Automated Detection and Tracking of Hyperbolic Diffractions Applied to Engineering GPR Data Sets

We developed an algorithm to automatically detect and track hyperbolic diffractions within GPR data sets. The procedure uses the apexes as initial seeds, and also pre-estimates the widths of their hyperbolas, thus producing a more objective search window that is automatically adapted to local conditions. Within the search window, hyperbolas with varying EM velocities are fitted to the signal phases surrounding the initial seed, which are then connected to form preliminary hyperbolic paths. Among these paths, the algorithm selects the best fit by assessing several attributes, while possible false positives and redundant hyperbolas are subsequently removed. The proposed procedure can be applied with minimal signal processing, and it requires only limited input from the interpreter. The algorithm was able to accurately track most diffractions within engineering GPR data sets, with very few false positives and negatives.