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基于图像子集的差分 GB-InSAR 技术进行水库大坝表面形变监测

Reservoir Dam Surface Deformation Monitoring by Differential GB-InSAR Based on Image Subsets.

机构信息

School of Environmental Science and Engineering, Suzhou University of Science and Technology, No. 99, Xuefu Road, Huqiu District, Suzhou 215009, China.

School of Geodesy and Geomatics, Wuhan University, No. 129, Luoyu Road, Hongshan District, Wuhan 430079, China.

出版信息

Sensors (Basel). 2020 Jan 10;20(2):396. doi: 10.3390/s20020396.

Abstract

Ground-based synthetic aperture radar interferometry (GB-InSAR) enables the continuous monitoring of areal deformation and can thus provide near-real-time control of the overall deformation state of dam surfaces. In the continuous small-scale deformation monitoring of a reservoir dam structure by GB-InSAR, the ground-based synthetic aperture radar (GB-SAR) image acquisition may be interrupted by multiple interfering factors, such as severe changes in the meteorological conditions of the monitoring area and radar equipment failures. As a result, the observed phases before and after the interruption cannot be directly connected, and the original spatiotemporal datum for the deformation measurement is lost, making the follow-up monitoring results unreliable. In this study, a multi-threshold strategy was first adopted to select coherent point targets (CPTs) by using successive GB-SAR image sequences. Then, we developed differential GB-InSAR with image subsets based on the CPTs to solve the dam surface deformation before and after aberrant interruptions. Finally, a deformation monitoring experiment was performed on an actual large reservoir dam. The effectiveness and accuracy of the abovementioned method were verified by comparing the results with measurements by a reversed pendulum monitoring system.

摘要

地基合成孔径雷达干涉测量(GB-InSAR)可实现对区域变形的连续监测,从而可以实时控制大坝表面的整体变形状态。在利用 GB-InSAR 对水库大坝结构进行连续的小范围变形监测时,地基合成孔径雷达(GB-SAR)图像采集可能会受到多种干扰因素的中断,例如监测区域气象条件的剧烈变化和雷达设备故障。结果,中断前后观测到的相位无法直接连接,并且丢失了原始的时空基准,从而导致后续监测结果不可靠。在本研究中,首先采用多阈值策略,通过连续的 GB-SAR 图像序列选择相干点目标(CPTs)。然后,我们基于 CPTs 开发了基于图像子集的差分 GB-InSAR,以解决异常中断前后的大坝表面变形问题。最后,在实际的大型水库大坝上进行了变形监测实验。通过与倒摆监测系统的测量结果进行比较,验证了上述方法的有效性和准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3028/7014032/90fe11ea5d79/sensors-20-00396-g001.jpg

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