<p>In this paper, we investigate the adaptive CFAR (Constant False Alarm Rate) detection for MIMO (Multi Input Multi Output) radar architecture considering a Pearson distributed clutter. Three CFAR detectors; the CA- (Cell Averaging-), GO- (Greatest Of-) and SO- (Smallest Of-) CFAR detectors are proposed and their performances are analyzed and compared for statistical MIMO radars in homogeneous and non-homogeneous background. We derive Close-form expressions of the probability of false alarm (<i>P</i>_FA) of the three CFAR detectors in homogeneous Pearson environment for the statistical MIMO radars. The detection performance of the three CFAR detectors in homogeneous and non-homogeneous background (presence of interfering targets and clutter edge) is carried out using Monte Carlo simulations and the obtained results show that the SO-CFAR gives the best performance in homogeneous clutter in the case where a high number of nodes is employed. In non-homogeneous clutter, the GO-CFAR detector gives the best performance in the case of clutter edge transition while the CA-CFAR is the best in the case of interfering targets.</p>