3D prestack reverse time migration of ground penetrating radar data based on the normalized correlation imaging condition

The reverse time migration (RTM) of ground penetrating radar (GPR) is usually implemented in its two-dimensional (2D) form, due to huge computational cost. However, 2D RTM algorithm is difficult to focus the scattering signal and produce a high precision subsurface image when the object is buried in a complicated subsurface environment. To better handle the multi-offset GPR data, we propose a three-dimensional (3D) prestack RTM algorithm. The high-order finite difference time domian (FDTD) method, with the accuracy of eighth-order in space and second-order in time, is applied to simulate the forward and backward extrapolation electromagnetic fields. In addition, we use the normalized correlation imaging condition to obtain pre-stack RTM result and the Laplace filter to suppress the low frequency noise generated during the correlation process. The numerical test of 3D simulated GPR data demonstrated that 3D RTM image shows excellent coincidence with the true model. Compared with 2D RTM image, the 3D RTM image can more clearly and accurately reflect the 3D spatial distribution of the target, and the resolution of the imaging results is far better. Furthermore, the application of observed GPR data further validates the effectiveness of the proposed 3D GPR RTM algorithm, and its final image can more reliably guide the subsequent interpretation.