a b s t r a c tThis work discusses the application and optimization of a spectral anomaly method for the real-time detection of gamma radiation sources from an aerial helicopter platform. Aerial detection presents several key challenges over ground-based detection. For one, larger and more rapid background fluctuations are typical due to higher speeds, larger field of view, and geographically induced background changes. As well, the possible large altitude or stand-off distance variations cause significant steps in background count rate as well as spectral changes due to increased gamma-ray scatter with detection at higher altitudes. The work here details the adaptation and optimization of the PNNLdeveloped algorithm Nuisance-Rejecting Spectral Comparison Ratios for Anomaly Detection (NSCRAD), a spectral anomaly method previously developed for ground-based applications, for an aerial platform. The algorithm has been optimized for two multi-detector systems; a NaI(Tl)-detector-based system and a CsI detector array. The optimization here details the adaptation of the spectral windows for a particular set of target sources to aerial detection and the tailoring for the specific detectors. As well, the methodology and results for background rejection methods optimized for the aerial gamma-ray detection using Potassium, Uranium and Thorium (KUT) nuisance rejection are shown. Results indicate that use of a realistic KUT nuisance rejection may eliminate metric rises due to background magnitude and spectral steps encountered in aerial detection due to altitude changes and geographically induced steps such as at land-water interfaces.
a b s t r a c tHelicopter-mounted gamma-ray detectors can provide law enforcement officials the means to quickly and accurately detect, identify, and locate radiological threats over a wide geographical area. The ability to accurately distinguish radiological threat-generated gamma-ray signatures from background gamma radiation in real time is essential in order to realize this potential. This problem is non-trivial, especially in urban environments for which the background may change very rapidly during flight. This exacerbates the challenge of estimating background due to the poor counting statistics inherent in real-time airborne gamma-ray spectroscopy measurements. To address this challenge, we have developed a new technique for real-time estimation of background gamma radiation from aerial measurements without the need for human analyst intervention. The method can be calibrated using radiation transport simulations along with data from previous flights over areas for which the isotopic composition need not be known. Over the examined measured and simulated data sets, the method generated accurate background estimates even in the presence of a strong, 60 Co source. The potential to track large and abrupt changes in background spectral shape and magnitude was demonstrated. The method can be implemented fairly easily in most modern computing languages and environments.
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