A Ground Penetrating Radar (GPR) survey for subsurface
investigation yields a large amount of data; within this data only
a small percentage represent the actual targets of interest. The
current GPR data processing for underground utilities relies on
skilled operators and involves many computationally expensive and
time consuming processing stages before any information about the
subsurface is concluded. These results are often based on broad
assumptions and involve human intervention, which is a source of
inconsistency and error, hence rendering the results to be
unreliable. The data processing stages involve pre-processing of
the data followed by detecting the areas that contain the targets
and extracting the target signature after which a final
interpretation of the target parameters is made. This book
automates the data processing stages as well as suggests
improvements in existing tools and techniques to make them more
efficient and robust. New data processing tools have been developed
which are superior to existing methods in terms of performance and
require less computational cost and time to produce results.
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