  A method is proposed, based on scan statistics, to detect, identify, and
localize illicit radiological material using mobile sensors in an urban
environment. Our method handles varying levels of background radiation that
change according to an (unknown) environment. Our method can accurately
determine if a source is present along a street segment as well as identify
which of six possible sources generated the radiation. Our method can also
localize the source, when detected, to within a few seconds. We have presented
our results across a range of decision thresholds allowing stakeholders to
evaluate the performance at different false alarm rates. Due to the simplicity
of our approach, our models can be trained in a few minutes with very little
training data and holds the potential to score a run in real-time. Our method
was one of the top performing submissions in the 'Detecting Radiological
Threats in Urban Areas' competition.
