Detection of radioactive sources in urban scenes using Bayesian Aggregation of data from mobile spectrometers.

Mobile radiation detector systems aim to help identify dangerous sources of radiation while minimizing frequency of false alarms caused by non-threatening nuisance sources prevalent in cluttered urban scenes. We develop methods for spatially aggregating evidence from multiple spectral observations to simultaneously detect and infer properties of threatening radiation sources.