Waveform Inversion of Crosshole Georadar Data: Influence of Source Wavelet Variability and the Suitability of a Single Wavelet Assumption

Belina, F.A.; Irving, James; Ernst, Jacques; Holliger, Klaus

doi:10.1109/tgrs.2012.2194154

Cited by 20 publications

(11 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FWI has been applied to interpret GPR data for approximately 20 years [13][14][15][16][17][18]. However, building accurate initial models is a challenge in the development of FWI.…”

Section: Discussionmentioning

confidence: 99%

“…The resolution of ray theory tomography is around the width of the first Fresnel-zone [8,9]. Full-waveform inversion (FWI) was first applied in seismic exploration (e.g., [10][11][12]) and was subsequently introduced to GPR (e.g., [13][14][15][16][17][18]). Under the most ideal conditions, the resolution of FWI can reach up to the scale of half the propagated wavelength [19].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application of Laplace Domain Waveform Inversion to Cross-Hole Radar Data

Meng

Liu

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

Full waveform inversion (FWI) can yield high resolution images and has been applied in Ground Penetrating Radar (GPR) for around 20 years. However, appropriate selection of the initial models is important in FWI because such an inversion is highly nonlinear. The conventional way to obtain the initial models for GPR FWI is ray-based tomogram inversion which suffers from several inherent shortcomings. In this paper, we develop a Laplace domain waveform inversion to obtain initial models for the time domain FWI. The gradient expression of the Laplace domain waveform inversion is deduced via the derivation of a logarithmic object function. Permittivity and conductivity are updated by using the conjugate gradient method. Using synthetic examples, we found that the value of the damping constant in the inversion cannot be too large or too small compared to the dominant frequency of the radar data. The synthetic examples demonstrate that the Laplace domain waveform inversion provide slightly better initial models for the time domain FWI than the ray-based inversion. Finally, we successfully applied the algorithm to one field data set, and the inverted results of the Laplace-based FWI show more details than that of the ray-based FWI.

show abstract

“…FWI has been applied to interpret GPR data for approximately 20 years [13][14][15][16][17][18]. However, building accurate initial models is a challenge in the development of FWI.…”

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of Laplace Domain Waveform Inversion to Cross-Hole Radar Data

Meng

Liu

et al. 2019

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…To our knowledge, full waveform inversion (FWI) applied on tree monitoring has not been reported to the literature. FWI is a powerful tool for interpreting GPR data [22], [23], [24], nonetheless, its high computational requirements combined with the need for an accurate antenna model incorporated in the forward solver [25] make implementation of FWI to GPR a laborious process with limited commercial applications.…”

Section: Introductionmentioning

confidence: 99%

Health Monitoring of Tree Trunks Using Ground Penetrating Radar

Giannakis

Tosti

Lantini

et al. 2019

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Ground penetrating radar (GPR) is traditionally applied to smooth surfaces in which the assumption of halfspace is an adequate approximation that does not deviate much from reality. Nonetheless, using GPR for internal structure characterization of tree trunks requires measurements on an irregularly shaped closed curve. Typical hyperbola-fitting has no physical meaning in this new context since the reflection patterns are strongly associated to the shape of the tree trunk. Instead of a clinical hyperbola, the reflections give rise to complex-shaped patterns that are difficult to be analyzed even in the absence of clutter. In the current paper, a novel processing scheme is described that can interpret complex reflection patterns assuming a circular target subject to any arbitrary shaped surface. The proposed methodology can be applied using commercial handheld antennas in real-time avoiding computationally costly tomographic approaches that require the usage of custom-made bespoke antenna arrays. The validity of the current approach is illustrated both with numerical and real experiments.

show abstract

“…In particular, a hybrid least-squares/simplex-search FWI is employed in [40], assuming a homogeneous half space and using a single dipole to describe the antenna system. In [41] and [42] a FWI scheme is proposed in which the pulse is part of the unknowns and the applicability of multiple wavelets is examined to address the fact that the effective wavelet is affected by the location of the transmitter. This results from describing the antenna with a single point source without incorporating its physical structure in the numerical model.…”

Section: Introductionmentioning

confidence: 99%

Realistic FDTD GPR Antenna Models Optimized Using a Novel Linear/Nonlinear Full-Waveform Inversion

Giannakis

Giannopoulos

Warren

2019

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Finite-Difference Time-Domain (FDTD) forward modelling of Ground Penetrating Radar (GPR) is becoming regularly used in model-based interpretation methods like full waveform inversion (FWI) and machine learning schemes. Oversimplifications in such forward models can compromise the accuracy and realism with which real GPR responses can be simulated, which degrades the overall performance of interpretation techniques. A forward model must be able to accurately simulate every part of the GPR problem that affects the resulting scattered field. A key element, especially for near-field applications, is the antenna system. Therefore the model must contain a complete description of the antenna, including the excitation source and waveform, the geometry, and the dielectric properties of any materials in the antenna. The challenge is that some of these parameters are not known or cannot be easily measured, especially for commercial GPR antennas that are used in practice. We present a novel hybrid linear/nonlinear FWI approach which can be used, with only knowledge of the basic antenna geometry, to simultaneously optimise the dielectric properties and excitation waveform of the antenna, and minimise the error between real and synthetic data. The accuracy and stability of our proposed methodology is demonstrated by successfully modelling a Geophysical Survey Systems (GSSI) Inc. 1.5 GHz commercial antenna. Our framework allows accurate models of GPR antennas to be developed without requiring detailed knowledge of every component of the antenna. This is significant because it allows commercial GPR antennas, regularly used in GPR surveys, to be more readily simulated.

show abstract

Waveform Inversion of Crosshole Georadar Data: Influence of Source Wavelet Variability and the Suitability of a Single Wavelet Assumption

Cited by 20 publications

References 61 publications

Application of Laplace Domain Waveform Inversion to Cross-Hole Radar Data

Application of Laplace Domain Waveform Inversion to Cross-Hole Radar Data

Health Monitoring of Tree Trunks Using Ground Penetrating Radar

Realistic FDTD GPR Antenna Models Optimized Using a Novel Linear/Nonlinear Full-Waveform Inversion

Contact Info

Product

Resources

About