列车通行期间的桥梁变形:使用同时操作的MIMO-SAR传感器监测多个剖面

Andreas Baumann-Ouyang, J. Butt, A. Wieser
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引用次数: 1

摘要

能够测量地表变形的传感器具有面积覆盖和高空间和时间分辨率,有利于许多监测应用。然而,这种传感器通常很昂贵,或者它们的配置不能像基于卫星的系统那样由用户灵活调整。汽车多输入多输出合成孔径雷达(MIMO-SAR)系统具有低成本和高灵活性等优点。在本文中,我们提出了一项实验研究,展示了一种特定的现成的汽车雷达系统用于结构监测的能力。我们分析了测量的视线位移的精度,空间和时间分辨率,以及两个相同类型的传感器同时覆盖同一区域的影响。最后,我们在一个真实的用例中演示了MIMO-SAR系统,该系统测量了铁路桥梁在火车经过时响应动载荷的变形。我们同时操作两个MIMO-SAR传感器,分析和解释单个干涉图,并将数据结合起来,得出沿选定剖面的垂直位移的时空分布。结果表明,现成的汽车级MIMO-SAR系统可用于量化结构的亚毫米变形,并获得有利于结构健康监测应用的高分辨率时间序列。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bridge deformations during train passage: monitoring multiple profiles using concurrently operating MIMO-SAR sensors
Sensors capable of measuring surface deformations with areal coverage and high spatial and temporal resolution are beneficial for many monitoring applications. However, such sensors are typically expensive, or their configuration cannot be adapted flexibly by the user like in case of satellite-based systems. Automotive Multiple-Input-Multiple-Output Synthetic Aperture Radar (MIMO-SAR) systems are interesting potential alternatives associated with low cost and high flexibility. In this paper, we present an experimental investigation showing the capabilities of a particular off-the-shelf, automotive radar system for structural monitoring. We analyse the accuracy of the measured line-of-sight displacements, the spatial and temporal resolution, and the impact of simultaneous coverage of the same area by two sensors of the same type. Finally, we demonstrate the MIMO-SAR system in a real-world use case measuring deformations of a railway bridge in response to dynamic load by trains passing over it. We operated two MIMO-SAR sensors simultaneously, analyse and interpret the individual interferograms and combine the data to derive the temporal and spatial distribution of vertical displacements along selected profiles. The results show that off-the-shelf automotive-grade MIMO-SAR systems can be used to quantify sub-millimetre deformations of structures and derive high-resolution time series beneficial for structural health monitoring applications.
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