Deconvolution beamforming based on a fast gradient algorithm for sound source localization

Abstract

Deconvolution beamforming has gotten increased attention as a way to improve the spatial resolution of delay-and-sum beamforming. It has the ability to decrease sidelobes and increase resolution. However, compared to conventional beamforming, the extra computation of the deconvolution method is a drawback. A more efficient approach is developed to improve the computing speed of the deconvolution method. Specifically, when tackling deconvolution problems, this method improves computational performance by combining Fourier operation with a fast gradient algorithm called the double momentum gradient algorithm. We compare the proposed method with two known effective deconvolution methods, namely the fast Fourier transform non-negative least squares algorithm and the fast iterative shrinkage threshold algorithm. The results of simulation and experiment reveal that the proposed method tends to give a better spatial resolution within a short computational time and is more suitable for engineering applications.