Abstract

ABSTRACTInversion of ground‐penetrating radar signals requires accurate and efficient forward modelling. The symplectic Euler method promises good results when simulating ground‐penetrating radar wave propagation in substructures, but its computational efficiency is limited by the same Courant–Friedrichs–Lewy stability condition as the finite‐difference time‐domain method. A two‐dimensional graphics processor unit–accelerated parallel symplectic Euler algorithm is used to simulate ground‐penetrating radar wave propagation. We compared the reflection waveforms as well as the simulation time of the complex underground structure models simulated by the parallel symplectic Euler method with traditional finite‐difference time‐domain method. Results show that the parallel symplectic Euler algorithm achieves the same level of accuracy as the standard finite‐difference time‐domain method. Moreover, it significantly improves the computational efficiency, as the calculation speed is improved by more than 21 times. We verify the performance of the proposed algorithm through a map of the single‐track radar data for a three‐layered pavement model and a simulation wiggle map for a structural damage pavement model. This provides a theoretical basis for accurately interpreting ground‐penetrating radar detection data and efficient forward modelling for the next step of inversion imaging.

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