A Ground Penetrating Radar Data Reconstruction Method Based on Generation Networks

In this paper, a ground penetrating radar (GPR) data reconstruction method based on generation networks is proposed. The main purpose of this method is to reconstruct the GPR data from degraded data such as missing traces data and sparse sampling data. The generation networks can obtain the reconstructed GPR data by training the network mapping degraded data from a two-dimensional random sequence. It can be used for obtaining denser GPR data and recovering missing GPR traces. Both simulated and field data are used to illustrate the validity. It could still be well reconstructed after 50% of the traces were removed.