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

Eric Boyer (1) , Monique Petitdidier (2) , Pascal Larzabal (1, 3)

1 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie
2 CETP - Centre d'étude des environnements terrestre et planétaires
3 IUT de Cachan, CRIIP

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.

Domaines: Océan, Atmosphère; Sciences de la Terre

Eric Boyer, Monique Petitdidier, Pascal Larzabal. Stochastic Maximum Likelihood (SML) parametric estimation of overlapped Doppler echoes. Annales Geophysicae, 2004, 22 (11), pp.3983-3993. ⟨hal-00329407⟩