中文摘要：

中国自主研制的环境减灾卫星星座（HJ）中包含多颗光学和雷达小卫星，这些小卫星计划于2007年底陆续升空。其中，载有S波段合成孔径雷达（SAR）的HJ-1C星，预计于2008年发射，该卫星设置有S波段（3．2GHz），采用VV极化方式，入射角变化范围是25°-47°。本文根据该雷达卫星的系统参数，利用AIEM模型的模拟数据反演土壤水分的变化。首先，对传统单极化SAR数据反演土壤水分的方法（基于简单散射模型）在S波段的适用性进行了分析（共检验了四个波段数据，分别是Ku波段、C波段、S波段和L波段），结果表明该方法可应用于S波段，且应用效果比C波段好；然后，对以往研究中该方法可采用的不同水分参数形式进行了比较分析，结果表明，以垂直极化幅度作为土壤水分参数效果最好；最后，利用模拟数据对该方法进行验证，结果在两次数据入射角差为5°时，近80％数据的误差在5％以内。

英文摘要：

There are several optical and radar small satellites in HJ constellation which is developed in China, and they will be launched gradually since the end of 2007. In the constellation, HJ-1C is planned to be launched in 2008, on which an S-Band SAR is loaded. The S-Band SAR will work at 3.2GHz, VV-polarization and incidence angle range is 25° -47°. Backscattering coefficient retrieved by radar is very sensitive to soll moisture, because soil dielectric constant has a strong influence on backscatter coefficient, and soil moisture content is a determined factor to soil moisture. Because the number of influencing factors is larger than the number of observations, inver- sion become an ＂ill＂ problem, the result is that conventional physical model can not be used to obtain the model inputs directly. So, physical model must be simplified for acquiring an input from the model output. Following this method, based on the configuration parameters of HJ-1C and SAR sensor, soil moisture change retrieval method is studied using AIEM （Advanced Integral Equation Model） simulation data in this paper. Firstly, the applicability of traditional method （based on Simple Scattering Model） for soil moisture change retrieval using single-polarization SAR data is analyzed at S-Band（totally four bands data is checked, namely, Ku-band, C-band, S-band and L-band）, the result shows the method is applicable at S-band, ever has better outcome than using C-band data. Then, a comparison is performed when using different soil moisture parameter as input in the method, the result shows the best result achieved when vertical-polarization amplitude is used. Finally, the validation is done using simulated data, the result shows that almost 80% of the data has an error less than 5%. The result of this paper will benefit to the quick-application of HJ data after its launched.