Passive Coherent Radar Tracking Algorithm Based on Particle Filter and Multiple TDOA Measurements

Abstract

In passive coherent radar tracking using external illuminator as transmitters, the traditional extended Kalman filter (EKF) is adopted frequently, but the tracking performance is affected seriously by the glint noise in practice. To solve this problem, a novel passive coherent radar tracking method is proposed based on particle filter (PF) and only time difference of arrival (TDOA) measurements. This new approach obtain measurements from multiple TDOA locating model, and then by using particle filter to track target, which avoid the error caused by EKF linearization, and reduce the measurements error resulted from glint noise, so it can improve the tracking precision. The simulation results show that the performance of the proposed method is superior to that of the EKF algorithm not only in Gaussian but also in glint noise environment. The experiment based on real data demonstrates the validity and feasibility of the new method.