| Citation: | Hai LI, Jiawei REN, Jinlei SHANG. Hydrometeor Classification Method in Dual-polarization Weather Radar Based on Fuzzy Neural Network-fuzzy C-means[J]. Journal of Electronics & Information Technology, 2019, 41(4): 809-815. doi: 10.11999/JEIT180529
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For the problem of hydrometeor classification in the presence of ground clutter, traditional methods produce large classification errors under different weather and environmental conditions. A new method for the classification of Hydrometeor based on Fuzzy Neural Network-Fuzzy C-Means (FNN-FCM) is proposed. Firstly, the FNN is trained by the clutter data received by the Dual-polarization weather radar in the clear sky mode. The parameters of the membership function of each polarization parameter of the clutter are calculated adaptively. Then the ground clutter in the rainfall mode is suppressed by the ground clutter membership function obtained by the training. Finally, FCM clustering algorithm is used to classify the Hydrometeor after clutter suppression. The processing results of the measured data show that the proposed method can effectively suppress ground clutter and obtain finer hydrometeor classification results.
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