Abstract
In this paper a Kalman filter fitted in the feedback active noise control system is derived for suppressing duct noise. The secondary path of a duct noise system is modeled by an IIR filter, whereas the controller filter is modeled by an FIR filter. The secondary path dynamics is obtained by an off-line system identification technique. The controller FIR filter is tuned on-line by the developed Kalman algorithm. Computer simulations show that Kalman algorithm outperforms the FXLMS algorithm in minimizing the duct noise, especially for white noise. To verify the effectiveness of the Kalman algorithm, experiments are conducted for duct noise suppression. A TI TMS320C6713 DSP is used for implementing the complex Kalman algorithm. While the Kalman algorithm and the FXLMS algorithm may have comparable performance is reducing pure-tone duct noise, noises with two-tone or more (even the narrowband white noise) can be shown experimentally to be reduced more by using the Kalman algorithm than the FXLMS algorithm. The experiment results indicated that up to 30dB and 20dB reductions was measured for two-tone and three-tone noise by using the Kalman algorithm, respectively, while a 6.8dB reduction is observed for a 200-300 narrowband white noise.
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