A Multi-Noise Multi-Channel ANC System using Relative Transfer Matrix-Based Approach

Remote microphone-based virtual sensing (RM-VS) methods are used in active noise control (ANC) systems to avoid the physical presence of microphones inside the region of interest (ROI). Conventionally, this is achieved by estimating an observation filter to obtain the primary noise signals at virtual microphones inside the ROI, with the physical microphones recording outside the ROI. In this paper, we present a novel structure of the RM technique, where we estimate the relative transfer matrix (ReTM) between the signals at virtual microphones and physical microphones with both noise sources and secondary sources active. This ReTM can be directly applied to the recorded residual error signals during noise control, as opposed to the conventional observation filter which is typically applied to the estimated primary noise signals. Simulation results show that the proposed ReTM-based approach achieves similar performance to the conventional RM method in a stationary environment, while being more robust to changes in the secondary paths.

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Published
2024-09-09
DOI
https://doi.org/10.1109/iwaenc61483.2024.10694679
Citations
1
Primary Topic
Advanced Adaptive Filtering Techniques
Type
article
Field-Weighted Citation Impact
0.37

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article

A Multi-Noise Multi-Channel ANC System using Relative Transfer Matrix-Based Approach

Thushara D. Abhayapala, Prasanga N. Samarasinghe, Amy Bastine, Huiyuan Sun et al.
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Advanced Adaptive Filtering Techniques
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article

A Multi-Noise Multi-Channel ANC System using Relative Transfer Matrix-Based Approach

Thushara D. Abhayapala, Prasanga N. Samarasinghe, Amy Bastine, Huiyuan Sun, Yile Angela Zhang
article en
1 citations

Abstract

Remote microphone-based virtual sensing (RM-VS) methods are used in active noise control (ANC) systems to avoid the physical presence of microphones inside the region of interest (ROI). Conventionally, this is achieved by estimating an observation filter to obtain the primary noise signals at virtual microphones inside the ROI, with the physical microphones recording outside the ROI. In this paper, we present a novel structure of the RM technique, where we estimate the relative transfer matrix (ReTM) between the signals at virtual microphones and physical microphones with both noise sources and secondary sources active. This ReTM can be directly applied to the recorded residual error signals during noise control, as opposed to the conventional observation filter which is typically applied to the estimated primary noise signals. Simulation results show that the proposed ReTM-based approach achieves similar performance to the conventional RM method in a stationary environment, while being more robust to changes in the secondary paths.

Australian National University (AU)
Australian Government
Openalex Percentile: Top 43%
Advanced Adaptive Filtering Techniques
0.37
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