Adaptive Noise Cancellation in Sinusoidal Signal Using Weiner Filter

Abstract

This Project involves the study of the principles of Adaptive Noise Cancellation and its Application. Adaptive noise Cancellation is an alternative technique of estimating signals corrupted by additive noise or interference. Its advantage lies in that, with no apriori estimates of signal or noise, levels of noise rejection are attainable that would be difficult or impossible to achieve by other signal processing methods of removing noise. ANC needs two inputs - a primary input containing the corrupted signal and a reference input containing noise correlated in some unknown way with the primary noise. The reference input is adaptively filtered and subtracted from the primary input to obtain the signal estimate. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time-variable. The effect of uncorrelated noises in primary and reference inputs and presence of signal components in the reference input on the ANC performance is investigated. It is shown that in the absence of uncorrelated noises and when the reference is free of signal; noise in the primary input can be essentially eliminated without signal distortion. Computer simulations for all cases are carried out using Matlab software and experimental results are presented that illustrate the usefulness of Adaptive Noise Canceling Technique.