Lithological Classification of Polarimetric SAR Data with Target Decomposition Method
极化雷达目标分解方法用于岩性分类

Due to the similarity of backscattering intensity of rocks, the general SAR data is not easy to make lithological classification on the earth surface. Polarimetric Radar records Stokes of Scattering Matrix of backscattering waves, which increases the classification precision. But meanwhile, the data fusion coming from the coherence of different polarizations in the polarimetric data produces more error for lithological classification. This paper divides the rock's backscattering into three parts: Single Scattering, Double Scattering, and Cross Scattering The decomposition decreases the coherence of co polarization backscattering waves, enhances the backscattering difference of rocks, and shows the ability of lithological classification for polarimetric data. The polarimetric data used in this paper was obtained in October 1993, in the north of Xinjiang Province. With the statistic analysis, this paper builds the scatter plots for each kind of rocks, and input them into the Neural Network Classifier. The maximum precision is 94% and minimum error 1.06%.