Interpreting ground-penetrating radar images using object-oriented, neural, fuzzy, and genetic processing

Exploration and exploitation of local planetary resources will require the acquisition of subsurface information. Continuous profiling subsurface imaging technology will permit the rapid acquisition and interpretation of information on board automated rover vehicles. The overall aim of this research is to provide base technology for an automated ground penetrating radar GPR vision system for interpretation of geophysical data. Image processing algorithms are generally classified as low-, intermediate-, or high-level to reflect both the nearness of the algorithm to the bit image, and the sequence of algorithms that are likely to be implemented on an image. This research primarily deals with the symbolic manipulation of GPR tokens at the highest-level of processing, with minor emphasis being directed to the lower-level task of determining target shape from input consisting of the slope, length, and shape of the GPR pattern signature arms. Major emphasis was directed towards determining the real world objects corresponding to these target shapes.