GPR Least-Squares Reverse Time Migration Based on the Improved Cross-Correlation Window

Ground penetrating radar (GPR) migration is a crucial imaging method to obtain the spatial position, size, and shape of the underground structures. However, Kirchhoff migration, finite-difference migration, F-K migration, and reverse time migration (RTM) focus on geometric structure imaging and cannot provide realistic reflection coefficients. Least-squares reverse time migration (LSRTM) regards imaging as an inversion problem in the sense of least squares. It continuously corrects the imaging results by minimizing the residual between the simulated data and the observed data to obtain realistic reflection coefficients. In order to enhance the accuracy of the LSRTM result, we introduce the cross-correlation window to suppress artifacts and noise. Although the non-interface information in the gradient is effectively suppressed, the cross-correlation window will cause new noise to appear. This makes the LSRTM result unsatisfactory because the window is used multiple times in the calculation. Therefore, we proposed the improved cross-correlation window that utilizes the Block-matching and 3D Filtering (BM3D). This improvement preserves the ability of eliminating artifacts while preventing the window from introducing new noise. Experiments results with the synthetic data and the measured data demonstrate that compared with the traditional methods, the LSRTM based on the improved cross-correlation window suppresses noise, reduces artifacts, enhances clarity of the interfaces, and achieves higher imaging accuracy.