SVRM-assisted soil moisture retrieval method using reflected signal from BeiDou GEO satellites

被引：0

作者：

Yang L. ^{[1
]}

Wu Q. ^{[1
]}

Zhang B. ^{[2
]}

Liang Y. ^{[1
]}

Hong X. ^{[2
]}

Zou W. ^{[2
]}

机构：

[1] School of Information Science and Engineering, Shandong Agricultural University, Taian

[2] School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing

来源：

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2016年 / 42卷 / 06期

关键词：

BeiDou; Geosynchronous orbit (GEO) satellites; Global navigation satellite system-reflection (GNSS-R); Remote sensing detection; Soil moisture; Support vector regression machine (SVRM);

D O I：

10.13700/j.bh.1001-5965.2015.0656

中图分类号：

学科分类号：

摘要：

We propose a support vector regression machine (SVRM)-assisted soil moisture retrieval method using the reflected signal from BeiDou geosynchronous orbit (GEO) satellites. This method uses a right hand circular polarization (RHCP) antenna and a left hand circular polarization (LHCP) antenna to gain the direct and reflected signal's power data from the BeiDou GEO satellites, respectively. Furthermore, it uses the direct and reflected signal power, BeiDou GEO satellites' elevation angle and azimuth angle as the input features and uses the soil moisture data which is obtained by oven-drying method as the output target of the ε-SVRM which uses a radial basis function (RBF) kernel function. The collected data is separated into two sets randomly: one as training set and the other as test set. The test results show that the error between retrieval model's prediction and the value of oven-drying method is less than 3%; the regression coefficient of determination is 0.897 9; the root mean square error (RMSE) is 1.492 6%, which proves that this method has good generalization ability and the practical results meet the application requirement. © 2016, Editorial Board of JBUAA. All right reserved.

引用

页码：1134 / 1141

页数：7

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