A nonlinear approach to harmonic signal modeling

Authors:
Emad Abd-Elrady
Affiliations:
Systems and Control, Department of Information Technology, Uppsala University, P.O. Box 337, SE-751 05 Uppsala, Sweden
Venue:
Signal Processing
Year:
2004

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Abstract

Periodic signals can be estimated recursively by exploiting the fact that a sine wave passing through a static nonlinear function generates a spectrum of overtones. A real wave with unknown period in cascade with a piecewise linear function is thefefore used as a parameterization for the estimated signal model. In this paper the driving periodic wave can be chosen depending on any prior knowledge. A recursive Gauss-Newton prediction error identification algorithm for joint estimation of the driving frequency and the parameters of the nonlinear output function is introduced. Local convergence properties as well as the Cramér-Rao bound (CRB) are derived for the suggested algorithm.