A dimension-reduced MVDR Beamforming Algorithm for MIMO Radar

The beamforming issues of Multiple-Input Multiple-Output(MIMO) radar have been studied. To avoid the great number of training samples and heavy computational burden when using the conventional minimum variance distortionless response(MVDR) beamforming algorithm in MIMO radar, a dimension-reduced MVDR beamforming algorithm is proposed. The new method firstly divides a MN dimension weight vector into two low dimension weight vectors’ Kronecker product, then uses the conventional MVDR algorithm to resolve the two low dimension weight vectors, and synthesizes the original optimal weight vector finally. The new method changes the problem of resolving a high-dimension weight vector into the problem of resolving two low-dimension weight vectors, so the computational complexity and the number of training samples of the proposed algorithm are reduced with the maintenance of good performance. As a result, our method has greater value in practice. Finally, simulation results are presented to verify the effectiveness of the proposed method.