Developing Realistic FDTD GPR Antenna Surrogates by Means of Particle Swarm Optimization

The antenna is the most important part of a ground-penetrating radar (GPR) system and defines the employed electromagnetic pulse and how it is transferred to the ground. It is crucial to account for these coupling effects in numerical simulations and to implement realistic antenna models, e.g., for full-waveform inversion (FWI). We present a method of developing and adapting 3-D finite-difference time-domain (FDTD) models of GPR antennas, complete with electric components, dielectric material properties, and feed pulse details. We exemplify this with a commercially available, shielded 400 MHz GPR antenna, a model of which was set up by fitting synthetic data to an experimental signal of the antenna reflected at a metal plate in the air. For this FWI, we used a particle swarm optimization (PSO) algorithm because the fit parameters show complex individual effects on the GPR waveform. The resulting antenna model is then validated against data measured in air, water, and with a metal plate in the near field of the antenna. Overall, the synthetic data reproduce the validation data very accurately. Signals of objects placed in the near field of the antenna and the change of the shape and frequency content of the radiated wavelet with varying subsurface properties are emulated correctly.

Automated summary

This paper presents a method for developing and adapting 3-D finite-difference time-domain models of ground-penetrating radar (GPR) antennas. The models are validated against measured data and are shown to accurately reproduce synthetic data. The method involves fitting synthetic data to an experimental signal and using a particle swarm optimization algorithm for full-waveform inversion. The resulting antenna models successfully emulate signals in the near field and the changes in wavelet shape and frequency content with varying subsurface properties.