Abstract

Numerical modelling of Ground Penetrating Radar (GPR) using the Finite-Difference Time-Domain (FDTD) method can be computationally intensive when large volumes must be discretised at fine spatial resolutions. This requirement exists because of the conditionally explicit nature of the FDTD algorithm, and the need to simulate fine geometrical details as commonly found in GPR antennas or in regions of high permittivity dielectric materials. We have developed and implemented a Huygens subgridding (HSG) approach in the open source software gprMax. The HSG can be applied to multiple localised regions of the FDTD grid where it is required, whilst the rest of the grid can be discretised at a more appropriate spatial resolution. An example of applying the HSG to a GPR model that includes a detailed antenna model, demonstrates the accuracy and efficiency of the approach. The relative error compared with a uniform fine grid is generally less than 1.3%. The computational time is reduced by a factor of 16. This level of computational saving is especially important for optimisation and inversion algorithms where many GPR forward models are computed in a single iteration.

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