Beamforming Regularization, Scaling Matrices, and Inverse Problems for Sound Field Extrapolation and Characterization: Part II - Experiments

Sound field extrapolation (S.h.h) is aimed at the prediction of a sound field in an extrapolation region using a microphone array. For sound environment reproduction purposes, sound field characterization (SFC) aims at a more generic or parametric description of a measured or extrapolated sound field using different physical or subjective metrics. In this paper experiments with a recently-developed SFE method (Part I - Theory) are reported in a first instance. The method is based on an inverse problem formulation combined with a recently proposed regularization approach: a delay-and-sum beamforming matrix in the discrete smoothing norm of the cost function. In a second instance, the results obtained from the SEE method are applied to SFC as presented in Part I. The SFC classification method is verified in two environments that recreate ideal or complex sound fields. In light of the presented results and discussion it is argued that the SEE and SFC proposed methods are effective.