Improve the robustness of MVDR beamforming method based on steering vector estimation and sparse constraint

Minimum variance distortionless response (MVDR) beamformer has two major drawback, High sidelobe level and direction of arrival (DOA) estimation sensitivity, many approaches was proposed to improve the robustness of the (MVDR) beamformer against array steering vector errors, and to deal with high sidelobe level. In this letter, We will propose a novel algorithm for robust MVDR depend on steering vector estimation and sparse constraint, so it deals with High sidelobe, and array steering vector errors in the same time, and compare its performance in different case of mismatch with other beamformers.