Robust Beamforming Technique with Sidelobe Suppression Using Sparse Constraint on Beampattern

In this paper, we propose two beamforming algorithms which impose sparse constraint on beampattern to suppress the sidelobe level and enhance robustness of the beamformer against steering vector error. The sparse constraint is given by an l(p)-norm, where p <= 2 holds. It is shown that the proposed algorithms can be solved using iterative algorithm. Computer simulations show that the proposed algorithms not only yield lower sidelobe level than that of the conventional beamformer, but also show better robustness against steering vector error than the conventional beam formers.