Multi-fold, multi-component and multi-azimuth GPR for subsurface imaging and material characterization

GPR can provide shallow subsurface images sharper than any other geophysical technique in the 0-5 m depth range and quantitative information about EM properties of materials. It is therefore best suited for the noninvasive high-resolution study of the near surface. Advances in UWB equipment and dedicated data processing methods have recently improved performances of GPR and fostered the successful application of the method at depths ranging from a few centimeters (UXO detection) to different kilometers (glaciology), as illustrated by several examples in this book. The two crucial tasks of the noninvasive method, namely sub-surface imaging and characterization of materials, are best accomplished by GPR methods that exploit redundant information. In this Section we show examples of successful application of such techniques, in particular linear multi-fold, azimuthal multi-fold and multi-polarization (multi-component) methods. Focusing of the radar wave field and clutter reduction are the key issues in image enhancement. Focusing is based on migration techniques that require knowledge of the velocity of radar waves in the sub-surface. Clutter reduction benefits from multiple data from the same sub-surface location. Multi-fold methods can provide an adequate solution for both problems. Target characterization implies reconstruction of images where properties of sub-surface scatterers are correctly represented. Multi-component imaging algorithms can accomplish such tasks, which exploit knowledge of transmitter and receiver antenna radiation characteristics and incorporate wave speed, polarization and amplitude of the scattered electric field. However, the data acquisition and computational costs of such methods do not presently allow their extensive application but for academic purposes. An alternative strategy is based on the analysis of amplitude variations versus azimuth and offset at different polarizations. The cost of such approaches is limited and the technique allows us to optimize data acquisition parameters in single-fold and multi-fold surveys depending on target characteristics.