Nonparametric Statistical Tests for Radioactive Source Detection

Autor:	James W. Howse, Kenneth R. Muske
Rok vydání:	2003
Předmět:	Engineering Nonparametric hypothesis testing business.industry Noise (signal processing) Radiation sensor Radioactive source Nonparametric statistics Nuclear material computer.software_genre Statistics Data mining business computer Statistical hypothesis testing
Zdroj:	IFAC Proceedings Volumes. 36:1125-1130
ISSN:	1474-6670
DOI:	10.1016/s1474-6670(17)36644-2
Popis:	This work describes a study carried out to assess the feasibility of using radiation sensors for real-time detection of radioactive sources within a facility. The source detection problem is formulated as a nonparametric hypothesis test using statistics computed from the radiation sensor signals. The purpose of this study is the development of tools that enhance the security and safety of nuclear material processing facilities by introducing new sensor modalities and developing remote monitoring capabilities. The results indicate that a source can be detected quite well using non parametric statistical tests in spite of poor signal to noise ratios, unknown background signals, and high measurement noise levels.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f855345e7a16e13c6df448f34882dff1 https://doi.org/10.1016/s1474-6670(17)36644-2 Zobrazit plný text záznamu