Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm

Ground-Penetrating Radar (GPR) has demonstrated significant advantages in the non-destructive detection of road structural defects due to its speed, safety, and efficiency. This paper proposes a three-dimensional (3D) reconstruction method for GPR images, integrating the back-projection (BP) imaging algorithm to accurately determine the size, location, and other parameters of road structural defects. Initially, GPR detection images were preprocessed, including direct wave removal and wavelet denoising, followed by the application of the BP algorithm to effectively restore the defect's location and size. Subsequently, a 3D data set was constructed through interpolation, and the effective reflection data were extracted by using a clustering algorithm. This algorithm distinguished the effective reflection data from the background data by determining the distance threshold between the data points. The 3D imaging of the defect was then performed in MATLAB. The proposed method was validated using both gprMax simulations and laboratory test models. The experimental results indicate that the correlation between the reconstructed and actual defects was approximately 0.67, demonstrating the method's efficacy in accurately achieving the 3D reconstruction of road structural defects.