| Author: | He, Wenchao |
| Title: | Optimization and parametric study of ground penetrating radar wave's ray-path models on buried objects |
| Advisors: | Lai, Wallace (LSGI) |
| Degree: | Ph.D. |
| Year: | 2025 |
| Department: | Department of Land Surveying and Geo-Informatics |
| Pages: | 166 pages : color illustrations |
| Language: | English |
| Abstract: | In densely populated urban environments, the complex network of buried objects, such as pipelines and cables, is indispensable to the daily functioning of the city, supporting everything from basic water supply and waste management to sophisticated communication and power distribution systems. The precision in locating and maintaining these hidden assets is crucial to prevent costly disruptions and facilitate urban planning and development. As a result, efficient and accurate methods for detecting underground structures are essential for minimizing the risk of damage during construction activities and for the timely repair of aging infrastructure. Ground Penetrating Radar (GPR) stands out as an indispensable technology in this field due to its ability to provide detailed insights into the subsurface landscape without the need for physical excavation. Utilizing high-frequency electromagnetic waves, GPR scans the underground to create an image of the subsurface features, reflecting variations in material properties. This technology is particularly effective for identifying the depth and position of buried utilities, assessing their condition, and detecting anomalies such as voids or leaks. Its capability to operate across various soil types and to detect non-metallic as well as metallic objects expands its utility, making GPR an essential tool in the toolkit of urban infrastructure management. A critical aspect of GPR analysis is the interpretation of hyperbolic reflections, which occur when electromagnetic waves are reflected from cylindrical objects like pipes and cables. The precise analysis of these hyperbolic patterns, through a process known as hyperbolic fitting, is essential for accurately determining the location, depth, and material characteristics of subsurface utilities. Hyperbolic fitting involves adjusting mathematical models to match the curved reflections observed in GPR data, allowing for the estimation of key subsurface parameters. Despite its capabilities, the application of GPR faces limitations due to the absence of unified, quantitative hyperbolic fitting models that can adapt to the varied and complex conditions of urban subsurface environments. The prevalent assumptions of perpendicular survey lines and homogenous media do not reflect the real-world complexities, leading to inaccuracies in data interpretation and necessitating advanced methodologies to handle non-ideal conditions and incomplete data effectively. This research has advanced hyperbolic fitting techniques for GPR applications, addressing core challenges and expanding the method's utility in complex environments. By incorporating global optimization algorithms and introducing novel methods such as angle-correction and depth-weighted velocity corrections, the thesis has enhanced the accuracy and adaptability of GPR for detecting and analyzing subsurface structures under varied conditions. Furthermore, it has established robust methods for assessing and managing uncertainties in GPR data, effectively bridging the gap between theoretical advancements and practical implementation in urban infrastructure management and archaeological assessments. This thesis contributed to the GPR research and engineering/surveying community in the following four facets imminently. Firstly, it undertakes a rigorous evaluation of various hyperbolic fitting models, developing strategic recommendations for model selection that adapt to changes in target characteristics such as radius and antenna separation, and demonstrating how variations in subsurface conditions affect GPR data interpretation. Secondly, it introduces angle-corrected hyperbolic fitting models that incorporate pipeline orientation, significantly improving the precision of parameter estimations and extending GPR applicability through validated simulation and field experiments. Thirdly, the study develops a depth-weighted velocity correction algorithm that refines velocity estimations in layered media, addressing the inaccuracies caused by non-homogeneous underground environments. This algorithm has been proven through extensive numerical and laboratory tests to enhance the accuracy of subsurface evaluations. Lastly, the research investigates the impact of hyperbolic data integrity on fitting accuracy, revealing robustness against data alterations and providing empirical insights that guide the handling of incomplete or sparse GPR data. Collectively, this study advances GPR from a basic detection tool to a measurement instrument capable of providing precise measurements in diverse environmental conditions, enhancing subsurface mapping for archaeological research and civil engineering. |
| Rights: | All rights reserved |
| Access: | open access |
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