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Ground-penetrating radars operating at a stand-off distance from the probed domain are attractive diagnostic tools in several contexts. Despite notable advantages offered in terms of noninvasiveness and flexibility, the usage of stand-off configurations makes the imaging process more difficult. Indeed, an accurate reconstruction of the subsurface/hidden scene requires accounting for the presence of the air–soil interface into the scattering model. This article deals with a comparison of three different linear models for describing the scattering phenomenon under a stand-off configuration, where the presence of the layered medium is explicitly accounted for in the scattering model. The first model is rigorous and based on the spectral domain representation of the incident field and Green’s function for the half-space scenario. The second model exploits a ray representation of the wave propagation from the radar to the target and vice versa by accounting for the refraction phenomenon at the interface. The third model is an approximated one, where the layered nature of the scenario is taken into account by means of an equivalent wavenumber, which allows a straightforward evaluation of the incident field and Green’s function. The resolution performance of each inversion approach is assessed by means of a numerical analysis. Moreover, data referred to an experiment carried out in controlled conditions are processed and reconstructions are provided to support the comparative analysis among the three imaging approaches. [ABSTRACT FROM AUTHOR]

Horizontally stratified media are commonly used to represent naturally occurring and man-made structures, such as soils, roads, and pavements, when probed by ground-penetrating radar (GPR). Electromagnetic (EM) wave scattering from such multilayered media is dependent on the roughness of the interfaces. In this paper, we developed a closed-form asymptotic EM model considering random rough layers based on the scalar Kirchhoff-tangent plane approximation (SKA) model that we combined with planar multilayered media Green’s functions. In order to validate our extended SKA model, we conducted simulations using a numerical EM solver based on the finite-difference time-domain (FDTD) method. We modeled a medium with three layers—a base layer of perfect electric conductor (PEC) overlaid by two layers of different materials with rough interfaces. The reflections at the first and at the second interface were both well reproduced by the SKA model for each roughness condition. For the reflection at the PEC surface, the extended SKA model slightly overestimated the reflection, and this overestimation increased with the roughness amplitude. Good agreement was also obtained between the FDTD simulation input values and the inverted root mean square (rms) height estimates of the top interface, while the inverted rms heights of the second interface were slightly overestimated. The accuracy and the performances of our asymptotic forward model demonstrate the promising perspectives for simulating rough multilayered media and, hence, for the full waveform inversion of GPR data to noninvasively characterize soils and materials. [ABSTRACT FROM AUTHOR]

Limestone has been a widely used building material for many years. Its degradation process has been strongly linked to its water content, to which the radar waves are sensitive. In this paper, the closed-form, near-field full-wave radar model of Lambot et al. is utilized for monitoring water ingress in limestone. This model is based on planar layered media Green's functions combined with an intrinsic representation of the antenna through global reflection and transmission functions. The Jonscher model is used to describe the frequency dependence of the limestone electromagnetic properties. Then, an inversion method based on a genetic algorithm is developed and optimized. The method is numerically validated by simulating electromagnetic wave propagation in medias, using a three-dimensional finite element software, namely high-frequency electromagnetic field simulation. Finally, the method is experimentally validated, with a stepped-frequency radar system and an ultrawide band antenna, during an imbibition process of a limestone slab. Results are compared to gammadensimetry measurements, a nuclear and semidestructive approach, performed as the reference. Analyses of the results show that the average relative difference between the estimated and the reference water front is 2.5%, thereby demonstrating the performance of the proposed nondestructive method. [ABSTRACT FROM PUBLISHER]

We present a closed-form equation for intrinsic modeling of near-field electromagnetic induction (EMI) antennas for planar layered media characterization. Resorting to a decomposition of the backscattered EM field into elementary distributions over the antenna aperture, the EMI transmitting and receiving antennas are modeled using infinitesimal magnetic dipoles and field points, and characteristic frequency-dependent global reflection and transmission coefficients. Low-frequency propagation of the EM fields in the medium is described using 3-D planar layered media Green's functions. We performed measurements with a loop antenna situated at different heights, ranging from near-field to far-field conditions, above water of known electrical conductivity to determine its intrinsic properties, and a range of salinity conditions was applied to subsequently validate the proposed model. The EMI system was set up using a vector network analyzer equipped with a prototype EMI antenna specifically designed for this application. The model showed good accuracy for reproducing the observed data, and model inversion provided good estimates of the medium electrical conductivity. Yet, insensitivity of the EMI signal to water electrical conductivity was encountered for low salinity due to the presence of a copper sheet as the bottom boundary condition of the experimental setup. Moreover, the efficiency of the antenna decreased rapidly as antenna height above water surface increases, leading to increasing discrepancies between estimated and measured water electrical conductivity values as the antenna moves away from the water surface. Although some technical improvements are still needed, the proposed approach is promising for quantitative estimation of soil electrical conductivity from EMI data. [ABSTRACT FROM PUBLISHER]

A new near-field radar modeling approach for wave propagation in planar layered media is presented. The radar antennas are intrinsically 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. The interactions between the antenna and layered medium are thereby inherently accounted for. The fields are calculated using 3-D Green's functions. We validated the model using an ultrawideband frequency-domain radar with a transmitting and receiving Vivaldi antenna operating in the range 0.8-4 GHz. The antenna characteristic coefficients are obtained from near- and far-field measurements over a copper plane. The proposed model provides unprecedented accuracy for describing near-field radar measurements collected over a water layer, the frequency-dependent electrical properties of which were described using the Debye model. Layer thicknesses could be retrieved through full-wave inversion. The proposed approach demonstrated great promise for nondestructive testing of planar materials and digital soil mapping using ground-penetrating radar. [ABSTRACT FROM AUTHOR]

The characterization of the subsurface can be performed by full-waveform inversion of electromagnetic data. The modeling process relies on the ability to retrieve the scattered field Green's function from the measured data using sets of antenna characteristic global reflection and transmission coefficients. Crucial for a successful implementation of this technique is the understanding of uncertainties involved in the acquisition of the antenna calibration and survey measurements, and how these propagate in the parameter estimation results. We find that averaging a number of possible Green's functions obtained from one measurement with several antenna characteristic coefficients sets works remarkably well in reducing the uncertainties. The accuracy of the inversions improves using characteristic coefficients acquired as close as possible to the measurement conditions. A clear relation between dynamic range and system resolution is highlighted, based on the number of effective bits contained in the data. [ABSTRACT FROM PUBLISHER]