Multiple input multiple output(MIMO) radar as a new radar system has received significant attention in the past few years. This article studies space-time adaptive processing(STAP) for airborne MIMO radar, Based on multistage winner filter with generalized sidelobe canceller structure, A new reduced-rank space-time adaptive processing algorithm using priori knowledge constraints is proposed for MIMO radar. Through the use of jamming direction knowledge and clutter subspace knowledge estimated by prolate spheroridal wave functions ,the algorithm can greatly reduce computation and sample needs of airborne MIMO radar STAP and at the same time keep the performance of clutter suppression. Also, knowledge-aided effect on the convergence performance when the knowledge is mis-matched is considered. Simulation results show that when there is a certain error of knowledge , the algorithm can still effectively improve the convergence performance of STAP algorithm.