LAUSR

Phase-mode array processing which utilizes the spherical harmonics decomposition offers a useful framework for spherical microphone arrays. In the modal domain, one of the major applications of spherical arrays is acoustic beamforming. Usually, beamforming is performed by minimizing the power of the beamformer output with a distortionless constraint towards the look direction. Also, most beamformers model the spectral coefficients of target speech using a Gaussian distribution. In this letter, a beamforming method that minimizes the $\ell _{0}$-norm of the beamformer output in the spherical harmonics domain with a distortionless constraint is proposed. The proposed method assumes a super-Gaussian prior for the target speech and sparsifies the beamformer output which is shown to reduce the residual elements of the interfering speech signals from the beamformer output leading to superior spatial separation. The formulation of the proposed beamformer in the spherical harmonics signal model is presented along with an algorithm to solve it. Simulation results show the effectiveness of the proposed beamformer in spatially filtering the desired speaker signal from the interfering signals using a number of objective measures.