Distributed Active Noise Control Robust to Impulsive Interference

Traditional centralized and distributed active noise control (ANC) algorithms, which are based on the minimum mean-square error (MMSE) criterion, manifest substantial efficacy diminution when exposed to impulsive noise. To mitigate this challenge, we propose a novel diffusion filtered-x least mean M-estimate (DFxLMM) algorithm be used for sensor network-based multichannel ANC systems, which adaptively adjusts the threshold parameter in accordance with estimated variance of error signal, thereby effectively improving the resilience of the algorithm against impulsive noise perturbations. Moreover, to attain expeditious convergence and minimal steady-state misalignment, the implementation of a variable step-size DFxLMM (VSS-DFxLMM) algorithm is also proposed. In addition, an analytical discourse on the mean and mean-square behavior of the DFxLMM algorithm is presented. Simulation results demonstrate that the algorithms proffered herein outperform existing techniques in noise reduction efficacy for various types of noise under impulsive noise interference.