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Multichannel active noise control for spatially sparse noise fields
Jihui Zhang1, Thushara D Abhayapala2, Prasanga N Samarasinghe2
1School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin Heilongjiang 150001, China jihui.zhang@anu.edu.au.
The Journal of the Acoustical Society of America
|January 2, 2017
Summary
This study introduces a new active noise control (ANC) method for sparse noise fields. It uses l1-norm regularization to efficiently cancel noise with fewer secondary sources.
Area of Science:
- Acoustics
- Signal Processing
- Control Engineering
Background:
- Multi-channel active noise control (ANC) is effective for low-frequency noise in 3D space.
- Existing methods may be inefficient for sparsely distributed noise sources.
Purpose of the Study:
- To develop an efficient ANC controller for sparse noise fields.
- To reduce the number of active secondary sources required for noise cancellation.
Main Methods:
- Developed a novel ANC controller incorporating l1-norm regularization on signal magnitude.
- Designed anti-noise signals to minimize residual errors and penalize inactive secondary sources.
- Proposed adaptive algorithms with reduced computational complexity and improved convergence.
Main Results:
- The proposed controller activates only secondary sources near sparse noise sources.
- Achieved efficient cancellation of sparse low-frequency noise fields.
- Demonstrated adaptive algorithms with low computational load and faster convergence.
Conclusions:
- The l1-norm regularized ANC controller is effective for sparse noise fields.
- The method offers a computationally efficient and faster converging solution for noise attenuation.
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