Single-Observer Passive Tracking Based on DOA and TDOA Using Iterative Pseudo-Liner Kalman Filter

Given the growing importance of electronic and information warfare in modern military field, localization and tracking methods based on passive coherent radar have become a research hotspot. This paper studies the problems in passive tracking based on DOA and TDOA, obtained by single-observer receiving signals from multiple passive transmitters. First of all, we deduce the pseudo-liner observation equations for DOA and TDOA. A traditional Kalman filter is applied to track target, on the condition that the least squares (LS) algorithm is used to get the initial value, a pseudo-liner Kalman filter (PKF). Furthermore, after analyzing the observation equations, an Iterative PKF (IPKF) algorithm is used to track a target. We also deduce the CRLB of the proposed algorithm. Simulations show that the tracking precision, the rate of convergence, and the tracking stability of proposed algorithm are higher than extended Kalman filter (EKF). The higher the number of iterations, the better the performance and the tracking errors will be closer to CRLB with smaller observation error.