Active noise control of noisy periodic signals using signal separation

Abstract

Periodic signals (since they can be easily predicted) can be canceled much more effectively when compared to non- periodic/stochastic signals. A large class of acoustic noise sources have an underlying periodic process that generates a periodic noise component, and thus the acoustic noise can in general be modeled as the sum of a periodic signal and a random signal (usually a background noise). In this paper we present the idea that separating the acoustic noise into periodic and random noise components and doing separate active noise control(ANC) for each tends to increase the over-all noise attenuation level (NAL). Formulae for the exact improvement in noise attenuation levels are derived. A novel signal separation and noise cancelation scheme based on adaptive filtering is developed and its effectiveness is shown for several periodic signal in white noise cases.