Direct Target Joint Detection and Tracking Based on Passive Multi-Static Radar

Abstract

Traditional target tracking is carried out based on the point measurements extracted from the radar resolution cells. This is not suitable for situations of low signal-to-noise ratio (SNR). In this paper, we aim to investigate the problem of the joint detection and tracking (JDT) of a target by directly using the received signals of passive multi-static radar without feeding the signals to matched filters. To this end, a novel likelihood function is proposed exploiting the statistical properties of coherent processing between the reference and surveillance signals. With such a likelihood function, the particle Bernoulli filter is employed to perform direct JDT (DJDT) of the target. A remarkable feature of the proposed method is that it is able to achieve satisfactory performance when the SNR of received signals is low. Furthermore, the proposed method cannot only achieve the existence and kinematic state of the target, but also the time-varying SNR of each receiver, which serves as an important input for sensor adjustment. The performance of the proposed method is verified via simulations.