Evaluation of Coded Aperture Radiation Detectors using a Bayesian Approach

We investigate the utility of coded aperture (CA) for roadside radiation threat detection applications. With coded aperture, information in the form of photon quantity is traded for directional information. Whether and in what scenarios this trade-off is beneficial is the focus of this study. We quantify the impact of a masking approach by comparing performance with an unmasked approach in terms of both detection and localization of a roadside nuclear threat. We measure performance over many instances of a drive-by scenario via Monte Carlo simulation based on empirical observations.

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