Robust Localization of an Arbitrary Distribution of Radioactive Sources for Aerial Inspection

Radiation source detection has seen various applications in the past decade, ranging from the detection of dirty bombs in public places to scanning critical nuclear facilities for leakage or flaws, and in the autonomous inspection of nuclear sites. Despite the success in detecting single point sources, or a small number of spatially separated point sources, most of the existing algorithms fail to deliver in complex scenarios involving a large number of point sources or non-trivial distributions & bulk sources. Even in simpler environments, most existing algorithms are not scalable to larger regions and/or higher dimensional spaces. In a setup for autonomous inspection, we would be required to estimate not only the positions of the sources, but also the number, distribution and intensities of each of them. In this report, we present a novel algorithm for the robust localization of an arbitrary distribution of radiation sources using multi-layer sequential Monte Carlo methods coupled with suitable clustering algorithms. We aim to achieve near-perfect accuracy, in terms of F1-scores, while allowing the algorithm to scale, both to larger regions in space, and to higher dimensional spaces.