Simultaneous Detection and Discrimination of Mainlobe Deceptive Jammers in FDA-MIMO Radar

In this article, the problem of detecting the true target in the background of mainlobe deceptive jammers is addressed in a frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. At the modeling stage, a simultaneous detection and discrimination method is formulated by utilizing the specific range degrees of freedom DOFs of the FDA-MIMO radar. In this respect, the detection problem for the window under test (WUT) is formulated as a multihypothesis test, where the alternative hypothesis is composed of possible true and false targets. In particular, the true target is discriminated from the mainlobe jammers as a byproduct. At the design stage, detectors are designed resorting to a suboptimal way, i.e., penalized log-likelihood ratio test. To obtain the maximum likelihood (ML) estimate of unknown parameters, the data in the transmit and transceive domain are jointly utilized. At the analysis stage, the detection performance as well as the discrimination performance are analyzed with comparisons among the proposed detectors and the competitors. Simulation results demonstrate the effectiveness of the proposed detectors.