This approach enhances convergence speed and stability in active road noise control using adaptive algorithms and coherence metrics.
Active road noise control (ARNC) is an effective method for mitigating low-frequency noise in vehicle cabins. Previous work introduced a decoupling-whitening frequency domain filtered-error least mean square (DWFDFeLMS) algorithm, which exhibits rapid convergence characteristics for steady-state environments. However, uncorrelated disturbances significantly impact the convergence performance and stability of adaptive algorithms in practical applications. In this paper, a coherence-based robust frequency-dependent variable step size method is proposed to dynamically adjust the step size, using the multichannel coherence coefficients between reference signals and error signals for system stability. Additionally, it is combined with the DWFDFeLMS algorithm for fast convergence speed in ARNC systems. The proposed algorithm ensures fast initial convergence, small steady-state error, and resilience to in-cabin interference. The superiority of this algorithm in terms of convergence speed and stability is confirmed through simulations with measured road noise data and in a real-time ANC system in a car cabin.
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Lian et al. (2025) studied this question.
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