查看文章

Most of the existing beamforming methods are based on the Minimum Variance (MV) criterion. The MV approach is statistically optimal only when the signal, interferences and the noise are Gaussian-distributed. However, non-Gaussian signals arise in a variety of practical applications. In this paper, Minimum Dispersion Distortionless Response (MDDR) beamforming, which minimizes the -norm of the output while constraining the desired signal response to be unity, is devised for non-Gaussian signals. It is shown that the MDDR beamformer, which implicitly exploits non-Gaussianity, can improve the performance significantly if p <; 2 for sub-Gaussian signals or p <; 2 for super-Gaussian signals. Three efficient algorithms, the Iteratively Reweighted Minimum Variance Distortionless Response (IR-MVDR), complex-valued full Newton's and partial Newton's methods, are developed to solve the resulting ℓ _p -norm …