Spherical Harmonic Smoothing for Localizing Coherent Sound Sources

Abstract

Correlated or coherent sources can cause the localization performance of subspace-based beamformers to deteriorate. To solve this problem, various smoothing techniques have been proposed for the localization of multiple coherent sound sources. A common principle of smoothing techniques is to increase the rank of a covariance matrix by constructing multiple subarrays in the space, time, or frequency domain. The construction of such subarrays, however, requires the satisfaction of strong assumptions regarding the microphone positions or the temporal/spectral structures of the signals. In this paper, we propose a spherical harmonic smoothing technique that can perform smoothing in terms of spherical harmonic coefficients only. Unlike other smoothing techniques, the proposed technique constructs subarrays of spherical harmonic coefficients and uses them to increase the number of linearly independent observations in a signal subspace. Subarray construction in the spherical harmonics domain enables the accurate localization of multiple coherent sources even at a single frequency. The proposed technique can be applied to an arbitrary microphone array as long as the spherical harmonic coefficients can be measured up to a finite order.