关键词: 波形分类, 特征优选, 雷达高度计, 北极海冰, CryoSat-2

Abstract: Monitoring the type change or thickness change of sea ice is a more effective way to monitor sea ice. In this paper, the CryoSat-2 radar altimeter is used to study the types of Arctic sea ice. Using radar altimeter to classify Arctic sea ice, on the one hand, it is difficult to select the optimal characteristic parameters, on the other hand, it is difficult to achieve a relatively refined classification of sea ice with a single radar altimeter data. In view of the above problems, this paper constructed a feature selection method using the combination of chi-square test, mutual information and Wrapper packing method. The feature subset (SSD+Sigma0+LTPP+PP+SK+LEW) selected by this method is combined Random forest classification divides the radar altimeter data in the Arctic into seawater, one-year thin ice, one-year thick ice, and multi-year ice. The correct classification rate of this method is 93.32% in the training set, 92.42% in the validation set, and the Kappa coefficient is 0.90, all of which are better than other feature combinations, which can basically achieve effective classification of sea ice in the Arctic region, and the classification results can also help in the inversion of sea ice thickness.

Key words: waveform classification, feature selection, radar altimeter, Arctic sea ice, CryoSat-2