Abstract: A reduced-dimension space-time adaptive processing (STAP) method for clutter suppression in airborne multiple-input multiple-output (MIMO) radar systems is developed. Firstly, the high-dimensional weight vector is decomposed into the Kronecker product of spatial and temporal weight vectors. Secondly, the quadratic cost function used in the optimum STAP is converted into two quadratic functions by using the information of the space-time correlation matrix. Finally, by iteratively optimizing two lower dimensional weight vectors in two quadratic functions, the proposed method can significantly decrease the computational load and training samples requirement. Experimental results using both simulated data and measured radar data demonstrate the effectiveness of the proposed method.