Analysis of Multiple Scattering Characteristics of Cable-Stayed Bridges with Multi-band SAR
Abstract. Accurate localization of multi-scattering features of cable-stayed bridges in multi-band Synthetic Aperture Radar (SAR) imagery is crucial for intelligent recognition of bridge targets within images, as well as for precise water level extraction. This study focuses on the Badong Yangtze River Bridge, utilizing Unmanned Aerial Vehicle (UAV) LiDAR data of the bridge, and analyzes the multi-scattering characteristics of different bridge structural targets based on Geometric Optics (GO) methods and the Range-Doppler principle. Furthermore, the study integrates LiDAR data of the bridge's cable-stays to examine their multi-scattering phenomena, finding that the undulations of the Yangtze River's surface waves significantly contribute to the pronounced double scattering features of the bridge's cable-stays. Additionally, statistical analysis of multi-source SAR data indicates that this phenomenon is not directly correlated with radar wavelength, implying no direct connection to surface roughness. Utilizing LiDAR point cloud data from the bridge's street lamps, this paper proposes a novel method for estimating water level elevation by identifying the center position of spots formed by double scattering from lamp posts. The results show that using TerraSAR ascending and descending orbit images, this method achieves a water level elevation accuracy of approximately 0.2 meters.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Analysis of Multiple Scattering Characteristics of Cable-Stayed Bridges with Multi-band SAR ; volume:XLVIII-1-2024 ; year:2024 ; pages:761-767 ; extent:7
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-1-2024 (2024), 761-767 (gesamt 7)
- Creator
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Xu, Yanhao
Wen, Yangmao
Li, Tao
Ma, Sijie
Liu, Jie
- DOI
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10.5194/isprs-archives-XLVIII-1-2024-761-2024
- URN
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urn:nbn:de:101:1-2405160438015.958310096722
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 11:00 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Xu, Yanhao
- Wen, Yangmao
- Li, Tao
- Ma, Sijie
- Liu, Jie
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