电波科学学报2016，Vol.31Issue(5)：896-905,10.DOI:10.13443/j.cjors.2015102601
基于支持向量机的粗糙海面风速及海表盐度反演研究
Inversion study of the rough sea surface wind speed and sea surface salinity based on the support vector machine
摘要
Abstract
In this paper,the support vector machine(SVM)regression techniques are applied to the inversion of sea state parameters (e.g.salinity and wind speed of the sea surface).The two scale model (TSM)is used to simulate backscattering coefficients of the rough sea surface with different radar parame-ters.After the sensitivity analysis,the L band (1.4 GHz)and the C band (6.8 GHz)are selected with ap-propriate angles as radar parameters.Then a variety of schemes of inversion are designed,in which single-frequency dual-polarization double angle,dual-frequency dual-polarization double angle and the ratio be-tween the VV and HH polarization backscattering coefficients are chosen respectively as the samples infor-mation.After appropriate training,the SVM forecasting model is applied to inverse the salinity and wind speed of the sea surface.As shown by the results,at the C band,the inversion of the sea surface wind speed bears the highest accuracy,whereas at the L band,the inversion of the sea surface salinity demon-strates the highest accuracy when the ratio between backscattering coefficients is chosen as the samples in-formation.The anti-noise performance of the SVM model is also examined,and the results show that the SVM model performs favorably in the sea state parameter inversion problem.关键词
支持向量机/双尺度模型/反演/海面风速/海表盐度Key words
support vector machine (SVM)/two scale model (TSM)/inversion/sea surface wind speed/sea surface salinity分类
数理科学引用本文复制引用
张清河,梁伟博..基于支持向量机的粗糙海面风速及海表盐度反演研究[J].电波科学学报,2016,31(5):896-905,10.基金项目
国家自然科学基金(61179025) （61179025）
