Tracking and convergence of multi-channel Kalman filters for active noise control

Arthur P. Berkhoff, S. van Ophem

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Abstract

The feed-forward broadband active noise control problem can be formulated as a state estimation problem 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 used 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 implementation was tested in simulations and in real-time experiments. It was found that for a constant primary path the Kalman filter has a fast rate of convergence and is able to track changes in the 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. It is shown that a forgetting factor lower than unity gives a significantly improved tracking performance. Numerical issues of the fast array form of the algorithm for such forgetting factors are discussed and possible solutions are presented.
Original languageEnglish
Title of host publicationProceedings Internoise 2013
Place of PublicationInnsbruck
PublisherINCE
Pages1-10
Publication statusPublished - 15 Sep 2013
Event42nd International Congress and Exposition on Noise Control Engineering, INTERNOISE 2013: Noise Control for Quality of Life - Innsbruck, Austria
Duration: 15 Sep 201318 Sep 2013
Conference number: 42
http://www.internoise2013.com/

Publication series

Namepaper no 0274
PublisherINCE

Conference

Conference42nd International Congress and Exposition on Noise Control Engineering, INTERNOISE 2013
Abbreviated titleINTERNOISE 2013
CountryAustria
CityInnsbruck
Period15/09/1318/09/13
Internet address

Keywords

  • METIS-308939
  • IR-94029

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    Berkhoff, A. P., & van Ophem, S. (2013). Tracking and convergence of multi-channel Kalman filters for active noise control. In Proceedings Internoise 2013 (pp. 1-10). (paper no 0274). Innsbruck: INCE.