A weighted sparse constraint Capon beamforming algorithm

Aiming at the problem of high sidelobes and nulls was not deep of Capon beamformer, the methods of reducing sidelobes and nulls were studied, a weighted sparse constraint Capon beamforming algorithm was proposed. Firstly, using the correlation operation of sidelobe array manifold matrix and the covariance matrix obtained the interference and noise energy were roughly posterior distribution in different directions. Then, different values were weighted in different directions according to the results, and restrained the interference. Simulation results show that the approach can reduce the sidelobes and deepen the null to fall the depth of the beam pattern, and improve the ability of suppress noise and interference. The proposed method is robust to both expected and array errors.