Ascending and Descending Orbits InSAR-GPS Data Fusion Method with Additional Systematic Parameters for Three-Dimensional Deformation Field

CAO Haikun; ZHAO Lihua; ZHANG Qin; QU Wei; NIE Jianliang

doi:10.13203/j.whugis20160461

Volume 43 Issue 9

Sep. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(9): 1362-1368. > DOI: 10.13203/j.whugis20160461

CAO Haikun, ZHAO Lihua, ZHANG Qin, QU Wei, NIE Jianliang. Ascending and Descending Orbits InSAR-GPS Data Fusion Method with Additional Systematic Parameters for Three-Dimensional Deformation Field[J]. Geomatics and Information Science of Wuhan University, 2018, 43(9): 1362-1368. DOI: 10.13203/j.whugis20160461

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Ascending and Descending Orbits InSAR-GPS Data Fusion Method with Additional Systematic Parameters for Three-Dimensional Deformation Field

1.
School of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China
2.
Geodetic Data Processing Center, National Administration of Surveying, Mapping and Geoinformation, Xi'an 710054, China

Funds:

The National Natural Science Foundation of China 41604001

The National Natural Science Foundation of China 41674001

The National Natural Science Foundation of China 41574003

The National Natural Science Foundation of China 41504005

the Fundamental Research Funds for the Central Universities 310826171005

the Fundamental Research Funds for the Central Universities 310826161023

the Fundamental Research Funds for the Central Universities 310826151050

the Natural Science Basic Research Plan in Shaanxi Province of China 2016JM4005

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Author Bio:
CAO Haikun, postgraduate, specializes in GPS-InSAR data processing.E-mail:872720268@qq.com
Corresponding author:
ZHAO Lihua, associate professor, PhD. E-mail:zhaolih@chd.edu.cn
Received Date: March 21, 2017
Published Date: September 04, 2018

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Abstract

Abstract

According to the fact that InSAR has the advantages of the high spatial resolution while GPS has the advantages of the high precision and high time resolution, we discuss the method of obtaining high precision three-dimensional deformation field by integrating both ascending and descen-ding orbits InSAR data and GPS data. To weaken the influence of the remaining systematic errors in InSAR data, an integrated deformation analysis model with additional systematic parameters is established, where systematic error functions related to the position of observed points are added in both ascending and descending orbits InSAR observation equations under the constraint of high accurate GPS observations. The simulated and practical examples show that the proposed method can identify systematic error in InSAR data effectively and the calculation is simple. As a result, the three-dimensional deformation field with a higher accuracy will be established by the method proposed in this paper.
- GPS,
- ascending and descending orbits InSAR,
- systematic parameters,
- three-dimensional deformation field

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References (15)

References

[1]	张永志.位错理论及其在大地变形研究中的应用[M].西安:西安交通大学出版社, 2011 Zhang Yongzhi. Dislocation Theory and Its Application in the Study of the Deformation of the Earth[M]. Xi'an:Xi'an Jiaotong University Press, 2011
[2]	Gudmundsson S, Sigmundsson F. Three-Dimensional Surface Motion Maps Estimated from Combined Interferometric Synthetic Aperture Radar and GPS Data[J]. Journal of Geophysical Research, 2002, 107(B10):2250-2264 doi: 10.1029/2001JB000283
[3]	Samsonov S V, Tiampo K F, Rundle J B, et al. Application of InSAR-GPS Optimization for Derivation of Fine Scale Surface Motion Maps of Southern California[J]. IEEE Transactions on Geoscience and Remote Sensing, 2007, 45(2):512-521 doi: 10.1109/TGRS.2006.887166
[4]	胡俊, 李志伟, 朱建军, 等.基于BFGS法融合InSAR和GPS技术监测地表三维形变[J].地球物理学报, 2013, 56(1):117-126 doi: 10.3969/j.issn.1672-7940.2013.01.024 Hu Jun, Li Zhiwei, Zhu Jianjun, et al. Measuring Three-Dimensional Surface Displacements from Combined InSAR and GPS Data Based on BFGS Method[J]. Chinese Journal of Geophysics, 2013, 56(1):117-126 doi: 10.3969/j.issn.1672-7940.2013.01.024
[5]	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 doi: 10.11908/j.issn.0253-374x.2015.10.022 He Xiufeng, Shi Guoqiang, Xiao Ruya. Integration of GPS and DInSAR for 3-D Deformation Monitoring Based on Ant Colony Optimization[J]. Journal of Tongji University (Natural Science), 2015, 43(10):1594-1600 doi: 10.11908/j.issn.0253-374x.2015.10.022
[6]	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, 2012 Hu Jun. Theory and Method of Estimating Three-Dimensional Displacement with InSAR Based on the Modern Surveying Adjustment[D]. Changsha: Central South University, 2012
[7]	Hu J, Li Z W, Sun Q, et al. Three-Dimensional Surface Displacements from InSAR and GPS Mea-surements with Variance Component Estimation[J]. IEEE Geoscience and Remote Sensing Letters, 2012, 9(4):754-758 doi: 10.1109/LGRS.2011.2181154
[8]	张勤, 张菊清, 岳东杰, 等.近代测量数据处理与应用[M].北京:测绘出版社, 2011 Zhang Qin, Zhang Juqing, Yue Dongjie, et al. Advanced Theory and Application of Surveying Data[M]. Beijing:Surveying and Mapping Press, 2011
[9]	Samsonov S V, Tiampo K F, Rundle J B. Application of InSAR-GPS Optimization for Derivation of Three-Dimensional Surface Motion of the Southern California Region Along the San Andreas Fault[J]. Computers & Geosciences, 2008, 34(5):503-514 http://adsabs.harvard.edu/abs/2006AGUFM.G53D0932S
[10]	Guglielmino F, Nunnari G, Puglisi G, et al. Simultaneous and Integrated Strain Tensor Estimation from Geodetic and Satellite Deformation Measurements to Obtain Three-Dimensional Displacement Maps[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6):1815-1826 doi: 10.1109/TGRS.2010.2103078
[11]	Catalao J, Nico G, Hanssen R, et al. Merging GPS and Atmospherically Corrected InSAR Data to Map 3-D Terrain Displacement Velocity[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6):2354-2360 doi: 10.1109/TGRS.2010.2091963
[12]	张勤, 赵超英, 丁晓利, 等.利用GPS与InSAR研究西安现今地面沉降与地裂缝时空演化特征[J].地球物理学报, 2009, 52(5):1214-1222 doi: 10.3969/j.issn.0001-5733.2009.05.010 Zhang Qin, Zhao Chaoying, Ding Xiaoli, et al. Research on Recent Characteristics of Spatio-Temporal Evolution and Mechanism of Xi'an Land Subsidence and Ground Fissure by Using GPS and InSAR Techniques[J]. Chinese Journal of Geophysics, 2009, 52(5):1214-1222 doi: 10.3969/j.issn.0001-5733.2009.05.010
[13]	Lee C W, Lu Z, Jung H S. Simulation of Time-Series Surface Deformation to Validate a Multi-interferogram InSAR Processing Technique[J]. International Journal of Remote Sensing, 2012, 33(22):7075-7087 doi: 10.1080/01431161.2012.700137
[14]	罗海滨, 何秀凤, 刘焱雄.利用DInSAR和GPS综合方法估计地表 3维形变速率[J].测绘学报, 2008, 37(2):960-963 http://d.old.wanfangdata.com.cn/Periodical/chxb200802007 Luo Haibin, He Xiufeng, Liu Yanxiong. Estimation of Three-Dimensional Surface Motion Velocities Using Integration of D-InSAR and GPS[J]. Acta Geodaetica et Cartographica Sinica, 2008, 37(2):960-963 http://d.old.wanfangdata.com.cn/Periodical/chxb200802007
[15]	黄维彬.近代平差理论及其应用[M].北京:解放军出版社, 1992 Huang Weibin. Modern Adjustment Theory and Its Application[M]. Beijing:Chinese People's Liberation Army Publishing House, 1992

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Ascending and Descending Orbits InSAR-GPS Data Fusion Method with Additional Systematic Parameters for Three-Dimensional Deformation Field

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