Random matrix theory inspired passive bistatic radar detection with noisy reference signal

Traditional passive radar systems with a noisy reference signal use the cross-correlation statistic for detection. However, owing to the composite nature of this hypothesis testing problem, no claims can be made about the optimality of this detector. In this paper, we consider digital illuminators such that the transmitted signal in a processing interval is a weighted periodic summation of several identical pulses. The target reflectivity is assumed to change independently from one pulse to another within a processing interval. Inspired by random matrix theory, we propose a singular value decomposition (SVD) and Eigen detector for this model that significantly outperforms the conventional cross-correlation detector. We demonstrate this performance improvement through extensive numerical simulations across various surveillance and reference signal-to-noise ratio (SNR) regimes.