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In this paper, the problems of simultaneously detecting and localizingmultiple targets are considered for noncoherent multiple-input multiple-output(MIMO) radar with widely separated antennas. By assuming a prior knowledge oftarget number, an optimal solution to this problem is presented first. It isessentially a maximum-likelihood (ML) estimator searching parameters ofinterest in a high dimensional space. However, the complexity of this methodincreases exponentially with the number G of targets.Besides, without the priorinformation of the number of targets, a multi-hypothesis testing strategy todetermine the number of targets is required, which further complicates thismethod. Therefore, we split the joint maximization into G disjoint optimizationproblems by clearing the interference from previously declared targets. In thisway, we derive two fast and robust suboptimal solutions which allow tradingperformance for a much lower implementation complexity which is almostindependent of the number of targets. In addition, the multi-hypothesis testingis no longer required when target number is unknown. Simulation results showthe proposed algorithms can correctly detect and accurately localize multipletargets even when targets share common range bins in some paths.

Suboptimum Low Complexity Joint Multi-target Detection and Localization for Noncoherent MIMO Radar with Widely Separated Antennas