Acoustic source localization using the open spherical microphone array in the low-frequency range

Boquan Yang,Shengguo Shi,Desen Yang,V Goussev,J Yin

doi:10.1051/matecconf/201928304001

Abstract

Recently, spherical microphone arrays (SMA) have become increasingly significant for source localization and identification in three dimension due to its spherical symmetry. However, conventional Spherical Harmonic Beamforming (SHB) based on SMA has limitations, such as poor resolution and high side-lobe levels in image maps. To overcome these limitations, this paper employs the iterative generalized inverse beamforming algorithm with a virtual extrapolated open spherical microphone array. The sidelobes can be suppressed and the main-lobe can be narrowed by introducing the two iteration processes into the generalized inverse beamforming (GIB) algorithm. The instability caused by uncertainties in actual measurements, such as measurement noise and configuration problems in the process of GIB, can be minimized by iteratively redefining the form of regularization matrix and the corresponding GIB localization results. In addition, the poor performance of microphone arrays in the low-frequency range due to the array aperture can be improved by using a virtual extrapolated open spherical array (EA), which has a larger array aperture. The virtual array is obtained by a kind of data preprocessing method through the regularization matrix algorithm. Both results from simulations and experiments show the feasibility and accuracy of the method.

Highlights

Over the last two decades, spherical microphone arrays have been variously applied to localize and identify aeroacoustics source in 3D sound field [1,2,9] due to the directivity of the whole space and the flexibility of 3D beam pattern synthesis [3,4,5]
To improve the spatial resolution and to suppress the disturbing sidelobes, Suzuki proposed the generalized inverse beamforming (GIB) [7,12,13], achieving higher computational efficiency and localization accuracy compared with conventional beamforming approaches
The first iteration: The regularization matrix L can be redefined by the solution of generalized inverse beamforming [13]

Summary

Introduction

Over the last two decades, spherical microphone arrays have been variously applied to localize and identify aeroacoustics source in 3D sound field [1,2,9] due to the directivity of the whole space and the flexibility of 3D beam pattern synthesis [3,4,5]. To improve the spatial resolution and to suppress the disturbing sidelobes, Suzuki proposed the generalized inverse beamforming (GIB) [7,12,13], achieving higher computational efficiency and localization accuracy compared with conventional beamforming approaches. The GIB algorithm is not effective in the low-frequency range because of physical and practical limitations, such as the number of microphone sensors and the aperture of the array in the acquisition system. In order to solve the problem mentioned above, this paper utilizes the double iteration generalized inverse beamforming (DI-GIB) and a novel kind of spherical array extrapolation method.

Array extrapolated using open spherical arrays

Iterative generalized inverse beamforming method

Simulation examples

Double source

Findings

Conclusions