Study of reduced-rank STAP based on estimation of clutter subspace for MIMO radar

Multiple input multiple output (MIMO) radar is a new radar system developed recently and space time adaptive processing (STAP) for airborne MIMO radar systems deserves further research. This article mainly studies a reduced-rank STAP algorithm in an airborne MIMO radar system. According to an analysis of the clutter suppression principle of STAP, a reduced-rank algorithm based on clutter subspace is derived. On the basis of the reduced-rank algorithm, and combined with the feature of prolate spheroidal wave functions (PSWF), the article proposes a new reduced-rank algorithm based on the estimation of clutter subspace and compares its performance with several other reduced-rank algorithms. The results show that when there exist amplitude and phase errors in the array elements, the new algorithm can effectively reduce computational complexity at the same time keep the clutter suppression performance of the STAP algorithm.