多源地壳形变场数据的总体最小二乘联合反演研究

项目名称： 多源地壳形变场数据的总体最小二乘联合反演研究

项目编号： No.41204003

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 地球物理学和空间物理学

项目作者： 王乐洋

作者单位： 东华理工大学

项目金额： 26万元

中文摘要： 联合GPS、InSAR等多源数据分析地壳形变及总体最小二乘（TLS）平差理论与方法已分别成为大地测量反演和测量数据处理领域的研究热点，然而同时基于多源数据和TLS方法交叉研究地壳形变在国内外还未见相关研究成果发表。联合多源数据可有效揭示三维形变场的时变信息，但形变分析模型中不仅观测值含有误差，系数矩阵往往由于数据采样、观测等同样含有不可忽略的误差；TLS方法可同时处理观测值和系数矩阵存在的误差，得到合理可靠的地球物理参数估值。本项目将利用GPS、InSAR等多源形变场数据和TLS方法研究地壳形变场的参数反演及其物理解释，深入研究TLS联合反演模型的建立、求解算法、不同类观测值相对权比的确定、附有不等式约束方法等，并研究这些理论和方法在地壳应变参数、地震断层参数及滑动分布反演等问题中的应用。本项目着眼于多源形变场数据的TLS联合反演研究，将进一步完善大地测量反演理论、推动多学科的交叉。

中文关键词： 多源数据；地壳形变分析；总体最小二乘；联合反演；相对权比

英文摘要： The crustal deformation analysis by multi-source data GPS and InSAR and the total least squares adjustment theory and method are the research hotspots in geodetic inversion and surveying data processing respectively. But the interdisciplinary research of multi-source data and TLS method have not been published simultaneously in crustal deformation analysis at home and abroad. The time-varying information of 3-dimensions deformation field can be effectively revealed by the combination of multi-source data. In the deformation analysis model, not only the observations contain noise, but also the coefficient matrix is contaminated by some noise from data sampling and measurement which also can not be ignored. The errors of observation and coefficient matrix can be treated by TLS method, and the reasonable and credible geophysical parameter estimations can be obtained. In the project, the multi-source data GPS and InSAR and TLS method will be used to inverse the parameters of crustal deformation field and obtain the geophysical explanations. The main research contents are the model construction of TLS joint inversion, its corresponding algorithm, the determination of relative weight ratio factors, inequality constraint inversion, and so on. And then the theory and methods will be used in the applications on the crust

英文关键词： multi-source data；crustal deformation analysis；total least squares；joint inversion；weight scaling factor