Multi-sound-source locating method based on spherical microphone array

Abstract

The invention discloses a multi-sound-source locating method based on a spherical microphone array, and the method comprises the following steps of firstly conducting spherical harmonics decomposition for high-order sound fields collected by a spherical microphone array, and building a noise-contained sound source signal model received by a spherical harmonics domain array; then expressing a covariance matrix of data received by the array; classifying the covariance matrix according to a subspace decomposition method to obtain two mutually-orthogonal signal subspace and noise subspace; utilizing the orthogonality of the signal subspace and the noise subspace to define a guide vector of the signal subspace, and extracting one characteristic vector of the noise subspace to build a space azimuth spectrum; and finally searching a spectrum peak position of an azimuth spectrum function, and determining a space azimuth of a sound source. The method utilizes a three-dimensional space rotary symmetric structure of the spherical microphone array to adequately sample the sound field, so that the operation quantity is remarkably reduced through the high-resolution spectrum estimation and dimensional-reduced noise subspace, the sound source azimuth is accurately estimated, and the method can be widely applied to the fields such as a voice signal processing field.

Description

technical field [0001] The invention relates to a method for locating multiple sound sources in three-dimensional space based on a spherical microphone array, which can be widely used in fields such as speech signal processing and the like. Specifically, based on the principle of spatial orientation spectrum estimation, combined with the dimensionality reduction subspace, the received signal model of the spherical harmonic domain array is subjected to covariance calculation, the mutually orthogonal subspaces are divided, the noise subspace eigenvectors are extracted, and a "needle" space is constructed. Spectrum peak, and finally get the position of the sound source through spectrum peak search. Compared with traditional sound source localization methods, this method makes full use of the high-resolution characteristics of spatial azimuth spectrum estimation and the low computational complexity of dimensionality reduction subspace to achieve fast and accurate sound source loca...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-sound source localization method based on a sph

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