Inversion of dispersive GPR pulse propagation in waveguides with heterogeneities and rough and dipping interfaces

Kruk, Jan van der; Diamanti, Nectaria; Giannopoulos, Antonios; Vereecken, Harry

doi:10.1016/j.jappgeo.2011.09.013

Cited by 21 publications

(17 citation statements)

References 30 publications

(33 reference statements)

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“…An alternative explanation for the second mode is disturbance introduced by interface roughness (compare Van der Kruk et al . []) or lateral changes in waveguide properties.…”

Section: Field Experiments and Resultsmentioning

confidence: 99%

Waveguide properties recovered from shallow diffractions in common offset GPR

et al. 2013

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[1] Near-surface heterogeneities produce diffractions in common offset ground-penetrating radar (GPR) data from the Gnangara Groundwater Mound, north of Perth, Western Australia. These diffracted wavefields can be enhanced and show a dispersion pattern if they propagate along a waveguide caused by a low velocity surface layer, such as moist sand on top of dry sand. Until now, GPR waveguide dispersion has been analyzed and inverted using common midpoint data. Using numerical modeling, we demonstrate that the same dispersion information can also be recovered from a diffracted electromagnetic wavefield recorded with common offset geometry. Frequency-slowness analysis of shallow diffractions in common offset GPR field data reveals high resolution dispersion curves. Inverting picked dispersion maxima to modeled curves (i.e., modal wave propagation in waveguide layer) allows estimation of waveguide height and velocities of waveguide and the underlying material. Data analysis in the frequency-wavenumber domain provides an alternative technique for extracting dispersion curves. Preliminary results validate this approach, which could be favorable in large-scale applications due to minimal processing requirement and inherent yet adjustable spatial averaging. The differences between waveguide parameters recovered from two surveys appear to be consistent with seasonal changes in moisture content and lateral changes due to variations in depositional environment. Our approach presents a new method to quantify the shallow dielectric permittivity structure of the subsurface from common offset gathers-the most commonly acquired type of GPR data. Potential applications of this method include estimation of shallow moisture distribution, early target identification for unexploded ordnance (UXO) detection, concrete slab characterization, pedological investigations, or planetary exploration.

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“…An alternative explanation for the second mode is disturbance introduced by interface roughness (compare Van der Kruk et al . []) or lateral changes in waveguide properties.…”

Section: Field Experiments and Resultsmentioning

confidence: 99%

Waveguide properties recovered from shallow diffractions in common offset GPR

et al. 2013

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“…In civil engineering, high resolution methods used to estimate the thickness of thin pavements are based on the assumption that the interfaces of the layers are flat. This paper presents a high resolution method by taking the roughness of the interfaces [5] into account. The media are assumed to be lossless.…”

Section: Introductionmentioning

confidence: 99%

Estimation of time delay and roughness parameters by GPR using esprit method

Sun

Bastard

Pinel³

et al. 2014

2014 IEEE Geoscience and Remote Sensing Symposium

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In civil engineering, ground penetrating radar is widely used for road pavement surveys. In this paper, the influence of interface roughness is taken into account. We propose a Modified ESPRIT algorithm for the data processing of radar signal, in order to jointly estimate the time delay and the interface roughness. The algorithm is tested on simulated data from the propagation inside layer expansion (PILE) method. Numerical examples are provided to demonstrate the performance of the algorithm.

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“…Numerical simulation of GPR is an efficient way to analyse probing problems and to study the EM (electromagnetic) wave propagation inside the considered medium. Ray tracing, FEA (finite elements analysis) and FDTD (frequency difference time domain) methods like GprMax (Giannopoulos ) are some common methods for numerical simulation, which are widely used for simulating the GPR response (Spagnolini et al ; Spagnolini et al ; Benedetto et al ; Giannopoulos et al ; Diamanti and Redman ; Van der Kruk et al ) over typical road diseases (surface cracks, base cracks and base replacements). Numerical simulation is sometimes also used for taking the surface roughness into account but generally only one rough interface is considered: either the upper surface (Lambot et al ; Jonard et al ) or the embedded interface (Giannopoulos and Diamanti ; Van der Kruk et al ).…”

Section: Introductionmentioning

confidence: 99%

“…The associated results show that the proposed algorithm can estimate both the time delay and roughness parameters with a small relative error. face roughness into account but generally only one rough interface is considered: either the upper surface (Lambot et al 2006;Jonard et al 2012) or the embedded interface (Giannopoulos and Diamanti 2008; Van der Kruk et al 2012). Nevertheless, these methods have a high computational complexity and/or a restricted domain of validity.…”

mentioning

confidence: 99%

Time delay and interface roughness estimations by GPR for pavement survey

Sun

Pinel²,

Bastard

et al. 2014

Near Surface Geophysics

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In civil engineering, ground‐penetrating radar is widely used for road pavement surveys. In contrast to the existing literature, this paper takes account of the influence of interface roughness (surface and interlayer roughness) within the scope of data processing of radar signals. The rigorous electromagnetic method PILE (Propagation Inside Layer Expansion) provides simulated data that show the influence of the interface roughness on the backscattered primary echoes of stratified media; the interface roughness provides a continuous frequency decay of the magnitude of the echoes. The observed frequency variations of the radar magnitude introduce some shape distortion on the radar waveform. The latter variations can be modelled by an exponential function, which provides satisfactory results for a narrow bandwidth (2 GHz). An adaptation of the root‐MUSIC algorithm is proposed. As a result, it is possible to jointly estimate the time delay and the interface roughness. The algorithm is tested on data simulated by the PILE method and numerical examples are provided to assess the performance of this algorithm. The associated results show that the proposed algorithm can estimate both the time delay and roughness parameters with a small relative error.

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Inversion of dispersive GPR pulse propagation in waveguides with heterogeneities and rough and dipping interfaces

Cited by 21 publications

References 30 publications

Waveguide properties recovered from shallow diffractions in common offset GPR

Waveguide properties recovered from shallow diffractions in common offset GPR

Estimation of time delay and roughness parameters by GPR using esprit method

Time delay and interface roughness estimations by GPR for pavement survey

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