Deconvolution Post-processing Algorithm of Minimum Variance Distortionless Response Beamformer
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Abstract
In order to improve the azimuth estimation capability of the minimum variance distortionless response (MVDR) beamforming algorithm, the output power spectrum of the MVDR algorithm was reformed as a convolution form, two deconvolution post-processing techniques were proposed to deconvolve the azimuth spectrum of MVDR. The algorithms take the MVDR azimuth spectrum of a single sound source at the center of the angular space as a point spreading function (PSF), and use the Richardson-Lucy algorithm and the fast iterative shrinkage-thresholding algorithm (FISTA) to deconvolute the MVDR (MVDR-RL, MVDR-FISTA) azimuth spectrum. The MVDR-RL and MVDR-FISTA azimuth spectrum has lower background level, higher resolution, and higher estimation accuracy. Simulation experiments show the good performance of the proposed algorithm.
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