Title :
A fast recursive algorithm for the maximum likelihood estimation of the parameters of a periodic signal
Author :
White, Langford B.
Author_Institution :
Electron. Res. Lab., Defence Sci. and Technol. Org., Salisbury, SA, Australia
fDate :
11/1/1993 12:00:00 AM
Abstract :
Describes a new recursive algorithm for the estimation of the parameters of a periodic signal in additive Gaussian white noise. These parameters are the period, and the complex amplitudes of the harmonics present. The proposed algorithm is based on recursive maximum likelihood (ML) algorithms for incomplete data as described by Titterington (1985) and others. These algorithms are of complexity O(NM), where N is the number of harmonics, and M is the signal length. The performance of the method is compared to that of the extended Kalman filter with the aid of simulations
Keywords :
harmonic analysis; maximum likelihood estimation; parameter estimation; signal processing; white noise; additive Gaussian white noise; algorithm complexity; complex amplitudes; extended Kalman filter; fast recursive algorithm; harmonics; incomplete data; maximum likelihood estimation; parameter estimation; period; periodic signal; recursive maximum likelihood algorithms; signal length; simulations; Amplitude estimation; Australia; Data analysis; Maximum likelihood estimation; Parameter estimation; Power harmonic filters; Recursive estimation; Signal processing algorithms; Statistics; White noise;
Journal_Title :
Signal Processing, IEEE Transactions on
