Abstract

Spherical harmonic analysis has been a widely used approach for spatial audio processing in recent years. Among all applications that benefit from spatial processing, spatial Active Noise Control (ANC) remains unique with its requirement for open spherical microphone arrays to record the residual sound field throughout the continuous region. Ideally, a low delay spherical harmonic recording algorithm for open spherical microphone arrays is desired for real-time spatial ANC systems. Currently, frequency domain algorithms for spherical harmonic decomposition of microphone array recordings are applied in a spatial ANC system. However, a Short Time Fourier Transform is required, which introduces undesirable system delay for ANC systems. In this paper, we develop a time domain spherical harmonic decomposition algorithm for the application of spatial audio recording mainly with benefit to ANC with an open spherical microphone array. Microphone signals are processed by a series of pre-designed finite impulse response (FIR) filters to obtain a set of time domain spherical harmonic coefficients. The time domain coefficients contain the continuous spatial information of the residual sound field. We corroborate the time domain algorithm with a numerical simulation of a fourth order system, and show the proposed method to have lower delay than existing approaches.

Highlights

  • Spherical harmonic analysis has been widely used for spatial acoustic signal processing for years [1]

  • We propose a finite impulse response (FIR) filter based time domain spherical harmonic analysis method to accurately record spatial sound fields with an open spherical microphone array for the purpose of spatial Active Noise Control (ANC)

  • While the frequency domain spatial sound field capture is well established as explained in Section 2.1, in this paper, our objective is to investigate the possibility of an analogous spherical harmonic analysis in time domain

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Summary

Introduction

Spherical harmonic analysis has been widely used for spatial acoustic signal processing for years [1]. The spherical harmonic decomposition has the advantage that a given sound field can be analyzed over a continuous spatial region rather than a set of distributed points [4]. This has embraced a wide range of algorithms in three-dimensional (3D) audio signal processing such as: sound intensity analysis [5], sound field diffusive analysis [6], beamforming [7,8], source localization [9,10], and spatial Active Noise Control (ANC) [11,12]. Multiple microphones are used to record the residual noise, and multiple loudspeakers are used to generate the anti-noise field

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