Adaptive signal enhancement by a robust TLS estimation

Abstract

An adaptive enhancement algorithm of signal disturbed by the impulse noise and the white Gaussian noise is proposed in this report. If the strong dependence between a signal enhancement and a needed-parameter estimation exists in an algorithm, it is difficult to reduce a large bias occurring in the first estimation. To weaken their relationship, the introduction of a total least squares (TLS) algorithm that estimates the model parameters directly from the disturbed signals is considered. However, the TLS estimation accuracy is dramatically deteriorated by the impulse noise, even if the TLS estimation accuracy is held to the non-Gaussian noise in some degree. Hence, we ensure the robustness of the algorithm by replacing a high amplitude signal with an estimated value based on a likelihood ratio test. Using these signals, we develop, an algorithm based on the TLS and the EM algorithm for enhancing the disturbed signal. We also show the effectiveness of the proposed algorithm through computer simulations.