Simulation and validation of the Mobile Urban Radiation Search (MURS) gamma-ray detector response

Abstract The Mobile Urban Radiation Search (MURS) system was designed for real-time detection, identification and localization of radiological and nuclear sources during search missions in urban environments. The MURS system comprises an array of commercial sensor technologies integrated into the cargo space of a sport-utility-vehicle, including six 2x4x16 inch NaI(Tl) detectors for gamma-ray detection, a 6 LiF panel for neutron detection, visible and near-infrared cameras for contextual awareness, cellular/radio antennae for data-telemetry and a global positioning system stabilized by an inertial navigation system. The MURS prototype, built by Physical Sciences Inc., was completed in March of 2018 and features a state-of-the-art gamma-ray detection isotope identification algorithm and two localization algorithms that provide the operator with real-time radioactive source identification and geo-location. These algorithms employ knowledge of the isotope-specific response of the gamma-ray detection system. This work discusses the simulation and experimental validation of these response functions and their applicability to a Maximum Likelihood Expectation–Maximization (ML-EM) based algorithm for source localization and mapping.