Ground penetrating radar (GPR) systems are increasingly being used for the detection and location of buried objects within the upper regions of the earth’s surface. The antenna is the most critical component of such a system. This thesis presents a comprehensive study of resistor-loaded planar dipole antennas for GPR applications using both theory and experiments. The theoretical analysis is performed using the finite difference time domain (FDTD) technique. The analysis starts with the most popular planar dipole, the bow-tie. A parametric study is done to find out how the flare angle, length, and lumped resistors of the antenna should be selected to achieve broadband properties and good target detection with less clutter. The screening of the antenna and the position of transmitting and receiving antennas with respect to each other and ground surface are also studied. A number of other planar geometrical shapes are considered and compared with the bow-tie in order to find what geometrical shape gives the best performance. The FDTD simulations are carried out for both lossless and lossy, dispersive grounds. Also simulations are carried out including surface roughness and natural clutter like rocks and twigs to make the modeling more realistic. Finally, a pair of resistor-loaded bow-tie antennas is constructed and both indoor and outdoor measurements are carried out to validate the simulation results. / <p>QC 20100923</p>

The terms &lsquo / ground-probing radar&rsquo / , &lsquo / ground penetrating radar (GPR)&rsquo / , &lsquo / sub-surface radar&rsquo / or &lsquo / surface-penetrating radar (SPR)&rsquo / refer to various techniques for detecting and imaging of subsurface objects. Among those terms GPR is preferred and used more often. In this thesis, the depth and the position of the buried circular cylinder are determined by a GPR system which comprises of an optical fiber sensor (OFS). The system is a combination of OFS, GPR and optical communication link. In order to determine the depth and the position, first of all the electric field distribution at the OFS is obtained by integrating the Green&rsquo / s function over the induced current distribution. Those distributions are observed for different frequency and depth values. The voltages inside the distribution are measured by OFS. By changing the depth of the cylinder and the frequency of the system, various plots showing x axis displacement versus measured voltages are obtained. Those plots are related to interference fringe patterns. The position and the depth of the cylinder are obtained using interference fringe patterns. All of the studies mentioned are performed in MATLAB R2007b program. The noises of the system due to OFS are extracted using OPTIWAVE OPTISYSTEM 7.0 program. By adding those noises to the measured voltage values, the operating frequency of the system is observed.

Rock glaciers play a significant role in the alpine debris transport system. For practical and engineering considerations, identifying the internal structure and its relationship to surface characteristics is significant in terms of how a rock glacier settles during periods of melting, and the mode of deformation. A better understanding of these factors is important for engineers, engineering geologists and geomorphologists who must make prudent evaluations of rock glaciers as potential sites for human development and uses. It is equally important for evaluating potential stores for water on other planets such as Mars. Ground penetrating radar (GPR) shows that the internal structure of a lobate rock glacier located in the San Juan Mountains of southwest Colorado consists of continuous to semi-continuous horizontal layers of ice-supersaturated sediments and coarse blocky rockslide debris which likely formed through catastrophic episodes of rockfall from the cirque headwall. Folds in the uppermost layers correspond to the surface expression of ridges and furrows, indicating that compressive stresses originating in the steep accumulation zone are transmitted downslope through the rock glacier. The rock glacier is a composite feature that formed by a process involving the development and overlap of discrete flow lobes that have overridden older glacial moraine and protalus rampart materials. The latter materials have been incorporated into the present flow structure of the rock glacier. The discovery of rock glacier-like features on Mars suggests the presence of flowing, or once-flowing ice-rock mixtures. These landforms, which include lobate debris aprons, concentric crater fill and lineated valley fill, hold significant promise as reservoirs of stored water ice that could be used as fuel sources for human exploration of Mars and provide a frozen record of the climatic history of the planet. To this end, the rock glacier in this study was used as a surrogate for similar Martian landforms. Liquid water, found to be abundant in this rock glacier, occurs within a network of interconnected channels that permeate throughout the landform. In terms of water storage within Martian analogs, consideration must include the possibility that some water ice may be stored in relatively pure form within lenses and vein networks that are supplied by seasonal frost accumulation and/or water influx from below.

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This dissertation details the design and development of a mobile autonomous platform from which to conduct a 3D ground-penetrating radar survey. The system uses a three-rover multiagent team to perform a site-selection activity during a lunar analog mission. The work took place beginning in 2008 and culminated in a final field test on Mauna Kea in Hawaii. This demonstration of autonomous acquisition of 3D ground-penetrating radar in a space robtic application is promising not only for in-situ resource utilization, but also for the concept of multiagent teaming.

This dissertation details the design and development of a mobile autonomous platform from which to conduct a 3D ground-penetrating radar survey. The system uses a three-rover multiagent team to perform a site-selection activity during a lunar analog mission. The work took place beginning in 2008 and culminated in a final field test on Mauna Kea in Hawaii. This demonstration of autonomous acquisition of 3D ground-penetrating radar in a space robtic application is promising not only for in-situ resource utilization, but also for the concept of multiagent teaming.

One of the most significant goals in coal mining technology research is the automation of underground coal mining machinery. A current challenge with automating underground coal mining machinery is measuring and maintaining a coal mining horizon. The coal mining horizon is the horizontal path the machinery follows through the undulating coal seam during the mining operation. A typical mining practice is to leave a thin remnant of coal unmined in order to maintain geological stability of the cutting face. If the remnant layer is too thick, resources are wasted as the unmined coal is permanently unrecoverable. If the remnant layer is too thin, the product is diluted by mining into the overburden and there is an increased risk of premature roof fall which increases danger. The main challenge therefore is to develop a robust sensing method to estimate the thickness of thin remant coal layers. This dissertation addresses this challenge by presenting a pattern recognition methodology to estimate thin remnant coal layer thickness using ground penetrating radar (GPR). The approach is based upon a novel feature vector, derived from the bispectrum, that is used to characterise the early-time segment of 1D GPR data. The early-time segment is dominated by clutter inherent in GPR systems such as antenna crosstalk, ringdown and ground-bounce. It is common practice to either time-gate the signal, disregard the clutter by rendering the early-time segment unusable, or configure the GPR equipment to minimise the clutter effects which in turn reduces probing range. Disregarding the early-time signal essentially imposes a lower thickness limit on traditional GPR layer thickness estimators. The challenges of estimating thin layer thickness is primarily due to these inherent clutter components. Traditional processing strategies attempt to minimise the clutter using pre-processing techniques such as the subtraction of a calibration signal. The proposed method, however, treats the clutter as a deterministic but unknown signal with additive noise. Hence the proposed approach utilises the energy from the clutter and monitors change in media from subtle changes in the signal shape. Two complementary processing methods important to horizon sensing have been also proposed. These methods, near-surface interface detection and antenna height estimation, may be used as pre-validation tools to increase the robustness of the thickness estimation technique. The proposed methods have been tested with synthetic data and validated with real data obtained using a low power 1.4 GHz GPR system and a testbed with known conditions. With the given test system, it is shown that the proposed thin layer thickness estimator and near-surface interface detector outperform the traditional matched filter based processing methods for layers less than 5 cm in thickness. It is also shown that the proposed antenna height estimator outperforms the traditional height estimator for heights less than 7 cm. These new methods provide a means for reliably extending layer thickness estimation to the thin layer case where traditional approaches are known to fail.

Thesis (M.A.)--University of Tennessee, Knoxville, 2009. / Title from title page screen (viewed on Oct. 22, 2009). Thesis advisor: Gerald F. Schroedl. Vita. Includes bibliographical references.

Made available in DSpace on 2015-03-26T13:27:54Z (GMT). No. of bitstreams: 1 texto completo.pdf: 4751258 bytes, checksum: 0e480b21213f063f9d31d1243a36f77a (MD5) Previous issue date: 2010-06-29 / This paper aims to analyze the Ground Penetrating RADAR as tool in the determination of the thickness of the layers of the flexible road pavement of automatic way and the density of the asphalt layer supported by integrated testing of GPR and geotechnical data. The first experiment was conducted at the Presidente Dutra highway (BR116), Pirai - RJ, while the data for the second experiment were obtained from the BR040 highway, Sete Lagoas - MG. In order to achieve the objectives of this study, two methodologies were developed: the first one, directed to the identification of the thicknesses of the layers of flexible pavements of automated way; the second one, focused on determining the density of the layer of asphalt surfaces. The first methodology showed promising results, once it presented good classification results for the classes 1 (off-set) and 3 (macadam), however, was confusion between the "blocks" classified for the classes 2 (asphalt) and 4 (subgrade). A possible alternative, for improvement, would be: to use other texture extractor of the wavelet transform family; to use another type of interpolation, using a that better represents the trends of the coefficients to be generated the surface; to increase the number of training and testing samples, or even to use another type of classifier, such as Artificial Neural Networks. However, this is a field that is worth being investigated more deeply, since the results proved to be significant. The second methodology, regarding the correlation of the density of the asphalt layer through the dielectric value, measured by means an ground coupled antenna, of 1,6GHz, using the technique of the reflection, it presented satisfactory values in spite of the few sampling points, showing to be a good alternative to determine indirectly the density of the asphalt layer and for future works in the area. / Este trabalho tem o propósito de analisar o desempenho do RADAR de penetração no solo como ferramenta na determinação das espessuras das camadas do pavimento rodoviário flexível de maneira automática e a densidade da camada de revestimento apoiado em testes integrados de GPR e dados geotécnicos. O primeiro experimento foi realizado na rodovia Presidente Dutra (BR116), município de Piraí - RJ, em quanto os dados para o segundo experimento foram obtidos na rodovia BR040, município de Sete Lagoas - MG. Para atingir os objetivos do trabalho foram elaboradas duas metodologias: a primeira delas, direcionada à identificação das espessuras das camadas de pavimentos flexíveis de modo automatizado; a segunda, voltada para a determinação da densidade da camada de revestimento asfáltico. A primeira metodologia apresentou, de uma maneira geral, resultados promissores, uma vez que foram bons os resultados de classificação para as classes 1 (off-set) e 3 (macadame), no entanto, houve confusão entre os &#8220;blocos&#8221; classificados para as classes 2 (revestimento) e 4 (subleito). Uma possível alternativa para a melhoria dos resultados seria mudar o extrator de textura utilizado (transformada wavelet), valeria apena testar outros extratores da família wavelet; outra opção seria utilizar outro tipo de interpolador, usando um que pegue mais as tendências dos coeficientes ao se gerar a superfície; também seria interessante aumentar o número de amostras de treinamento e teste, ou até mesmo, utilizar outro tipo de classificador, como por exemplo, Redes Neurais Artificiais. Todavia, esse é um campo que vale ser pesquisado mais profundamente, uma vez que os resultados alcançados se mostraram esperançosos. A segunda metodologia, referente à correlação da densidade da camada de revestimento através do valor dielétrico, medido por meio de uma antena de contato no solo, de 1,6 GHz, utilizando a técnica da reflexão, apresentou valores satisfatórios apesar dos poucos pontos amostrados, mostrando ser uma boa escolha para se determinar a densidade da camada de revestimento de maneira indireta e para trabalhos futuros na área.