| GNSS垂直位移反演区域地表质量变化的模拟分析 |
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| 引用本文： | 李贤炮,钟波,刘滔.GNSS垂直位移反演区域地表质量变化的模拟分析[J].武汉大学学报(信息科学版),2022,47(1):45-54. |
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| 作者姓名： | 李贤炮 钟波 刘滔 |
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| 作者单位： | 1.武汉大学测绘学院，湖北 武汉，430079 |
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| 基金项目： | 国家重点研发计划2018YFC1503503国家自然科学基金41974015国家自然科学基金42061134007民用航天技术预先研究D010103 |
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| 摘 要： | 连续密集的全球导航卫星系统(global navigation satellite system,GNSS)地表形变监测为反演精细的区域地表质量变化提供了有效技术手段.针对格林函数方法反演区域地表质量变化的病态问题,给出了一种改进的正则化拉普拉斯约束矩阵,讨论了广义交叉检验(generalized cross-vali...
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| 关 键 词： | 地表垂直位移 区域地表质量变化 格林函数方法 模拟分析 Tikhonov正则化 |
| 收稿时间： | 2020-11-05 |
Simulation Analysis of Inverting Regional Surface Mass Variations Using GNSS Vertical Displacement |
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| Affiliation: | 1.School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China2.Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan 430079, China |
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| Abstract: | Objectives Continuous and dense global navigation satellite system (GNSS) surface deformation data provide an effective tool to invert refined regional surface mass variations. However, the factors influencing the reliability of GNSS inversion results need to be further studied, such as regularization (includ?ing the construction of regularization matrix and determination of optimal regularization parameter), observation noise and distribution of GNSS stations. Methods First, we proposed an improved regularized Laplacian constraint matrix and discussed the adaptability of the generalized cross-validation (GCV) method in selecting the regularization parameter of ill-posed equations for inversion of regional surface mass variations based on the loading Green's function theory. Second, we compared the effects of different constraint matrices and constraint methods on the GNSS inversion results. Third, we further investigated the influ?enc?es of different noise levels of GNSS vertical displacement, the number and distribution of GNSS stations on the inversion results. Results (1) The regularized Laplacian matrix in this paper can better suppress the edge effects than the traditional Laplacian matrix. (2) The GCV method can effectively determine the optimal regularization parameter, and the inversion results are in good agreement with those solved by the root mean square error (RMSE) criterion. (3) If there are enough GNSS stations and the observation accuracy is high enough in the studied area, the inversion results will be more reliable. Meanwhile, the accuracy of inversion results for uniformly distributed stations is comparable to that of randomly distributed stations when the number of stations is large enough. Conclusions The improved regularized Laplacian matrix and the GCV method can improve the reliability of GNSS inversion results, which can guide the inversion of surface mass variations using measured GNSS data. |
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