Conditional mean and maximum likelihood approaches to multiharmonic frequency estimation

Author

James, Ben ; Anderson, Brian D O ; Williamson, Robert C.

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK

Volume

42

Issue

6

fYear

1994

fDate

6/1/1994 12:00:00 AM

Firstpage

1366

Lastpage

1375

Abstract

The performance of an extended Kalman filter (EKF) applied to the problem of estimating the (assumed constant) parameters (fundamental frequency, harmonic phases, and amplitudes) of a complex multiharmonic signal measured in noise is shown to be asymptotically (i.e., as the number of measurements tends to infinity) efficient. The Cramer-Rao (CR) bounds associated with the estimation problem are derived for the case where the measurements commence at an arbitrary time distinct from zero

Keywords

Kalman filters; filtering and prediction theory; maximum likelihood estimation; parameter estimation; signal processing; Cramer-Rao bounds; amplitudes; complex multiharmonic signal; conditional mean; extended Kalman filter; fundamental frequency; harmonic phases; maximum likelihood approaches; multiharmonic frequency estimation; performance; Amplitude estimation; Frequency estimation; Frequency measurement; Maximum likelihood estimation; Noise level; Noise measurement; Phase estimation; Phase measurement; Phase noise; Power harmonic filters;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.286953

Filename

286953