Assessment and Analysis of Radiation Background Variation for Moving Detection Systems

It is well known that variation in radiation background presents serious challenges to radiation detection systems designed to scan vehicles, buildings, and other objects while the detection systems themselves are in motion. Examples of these challenges would be screening parked vehicles along roadsides or in parking lots at venues such as football stadiums or rock concerts. However, most of the information concerning background variation is anecdotal. A team at Los Alamos National Laboratory has completed an assessment and analysis of radiation background variation. Background data were collected in numerous venues in northern New Mexico that included parking lots, urban and rural roadways, and residential areas. Data were recorded with a Rapiscan TSA MD-134 instrument skid that contained polyvinyl toluene gamma scintillation detectors and 3He neutron detectors. Both detectors operated in a gross-counting mode, with a single energy window set to optimize the response to highly enriched uranium and weapons- grade plutonium. The instrument skid was mounted in a Mercedes van, and the van-skid system was instrumented with a global positioning system (GPS) data collection capability, as well as a readout capability for onboard data (in particular, the van’s speed). The data were assembled into a system that provided a record every 200 ms and included accumulated detector counts and GPS location, speed, and time. A spatial frequency analysis was performed on the data that were acquired. The result of the analysis was a frequency distribution of background gradients, both positive and negative. These data have been used to complement real-time data to predict performance (false alarm rate and detection sensitivity) of the detection system in various venues. The background variation data will be useful for estimating the upper performance limits of other similarly sized detection systems and detection technologies in moving-mode operations, such as spectroscopic systems, which may offer leverage against background variation that gross-counting systems cannot.