Detection in Passive MIMO Radar Networks

This paper considers detection in passive multiple-input multiple-output (MIMO) radar sensor networks. Multiple centralized and decentralized detection architectures are surveyed and compared via Monte Carlo simulation. A recently proposed generalized likelihood ratio test (GLRT) detector, termed the reference-surveillance GLRT, is shown to have superior detection performance because it maximally exploits the correlations in the measured data. Specifically, it exploits inter-receiver reference-surveillance correlations and inter-receiver surveillance-surveillance correlations, two concepts that are explained in this paper. In this way, the reference-surveillance GLRT achieves better sensitivity under all direct-path-to-noise ratio conditions than more conventional matched filter-inspired detection approaches, which exploit only some of the correlations within the measured data.