  The detection, identification, and localization of illicit radiological and
nuclear material continue to be key components of nuclear non-proliferation and
nuclear security efforts around the world. Networks of radiation detectors
deployed at strategic locations in urban environments have the potential to
provide continuous radiological/nuclear (R/N) surveillance and provide high
probabilities of intercepting threat sources. The integration of contextual
information from sensors such as video, Lidar, and meteorological sensors can
provide significantly enhanced situational awareness, and improved detection
and localization performance through the fusion of the radiological and
contextual data. In this work, we present details of our work to establish a
city-scale multi-sensor network testbed for intelligent, adaptive R/N detection
in urban environments, and develop new techniques that enable city-scale source
detection, localization, and tracking.
