X. Xun, B. Mallick, R. Carroll, and P. Kuchment,
"Bayesian Approach to Detection of Small Low Emission Sources,"
27, 115009-115020 (2011).
This paper addresses the problem of detecting the presence and
location of a small low emission source inside an object, when
the background noise dominates. This problem arises, for
instance, in some homeland security applications. The goal is
to reach the signal-to-noise ratio levels in the order
of 10−3. A Bayesian approach to this problem is implemented in
2D. The method allows inference not only about the existence
of the source, but also about its location.We derive Bayes
factors for model selection and estimation of location based
on Markov chainMonte Carlo simulation. A simulation study shows
that with sufficiently high total emission level, our method
can effectively locate the source.
Associated Project(s):SHIELD (Smuggled HEU Interdiction through Enhanced anaLysis and Detection): A Framework for Developing Novel Detection Systems Focused on Interdicting Shielded HEU