Estimation of subsurface cylindrical object properties from GPR full-waveform inversion

A Machine Learning-Based Fast-Forward Solver for Ground Penetrating Radar With Application to Full-Waveform Inversion

“…It also overcomes the problem of instabilities due to differences in sensitivity between permittivity and conductivity [49], [50]. This is the reason why a two-step procedure is used in the FWI by [39] (similar to that of [50]), in which an initial permittivity is estimated and subsequently, subject to the derived permittivity an optimized conductivity is calculated. Relating the dielectric properties to the water fraction overcomes these aforementioned instabilities, and furthermore accelerates the overall inversion process.…”

“…In [38] it is shown that using a Kirchoff-based linearized inversion can effectively recover some information regarding the shape of the targets regardless of the medium velocity. In the same context, a FWI approach is suggested in [39] to estimate the host medium properties and the size and depth of a steel rebar. The suggested inversion assumes a simplified source but the source wavelet is one of the unknowns and is evaluated through a deconvolution in each iteration step.…”

Two-Dimensional Linear Inversion of GPR Data with a Shifting Zoom along the Observation Line

“…The problem at hand inserts into the framework of microwave tomography from GPR data, which has been largely investigated in the literature, both from the point of view of the imaging algorithms [30][31][32][33] and from the point of view of the effects of the soil and antennas on the data [34][35][36]. Applications to cases in the field have been also presented, e.g., in [37,38].…”

A Machine Learning Scheme for Estimating the Diameter of Reinforcing Bars Using Ground Penetrating Radar

“…However, these methods are based on simplified assumptions and they fail to provide a universal and reliable solution [11]. To tackle this, a detection algorithm based on full-waveform inversion (FWI) using shuffled complex evolution optimization has been suggested [18]. FWI is a holistic approach that keeps simplifications to a minimum and exploits all the available information embedded in the investigated signal.…”

“…FWI is a holistic approach that keeps simplifications to a minimum and exploits all the available information embedded in the investigated signal. This gives rise to a robust detection tool that accurately manages to recover both the coordinates and the diameter of buried cylindrical targets [18]. Nonetheless, FWI is a time-consuming process, primarily due to the large computational resources necessary for the numerical evaluation of Maxwell's equations.…”