Improvements in closed-section wind-tunnel beamforming experiments of acoustic sources distributed along a line

Theoretical analysis of the DAMAS algorithm and efficient implementation of the covariance matrix fitting method for large-scale problems

“…Since its introduction by Brooks and Humphreys, the DAMAS algorithm [1] has enjoyed a certain popularity (see, e.g. [2][3][4]) in the acoustical imaging community for the deconvolution of beamforming maps (DAMAS stands for Deconvolution Approach for the Mapping of Acoustical Sources). Indeed, it has been observed that when it converges, the DAMAS algorithm yields accurate and useful power estimates [2,3,5].…”

“…Several methods, most of them numerically more efficient than the DAMAS algorithm, have been proposed since 2006 (see [2] for a review of such methods), and are frequently compared with it, one recurring remark being the computational effort that the DAMAS algorithm requires [3][4][5][6][7][8][9][10][11][12] . Among these methods, several variants of the DAMAS algorithm with improved numerical efficiency have been proposed, based on the formulation of the problem in the Fourier domain [13], or pruning of the grid points that will not be involved in the final source map either directly [10,11], or similarly in a wavelet basis [8].…”