Diffraction Tomographic Imaging of Shallowly Buried Targets using Ground Penetrating Radar

The problem of subsurface imaging with Ground Penetrating Radar (GPR) is a challenging one. Due to the low-pass nature of soil sensors must utilise wave-lengths that are of the same order of magnitude as the object being imaged. This makes imaging difficult as straight ray approximations commonly used in higher frequency applications cannot be used. The problem becomes even more challenging when the target is shallowly buried as in this case the ground surface reflection and the near-field parameters of the radar need to be considered. This thesis has investigated the problem of imaging shallowly buried targets with GPR. Two distinct problems exist in this field radar design and the design of inverse scattering techniques. This thesis focuses on the design of inverse scattering techniques capable of taking the electric field measurements from the receiver and providing accurate images of the scatterer in real time.\ud \ud \ud \ud The thesis commences with a brief introduction to GPR theory. It then provides an extensive review of linear inverse scattering techniques applied to raw GPR data. As a result of this review the thesis draws the conclusion that, due to its strong foundations in Maxwell's equations, diffraction tomography is the most appropriate approach for imaging shallowly buried targets with GPR. A three-dimensional diffraction tomographic technique is then developed. This algorithm forms the primary contribution of the thesis.\ud \ud \ud \ud The novel diffraction tomography technique improves on its predecessors by catering for shallowly buried targets, significant antenna heights and evanescent waves. This is also the first diffraction tomography technique to be derived for a range of antenna structures. The advantages of the novel technique are demonstrated first mathematically then on synthetic and finally practical data. The algorithm is shown to be of high practical value by producing accurate images of buried targets in real time