A Synchronized Filter-s Least Mean Square (SFsLMS) algorithm for multi-channel ANC in aviation noise suppression

Abstract

This paper presents a synchronized Filtered-s Least Mean Squares (SFsLMS) algorithm for multichannel Active Noise Control (ANC) systems aimed at mitigating aviation noise. The SFsLMS algorithm addresses signal delays inherent in aircraft environments, which degrade the performance of traditional ANC algorithms. Incorporating delay estimation into the adaptive filtering process ensures accurate alignment of input and reference signals, leading to improved convergence speed and stability. The results demonstrate that the SFsLMS algorithm significantly enhances noise cancellation performance in dynamic aviation noise conditions, offering a scalable and robust solution for real-time noise reduction in enclosed areas near airports. This advancement contributes to increased comfort and reduced noise pollution, highlighting the algorithm's potential for widespread application in aviation noise control systems. The evaluation is conducted using a $(2\times 4\times 4)$ (ANC) system, with performance measured in terms of Averaged Noise Reduction (ANR). The results reveal a marked improvement in convergence speed and stability, as demonstrated by the rapid decrease and sustained low levels of ANR across all microphones.