Brief paper: Frequency domain maximum likelihood estimation of linear dynamic errors-in-variables models

Authors:
R. Pintelon;J. Schoukens
Affiliations:
Department ELEC, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium;Department ELEC, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
Venue:
Automatica (Journal of IFAC)
Year:
2007

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Abstract

This paper studies the linear dynamic errors-in-variables problem for filtered white noise excitations. First, a frequency domain Gaussian maximum likelihood (ML) estimator is constructed that can handle discrete-time as well as continuous-time models on (a) part(s) of the unit circle or imaginary axis. Next, the ML estimates are calculated via a computationally simple and numerically stable Gauss-Newton minimization scheme. Finally, the Cramer-Rao lower bound is derived.