中文摘要：

随着极化合成孔径雷达系统的发展,Pol SAR数据在各个领域得到了广泛的应用。本文研究了Pol SAR数据在矿山监测领域的可行性。首先对Pol SAR数据进行滤波去噪等预处理;然后介绍了适合矿山地物分类的Cloude特征向量分解和Freeman分解方法,在极化分解的基础上采用了一种结合散射熵和Freeman分解的Wishart分类方法进行分类,最终得到矿山监测地物的分类图,并通过人工解译的方式对分类后的图像信息进行归类并建立数据库,得到矿山地区的地物分类图。以机载Pol SAR数据为例,得到了较好的实验结果。

英文摘要：

With the development of polarimetric synthetic aperture radar system, PolSAR data has been widely used in various fields. This paper studies the feasibility of PolSAR data in the field of mine monitoring. Firstly, carried out the preprocessing of remote sens- ing such as filtering noise, and then introduced the method of Cloude feature vector decomposition and Freeman decomposition. Based on the polarization decomposition, a Wishart classification method, which combines the scattering entropy and the Freeman decomposi- tion is used to be introduced, and obtained the classification map of the mine monitoring features. Classification and establishment of the database by using the method of artificial interpretation obtained classification map of mining area. Taking airborne PolSAR data as an example, the better results are obtained.