Adaptive multiple targets detection for FDA-MIMO radar with Gaussian clutter

This paper presents an adaptive multiple targets detection framework for frequency diverse array multiple-input multiple-output radar embedded in Gaussian noise with an unknown covariance matrix. To this end, we define the one-range-cell multiple targets model as a summation expression and then design four detectors, i.e., the generalized likelihood ratio test, adaptive matched filter, Rao, and Wald tests for the above newly built problem. Closed-form expressions for the probability of false alarm and the probability of detection are provided to assess the aforementioned detectors. The numerical exam-ples show that the proposed architectures can ensure better detection performance than the considered competitors. Finally, notice that each proposed detector has a specific behavior in terms of robustness to low volumes of data. Thus, the choice of a specific solution is dictated by the operating requirements of the radar system.(c) 2022 Elsevier B.V. All rights reserved.