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目的针对合成孔径雷达(SAR)影像由于地形起伏引起的图像畸变问题,提出了基于相干矩阵的全极化SAR影像地形纠正算法,并运用于雪冰制图。方法该方法首先采用距离多普勒模型建立SAR成像几何模型;然后利用全极化Cloude特征分解方法对全极化SAR图像进行融合,将融合后的SAR图像与模拟图像进行配准提高SAR影像几何定位精度;最后利用投影面积归一化和极化方位角移动补偿技术对地形引起的辐射畸变进行纠正。结果采用中国长江源区南部唐古拉山中段冬克玛底冰川区域的C波段Radarsat-2全极化SAR数据进行验证,配准模拟SAR和原始SAR影像的控制点方位向和距离向的均方根误差(RMSE)分别为7.765像素和14.586像素;经过地形纠正后的地物分类精度达80%以上。结论实验结果表明:1)该方法能够有效消除SAR影像中几何和辐射畸变的影响;2)地形纠正后的SAR数据在雪冰制图中具有可行性。
Aiming at the problem of image distortion caused by topography in Synthetic Aperture Radar (SAR) images, a coherence matrix-based total-polarimetric SAR image topological correction algorithm is proposed and applied to snow ice mapping. Methods Firstly, the distance Doppler model was used to establish the geometric model of SAR imaging. Then the fully polarimetric Cloude eigen-decomposition method was used to merge the fully polarimetric SAR images. The fused SAR images and the simulated images were registered to improve the SAR image geometry Finally, the radiation distortion caused by the terrain is corrected by using the normalized projection area and polarization azimuth movement compensation. Results The C-band Radarsat-2 Polarimetric SAR data in the Dongklamadi Glacier in the middle of the Tanggula section in the southern part of the Yangtze River source area were validated. The root mean square error (RMSE) of the control points in the simulated SAR and the original SAR images RMSE) were 7.765 pixels and 14.586 pixels, respectively. After topographic correction, the accuracy of feature classification was over 80%. Conclusions The experimental results show that: 1) the method can effectively eliminate the influence of geometric and radiological distortion in SAR images; and 2) the terrain-corrected SAR data is feasible in snow ice mapping.