Book Description

Gamma-ray background radiation significantly reduces detection sensitivity when searching for radioactive sources in the field, such as in wide-area searches for homeland security applications. Mobile detector systems in particular must contend with a variable background that is not necessarily known or even measurable a priori. This work will present measurements of the spatial and temporal variability of the background, with the goal of merging gamma-ray detection, spectroscopy, and imaging with contextual information--a "nuclear street view" of the ubiquitous background radiation. The gamma-ray background originates from a variety of sources, both natural and anthropogenic. The dominant sources in the field are the primordial isotopes potassium-40, uranium-238, and thorium-232, as well as their decay daughters. In addition to the natural background, many artificially-created isotopes are used for industrial or medical purposes, and contamination from fission products can be found in many environments. Regardless of origin, these backgrounds will reduce detection sensitivity by adding both statistical as well as systematic uncertainty. In particular, large detector arrays will be limited by the systematic uncertainty in the background and will suffer from a high rate of false alarms. The goal of this work is to provide a comprehensive characterization of the gamma-ray background and its variability in order to improve detection sensitivity and evaluate the performance of mobile detectors in the field. Large quantities of data are measured in order to study their performance at very low false alarm rates. Two different approaches, spectroscopy and imaging, are compared in a controlled study in the presence of this measured background. Furthermore, there is additional information that can be gained by correlating the gamma-ray data with contextual data streams (such as cameras and global positioning systems) in order to reduce the variability in the background. This is accomplished by making many hours of background measurements with a truck-mounted system, which utilizes high-purity germanium detectors for spectroscopy and sodium iodide detectors for coded aperture imaging. This system also utilizes various peripheral sensors, such as panoramic cameras, laser ranging systems, global positioning systems, and a weather station to provide context for the gamma-ray data. About three hundred hours of data were taken in the San Francisco Bay Area, covering a wide variety of environments that might be encountered in operational scenarios. These measurements were used in a source injection study to evaluate the sensitivity of different algorithms (imaging and spectroscopy) and hardware (sodium iodide and high-purity germanium detectors). These measurements confirm that background distributions in large, mobile detector systems are dominated by systematic, not statistical variations, and both spectroscopy and imaging were found to substantially reduce this variability. Spectroscopy performed better than the coded aperture for the given scintillator array (one square meter of sodium iodide) for a variety of sources and geometries. By modeling the statistical and systematic uncertainties of the background, the data can be sampled to simulate the performance of a detector array of arbitrary size and resolution. With a larger array or lower resolution detectors, however imaging was better able to compensate for background variability.