New Signal Processing Methods for Single-Channel Feedforward Active Noise Control Systems

摘要

This thesis is a study of active noise control (ANC) systems with the viewpoint of adaptive signal processing. We have proposed new signal processing methods to improve the performance of active noise control systems. We combine the concepts of the FxLMS algorithm and adaptive filtering with averaging, and propose a new algorithm (FxAFA, filtered-x adaptive filtering with averaging, algorithm) for ANC systems. The proposed algorithm outperforms the conventional FxLMS based ANC systems under the situation of large measurement noise. The effectiveness of the proposed algorithm in ANC systems with online secondary path modeling is also demonstrated. This thesis also proposes a new variable step size (VSS) LMS algorithm for online secondary path modeling in ANC systems. Here the step size is varied in accordance with the power of the disturbance signal in the desired response of the modeling filter. The basic idea of the proposed VSS stems from the fact that the disturbance signal, in the desired response of the modeling filter, is decreasing in nature (ideally) converging to zero. Hence a small step size is used initially and later its value is increased accordingly. Extensive computer simulations are carried out to demonstrate the effectiveness of the methods proposed in this thesis.