The problem of detecting signal with multiple input mul-tiple output (MIMO) radar in correlated Gaussian clutter dominated scenario with unknown covariance matrix is dealt with. The gen-eral MIMO model, with widely separated sub-arrays and co-located antennas at each sub-array, is adopted. Firstly, the generalized likelihood ratio test (GLRT) with known covariance matrix is ob-tained, and then the Rao and Wald detectors are devised, which have proved that the Rao and Wald test coincide with GLRT detec-tor. To make the detectors fully adaptive, the secondary data with signal-free will be collected to estimate the covariance. The per-formance of the proposed detector is analyzed, however, it is just ancillary. A thorough performance assessment by several numer-ical examples is also given, which has considered the sense with co-located antennas configure of transmitters and receivers array. The results show that the performance the proposed adaptive de-tector is better than LJ-GLRT, and the loss can be acceptable in comparison to their non-adaptive counterparts. The problem of detecting signal with multiple input mul-tiple output (MIMO) radar in correlated Gaussian clutter dominated scenario with unknown covariance matrix is ​​dealt with. The gen-eral MIMO model, with widely separated sub-arrays and co-located antennas at each The generalized likelihood ratio test (GLRT) with known covariance matrix is ​​ob-tained, and then the Rao and Wald detectors are devised, which have proved that the Rao and Wald test coincide with GLRT detec- tor. To make the detectors fully adaptive, the secondary data with signal-free will be collected to estimate the covariance. The per-formance of the proposed detector is however, it is just ancillary. A thorough performance assessment by several numer- The results show that the performance the proposed adaptive adaptive detector is better than LJ-GLRT, and t he loss can be acceptable in comparison to comparison to their non-adaptive counterparts.