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Description
This paper proposes a strategy for an FxLMS-based automotive active road noise control (ARNC) that accounts for redundancy among reference signals and is suitable for application in production vehicles. Usually, multiple reference signals of vehicles with ARNC system are measured by accelerometers mounted at each wheel hub. However, due to the structural characteristics of vehicles, these reference signals are often strongly correlated with each other, and the increased number of references does not necessarily yield proportional improvements in noise attenuation performance, while raising computational load as well as requiring additional memory resources. The proposed method evaluates independent contribution of each candidate reference signal across the operating frequency band and progressively selects the subset that maximizes noise attenuation potential among all reference signals, while excluding reference signal channels whose contribution is already explained by the selected subset, which are redundant signals. Real-vehicle experiments demonstrate that comparable noise attenuation performance is achieved with a reduced number of reference signals, even with significantly reducing computational load and memory resource consumed.