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.

A spatial active noise control (ANC) method taking prior information on the approximate direction of primary noise sources into consideration is proposed. ANC aims to cancel incoming primary noise using secondary loudspeakers. Conventional multipoint ANC does not guarantee the reduction of noise between multiple discrete control points; therefore, several attempts have been made to reduce the noise over an entire target region, i.e., by spatial ANC. We have recently proposed a spatial ANC method based on kernel ridge regression for sound field interpolation using distributed microphones and loudspeakers, where the cost function is formulated on the basis of the regional power obtained by kernel interpolation. In this study, we incorporate prior knowledge on the noise source direction into spatial ANC based on the kernel interpolation with directional weighting. Numerical simulation results indicate that the proposed method can achieve larger regional noise reduction than the methods without the information on noise source direction.

A method for feedforward active noise control (ANC) over a spatial region is proposed. Conventional multipoint ANC aims to reduce the noise at multiple discrete positions; therefore, the noise reduction in the region between these points cannot be guaranteed. Recent studies revealed the possibility of spatial ANC, i.e., noise control in a continuous target region. These methods are essentially based on spherical/circular harmonic decomposition of the sound field by using spherical/circular arrays and have mainly been investigated for feedback control under the assumption of periodicity of the noise. We apply a sound field interpolation method based on kernel ridge regression to feedforward spatial ANC to control spatial nonstationary noise using distributed arrays. Numerical simulation results indicated that a large regional noise reduction is achieved by the proposed method compared with feedforward multipoint ANC.