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A virtual sensing method based on plane-wave assumptions for active noise control headrests

Active noise control (ANC) headrests have been studied to suppress cabin noise and achieve a comfortable sound environment in public transportation mobility. To improve the suppression performance at the ear, this system requires virtual sensing technology to estimate sound pressure at the ear from...

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Bibliographic Details
Published in:The Journal of the Acoustical Society of America 2023-10, Vol.154 (4_supplement), p.A122-A122
Main Authors: Yoshimatsu, Toma, Shinobu, Naoki, Itou, Hiroaki, Kozuka, Shihori, Kamado, Noriyoshi, Haneda, Yoichi
Format: Article
Language:English
Online Access:Get full text
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Summary:Active noise control (ANC) headrests have been studied to suppress cabin noise and achieve a comfortable sound environment in public transportation mobility. To improve the suppression performance at the ear, this system requires virtual sensing technology to estimate sound pressure at the ear from microphone observations on the headrest. In this study, we propose a virtual sensing method for ANC headrests based on the assumption that noise arrives as plane-wave. The proposed method assumes that the cross-correlation between the observed signals of two adjacent microphones located on a grid point in space is constant and independent of absolute position. Based on this assumption, the cross-correlation estimated from observations between two microphones far from the ear is used to predict the noise propagation from the microphones near the ear to the ear. When noise reaches the ear first, the estimated cross-correlation becomes non-causal. To address this issue, we propose a method for predicting noise at the ear that involved removing pure delays in the impulse response of primary path estimated from observations of a reference microphone placed near the noise source and a microphone placed far from the ear. The effectiveness of the proposed method is demonstrated by computer simulation.
ISSN:0001-4966
1520-8524
DOI:10.1121/10.0022991