NONPARAMETRIC ESTIMATION OF MEAN
DOPPLER AND SPECTRAL WIDTHy
Jose M. B. Diasz, Member, IEEE and Jose M. N. Leit~ao, Member, IEEE
Instituto de Telecomunicac~oes, and
Departamento de Engenharia Electrotecnica e de Computadores.
Instituto Superior Tecnico
1049-001 Lisboa, PORTUGAL.
Email:[email protected] Phone: +351 1 8418466 Fax: +351 1 8418472
February 25, 1998
Abstract
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 (rst moment)
and to the spectral width (square root of the second spectral centered moment). By assuming
that the power spectral density of the underlying process is bandlimited, the maximum likelihood
estimates of its spectral moments are derived. A suboptimal estimate based on the sample
covariances is also studied. Both methods are robust in the sense that they do not rely on
any assumption concerning the power spectral density (besides being bandlimited). Under
weak conditions, the set of estimates based on sample covariances are unbiased and strongly
consistent. Compared with the classical pulse pair and the periodogram based estimates, 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.
Refererence [1] is a short version of this work.
This work was supported by Portuguese PRAXIS XXI program, under project 2/2.1.TIT/1580/95.
z Corresponding Author.
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1