Spatial active noise control based on individual kernel interpolation of primary and secondary sound fields

TL;DR

This paper introduces a novel spatial active noise control method that individually interpolates primary and secondary sound fields using kernel functions, enhancing noise attenuation over a target region with flexible array configurations.

Contribution

It proposes a new kernel interpolation approach for primary and secondary sound fields, improving noise control performance over previous total field methods.

Findings

Outperforms previous total kernel interpolation methods in experiments

Effectively attenuates noise within a target region

Utilizes directional weighting for primary noise sources

Abstract

A spatial active noise control (ANC) method based on the individual kernel interpolation of primary and secondary sound fields is proposed. Spatial ANC is aimed at cancelling unwanted primary noise within a continuous region by using multiple secondary sources and microphones. A method based on the kernel interpolation of a sound field makes it possible to attenuate noise over the target region with flexible array geometry. Furthermore, by using the kernel function with directional weighting, prior information on primary noise source directions can be taken into consideration. However, whereas the sound field to be interpolated is a superposition of primary and secondary sound fields, the directional weight for the primary noise source was applied to the total sound field in previous work; therefore, the performance improvement was limited. We propose a method of individually interpolating the primary and secondary sound fields and formulate a normalized least-mean-square algorithm based on this interpolation method. Experimental results indicate that the proposed method outperforms the method based on total kernel interpolation.