An improved bicubic imaging fitting algorithm for 3D radar detection target

3D ground-penetrating radar has been widely used in urban road underground disease detection due to its nondestructive, efficient, and intuitive results. However, the 3D imaging of the underground target body presents the edge plate phenomenon due to the space between the 3D radar array antennas. Consequently, direct 3D imaging using detection results cannot reflect underground spatial distribution characteristics. Due to the wide-beam polarization of the ground-penetrating radar antenna, the emission of electromagnetic waves with a specific width decreases the strong middle energy on both sides gradually. Therefore, a bicubic high-precision 3D target body slice-imaging fitting algorithm with changing trend characteristics is constructed by combining the subsurface target characteristics with the changing spatial morphology trends. Using the wide-angle polarization antenna’s characteristics in the algorithm to build the trend factor between the measurement lines, the target body change trend and the edge detail portrayal achieve a 3D ground-penetrating radar-detection target high-precision fitting. Compared with other traditional fitting techniques, the fitting error is small. This paper conducts experiments and analyses on GpaMax 3D forward modeling and 3D ground-penetrating measured radar data. The experiments show that the improved bicubic fitting algorithm can effectively improve the accuracy of underground target slice imaging and the 3D ground-penetrating radar’s anomaly interpretation.