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ABSTRACT: Physically-based ground-penetrating radar (GPR) data processing is essential for quantitative characterization of soils and materials. A novel near-field GPR antenna model coupled with layered media Green’s functions was used to investigate the effect of antenna-medium coupling in the analysis of GPR data. The radar antennas are modeled using an equivalent set of infinitesimal electric dipoles and characteristic, frequency-dependent, global reflection and transmission coefficients. These coefficients determine through a plane wave decomposition, wave propagation between the radar reference plane, point sources, and field points. We calibrated an actual commercial 400 MHz time-domain antenna, from which synthetic GPR data sets were generated. We observed that, depending on the model configuration, antenna effects may affect the topography of the objective function in full-waveform inverse problems. In addition, antenna-medium coupling has a significant impact on the medium surface reflection, whether in terms of amplitude or propagation time (which usually defines the so-called time zero). We also showed that an effective source can not be used for simulating near-field radar data as the antenna-medium coupling strongly depends on the medium properties. In that respect, numerical experiments demonstrated the promising perspectives for simultaneous estimates of medium permittivity and conductivity from antenna-medium coupling.
Near Surface Geophysics. 12/2012; 10(6):631-639.
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ABSTRACT: The quantitative retrieval of soil apparent electrical conductivity using electromagnetic induction (EMI) has remained limited due to strong simplifications regarding EMI antenna modelling. In this paper, a new technique for EMI antenna modelling is applied for the common-offset EMI systems. The EMI system is efficiently described using global transmission and reflection coefficients and Green's functions are used to describe wave diffusion for horizontal and vertical dipole modes. We performed EMI measurements along a 180-metre-long transect with two different instrument heights above the soil surface, as well as with different orientations and frequencies. To ensure proper retrieval of the soil apparent electrical conductivity, the reference values were obtained from electrical conductivity data measured from 11 undisturbed soil cores taken along the EMI transect. The apparent electrical conductivity values calculated by applying the proposed model have a good agreement with reference values, however some discrepancies can be observed that are mainly attributed to the presence of local heterogeneities and also errors due to the variations in the height of the EMI instruments above the ground. The proposed method appears to be promising for quantitative retrieval of soil apparent electrical conductivity and resolving calibration issues that are typically encountered using EMI. In addition, the model calibration (antenna transfer functions determination) was successfully accomplished using conductivity values measured from the soil cores.
Near Surface Geophysics. 06/2012; 10(3):237-247.
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Journal of Hydrology. 01/2012; 424-425:112-123.
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ABSTRACT: We conducted a laboratory experiment to test the ground penetrating radar (GPR) full-waveform forward and inverse modeling approach for electromagnetic wave propagation in water. The GPR system consisted of a vector network analyzer combined with an air-launched, 0.8-2.2 GHz horn antenna, thereby setting up an ultra wideband stepped-frequency continuous-wave radar. The apparent frequency-, salinity-, and temperature-dependent dielectric permittivity and electrical conductivity of water were estimated by using existing electrical models. Using these models, the radar data could be simulated and a remarkable agreement was obtained with the laboratory measurements. Neglecting the frequency-, salinity-, and temperature-effects led to less satisfactory results, especially regarding signal amplitude. Inversion of the radar data permitted to reconstruct the air and water layer thicknesses, and to some extent, the water electrical properties. This analysis particularly showed the benefit of using proper water electrical models compared to commonly used simplified approaches in GPR forward and inverse modeling.
Advanced Ground Penetrating Radar (IWAGPR), 2011 6th International Workshop on; 07/2011
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ABSTRACT: The antenna of a zero-offset off-ground ground-penetrating radar can be accurately modeled using a linear system of frequency-dependent complex scalar transfer functions under the assumption that the electric field measured by the antenna locally tends to a plane wave. First, we analyze to which extent this hypothesis holds as a function of the antenna height above a multilayered medium. Second, we compare different methods to estimate the antenna phase center, namely, 1) extrapolation of peak-to-peak reflection values in the time domain and 2) frequency-domain full-waveform inversion assuming both frequency-independent and -dependent phase centers. For that purpose, we performed radar measurements at different heights above a perfect electrical conductor. Two different horn antennas operating, respectively, in the frequency ranges 0.2-2.0 and 0.8-2.6 GHz were used and compared. In the limits of the antenna geometry, we observed that antenna modeling results were not significantly affected by the position of the phase center. This implies that the transfer function model inherently accounts for the phase-center positions. The results also showed that the antenna transfer function model is valid only when the antenna is not too close to the reflector, namely, the threshold above which it holds corresponds to the antenna size. The effect of the frequency dependence of the phase-center position was further tested for a two-layered sandy soil subject to different water contents. The results showed that the proposed antenna model avoids the need for phase-center determination for proximal soil characterization.
IEEE Transactions on Geoscience and Remote Sensing 06/2011; · 2.89 Impact Factor
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ABSTRACT: We used advanced ground-penetrating radar (GPR) inversion techniques for detecting landmines in laboratory conditions. The radar data were acquired with a calibrated vector network analyzer combined with an off-ground monostatic horn antenna, thereby setting up a stepped-frequency continuous-wave radar. Major antenna effects and interactions with the soil and targets were filtered out using frequency-dependent complex antenna transfer functions. The proposed strategy first exploits inversion approaches that are able to give an accurate characterization of the antenna-soil interaction and a reliable estimate of the soil permittivity. The outcomes of this first phase are at the basis of the application of a microwave tomographic approach based on the Born approximation to achieve the imaging of the subsurface. The algorithms were applied for imaging three landmines of different sizes and buried at different depths in sand. Although the radar system was off the ground, the results showed that it was possible to reconstruct all mines, including a shallow plastic mine as small as 5.6 cm in diameter. This last mine was invisible in the raw radar data, and the use of common GPR imaging techniques did not lead to satisfactory results. The proposed integrated method shows great promise for shallow subsurface imaging in a demining context, particularly because it automatically provides accurate information on the shallow soil dielectric permittivity.
IEEE Transactions on Geoscience and Remote Sensing 02/2011; · 2.89 Impact Factor
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ABSTRACT: In a hydrological modelling scenario, often the modeller is confronted with external data, such as remotely-sensed soil moisture observations, that become available to update the model output. However, the scale triplet (spacing, extent and support) of these data is often inconsistent with that of the model. Furthermore, the external data 5 can be cursed with epistemic uncertainty. Hence, a method is needed that not only in-tegrates the external data into the model, but that also takes into account the difference in scale and the uncertainty of the observations. In this paper, a synthetic hydrological modelling scenario is set up in which a high-resolution distributed hydrological model is run over an agricultural field. At regular time steps, coarse-scale field-averaged soil 10 moisture data, described by means of possibility distributions (epistemic uncertainty), are retrieved by synthetic aperture radar and assimilated into the model. A method is presented that allows to integrate the coarse-scale possibility distribution of soil mois-ture content data with the fine-scale model-based soil moisture data. To this end, a scaling relationship between field-averaged soil moisture content data and its corre-15 sponding standard deviation is employed.
Earth Syst. Sci. Discuss. 01/2011; 8(8):6031-6067.
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Hydrology and Earth System Sciences. 01/2011; 15:1323?1338.
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ABSTRACT: This paper presents the mutual coupling analysis in Ultra-Wideband (UWB) antenna arrays devoted to near-field imaging from 1 to 4 GHz. Vivaldi antennas have been designed to build the antenna array. The Method of Moments (MoM) in iterative form is used to find the array impedance matrix and the different near-field patterns. Very strong agreement between the simulated and the measured coupling coefficients, testifies the validity of the modelling of the antenna array. The localization of isolated targets with an accuracy of the order of 2 mm is also demonstrated.
Antennas and Propagation Conference (LAPC), 2010 Loughborough; 12/2010
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ABSTRACT: Full-waveform inversion of proximal ground penetrating radar (GPR) data is used to determine the electromagnetic properties of layered media. The radar system consists of a vector network analyzer combined with an off-ground horn antenna operating at ultra wideband. The GPR wave propagation is modeled for a multilayered medium using a recursive Green's function computed in the frequency domain. The antenna and its interactions with the layered medium are modeled using a linear system of complex transfer functions. GPR signals were acquired in laboratory above a two-layered sand medium and two concrete slabs separated by a thin air layer (simulating a fracture). Subsequent inversions permit to retrieve the electromagnetic properties and the dimensions of these thin-layered media. For humid sand, GPR-derived dielectric permittivities showed a good agreement (RMSE = 1.65) with measured volumetric water contents. Dimensions of the three-layered concrete medium could be retrieved with a millimetric accuracy. The method is promising for the non-destructive characterization of multilayered media, including thin layers, owing to the full-waveform inversion of the radar data in a large frequency bandwidth.
Electromagnetic Theory (EMTS), 2010 URSI International Symposium on; 09/2010
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ABSTRACT: A joint analysis of full-waveform information content in ground penetrating radar (GPR) and electromagnetic induction (EMI) synthetic data was investigated to reconstruct the electrical properties of multilayered media. The GPR and EMI systems operate in zero-offset, off-ground mode and are designed using vector network analyser technology. The inverse problem is formulated in the least-squares sense. We compared four approaches for GPR and EMI data fusion. The two first techniques consisted of defining a single objective function, applying different weighting methods. As a first approach, we weighted the EMI and GPR data using the inverse of the data variance. The ideal point method was also employed as a second weighting scenario. The third approach is the naive Bayesian method and the fourth technique corresponds to GPR–EMI and EMI–GPR sequential inversions. Synthetic GPR and EMI data were generated for the particular case of a two-layered medium. Analysis of the objective function response surfaces from the two first approaches demonstrated the benefit of combining the two sources of information. However, due to the variations of the GPR and EMI model sensitivities with respect to the medium electrical properties, the formulation of an optimal objective function based on the weighting methods is not straightforward. While the Bayesian method relies on assumptions with respect to the statistical distribution of the parameters, it may constitute a relevant alternative for GPR and EMI data fusion. Sequential inversions of different configurations for a two layered medium show that in the case of high conductivity or permittivity for the first layer, the inversion scheme can not fully retrieve the soil hydrogeophysical parameters. But in the case of low permittivity and conductivity for the first layer, GPR–EMI inversion provides proper estimation of values compared to the EMI–GPR inversion.
Geophysical Journal International 09/2010; 182(3):1267-1278. · 2.42 Impact Factor
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ABSTRACT: GPR and EMI surveys were carried out in a vineyard in southern France in order to produce high-resolution maps of soil stratigraphy and to retrieve soil hydrogeophysical properties of the different soil layers. The preliminary results presented in this paper show large spatial variations of the vineyard soil properties, which are in accordance with the distribution of the different soil types within the study area. This is particularly observable from soil electrical conductivity data, which show strong spatial correlation with large areas of comparable values delimited by well-defined discontinuities, revealing sharp variations of soil characteristics over short distances. These discontinuities almost systematically correspond to the limits of the vineyard plots, though areas of contrasted soil electrical conductivity values are also found within some plots. Furthermore, the patterns of soil electrical conductivity are in good agreement with soil stratigraphy observed from GPR measurements. Finally, these results also highlighted compaction as a likely explanation to vine vigour problems observed locally in the vineyard. Future work will focus on the full-waveform inversion of GPR and EMI data to retrieve the properties of the different soil layers and to investigate the spatial variation of soil water availability in the study area, and provide on this basis recommendations for the vineyard management.
Ground Penetrating Radar (GPR), 2010 13th International Conference on; 07/2010
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ABSTRACT: We propose a full-waveform approach for modeling time and frequency domain, off-ground and on-ground radars for wave propagation in multilayered media. The radar antennas are modeled using an equivalent set of infinitesimal electric dipoles placed over the antenna aperture. The linear relations between the fields in the transmission line, the sources, and the backscattered fields over the antenna aperture are expressed in terms of frequency dependent, global reflection and transmission coefficients, which are characteristic to the antenna. The interactions between the antenna and the layered medium are thereby accounted for. Far-field and near-field measurements are used to determine these antenna coefficients. The fields over the antenna aperture are calculated using three-dimensional Green's functions. We validated the approach using measurements with a 900 MHz centre frequency transmitting and receiving antenna situated at different heights above a copper plane. For heights larger than the antenna, a single point source and receiver was sufficient for accurately modeling the radar data. For smaller distances, using six sources and receivers provided remarkably good results. Although some simplifications were made in this paper, the proposed method shows great promise for characterizing multilayered media using full-waveform inversion, with very limited computation time compared to numerical methods.
Ground Penetrating Radar (GPR), 2010 13th International Conference on; 07/2010
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ABSTRACT: Electromagnetic parameters of the subsurface such as electrical conductivity are of great interest for non-destructive determination of soil properties (e.g., clay content) or hydrologic state variables (e.g., soil water content). In the past decade, several non-invasive geophysical methods have been developed to measure subsurface parameters in situ. Among these methods, electromagnetic (EM) induction appears to be the most efficient one that is able to cover large areas in a short time. However, this method currently does not provide absolute values of electrical conductivity due to calibration problems, which hinders a quantitative analysis of the measurement. In this study, we propose to calibrate EM induction measurements with electrical conductivity values measured with electrical resistivity tomography (ERT). EM induction measures an apparent electrical conductivity at the surface, which represents a weighted average of the electrical conductivity distribution over a certain depth range, whereas ERT inversion can provide absolute values for local conductivities as a function of depth. EM induction and ERT measurements were collected along a 120-metre-long transect. To reconstruct the apparent electrical conductivity measured with EM induction, the inverted ERT data were used as input in an electromagnetic forward modelling tool for magnetic dipoles over a horizontally layered medium considering the frequencies and offsets used by the EM induction instruments. Comparison of the calculated and measured apparent electrical conductivities shows very similar trends but a shift in absolute values, which is attributed to system calibration problems. The observed shift can be corrected for by linear regression. This new calibration strategy for EM induction measurements now enables the quantitative mapping of electrical conductivity values over large areas.
Near Surface Geophysics. 06/2010; 8(6):553-561.
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ABSTRACT: Retrieval of the subsurface electrical properties from electromagnetic induction �EMI� data using inverse modeling relies in particular on the accuracy of the considered EMImodel. We have developed a new EMI approach whereby a zerooffset, off-ground loop antenna is efficiently modeled using frequency-dependent, complex linear transfer functions and the air subsurface is described by aGreen’s function for wave propagation in 3D multilayered media.To ensure proper calibration of the system, vector network analyzer �VNA� technology is used as the transmitter and receiver. An optimal integration path is proposed for fast evaluation of the spatial Green’s function from its spectral counterpart.We validated the antenna model in laboratory conditions with measurements performed with a loop antenna in free space and at different heights above a perfect electrical conductor. Provided that the loop antenna is high enough above the reflector �offground condition�, the measured and modeled Green’s functions agreed remarkably well. In addition, inversion of the EMI data resulted in accurate estimates of the antenna heights. Yet, as expected, signal-to-noise-ratio issues occurred for the higher antenna heights and frequencies away
from the loop resonant frequency. The method appears to be promising for accurate and robust soil characterization, but needs highVNA dynamic range and antenna gain.
Geophysics. 04/2010; 75(4):WA125-WA134.
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ABSTRACT: We analyzed the effect of shallow thin layers on the estimation of soil surface water content using full-waveform inversion of off-ground ground penetrating radar (GPR) data. Strong dielectric contrasts are expected to occur under fast wetting or drying weather conditions, thereby leading to constructive and destructive interferences with respect to surface reflection. First, synthetic GPR data were generated and subsequently inverted considering different thin-layer model configurations. The resulting inversion errors when neglecting the thin layer were quantified, and then, the possibility to reconstruct these layers was investigated. Second, laboratory experiments reproducing some of the numerical experiment configurations were conducted to assess the stability of the inverse solution with respect to actual measurement and modeling errors. Results showed that neglecting shallow thin layers may lead to significant errors on the estimation of soil surface water content(????>0.03 m<sup>3</sup>/m<sup>3</sup>), depending on the contrast. Accounting for these layers in the inversion process strongly improved the results, although some optimization issues were encountered. In the laboratory, the proposed full-waveform method permitted to reconstruct thin layers with a high resolution up to 2 cm and to retrieve the soil surface water content with an rmse less than 0.02 m<sup>3</sup>/m<sup>3</sup>, owing to the full-waveform inverse modeling. These results suggest that the proposed GPR approach is promising for field-scale mapping of soil surface water content of nondispersive soils with low electrical conductivity and for instances when soil layering is encountered.
IEEE Transactions on Geoscience and Remote Sensing 04/2010; · 2.89 Impact Factor
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Vadose Zone Journal 01/2010; 9(4):1063-1072. · 1.65 Impact Factor
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ABSTRACT: We present a new technique for real-time, proximal sensing of the soil hydrogeophysical properties using ground-penetrating
radar (GPR). The radar system is based on international standard vector network analyser technology, thereby setting up stepped-frequency
continuous-wave GPR. The radar is combined with an off-ground, ultra-wideband, and highly directional horn antenna acting
simultaneously as transmitter and receiver. Full-waveform forward modelling of the radar signal includes antenna propagation
phenomena through a system of linear transfer functions in series and parallel. The system takes into account antenna–soil
interactions and assumes the air–subsurface compartments as a three-dimensional multilayered medium, for which Maxwell’s equations
are solved exactly. We provide an efficient way for estimating the spatial Green’s function as a solution of Maxwell’s equations
from its spectral counterpart by deforming the integration path in the complex plane of the integration variable. Signal inversion
is formulated as a complex least squares problem and is solved iteratively using the global multilevel coordinate search optimisation
algorithm combined with the local Nelder–Mead simplex method. The electromagnetic model has unprecedented accuracy for describing
the GPR signal in controlled laboratory conditions, providing accurate estimates for both soil dielectric permittivity and
electrical conductivity. The proposed method has been specifically designed for the retrieval of soil surface dielectric permittivity
and correlated surface water content, which has been validated in field conditions. We also show that constraining the electromagnetic
inverse problem using hydrodynamic modelling theoretically permits retrieval of the soil hydraulic properties and reconstruction
of continuous vertical water content profiles from time-lapse GPR data. The proposed method shows great promise for field-scale,
high-resolution digital soil mapping, and thereby for bridging the spatial-scale gap between ground truthing based on soil
sampling or local probes and airborne and spaceborne remote sensing.
KeywordsGround-penetrating radar-Multilayered media-Green’s function-Full-waveform inversion
12/2009: pages 299-311;
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ABSTRACT: We present a new integrated method for full-waveform modeling of zero-offset, off-ground ground penetrating radar (GPR) and electromagnetic induction (EMI) in multilayered media. For both GPR and EMI systems, a vector network analyser (VNA) is used as transmitter and receiver. The antennas and their interactions with the investigated medium are modeled in the frequency domain by means of a linear system of complex transfer functions. The air-subsurface is represented by a 3-D multilayered medium, for which Maxwell's equations are exactly solved. These approaches have been validated in laboratory conditions, demonstrating the high accuracy of the GPR and EMI models. The results show great promise for non-invasive reconstruction of multilayered media using GPR and EMI.
Microwave Symposium (MMS), 2009 Mediterrannean; 12/2009
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ABSTRACT: We propose a unified full-waveform method for modeling zero-offset, off-ground ground penetrating radar (GPR) and electromagnetic induction (EMI) in multilayered media. Both GPR and EMI systems are set up using vector network analyzer technology. The antennas are modeled using frequency dependent, complex transfer functions, which include interactions with the medium layers. Wave propagation and induction effects are accounted for by means of three-dimensional (3-D) Green's functions. Laboratory results demonstrated the high accuracy of the GPR and EMI models. This shows great promise for non-destructive characterization of soil and materials.
Electromagnetics in Advanced Applications, 2009. ICEAA '09. International Conference on; 10/2009
