Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/169092
Title: Real-time modelling of observation filter in the remote microphone technique for an active noise control application
Authors: Lai, Chung Kwan
Lam, Bhan
Shi, Dongyuan
Gan, Woon-Seng 
Keywords: Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2023
Source: Lai, C. K., Lam, B., Shi, D. & Gan, W. (2023). Real-time modelling of observation filter in the remote microphone technique for an active noise control application. 2023 IEEE International Conference On Acoustics, Speech and Signal Processing (ICASSP 2023). https://dx.doi.org/10.1109/icassp49357.2023.10095752
Project: COT-V4-2019-1 
Conference: 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023)
Abstract: The remote microphone technique (RMT) is often used in active noise control (ANC) applications to overcome design constraints in microphone placements by estimating the acoustic pressure at inconvenient locations using a pre-calibrated observation filter (OF), albeit limited to stationary primary acoustic fields. While the OF estimation in varying primary fields can be significantly improved through the recently proposed source decomposition technique, it requires knowledge of the relative source strengths between incoherent primary noise sources. This paper proposes a method for combining the RMT with a new source-localization technique to estimate the source ratio parameter. Unlike traditional source-localization techniques, the proposed method is capable of being implemented in a real-time RMT application. Simulations with measured responses from an open-aperture ANC application showed a good estimation of the source ratio parameter, which allows the observation filter to be modelled in real-time.
URI: https://hdl.handle.net/10356/169092
ISBN: 978-1-7281-6327-7
DOI: 10.1109/icassp49357.2023.10095752
Schools: School of Electrical and Electronic Engineering 
Rights: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/ICASSP49357.2023.10095752.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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