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

Abstract

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.

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

“…Nonetheless, the absence of an actual antenna decreases somewhat the general applicability of the approach. In addition, wavelet estimation based on deconvolution is an ill-posed problem that without any regularization can lead to non-unique results [40]. Lastly, the forward-solver, is still a time-consuming routine that, when coupled with a global optimizer, greatly increases the computational requirements of the inversion.…”

The Use of Ground Penetrating Radar and Microwave Tomography for the Detection of Decay and Cavities in Tree Trunks

“…The spatial discretisation step of the problem was fixed at ∆ = 2 mm and the time step at ∆t = 3.84 ps (Courant limit). Regarding the excitation, a modelled equivalent of the GSSI 1.5 GHz signal, was used [73]. Table 1 shows the dielectric properties of the tree layers used for the numerical simulations, which were derived from the available literature [58].…”

Finite difference time domain modelling as support to ground penetrating radar surveys of precast concrete units

“…Complex structures (either geometrically or electrically) can be modelled using simulators able to reproduce commercial antenna characteristics to obtain realistic pulses (Warren, Giannopoulos and Giannakis ) even with the only knowledge of the basic antenna geometry (Giannakis, Giannopoulos and Warren ), modelling the concrete as electrically heterogeneous (adding its dispersion properties as described in Lachowicz and Rucka ) or considering simulators capable of sub‐gridding techniques as reported in Diamanti and Giannopoulos (), Wei et al . () and Hartley, Giannopoulos and Warren () to get fine details in critical areas of the elements to be simulated at reasonable computational costs.…”