Detection of False Targets in a Full-Polarization Radar Network Under Deception Jamming
Lei Zhang, Ying Luo, Huan Wang, Qun Zhang
Abstract
This study investigates the target detection and discrimination method in the presence of deceptive jamming using a full-polarization radar network. Within the target detection framework by multiple radars with full-polarization capabilities, we formulate the problem of detecting false targets as a multivariate hypothesis testing task. Based on the generalized likelihood ratio test, we propose a two-stage detection scheme comprising a predetection stage at each radar system and a discrimination stage at the information fusion center. The predetection step is crucial when interference signals cannot deceive all radars. The discrimination stage exploits spatial distinctions in polarization scattering properties between physical and false targets. By leveraging the capabilities of full-polarization radar for acquiring and processing target polarization information, along with the multiview observation potential of radar networks, our proposed approach can obtain more comprehensive scattering information about physical and false targets as well as their differences, thereby achieving enhanced accuracy in target discrimination. We validate the effectiveness of our algorithm through Monte Carlo experiments.