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.

Deception Velocity-Based Method to Discriminate Physical Targets and Active False Targets in a Multistatic Radar System

“…The electronic counter-countermeasures (ECCMs) for active deception jamming have been developing from the early monostatic radar system to the distributed multistatic radar system [4,5]. Compared with the monostatic radar with limited resources, the multistatic radar system can perceive the environment from multiple dimensions and perspectives and benefits from fusion processing, therefore improving the performance on target detection [6,7], target tracking [8,9] and ECCM [10,11]. The multistatic radar system can suppress jamming signals or discriminate false targets by fusing and processing the redundant detection information of different receivers.…”