探地雷达
地质学
雷达
遥感
数据集
领域(数学)
计算机科学
人工智能
电信
数学
纯数学
作者
Hai Liu,Shi Zhenshi,Jianhui Li,Chao Liu,Xu Meng,Yanliang Du,Jie Chen
出处
期刊:Geophysics
[Society of Exploration Geophysicists]
日期:2021-03-19
卷期号:86 (3): WA25-WA33
被引量:38
标识
DOI:10.1190/geo2020-0384.1
摘要
Cavities under urban roads have increasingly become a great threat to traffic safety in many cities. As a quick, effective, and high-resolution geophysical method, ground-penetrating radar (GPR) has been widely used to detect and image near-surface objects. However, the interpretation of field GPR data remains challenging. For example, it is hard to distinguish reflections caused by road cavities or other urban utilities with a conventional 2D GPR survey. The superiority of 3D GPR in data interpretation is demonstrated by a laboratory experiment. Two pipes and a glass-made cavity buried in a sandpit show similar hyperbolic reflections in the 2D GPR profiles; thus, they are difficult to discriminate. In contrast, their geometric shapes and dimensions are readily identified in the 3D image reconstructed from the synthetic 3D GPR data set. Based on these ideas, we have developed a car-mounted 3D GPR system with two antenna arrays oriented in different polarization directions and have detected more than 100 cavities in three Chinese cities over the past year. The field data of two such cavities are presented. As a result, the cavity depth, horizontal size, and height can be accurately estimated from the 3D GPR data set. Laboratory and field experimental results indicate that 3D GPR possesses potential in the detection and recognition of road cavities and utilities in the complex urban environment.
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