  In this paper we consider the development of algorithms for the automatic
detection of buried threats using ground penetrating radar (GPR) measurements.
GPR is one of the most studied and successful modalities for automatic buried
threat detection (BTD), and a large variety of BTD algorithms have been
proposed for it. Despite this, large-scale comparisons of GPR-based BTD
algorithms are rare in the literature. In this work we report the results of a
multi-institutional effort to develop advanced buried threat detection
algorithms for a real-world GPR BTD system. The effort involved five
institutions with substantial experience with the development of GPR-based BTD
algorithms. In this paper we report the technical details of the advanced
algorithms submitted by each institution, representing their latest technical
advances, and many state-of-the-art GPR-based BTD algorithms. We also report
the results of evaluating the algorithms from each institution on the large
experimental dataset used for development. The experimental dataset comprised
120,000 m^2 of GPR data using surface area, from 13 different lanes across two
US test sites. The data was collected using a vehicle-mounted GPR system, the
variants of which have supplied data for numerous publications. Using these
results, we identify the most successful and common processing strategies among
the submitted algorithms, and make recommendations for GPR-based BTD algorithm
design.
