干涉合成孔径雷达
全球导航卫星系统增强
合成孔径雷达
计算机科学
系列(地层学)
大地测量学
全球导航卫星系统应用
算法
变形(气象学)
变形监测
时间序列
实时计算
人工智能
计算机视觉
遥感
地质学
全球定位系统
电信
机器学习
古生物学
海洋学
作者
Maodu Yan,Chaoying Zhao,Xiaojie Liu,Baohang Wang
出处
期刊:IEEE Geoscience and Remote Sensing Letters
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:21: 1-5
标识
DOI:10.1109/lgrs.2023.3345341
摘要
In recent years, many Synthetic Aperture Radar (SAR) satellites have been launched to provide abundant SAR data, which creates a demand for dynamic monitoring of surface deformation. In general scenarios, we process SAR images within a fixed period to obtain the deformation time series. However, conventional InSAR processing involves manually selecting a specific time period, making it impossible to capture the complete deformation process. Therefore, we propose a novel framework, that is, the sequential SBAS-InSAR backward estimation algorithm, which utilizes sequential least squares adjustment to dynamically recover previous surface deformation time series. To validate the effectiveness of the proposed method, we conduct both simulated and real data experiments. And the simulated results obtained by new method are totally consistent with the traditional SBAS-InSAR method, while the standard deviation of the difference between the deformation time series obtained by InSAR and GNSS results is better than 6 mm . Moreover, the new method has higher computation efficiency.
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