Blind multi-target detection for bistatic MIMO radar based on random matrix theory

In this paper, the random matrix theory (RMT) is applied in detecting the number of targets in the large dimensional regime for bistatic multiple input multiple output (MIMO) radar systems. A blind MIMO radar multi-target detection algorithm is proposed exploiting a sequence of nested RMT-based generalized-likelihood ratio test (GLRT) hypothesis tests. The decision threshold is derived by use of the Marcenko-Pastur (M-P) law and Tracy-Widom distribution. The proposed algorithm does not require the priori information of noise variance, target scattering and location. Therefore, it has advantages in the presence of noise uncertainty. Simulations are conducted to illustrate the effectiveness of the proposed algorithm. Compared with two conventional algorithms of minimum description length (MDL) and Akaike information criteria (AIC), it owns superiorities in both performance at lower SNR and consistency at larger snapshot size.