A robust direct data domain least squares (D3LS) beamforming algorithm that is capable of reducing the sidelobe level of the beam pattern is presented. By exploiting the sparsity of the desired beam pattern, the proposed method can enhance the performance with its lower sidelobe level and deeper null for interference while the robustness against steering vector mismatch is increased when a proper regularization parameter is selected. Simulation results demonstrate the effectiveness of the proposed method.
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