Real time implementation of adaptive line enhancer

ABSTRACT: The contamination of a desired signal by noise (undesired signal) is a main problem encountered in many applications. The digital filters with fixed coefficients exhibit satisfactory performance in cancelling the noise when the desired signal has stationary characteristics. However, when the desired signal has changing characteristics, there may be a performance degradation in eliminating the noise by a digital filter with fixed coefficients. As a remedy to this, adaptive noise cancellation method is used. In the adaptive noise cancellation method, the coefficients of the digital filter are updated by using an adaptive algorithm, until a minimum error is obtained. In this thesis, the principles of adaptive noise cancellation have been studied by using an adaptive line enhancer (ALE) configuration. The ALE configuration is simulated by using Simulink of Matlab and is implemented by using a digital signal processor (TI TMS320C6416T) in real time. The performance of ALE under different signal to noise ratio, number of filter coefficients, and step size of the adaptive algorithm has been studied extensively. When step size is small it leads to a good estimation of the sinusoidal signal, but the convergence speed slows down. The ALE output becomes more accurate when more coefficients are used in the filter. When SNR value is increased the estimation becomes more successful resulting in a small error at the ALE output. Keywords: Adaptive Filters, Adaptive Noise Cancellation, Least Mean Square Algorithm, Adaptive Line Enhancer, Signal to Noise Ratio. …………………………………………………………………………………………………………………………