2009•The Journal of the Acoustical Society of AmericaRequires access

Spherical harmonic beamforming for room acoustic analysis.

Gary W. Elko, Jens M. Meyer

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Abstract

We describe the potential of using a spherical beamforming microphone array to investigate the spatial correlation of sound fields in rooms. We are building spherical microphone arrays consisting of many acoustic pressure sensors mounted appropriately on the surface of a rigid sphere. Our associated spherical eigenbeamformer decomposes the sound-field into spatially orthonormal spherical harmonics up to third-order. We refer to the signals from the eigenbeamformer as eigenbeams. All eigenbeams have phase centers at the physical center of the array. Due to the orthonormal property of the eigenbeamformer, a diffuse field ideally results in zero correlation between the eigenbeams. Therefore, by measuring the cross-correlation between the eigenbeam signals, one can investigate the proximity to the isotropy (or “diffuseness”) of the sound-field. Simultaneously, the underlying eigen-beam patterns can be steered without effecting the orthonormality property. How the cross-correlation function changes with general orientation of the eigenbeams is another potential measure for sound field diffuseness in rooms. We will show some real room measurements demonstrating the potential usefulness of this approach.

About this research paper

What this paper is about

We describe the potential of using a spherical beamforming microphone array to investigate the spatial correlation of sound fields in rooms. We are building spherical microphone arrays consisting of many acoustic pressure sensors mounted appropriately on the surface of a rigid sphere. Our associated spherical eigenbeamformer decomposes the sound-field into spatially orthonormal spherical harmonics up to third-order. We refer to the signals from the eigenbeamformer as eigenbeams. All eigenbeams have phase centers at the physical center of the array. Due to the orthonormal property of the eigenbeamformer, a diffuse field ideally results in zero correlation between the eigenbeams. Therefore, by measuring the cross-correlation between the eigenbeam signals, one can investigate the proximity to the isotropy (or “diffuseness”) of the sound-field. Simultaneously, the underlying eigen-beam patterns can be steered without effecting the orthonormality property. How the cross-correlation function changes with general orientation of the eigenbeams is another potential measure for sound field diffuseness in rooms. We will show some real room measurements demonstrating the potential usefulness of this approach.

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Available abstract

We describe the potential of using a spherical beamforming microphone array to investigate the spatial correlation of sound fields in rooms. We are building spherical microphone arrays consisting of many acoustic pressure sensors mounted appropriately on the surface of a rigid sphere. Our associated spherical eigenbeamformer decomposes the sound-field into spatially orthonormal spherical harmonics up to third-order. We refer to the signals from the eigenbeamformer as eigenbeams. All eigenbeams have phase centers at the physical center of the array. Due to the orthonormal property of the eigenbeamformer, a diffuse field ideally results in zero correlation between the eigenbeams. Therefore, by measuring the cross-correlation between the eigenbeam signals, one can investigate the proximity to the isotropy (or “diffuseness”) of the sound-field. Simultaneously, the underlying eigen-beam patterns can be steered without effecting the orthonormality property. How the cross-correlation function changes with general orientation of the eigenbeams is another potential measure for sound field diffuseness in rooms. We will show some real room measurements demonstrating the potential usefulness of this approach.

Key concepts: Spherical harmonics, Acoustics, Microphone array, Beamforming, Microphone, Ambisonics, Isotropy, Orthonormal basis

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Spherical harmonic beamforming for room acoustic analysis. — Research Paper | ScholarLens