Nonparametric estimation of mean Doppler and spectral width

This paper proposes a new nonparametric method for estimation of spectral moments of a zero-mean Gaussian process immersed in additive white Gaussian noise. Although the technique is valid for any order moment, particular attention is given to the mean Doppler (first moment) and to the spectral widt...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2000-01, Vol.38 (1), p.271-282
Main Authors: Dias, J.M.B., Leitao, J.M.N.
Format: Article
Language:English
Subjects:
Applied geophysics
Biomedical imaging
Covariance
Doppler
Doppler effect
Earth sciences
Earth, ocean, space
Estimates
Exact sciences and technology
Frequency measurement
Gaussian processes
Internal geophysics
Maximum likelihood estimation
Meteorological radar
Pollution measurement
Power measurement
Samples
Spectra
Statistical analysis
Statistical methods
Studies
Ultrasonic imaging
Velocity measurement
Wind
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Summary:This paper proposes a new nonparametric method for estimation of spectral moments of a zero-mean Gaussian process immersed in additive white Gaussian noise. Although the technique is valid for any order moment, particular attention is given to the mean Doppler (first moment) and to the spectral width (square root of the centered second spectral moment). By assuming that the power spectral density (PSD) of the underlying process is bandlimited, the maximum-likelihood estimates of its spectral moments are derived. A suboptimal estimate based on the sample covariance is also studied. Both methods are robust in the sense that they do not rely on any assumption concerning the PSD (besides being bandlimited). Under weak conditions, the set of estimates based on sample covariance is unbiased and strongly consistent. Compared with the classical pulse pair and the periodogram-based estimators, the proposed methods exhibit better statistical properties for asymmetric spectra and/or spectra with large spectral widths, while involving a computational burden of the same order.
ISSN:0196-2892
1558-0644
DOI:10.1109/36.823919