Asymptotically efficient estimation of spectral moments

The article studies parametric estimation of spectral moments of a zero-mean complex Gaussian stationary process immersed in independent Gaussian noise. With the merit of the maximum-likelihood (ML) approach as motivation, this work exploits a Whittle's (1953) type objective function that is ab...

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Bibliographic Details
Published in:IEEE transactions on signal processing 1995-09, Vol.43 (9), p.2222-2225
Main Authors: Dias, J.M.B., Leitao, J.M.N.
Format: Article
Language:English
Subjects:
Applied sciences
Exact sciences and technology
Gaussian noise
Information, signal and communications theory
Maximum likelihood estimation
Meteorological radar
Power measurement
Samarium
Signal and communications theory
Signal representation. Spectral analysis
Signal, noise
State estimation
Telecommunications and information theory
Ultrasonic imaging
Ultrasonic variables measurement
Velocity measurement
Yield estimation
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Summary:The article studies parametric estimation of spectral moments of a zero-mean complex Gaussian stationary process immersed in independent Gaussian noise. With the merit of the maximum-likelihood (ML) approach as motivation, this work exploits a Whittle's (1953) type objective function that is able to capture the relevant features of the log-likelihood function while being much more manageable. The resulting estimates are strongly consistent and asymptotically efficient. As an example, application to Doppler weather radar data is considered.< >
ISSN:1053-587X
1941-0476
DOI:10.1109/78.414791