Spatial Active Noise Control Based on Kernel Interpolation of Sound Field

Shoichi Koyama,Jesper Brunnstrom,Natsuki Ueno,Hiroshi Saruwatari,Hayato Ito

doi:10.1109/taslp.2021.3107983

Shoichi Koyama, Jesper Brunnstrom + Show 3 more

Open Access

https://doi.org/10.1109/taslp.2021.3107983

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Abstract

An active noise control (ANC) method to reduce noise over a region in space based on kernel interpolation of sound field is proposed. Current methods of spatial ANC are largely based on spherical or circular harmonic expansion of the sound field, where the geometry of the error microphone array is restricted to a simple one such as a sphere or circle. We instead apply the kernel interpolation method, which allows for the estimation of a sound field in a continuous region with flexible array configurations. The interpolation scheme is used to derive adaptive filtering algorithms for minimizing the acoustic potential energy inside a target region. A practical time-domain algorithm is also developed together with its computationally efficient block-based equivalent. We conduct experiments to investigate the achievable level of noise reduction in a two-dimensional free space, as well as adaptive broadband noise control in a three-dimensional reverberant space. The experimental results indicated that the proposed method outperforms the multipoint-pressure-control-based method in terms of regional noise reduction.

Highlights

T HE aim of active noise control (ANC) or active noise cancellation is to suppress unwanted noise by generating antinoise with secondary sources, i.e., loudspeakers
We propose a spatial ANC approach based on the kernel interpolation of a sound field
We proposed a spatial ANC method based on kernel interpolation for the suppression of noise inside a continuous region

Summary

Introduction

T HE aim of active noise control (ANC) or active noise cancellation is to suppress unwanted noise by generating antinoise with secondary sources, i.e., loudspeakers. ANC techniques have been extensively investigated [1]–[4] along with their practical applicability, especially for canceling lowfrequency noise [5]–[8]. Achieving effective ANC over a three-dimensional (3D) space generally requires multiple microphones and loudspeakers to capture and synthesize a 3D sound field. Adaptive filters are typically used to minimize the cost function, which in conventional multipoint pressure control is defined as the power of the residual noise signals captured by error microphones [3], [9]. The associate editor coordinating the review of this manuscript and approving it for publication was Prof.

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