首页> 外文会议>Proceedings of Fringe 2015 Workshop >DEFORMATION MONITORING OF URBAN INFRASTRUCTURE BY TOMOGRAPHIC SAR USING MULTI-VIEW TERRASAR-X DATA STACKS
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DEFORMATION MONITORING OF URBAN INFRASTRUCTURE BY TOMOGRAPHIC SAR USING MULTI-VIEW TERRASAR-X DATA STACKS

机译:使用多视图TERRASAR-X数据堆栈的层析成像SAR监测城市基础设施的变形

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Synthetic Aperture Radar Tomography (TomoSAR) coupled with data from modern SAR sensors, such as the German TerraSAR-X (TS-X) produces the most detailed three-dimensional (3D) maps by distinguishing among multiple scatterers within a resolution cell. Furthermore, multi-temporal TomoSAR allows for recording the underlying deformation phenomenon of each individual scatterer. One of the limitations of using InSAR techniques, including TomoSAR, is that they only measure deformation along the radar Line-of-Sight (LOS). In order to enhance the understanding of deformation, a decomposition of the observed LOS displacement into the 3D deformation vector in the local coordinate system is desired. In this paper we propose a method, based on L1 norm minimization within local spatial cubes, to reconstruct 3D deformation vectors from TomoSAR point clouds available from, at least, three different viewing geometries. The methodology is applied on two pair of cross-heading TS-X spotlight image stacks over the city of Berlin. The linear deformation rate and amplitude of seasonal deformation are decomposed and the results from two individual test sites with remarkable deformation patterns are discussed in details.
机译:合成孔径雷达层析成像(TomoSAR)结合现代SAR传感器(例如德国TerraSAR-X(TS-X))的数据,通过在分辨单元内的多个散射体之间进行区分,可以生成最详细的三维(3D)地图。此外,多时间TomoSAR可以记录每个散射体的潜在变形现象。使用InSAR技术(包括TomoSAR)的局限性之一是它们只能测量沿雷达视线(LOS)的变形。为了增强对变形的理解,需要将观察到的LOS位移分解为局部坐标系中的3D变形向量。在本文中,我们提出了一种基于局部空间立方体内L1范数最小化的方法,该方法可从至少三个不同的观察几何结构中可用的TomoSAR点云重构3D变形矢量。该方法应用于柏林市上的两对交叉标题TS-X聚光灯图像堆栈。分解了线性变形率和季节性变形幅度,并详细讨论了两个具有明显变形模式的测试点的结果。

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    Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Muenchner strasse 20, Oberpfaffenhofen, 82234 Wessling, Germany sina.montazeri@dlr.de;

    Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Muenchner strasse 20, Oberpfaffenhofen, 82234 Wessling, Germany,Technische Universitae1t Muenchen (TUM), Arcisstrasse 21, 80333 Munich, Germany sina.montazeri@dlr.de;

    Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Muenchner strasse 20, Oberpfaffenhofen, 82234 Wessling, Germany,Technische Universitae1t Muenchen (TUM), Arcisstrasse 21, 80333 Munich, Germany;

    Department of Geoscience and Remote Sensing (GRS), Delft University of Technology, Stevinweg 1, 2628 CN Delft, the Netherlands;

    Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Muenchner strasse 20, Oberpfaffenhofen, 82234 Wessling, Germany,Technische Universitae1t Muenchen (TUM), Arcisstrasse 21, 80333 Munich, Germany;

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