Blind Target Detection for MIMO Radar Based on Random Matrix Theory Under Correlated Noise

Based on random matrix theory (RMT), a blind target detection algorithm for bistatic MIMO radar is investigated under correlated noise. In relatively snapshot-starving scenarios in which the number of snapshots is comparable in magnitude to the number of the arrays, robust detection perfounance of the proposed algorithm can be guaranteed. Exploiting the standard condition number (SCN) detector, a novel decision threshold under correlated noise is derived by the use of Stieltjes transform and multiplicative free convolution. The proposed algorithm does not require any prior infounation of the noise variance and the target scattering matrix. Compared with the existing target detector using M-P law-based threshold, the proposed algorithm significantly improves the robustness of target detection in bistatic MIMO radar under correlated noise environment. Simulations are conducted to illustrate its effectiveness.