Department of Nuclear, Plasma, and Radiological Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
Cyberinfrastructure and Geospatial Information Laboratory, Department of Geography & Geographic Information Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
PLoS One. 2019 May 1;14(5):e0216131. doi: 10.1371/journal.pone.0216131. eCollection 2019.
Nuclear security is a critical concept for public health, counter-terrorism efforts, and national security. Nuclear radioactive materials should be monitored and secured in near real-time to reduce potential danger of malicious usage. However, several challenges have arose to detect the anomalous radioactive source in a large geographical area. Radiation naturally occurs in the environment. Therefore, a non-zero level of radiation will always exist with or without an anomalous radioactive source present. Additionally, radiation data contain high levels of uncertainty, meaning that the measured radiation value is significantly affected by the velocity of the detector and background noise. In this article, we propose an innovative approach to detect anomalous radiation source using mobile sensor networks combined with a Poisson kriging technique. We validate our results using several experiments with simulated radioactive sources. As results, the accuracy of the model is extremely high when the source intensity is high or the anomalous source is close enough to the detector.
核安全是公共卫生、反恐努力和国家安全的一个关键概念。核放射性材料应进行近实时监测和保护，以减少恶意使用的潜在危险。然而，在大面积地理区域检测异常放射性源方面出现了一些挑战。辐射在环境中自然存在。因此，无论是否存在异常放射性源，总会存在一定水平的辐射。此外，辐射数据包含高度的不确定性，这意味着测量的辐射值会受到探测器速度和背景噪声的显著影响。在本文中，我们提出了一种使用移动传感器网络结合泊松克里金技术来检测异常辐射源的创新方法。我们使用带有模拟放射性源的几个实验来验证我们的结果。结果表明，当源强度较高或异常源足够接近探测器时，该模型的准确性非常高。
