Performance of a multi-channel adaptive Kalman algorithm for active noise control of non-stationary sources

摘要

Commonly used adaptive algorithms which determine the coefficients of a finite impulseresponse feed-forward filter in an active noise control application, as the filtered referenceleast mean squares algorithm, are not performing well when the sound source is nonstationary.A multiple input and multiple output Kalman algorithm potentially has a muchbetter tracking performance, but has a few disadvantages, such as a high calculationcomplexity and the potential build-up of round-off errors. To overcome these problems amulti-channel Kalman algorithm is presented in fast-array form. The performance of thisalgorithm 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 ahigher velocity, the Doppler effect plays a significant role on the sound waves, giving areduction in performance of the algorithm. Also the performance of the Kalman algorithmwas validated in a real-time experiment. When the state space equations are rewritten, sothe estimated impulse response of the secondary path is equal to a finite impulse responsefilter, the algorithm shows a comparable rate of convergence in experiments andsimulations.