A Fast Matched Filtered Method for Ground Penetrating Radar Tomographic Imaging

This thesis proposes a fast matched-filtered based imaging algorithm to detect and image below ground objects with ground penetrating radar. To image below ground objects, a set of distributed transmitters and receivers are placed above the ground, or slightly buried. The transmitters radiate waveforms into the subsurface. The resulting wave-front impinges upon underground objects, scattering electromagnetic energy in all directions. Receivers collect the reflected electromagnetic signals, retrieve the phase of the scattered signals, and transmit this information to a signal processing system for post-processing. After applying adaptive signal processing algorithms to the collected data, an image of the buried objects can be reconstructed. Reconstructed 2D images of buried objects are computed via numerical discretization and matched filtering techniques. The matched filtering technique requires less computational power and is easier to implement as compared to the matrix inversion technique. Results from simulation analyses and experimental data are used to validate this method. This work includes simulations and experiments with ground penetrating radar calibration techniques to justify the method introduced here.