Within the homeland security and emergency response communities, there is a need for a low-profile system to detect and locate radioactive sources. RadTrac has been developed at Argonne National Laboratory as an integrated system for the detection, localization, identification, and tracking of radioactive sources in real time. The system is based on a network of radiation detectors and advanced signal-processing algorithms. Features include video surveillance, automated tracking, easy setup, and logging of all data and images.

This paper describes the advanced algorithms that were developed and implemented for source detection, localization, and tracking in real time. In the physio-spatial integration approach to source localization, counts from multiple detectors are processed according to the underlying physics linking these counts to obtain the probability that a source is present at any point in space. This information is depicted in a probability density function map. This type of depiction allows the results to be presented in a simple, easy-to-understand manner. It also allows for many different complicated factors to be accounted for in a single image as each factor is computed as a probability density in space. These factors include spatial limitations, variable shielding, directional detectors, moving detectors, and different detector sizes and orientations. The utility and versatility of this approach is described in further detail. Advanced signal-processing algorithms have also been incorporated to improve real-time tracking and to increase signal-to-noise ratios including temporal linking and energy binning.

Measurements aimed at demonstrating the sensitivity improvements through the use of advanced signal-processing techniques were performed and are presented. Results of tracking weak sources (<100 Ci 137Cs) using four fixed-position detectors are presented.