Spatial Wiener filter to reduce spatial aliasing with spherical microphone arrays.

Abstract

Three dimensional acoustic soundfields can be represented by a set of spherical harmonic coefficients that are extracted from pressure signals recorded by a spherical microphone array. The extraction method used and truncation order chosen introduce errors of spatial aliasing in the coefficients and truncation error in a reconstructed signal. A spatial Wiener filter (SWF) extraction method is proposed in this paper, using second order statistics of typical soundfield characteristics (signal power, estimated source locations, and internal microphone noise) and accounts for the presence of coefficients beyond the truncation order to reduce spatial aliasing in the extracted coefficients. The SWF can also distinguish between "wanted" and "unwanted" sources, reducing the contributions of unwanted sources to the extracted coefficients. The SWF is compared against the state of the art methods; regularized inverse (or generalized inverse), and orthonormal extraction methods, which are explored under a similar framework to the SWF. The authors compare these methods and show the benefit of the SWF for plane waves, with varying assumptions about the source characteristics. The SWF can also extract coefficients beyond the traditional truncation limit of a given array, unlike other methods.