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Proceedings Paper

Fuzzy detection and classification of dangerous weather phenomena using dual-polarimetric radar measurements
Author(s): Van Tho Dang; F. J. Yanovsky
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Paper Abstract

A fuzzy detector and classifier of dangerous weather phenomena based on polarimetric radar measurements are described in this paper. Five polarimetric radar measurands, namely, horizontal reflectivity factor, differential reflectivity factor, linear depolarization ratio, specific differential phase, cross-correlation coefficient and altitude of resolution volume serve as inputs of the fuzzy detector and classifier. The output of the fuzzy detector and classifier is one of 8 possible classes: 0) No dangerous weather phenomenon is detected; 1) Lightning; 2) Aircraft icing; 3) Hail; 4) Hail+rain; 5) Heavy rain; 6) Wet snow; 7) Dense snow. A neural network backpropagation algorithm is also considered for training the fuzzy detector and classifier in case of having verified data.

Paper Details

Date Published: 5 August 2009
PDF: 10 pages
Proc. SPIE 7502, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009, 750212 (5 August 2009); doi: 10.1117/12.838058
Show Author Affiliations
Van Tho Dang, National Aviation Univ. (Ukraine)
F. J. Yanovsky, National Aviation Univ. (Ukraine)


Published in SPIE Proceedings Vol. 7502:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009
Ryszard S. Romaniuk; Krzysztof S. Kulpa, Editor(s)

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