Spatial Active Noise Control Based On Kernel Interpolation With Directional Weighting

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.