An Improved Method of Joint Inversion Using GPS and Gravity Observation Data

作     者：LI Zhicai XU Caijun 

作者机构：National Geomatics Center of China Haidian District Beijing China Key Laboratory of Geospace Environment and Geodesy Ministry of Eduction School of Geodesy and Geomatics Wuhan University Wuhan China 

出 版 物：《Geo-Spatial Information Science》 (地球空间信息科学学报（英文）)

年 卷 期：2005年第8卷第3期

页      面：225-229页

核心收录：

学科分类：081802[工学-地球探测与信息技术] 08[工学] 081105[工学-导航、制导与控制] 0818[工学-地质资源与地质工程] 0804[工学-仪器科学与技术] 0811[工学-控制科学与工程] 

基　　金：Project supported by Programfor NewCentury Excellent Talentsin University(No. NCET-04-0681) Hubei Province Excellent Young Sciencisit Foun-dation (No.2002AC011) the National Natural Science Foundation of China (No.40344023) Fund of Key Laboratory of Geodesy and Dynamic ,In-stitute of Geodesy and Geophysics , Chinese Academy of Science (No.L04-02) and Open Research Fund Programof the Key Laboratory of GeospaceEnvironment and Geodesy, Ministry of Education, China (No.905276031-04-08 ,950276031-04-10) 

主　　题：joint inversion scale parameter random cost method 

摘      要：On the basis of the dislocation theory and gravity observation, a joint inversion model is presented with a fitting factor A scaling amplitudes between the gravity and GPS observation data. The test results show that the new joint model is better than that taking the scale factor ）, as a constant from the inversion result of MSE （mean square error）. In addition, the random cost method used in the inversion algorithm is revised and improved, which shows that the improved random cost method can easily get the local minimum value and greatly decrease the iteration steps.