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- Volume 2, Issue 1, 2004
Near Surface Geophysics - Volume 2, Issue 1, 2004
Volume 2, Issue 1, 2004
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GPR using an array antenna for landmine detection
Authors Motoyuki Sato, Yusuke Hamada, Xuan Feng, Fan‐Nian Kong, Zhaofa Zeng and Guangyou FangABSTRACTWe propose a new ground‐penetrating radar (GPR) methodology for buried land‐mine detection. A GPR system using an antenna array was used for common‐midpoint (CMP) data acquisition. This system uses an array of ten Vivaldi antennae and operates from 30 MHz to 6 GHz. The moveout of the CMP data was corrected and the data were stacked to suppress ground clutter. The system was tested in the laboratory and we showed that it images buried mine‐like targets with a high resolution. A model of a plastic land‐mine of Type‐72 was buried in soil consisting of a mixture of gravel and crushed rocks and could be detected by the proposed technique. CMP processing applied to the array signal effectively suppresses the clutter from rough ground surfaces and inhomogeneous soil. We found that the migration algorithm is effective in suppressing ground clutter, but it is even more effective if it is combined with the CMP technique.
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Realistic modelling of surface ground‐penetrating radar antenna systems: where do we stand?
Authors Klaus Holliger, Bernhard Lampe, Ueli Meier and Marc LambertABSTRACTThe generation and recording of electromagnetic waves by ground‐penetrating radar (GPR) systems are complex phenomena. To investigate the characteristics of typical surface GPR antennae operating in realistic environments, we have developed an antenna simulation tool based on a finite‐difference time‐domain (FDTD) approximation of Maxwell’s equations in 3D Cartesian coordinates. The accuracy of the algorithm is validated with respect to laboratory measurements for comparable antenna systems. Numerically efficient and accurate modelling of small antenna structures and high permittivity materials is achieved through a grid‐refinement procedure. We simulate the radiation characteristics of a wide range of common surface GPR antenna types ranging from thin‐wire antennae to bow‐tie antennae with arbitrary flare angles based on the assumption of perfect electrical conductivity (PEC) of the metal parts. Due to the modular structure of the algorithm, additional planar antenna designs can readily be added. Shielding is achieved by placing a metal box immediately above the antenna. To enhance the damping effects, this metal box can be filled with a dielectric absorber and/or connected to the antenna panels through discrete resistors. Finally, we also consider the effects of continuous resistive loading of the antenna panels using a sub‐cell algorithm. We find that GPR antennae with Wu–King‐type resistivity profiles radiate compact, broadband pulses and, as opposed to PEC antennae, are largely insensitive to their operating environment. Unfortunately, these favourable radiation characteristics are accompanied by a dramatic loss in radiation efficiency compared to the corresponding PEC antennae.
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Three‐dimensional GPR imaging in the horizontal wavenumber domain for different heights of source and receiver antennae
More LessABSTRACTFor imaging ground‐penetrating radar (GPR) data, three of the most important parameters are the wave speed, polarization and amplitude of the propagating electromagnetic wave‐field. Choosing an appropriate forward model that incorporates these three parameters is a critical aspect of imaging. Also, the height of the antennae above the surface influences the scattered field significantly and should be taken into account. As the height of the antennae above the surface is increased, the widths of the antenna patterns decrease, resulting in decreasing horizontal spatial bandwidths of the scattered electric fields. Imaging is carried out in the horizontal wavenumber domain using the spatial bandwidths of the scattered data. Decreased spatial resolution is obtained for increasing heights. The far‐field expressions do not account for geometrical spreading in air above the surface, resulting in anomalously low image amplitudes for elevated antennae. Experimental data measured with 900 MHz antennae also show reductions in spatial bandwidth as the height of the source and receiver antennae is increased. For heights and , similar spatial bandwidths as predicted by the synthetic results are obtained. For , this reduction in bandwidth is not as strong as predicted by the synthetic results, primarily because of limitations of the far‐field expressions. For stability reasons, the imaging could only be carried out using the limited bandwidth for the forward far‐field model. Images of a spherical metal sphere for measurements at and were almost identical, whereas those at were similar to those at low heights. In one direction, a higher spatial resolution was observed for the antennae with zero height and decreasing spatial resolution for increasing height. In the other direction, the difference in spatial resolution was not very obvious.
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Subsurface imaging using measured near‐field antenna footprints
Authors Koen W.A. van Dongen, Peter M. van den Berg and Ioan NicolaescuABSTRACTImages of the subsurface are made for the detection of land‐mines using a bistatic stepped‐frequency continuous‐wave spiral‐antenna system. While the system moves along the surface, the emitted electromagnetic wavefields are scattered by objects in the subsurface and cause changes in the voltages measured at the receiver. These changes are formulated as a convolution of a sensitivity function and a complex contrast function. Within the Born approximation, this sensitivity function is equal to the inner product of the wavefield emitted by the transmitter and the field from the receiver operating in transmitting mode. For true amplitude imaging purposes, knowledge of the wavefields in the subsurface is needed. Since it is difficult to obtain a model which describes the radiation characteristics accurately, we measure the footprints of the antennae at one level in the near‐field region and propagate the emitted wavefields using Huygens’ principle. We use both synthetic and experimental data to localize objects in a homogeneous space. First, we apply time‐domain synthetic‐aperture‐radar (SAR) imaging in its most basic appearance. Next, we apply a single‐step inversion algorithm to the data, where we use the measured radiation characteristics of the antenna system. This results in an increase in resolution. We refer to this method as ‘minimized back‐propagation’.
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Material response analysis of georadar reflection data
Authors Jacob T. Fokkema, Evert C. Slob, Emile Fokkema and Sicco BeekmanABSTRACTUnderstanding the nature of the ground‐penetrating radar (GPR) reflection response in terms of the dielectric permittivity and conductivity contrast is an important factor in interpretation. This is the reason for the present study, which aims to carry out an experiment in a controlled fashion, so that the relationship between measurements and the relevant physical parameters can be established. Accurate modelling of the subsurface parameter distribution is hampered by lack of both knowledge of the source signature and an appropriate model. We have therefore constructed a controlled environment in which to carry out measurements that can be modelled with sufficient accuracy in a 1D setting, under the constraint that subsurface conditions can be changed without disturbing the overburden. We present the results of such measurements, an analysis of the data and an interpretation based upon a 1D model, which is sufficiently realistic to accommodate sophisticated physical parameter models.
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A comparison of segmentation techniques for target extraction in ground‐penetrating radar data
Authors S. Shihab and W. Al‐NuaimyABSTRACTIn a typical GPR survey, only a small fraction of the collected data actually represent useful data (i.e. target data), whereas the majority of the data is considered redundant. The first of the post‐processing stages, which relies heavily on a skilled operator, involves indicating those areas that may contain targets and suppressing others. Consequently, this process consumes considerable amounts of time and effort, apart from the fact that the existence of the human factor at this critical stage invariably introduces inconsistency and error into the interpretation. In this paper, automatic detection and segmentation techniques for GPR data are discussed and compared. The techniques rely on the computation of certain features from which a neural network is then able to arrive at a decision whether to classify the data segments in question as targets or otherwise. The first technique is based on extracting statistical features from A‐scan segments while the second technique computes statistical features from B‐scan regions. In the third technique, some regional properties of B‐scan segments are used to achieve discrimination not only between targets and non‐targets, but also between hyperbolic‐shaped and non‐hyperbolic‐shaped targets. All the techniques were tested on different types of GPR data collected from a variety of sites, and they proved to be very efficient in forming a robust automatic technique for data reduction and segmentation. In addition, these techniques are carried out in near real‐time enabling on‐site processing and interpretation of collected data.
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Volumes & issues
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Volume 22 (2024)
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Volume 21 (2023)
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Volume 20 (2022)
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Volume 19 (2021)
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Volume 18 (2020)
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Volume 17 (2019)
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Volume 16 (2018)
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Volume 15 (2017)
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Volume 14 (2015 - 2016)
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Volume 13 (2015)
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Volume 12 (2013 - 2014)
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Volume 11 (2013)
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Volume 10 (2012)
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Volume 9 (2011)
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Volume 8 (2010)
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Volume 7 (2009)
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Volume 6 (2008)
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Volume 5 (2007)
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Volume 4 (2006)
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Volume 3 (2005)
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Volume 2 (2004)
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Volume 1 (2003)