1997
DOI: 10.1029/97rs00250
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Statistical characteristics of the noise power spectral density in UHF and VHF wind profilers

Abstract: Abstract. In the first part of the paper, from a large set of spectrum data, obtained with the UHF/VHF (INSU/METEO) radars during the FRONTS87 and PYREX experiments, statistical characteristics of the noise power spectral density and behavior of its mean are pointed out. For each range gate and various sets of number of coherent and incoherent integrations, histograms of the noise power spectral density are computed using data from different parts of the campaign. The probability density function, so computed,… Show more

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Cited by 28 publications
(19 citation statements)
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“…However, a recent study argues that this approach can overestimate the radar noise power and so is not appropriate for solid-state cloud radars. In contrast, a segmental approach reported by Petitdidier et al can achieve better accuracy and stability [29,32]. So, in this study, a simple 8-segment technology Remote Sens.…”
Section: Data Processing Of Cloud Radar Doppler Spectramentioning
confidence: 97%
“…However, a recent study argues that this approach can overestimate the radar noise power and so is not appropriate for solid-state cloud radars. In contrast, a segmental approach reported by Petitdidier et al can achieve better accuracy and stability [29,32]. So, in this study, a simple 8-segment technology Remote Sens.…”
Section: Data Processing Of Cloud Radar Doppler Spectramentioning
confidence: 97%
“…For that reason, the noise power σ 2 n is initialized with an estimateσ 2 n given, for example, by the segment method (Petitdidier et al, 1997). For both cases (N=1 or N=2), the total power of sourcesP tot is estimated from the autocorrelation function.…”
Section: Implementation Of the Methodsmentioning
confidence: 99%
“…There are not many investigations about the properties of RWP raw data. Normally, using statistical arguments, one assumes simply a Gaussian signal characteristic for atmospheric and clutter signals, as well as for noise (Doviak and Zrnić, 1993;Petitdidier et al, 1997). Recently, Muschinski et al (1999) used data from a large-eddy simulation to derive I/Q signals for clear air scattering, and Capsoni and D'Amico (1998) presented a software-based radar simulator for generating time series from a synthetic distribution of hydrometeors.…”
Section: Statement Of the Problemmentioning
confidence: 99%