An adaptive signal parameter estimation technique using quadratic polynomial signal model and Least square techniques

Abstract

This paper proposes a new modified approach using Least square algorithm associated with a ridge regression factor and Taylor expansion for estimation of fundamental frequency and phasor of the fundamental frequency component with time varying envelope. The signal considered comprises of decaying dc component and fundamental frequency component which are expressed in terms of Taylor coefficients upto second order. The modified Least square technique is then used to estimate the Taylor coefficients using which the time varying amplitude, phase, fundamental frequency and dc component can be accurately evaluated. This approach shows excellent tracking capability of the signal parameters of a time variant sinusoidal signal even under extreme noise conditions with low SNR value.