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 impulsernresponse feed-forward filter in an active noise control application, as the filtered referencernleast mean squares algorithm, are not performing well when the sound source is nonstationary.rnA multiple input and multiple output Kalman algorithm potentially has a muchrnbetter tracking performance, but has a few disadvantages, such as a high calculationrncomplexity and the potential build-up of round-off errors. To overcome these problems arnmulti-channel Kalman algorithm is presented in fast-array form. The performance of thisrnalgorithm was tested in simulations and gives promising results for non-stationary sources,rnas long as the velocity of the sound source is relatively low. When the sound source has arnhigher velocity, the Doppler effect plays a significant role on the sound waves, giving arnreduction in performance of the algorithm. Also the performance of the Kalman algorithmrnwas validated in a real-time experiment. When the state space equations are rewritten, sornthe estimated impulse response of the secondary path is equal to a finite impulse responsernfilter, the algorithm shows a comparable rate of convergence in experiments andrnsimulations.