DocumentCode :
3462513
Title :
Identification of the Dangerous Meteorological Objects on Doppler-Polarimetric Radar Data Using the Neural Network Based Algorithm. Part 1: Statistical Modeling
Author :
Pitertsev, A.A. ; Marchuk, V.V. ; Yanovsky, F.J.
Author_Institution :
Department of Aero navigation system, National Aviation University, Prospect Komarova 1, 03058, Kiev, Ukraine. e-mail: pitertsev@gmail.com
fYear :
2006
fDate :
24-26 May 2006
Firstpage :
1
Lastpage :
4
Abstract :
This article deals with the process of identification of the dangerous meteorological objects using the neural network based algorithm. Dangerous objects are considered by the example of probable aircraft icing zones. In the first part of this paper theoretical models of microwave backscattering on water drops and ice crystals are considered. The results of statistical calculation on these models are used to train the network. In the second part of this research the identification algorithm will be discussed. Checking of the theoretical calculation of Doppler-polarimetric variables is done on the basis of the experimental data.
Keywords :
Acoustic scattering; Aircraft; Clouds; Meteorological radar; Meteorology; Neural networks; Radar scattering; Rain; Rayleigh scattering; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radar Symposium, 2006. IRS 2006. International
Conference_Location :
Krakow, Poland
Print_ISBN :
978-83-7207-621-2
Type :
conf
DOI :
10.1109/IRS.2006.4338041
Filename :
4338041
Link To Document :
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