Harmonic signal modeling using adaptive nonlinear function estimation

• It is well-known that sine waves produce harmonic overtones when passed through static nonlinear functions. This paper describes a new algorithm where an arbitrary periodic signal is estimated recursively. The estimated signal model is typically parameterised as a real sine wave with unknown frequency in cascade with a piecewise linear function. A recursive Gauss-Newton prediction error identification algorithm for joint estimation of the driving frequency and the parameters of the nonlinear output function can then be derived. The approach handles colored measurement disturbances and gives a direct measure of the size of the nonlinearity that corresponds to the harmonic spectrum. The Cramer-Rao bound (CRB) is also calculated in the paper

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

Cramer-Rao bound;adaptive nonlinear function estimation;arbitrary periodic signal;colored measurement disturbances;driving frequency;harmonic overtones;harmonic signal modeling;harmonic spectrum;nonlinear output function;piecewise linear function;recursive Gauss-Newton prediction error identification algorithm ;recursive estimation;sine waves;static nonlinear functions;adaptive estimation;error analysis;frequency estimation;harmonic analysis;identification;piecewise-linear techniques;prediction theory;recursive estimation;spectral analysis

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