GPS-InSAR data fusion method with robust vertical variance component estimation for 3D deformation field

doi:10.13474/j.cnki.11-2246.2021.369

Abstract

Abstract: It is easily affected for the three-dimensional deformation field model of GPS-InSAR data fusion by the gross error of the observation value. The weighting method based on the Helmert variance component estimation cannot be used to resist gross errors and the calculation efficiency is low. In view of this, a method based on the GPS-InSAR fusion solution model for robust vertical variance component estimation is proposed. The variance component estimation method and the robust estimation theory are used to calculate the 3D deformation field effectively by optimizing the classification of the observed values and carrying out the weight selection iteration to allocate the weight accurately. Experimental results show that it is effectively resisted the influence of gross errors in observations by this way. The accuracy of 3D deformation field inversion and the efficiency of 3D deformation field calculated point by point is effectively improved.

Key words: variance component estimation, robust estimation, 3D deformation field, GPS-InSAR data fusion

CLC Number:

P228.4

WU Xueyu, LI Mingfeng, DONG Sixue, WANG bin, ZHAO Zhisheng. GPS-InSAR data fusion method with robust vertical variance component estimation for 3D deformation field[J]. Bulletin of Surveying and Mapping, 2021, 0(12): 38-43.

References

[1] 朱邦彦,姚冯宇,孙静雯,等.利用InSAR与地质数据综合分析南京河西地面沉降的演化特征和成因[J].武汉大学学报(信息科学版),2020,45(3):442-450.
[2] 王茹,杨天亮,杨梦诗,等. PS-InSAR技术对上海高架路的沉降监测与归因分析[J].武汉大学学报(信息科学版),2018,43(12):2050-2057.
[3] FIALKO Y, SIMONS M, AGNEW D. The complete (3-D) surface displacement field in the epicentral area of the 1999 M_W7.1 Hector Mine Earthquake, California, from space geodetic observations[J]. Geophysical Research Letters, 2001, 28(16):3063-3066.
[4] 宋小刚,申星,姜宇,等.通过InSAR与GPS数据融合获取汶川地震同震三维形变场[J].地震地质,2015,37(1):222-231.
[5] SAMSONOV S, TIAMPO K. Analytical optimization of a DInSAR and GPS dataset for derivation of three-dimensional surface motion[J]. IEEE Geoscience & Remote Sensing Letters, 2006, 3(1):107-111.
[6] 班保松,伍吉仓,陈永奇,等. 联合GPS和InSAR观测结果计算汶川地震三维地表形变[J].大地测量与地球动力学,2010,30(4):25-28.
[7] 单新建,屈春燕,郭利民,等.基于InSAR与GPS观测的汶川同震垂直形变场的获取[J].地震地质,2014,36(3):718-730.
[8] 何秀凤,史国强,肖儒雅.基于蚁群优化的GPS/DInSAR三维形变监测方法[J].同济大学学报(自然科学版),2015,43(10):1594-1600.
[9] 郭利民.基于InSAR与多源数据的三维形变场获取研究与应用[J].国际地震动态,2015(8):40-42.
[10] 胡俊.基于现代测量平差的InSAR三维形变估计理论与方法[D].长沙:中南大学,2013.
[11] 罗海滨,何秀凤. GPS-DInSAR集成监测的改进定权方法与仿真实验分析[J]. 煤炭学报, 2012,37(10):1612-1617.
[12] 王霞迎,张菊清,张勤,等.升降轨InSAR与GPS数据集成反演西安形变场[J].测绘学报,2016,45(7):810-817.
[13] 曹海坤,赵丽华,毕研磊.利用附加系统参数的GPS-InSAR综合形变模型建立三维形变场[J].大地测量与地球动力学,2017,37(4):344-348.
[14] 马艳鸽,赵丽华,张盼盼,等.函数模型与随机模型双约束的GPS-InSAR数据融合方法建立三维形变场[J].大地测量与地球动力学,2019,39(11):1112-1117.
[15] 曹海坤. GPS、InSAR数据联合解算地表三维形变场[D].西安:长安大学,2017.
[16] 杨元喜.抗差估计理论及其应用[M]. 北京:八一出版社,1993.
[17] 刘长建,吴洪举,明锋. Helmert方差分量估计严密公式与简化公式等价性的证明[J].测绘科学,2006,31(2):66-67.
[18] YANG Y X, XU T H, SONG L J. Robust estimation of variance components with application in global positioning system network adjustment[J]. Journal of Surveying Engineering, 2005, 131(4):107-112.
[19] 刘长建,马高峰.抗差Helmert方差分量估计及其应用[J].北京测绘,2002(1):16-18.
[20] 胡俊,李志伟,孙倩,等.基于方差分量估计的InSAR和GPS融合监测地表三维形变[C]//中国地球物理学会第二十七届年会论文集.长沙:中国地球物理学会,2011.