Parametric spectral moments estimation for wind profiling radar

Parametric spectral moments estimation for wind profiling radar

The purpose of this work is the estimation of Doppler echoes spectral moments. In case of strong overlapping, Fourier-like techniques provide poor results because of the lack of resolution. We propose the use of stochastic maximum-likelihood (SML) and subspace-based methods (WPSF algorithm) for a jo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on geoscience and remote sensing 2003-08, Vol.41 (8), p.1859-1868
Hauptverfasser: Boyer, E., Larzabal, P., Adnet, C., Petitdidier, M.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Applied geophysics
Clutter
Computer simulation
Doppler effect
Doppler radar
Earth sciences
Earth, ocean, space
Estimators
Exact sciences and technology
Frequency estimation
Internal geophysics
Mathematical models
Maximum likelihood estimation
Monte Carlo methods
Performance evaluation
Profiling
Radar scattering
Signal resolution
Spectra
Spectral analysis
Stochastic processes
Testing
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The purpose of this work is the estimation of Doppler echoes spectral moments. In case of strong overlapping, Fourier-like techniques provide poor results because of the lack of resolution. We propose the use of stochastic maximum-likelihood (SML) and subspace-based methods (WPSF algorithm) for a joint estimation of spectral moments. The statistical performances (theoretical and empirical by Monte Carlo simulations) of estimators are compared with the Cramer-Rao lower bound. The results of tests performed on very high frequency (VHF) times series obtained during Thunderstorm, Arecibo, PR during September and October 1998 validate the model and algorithms and confirm the interest of both approaches.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2003.813487