Stochastic Maximum Likelihood (SML) parametric estimation of overlapped Doppler echoes

被引:6
|
作者
Boyer, E
Petitdidier, M
Larzabal, P
机构
[1] ENS, UMR CNRS 8029, SATIE, F-94235 Cachan, France
[2] CETP, F-78140 Velizy Villacoublay, France
[3] Univ Paris 11, IUT Cachan, CRIIP, F-94234 Cachan, France
关键词
meteorology and atmospheric dynamics; tropical meteorology; radio science; signal processing; atmospheric propagation;
D O I
10.5194/angeo-22-3983-2004
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
This paper investigates the area of overlapped echo data processing. In such cases, classical methods, such as Fourier-like techniques or pulse pair methods, fail to estimate the first three spectral moments of the echoes because of their lack of resolution. A promising method, based on a modelization of the covariance matrix of the time series and on a Stochastic Maximum Likelihood (SML) estimation of the parameters of interest, has been recently introduced in literature. This method has been tested on simulations and on few spectra from actual data but no exhaustive investigation of the SML algorithm has been conducted on actual data: this paper fills this gap. The radar data came from the thunderstorm campaign that took place at the National Astronomy and Ionospheric Center (NAIC) in Arecibo, Puerto Rico, in 1998.
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页码:3983 / 3993
页数:11
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