing of modern radar, a high-performance target tracking model and implementation algorithm is proposed by integrating the square-root unscented Kalman filter (SRUKF). The algorithm is based on target’s aspect angle (referred to as feature information), which is a derived measurement from a high range resolution profile (HRRP) recognition. The performance improvement of tracking comes from this extra feature information, which is inherently related with target motion state. Simulation results show that the presented method has fast convergence speed, high tracking precision and low computational cost compared with the traditional one.