FIELD-SCALE GROUND-PENETRATING-RADAR TOMOGRAPHY AND UNCERTAINTY QUANTIFICATION THROUGH ENTROPY-BASED BAYESIAN INVERSION

2013 ◽  
Author(s):  
Neil Terry ◽  
Zhangshuan Hou ◽  
Susan S. Hubbard
Keyword(s):  
Uncertainty Quantification ◽  
Ground Penetrating Radar ◽  
Bayesian Inversion ◽  
Field Scale ◽  
Ground Penetrating

scholarly journals Evaluation of a Straight-Ray Forward Model for Bayesian Inversion of Crosshole Ground Penetrating Radar Data

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 630 ◽  
Author(s):  
Hui Qin ◽  
Xiongyao Xie ◽  
Yu Tang
Keyword(s):  
Ground Penetrating Radar ◽  
Computational Cost ◽  
Measurement Data ◽  
Forward Model ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Model Parameters ◽  
Model Structure ◽  
Modeling Error ◽  
Ground Penetrating

Bayesian inversion of crosshole ground penetrating radar (GPR) data is capable of characterizing the subsurface dielectric properties and qualifying the associated uncertainties. Markov chain Monte Carlo (MCMC) simulations within the Bayesian inversion usually require thousands to millions of forward model evaluations for the parameters to hit their posterior distributions. Therefore, the CPU cost of the forward model is a key issue that influences the efficiency of the Bayesian inversion method. In this paper we implement a widely used straight-ray forward model within our Bayesian inversion framework. Based on a synthetic unit square relative permittivity model, we simulate the crosshole GPR first-arrival traveltime data using the finite-difference time-domain (FDTD) and straight-ray solver, respectively, and find that the straight-ray simulator runs 450 times faster than its FDTD counterpart, yet suffers from a modeling error that is more than 7 times larger. We also perform a series of numerical experiments to evaluate the performance of the straight-ray model within the Bayesian inversion framework. With modeling error disregarded, the inverted posterior models fit the measurement data nicely, yet converge to the wrong set of parameters at the expense of unreasonably large number of iterations. When the modeling error is accounted for, with a quarter of the computational burden, the main features of the true model can be identified from the posterior realizations although there still exist some unwanted artifacts. Finally, a smooth constraint on the model structure improves the inversion results considerably, to the extent that it enhances the inversion accuracy approximating to those of the FDTD model, and further reduces the CPU demand. Our results demonstrate that the use of the straight-ray forward model in the Bayesian inversion saves computational cost tremendously, and the modeling error correction together with the model structure constraint are the necessary amendments that ensure that the model parameters converge correctly.

scholarly journals Validation of ground penetrating radar full-waveform inversion for field scale soil moisture mapping

2012 ◽  
Vol 424-425 ◽  
pp. 112-123 ◽  
Author(s):  
Julien Minet ◽  
Patrick Bogaert ◽  
Marnik Vanclooster ◽  
Sébastien Lambot
Keyword(s):  
Soil Moisture ◽  
Ground Penetrating Radar ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Field Scale ◽  
Full Waveform ◽  
Ground Penetrating

scholarly journals Mapping shallow soil moisture profiles at the field scale using full-waveform inversion of ground penetrating radar data

Geoderma ◽  
2011 ◽  
Vol 161 (3-4) ◽  
pp. 225-237 ◽  
Author(s):  
Julien Minet ◽  
Agung Wahyudi ◽  
Patrick Bogaert ◽  
Marnik Vanclooster ◽  
Sébastien Lambot
Keyword(s):  
Soil Moisture ◽  
Ground Penetrating Radar ◽  
Waveform Inversion ◽  
Radar Data ◽  
Full Waveform Inversion ◽  
Field Scale ◽  
Full Waveform ◽  
Shallow Soil ◽  
Ground Penetrating ◽  
Moisture Profiles

Uncertainty Quantification in Off-Ground Monostatic Ground Penetrating Radar

2013 ◽  
Vol 61 (6) ◽  
pp. 3334-3344 ◽  
Author(s):  
Claudio Patriarca ◽  
Mattia Miorali ◽  
Evert Slob ◽  
Sebastien Lambot
Keyword(s):  
Uncertainty Quantification ◽  
Ground Penetrating Radar ◽  
Ground Penetrating

Optimization of multi-channel ground-penetrating radar for quantifying field-scale soil water dynamics

2012 ◽  
Vol 82 ◽  
pp. 101-109 ◽  
Author(s):  
Xicai Pan ◽  
Ute Wollschläger ◽  
Holger Gerhards ◽  
Kurt Roth
Keyword(s):  
Soil Water ◽  
Ground Penetrating Radar ◽  
Water Dynamics ◽  
Field Scale ◽  
Soil Water Dynamics ◽  
Ground Penetrating

Mapping Field-Scale Soil Moisture With L-Band Radiometer and Ground-Penetrating Radar Over Bare Soil

2011 ◽  
Vol 49 (8) ◽  
pp. 2863-2875 ◽  
Author(s):  
François Jonard ◽  
Lutz Weihermuller ◽  
Khan Zaib Jadoon ◽  
Mike Schwank ◽  
Harry Vereecken ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Ground Penetrating Radar ◽  
Bare Soil ◽  
Field Scale ◽  
L Band ◽  
Ground Penetrating ◽  
Band Radiometer
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