Performance of a multi-channel adaptive Kalman algorithm for active noise control of non-stationary sources
conference paper
Commonly used adaptive algorithms which determine the coefficients of a finite impulse response feed-forward filter in an active noise control application, as the filtered reference least mean squares algorithm, are not performing well when the sound source is non-stationary. A multiple input and multiple output Kalman algorithm potentially has a much better tracking performance, but has a few disadvantages, such as a high calculation complexity and the potential build-up of round-off errors. To overcome these problems a multi-channel Kalman algorithm is presented in fast-array form. The performance of this algorithm was tested in simulations and gives promising results for non-stationary sources, as long as the velocity of the sound source is relatively low. When the sound source has a higher velocity, the Doppler effect plays a significant role on the sound waves, giving a reduction in performance of the algorithm. Also the performance of the Kalman algorithm was validated in a real-time experiment. When the state space equations are rewritten, so the estimated impulse response of the secondary path is equal to a finite impulse response filter, the algorithm shows a comparable rate of convergence in experiments and simulations.
TNO Identifier
478785
Publisher
The Institute of Noise Control Engineering of the USA
Source title
41st International Congress and Exposition on Noise Control Engineering, INTER-NOISE 2012, 19-22 August 2011, New York, NY, USA
Place of publication
Washington,DC
Pages
7780-7790
Files
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