Within the homeland security and emergency response communities, there is a need for a low-profile system to detect, locate, and identify radioactive sources in real time. Such a system could be deployed for area monitoring around venues for special events. A system was developed at Argonne National Laboratory, called RADTRAC, which is based on a network of radiation detectors and advanced signal-processing algorithms. The initial implementation of RADTRAC did not account for dynamically changing shielding due to crowd movements.

An algorithm was developed that utilizes the gamma-ray energy spectrum from each detector to estimate the amount of attenuation and scattering that is present between the source location (a priori unknown) and the detector location in real time. The attenuation and scattering estimations are then included in the maximum likelihood model to significantly improve the source localization solution. Results are presented for several test cases showing the improvement in the real-time source localization solution.

This algorithm has been implemented into the current version of RADTRAC such that it now accounts for the effects of dynamically changing shielding and scattering due to crowd movements in real time in order to accurately determine the source location in crowded venues.