Nuclear Scene Data Fusion (SDF) integrates radiation data and other contextual sensor measurements to enable free-moving localization and mapping of nuclear radiation from person or robot-borne sensor systems referred to as Localization and Mapping Platforms (LAMPs). The LAMP sensor suite typically utilizes lidar to create high-fidelity 3D point clouds representing the measurement scene. The high precision and accuracy of lidar has been essential to SDF, but its larger size, weight, power, and cost (SWaP-C) requirements limit its use in lightweight, portable applications, such as drones or handheld systems for remote field operations. In these cases, automotive millimeter-Wave radar presents a cost-effective, lightweight, and energy-efficient alternative, albeit with a significant compromise in spatial resolution and accuracy. We consider utilizing 2D radar point clouds to create occupancy maps of the scene. One method explored generates radar occupancy grids refined by a lidar-trained Pix2Pix conditional Generative Adversarial Network (cGAN) to approach lidar occupancy grid accuracy. We utilize these radar point occupancy grids to locate and quantify a gamma-ray point source in an environment never-before-seen by our lidar-trained Pix2Pix model, and we compare the results to those generated using standard lidar occupancy grids to assess the feasibility of using radar in place of lidar in some situations and environments.
By combining radiation detection technologies with robotics sensing, the ability to continuously conduct gamma-ray imaging using freely-moving systems was demonstrated in 2015.1 This new method, which was named free-moving 3D Scene Data Fusion (SDF), was then applied to mapping radioactive contamination and to contextualizing the extent of contamination and the efficacy of radiological clean-up efforts.2, 3 Since then, further studies into the types of radiation detection systems to which SDF could be applied resulted in the discovery and demonstration that neutron activity could be mapped using neutron-sensitive CLLBC scintillators, arrays of pixelated CZT detectors could be used to create multi-modal imagers, and more rudimentary detector systems such as arrays of four CsI modules could still achieve good-quality mapping by inferring source positioning through the encoded modulation of source-to-detector distance. This paper provides an overview of the SDF technology, highlights recent measurements leveraging SDF-equipped systems, discusses the continued development of quantitative algorithms4, 5 and their ramifications for developing autonomous SDF-capabilities, and summarizes future directions of research and application development for free moving radiation detection systems.
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