Multi-channel Kalman filters for active noise control
Multi-channel Kalman filters for active noise control
By formulating the feed-forward broadband active noise control problem as a state estimation problem it is possible to achieve a faster rate of convergence than the filtered reference least mean squares algorithm and possibly also a better tracking performance. A multiple input/multiple output Kalman algorithm is derived to perform this state estimation. To make the algorithm more suitable for real-time applications, the Kalman filter is written in a fast array form and the secondary path state matrices are implemented in output normal form. The resulting filter implementation is tested in simulations and in real-time experiments. It was found that for a constant primary path the filter has a fast rate of convergence and is able to track changes in the frequency spectrum. For a forgetting factor equal to unity the system is robust but the filter is unable to track rapid changes in the primary path. A forgetting factor lower than 1 gives a significantly improved tracking performance but leads to a numerical instability for the fast array form of the algorithm.
active noise control, Kalman filters, moving sound source, round-off errors, Science & Technology, Technology, Life Sciences & Biomedicine, Acoustics, Audiology & Speech-Language Pathology, Algorithms, Computer Simulation, Doppler Effect, Least-Squares Analysis, Motion, Noise, Transportation, Pressure, Reproducibility of Results, Signal Processing, Computer-Assisted, Signal-To-Noise Ratio, Sound, Sound Spectrography, Time Factors
2105-2115
van Ophem, S.
bb3fb37e-577b-4152-86bc-2248943f882d
Berkhoff, A.P.
42d2587c-a84a-42fb-a7d4-cb78bc2f62a4
3 April 2013
van Ophem, S.
bb3fb37e-577b-4152-86bc-2248943f882d
Berkhoff, A.P.
42d2587c-a84a-42fb-a7d4-cb78bc2f62a4
van Ophem, S. and Berkhoff, A.P.
(2013)
Multi-channel Kalman filters for active noise control.
Journal of the Acoustical Society of America, 133 (4), .
(doi:10.1121/1.4792646).
Abstract
By formulating the feed-forward broadband active noise control problem as a state estimation problem it is possible to achieve a faster rate of convergence than the filtered reference least mean squares algorithm and possibly also a better tracking performance. A multiple input/multiple output Kalman algorithm is derived to perform this state estimation. To make the algorithm more suitable for real-time applications, the Kalman filter is written in a fast array form and the secondary path state matrices are implemented in output normal form. The resulting filter implementation is tested in simulations and in real-time experiments. It was found that for a constant primary path the filter has a fast rate of convergence and is able to track changes in the frequency spectrum. For a forgetting factor equal to unity the system is robust but the filter is unable to track rapid changes in the primary path. A forgetting factor lower than 1 gives a significantly improved tracking performance but leads to a numerical instability for the fast array form of the algorithm.
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More information
Accepted/In Press date: 5 February 2013
Published date: 3 April 2013
Keywords:
active noise control, Kalman filters, moving sound source, round-off errors, Science & Technology, Technology, Life Sciences & Biomedicine, Acoustics, Audiology & Speech-Language Pathology, Algorithms, Computer Simulation, Doppler Effect, Least-Squares Analysis, Motion, Noise, Transportation, Pressure, Reproducibility of Results, Signal Processing, Computer-Assisted, Signal-To-Noise Ratio, Sound, Sound Spectrography, Time Factors
Identifiers
Local EPrints ID: 494866
URI: http://eprints.soton.ac.uk/id/eprint/494866
ISSN: 1520-8524
PURE UUID: dd094e63-64c4-4c26-bd0c-bb9c5a34c675
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Date deposited: 18 Oct 2024 16:32
Last modified: 19 Oct 2024 02:13
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Author:
S. van Ophem
Author:
A.P. Berkhoff
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