1
Master's degree, Malek Ashtar University of Technology, Tehran, Iran
2
Associate Professor, Malek Ashtar University of Technology, Tehran, Iran
Abstract
The main purpose of this article is to design and simulate an algorithm for the buried target from InSAR, and the purposeof this study is to start with the construction and analysis of the subsidence rate of the subway tunnel in the construction of Isfahan city. The main connections of InSAR for the construction and monitoring of subsidence of such goals are in determining the measuring time and reducing the correlation due to the change of the reflective characteristics of the geographical objects over time, which leads to the reduction of the interference coherence. In the design of this algorithm, an attempt has been made to increase the degree of coherence between the interference views by using the interferometer radar time series processing and the selection of widespread stable scatterers, as well as the optimal and continuous graphic design between the images under processing, which causes the stability of the phase of the distributed targets. Also, in order to reduce the amount of noise in the interference of views, in the stage before phase unwrapping, by applying a filter and suitable parameters to increase the signal to noise, in which the average coherence in the interference of the created views is 9% compared to other filters. It is closer to the number 1, which is the highest level of coherence, and in the end, in order to increase the accuracy and not to remove the regions with relatively low coherence, we will implement the optimal fuzzy unwrapping algorithm, which measures the average absolute value of the relative error in phase unwrapping by 12%. It will perform better than other phase unwrapping algorithms. Finally, after the mentioned processes, it is clear that the subsidence of the target under study is different from the subsidence caused by natural causes such as underground water or drought and has a recognizable subsidence pattern.
Damoah-Afari, X. L. Ding, Z. Lu and Z. W. Li. “DETECTING GROUND SETTLEMENT OF SHANGHAI USING INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) TECHNIQUES.”,Vol. 05, pp.019, 2008.
Xiang, K. Wang, and X. Liu, "A model-spectrum-based flattening algorithm for airborne single-pass SAR interferometry," IEEE Geoscience and Remote Sensing Letters, Vol. 06, pp. 311-307, 2009.
Xu, D. Zhao, C. Ma and D. Lian, "Monitoring Subsidence Deformation of Suzhou Subway Using InSAR Timeseries Analysis," in IEEE Access, Vol. 09, pp. 24-116, 2021.
Wei, L. Pu, X. Tang, X. Zhang, and J. Shi, "Efficient Registration for InSAR Large-Scale Image Using Quadtree Segmentation," in IGARSS 2018 IEEE International Geoscience and Remote Sensing Symposium, Vol. 11, pp. 38-135, 2018.
Eppler, J. and Rabus. “Monitoring Urban Infrastructure with An Adaptive Multilooking INSAR Technique”, Journal of Geophysical Research, Vol. 06, pp. 194-68, 2012.
Biswas, D. Chakravarty, P. Mitra, and A. Misra, "Spatial-Correlation Based Persistent Scatterer Interferometric Study for Ground Deformation," Journal of the Indian Society of Remote Sensing, Vol. 04, pp. 26-113,2017.
W. Chen and H. A. Zebker, “Phase Unwrapping for Large SAR Interferograms: Statistical Segmentation and Generalized Network Models,” IEEE Transactions on Geoscience and Remote Sensing, Vol. 03, No. 8, pp. 1709-1719, 2002.
Kristina J. Reinders a, Ramon F. Hanssen a, Freek J. van Leijen a, Mandy Korff, "Augmented satellite InSAR for assessing short-term and long-term surface deformation due to shield tunnelling," Journal of the Tunnelling and Underground Space Technology incorporating Trenchless Technology Research, Vol. 36, pp.1016,2020.
Reinders, K. J, Hanssen, R. F, van Leijen, F. J, & Korff, M. Augmented satellite InSAR for assessing short-term and long-term surface deformation due to shield tunnelling. Tunnelling and Underground Space Technology, Vol. 12, pp.1016, 2021.
Berardino, G. Fornaro, R. Lanari, and E. Sansosti, "A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms," IEEE transactions on geoscience and remote sensing, Vol. 40, pp. 2383-2375, 2002.
Lanari, O. Mora, M. Manunta, J. J. Mallorquí, P. Berardino, and E. Sansosti, "A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms," IEEE Transactions on Geoscience and Remote Sensing, Vol. 42, pp. 1377-1386, 2004.
Hooper, P. Segall, and H. Zebker, "Persistent scatterer InSAR for crustal deformation analysis, with application to Volcán Alcedo, Galápagos," Journal of Geophysical Research, Vol. 112, pp. 19-13, 2007.
Bo Hu, " Time-Series Displacement of Land Subsidence in Fuzhou Downtown, Monitored by SBAS-InSAR Technique" Journal of Sensors, Vol. 35, pp. 316-2652, 2019.
Huang, H. Zhou, S. Dong, and S. Xu, "Parallel branch-cut algorithm based on simulated annealing for large-scale phase unwrapping," IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, pp. 3846-3833, 2015.
Roccheggiani, M. Piacentini, D.Tirincanti, E.Perissin, D.Menichetti, M, "Detection and Monitoring of Tunneling Induced Ground Movements Using Sentinel-1 SAR Interferometry," Remote Sens, Vol. 73, pp. 1121-4517, 2019.
Qiuxiang Tao1,Zaijie Guo1,Fengyun Wang1,Qingguo An2,Yu Han1"SBAS‑InSAR time series ground subsidence monitoring along Metro Line 13 in Qingdao, China" Arabian Journal of Geosciences, Vol. 21, pp. 125-017, 2021.
Li henjin, Wang Zhiyong, Liu Wei, Li, Xing Zhou, Maotong, Zhang Baojing. “Detecting, Monitoring, and Analyzing the Surface Subsidence in the Yellow River Delta (China) Combined with Center Net Network and SBAS-InSAR.” Journal of Spectroscopy, Vol. 14, pp. 174-321, 2022.
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