ANP is developing innovative algorithms and frameworks to enable more robust radiation detection capabilities, including modeling variable gamma-ray backgrounds, enabling development, testing and deployment of spectroscopic detection algorithms, and enabling real-time, 3-D gamma-ray image reconstruction. The variability of radiological backgrounds, convolved with gamma-ray transport through the environment and a detector’s response, creates a variable baseline upon which anomalous sources may appear. While the physical phenomena underlying these signals are well understood, direct prediction is computationally intensive. By leveraging matrix decomposition methods ANP is developing fast and efficient tools to decompose radiological backgrounds in a statistically accurate way.
These tools are now enabling ANP researchers to study and correlate radiological backgrounds with environmental and contextual information, develop spectroscopic detection and identification algorithms that perform at the state-of-the-art, and develop more efficient and accurate methods for 3-D gamma-ray reconstruction.