Multimodal detection of subsurface targets such as tunnels, pipes, reinforcement bars, and structures has been
investigated using both ground-penetrating radar (GPR) and seismic sensors with signal processing techniques
to enhance localization capabilities. Both systems have been tested in bi-static configurations but the GPR has
been expanded to a multi-static configuration for improved performance. The use of two compatible sensors
that sense different phenomena (GPR detects changes in electrical properties while the seismic system measures
mechanical properties) increases the overall system's effectiveness in a wider range of soils and conditions. Two
experimental scenarios have been investigated in a laboratory model with nearly homogeneous sand. Images
formed from the raw data have been enhanced using beamforming inversion techniques and Hough Transform
techniques to specifically address the detection of linear targets. The processed data clearly indicate the locations
of the buried targets of various sizes at a range of depths.
Multi-static ground-penetrating radar (GPR) uses an array of antennas to conduct a number of bistatic operations simultaneously. The multi-static GPR is used to obtain more information on the target of interest using angular diversity. An entirely computer controlled, multi-static GPR consisting of a linear array of six resistively-loaded vee dipoles (RVDs), a network analyzer, and a microwave switch matrix was developed to investigate the potential of multi-static inversion algorithms. The performance of a multi-static inversion algorithm is evaluated for targets buried in clean sand, targets buried under the ground covered by rocks, and targets held above the ground (in the air) using styrofoam supports. A synthetic-aperture, multi-static, time-domain GPR imaging algorithm is extended from conventional mono-static back-projection techniques and used to process the data. Good results are obtained for the clean surface and air targets; however, for targets buried under rocks, only the deeply buried targets could be accurately detected and located.