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5 August 2009 Fuzzy detection and classification of dangerous weather phenomena using dual-polarimetric radar measurements
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Proceedings Volume 7502, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009; 750212 (2009) https://doi.org/10.1117/12.838058
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009, 2009, Wilga, Poland
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.
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Van Tho Dang and F. J. Yanovsky "Fuzzy detection and classification of dangerous weather phenomena using dual-polarimetric radar measurements", Proc. SPIE 7502, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2009, 750212 (5 August 2009); https://doi.org/10.1117/12.838058
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