Radar scattering models for the identification of buried low-metal content landmines

Abstract—Identification of buried antipersonnel landmines with ground penetrating radar (GPR) establishes a need for scattering models relating the measured scattered field to target characteristics such as size, material composition and burial depth. In this paper, we present generalizations of our previously published convolutional models for plane wave backscattering from a dielectric minelike target embedded in an unbounded host medium, which account for the ground surface, the GPR hardware and internal mine structure. Using 3D finite-difference time-domain (FDTD) and measured data examples, we illustrate the validity of the convolutional models and how they can be used to characterize buried targets. In particular, we show that it is possible to determine target size and depth with millimeter accuracy under laboratory conditions, both of which are valuable information for landmine identification. Keywords-ground penetrating radar (GPR); buried landmine identification; convolutional model.