Radiation anomaly detection algorithms for field-acquired gamma energy spectra

Sanjoy Mukhopadhyay; Richard Maurer; Ron Wolff; Paul Guss; Stephen Mitchell

doi:10.1117/12.2185736

26 August 2015 Radiation anomaly detection algorithms for field-acquired gamma energy spectra

Sanjoy Mukhopadhyay, Richard Maurer, Ron Wolff, Paul Guss, Stephen Mitchell

Proceedings Volume 9593, Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XVII; 95930S (2015) https://doi.org/10.1117/12.2185736
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

The Remote Sensing Laboratory (RSL) is developing a tactical, networked radiation detection system that will be agile, reconfigurable, and capable of rapid threat assessment with high degree of fidelity and certainty. Our design is driven by the needs of users such as law enforcement personnel who must make decisions by evaluating threat signatures in urban settings. The most efficient tool available to identify the nature of the threat object is real-time gamma spectroscopic analysis, as it is fast and has a very low probability of producing false positive alarm conditions. Urban radiological searches are inherently challenged by the rapid and large spatial variation of background gamma radiation, the presence of benign radioactive materials in terms of the normally occurring radioactive materials (NORM), and shielded and/or masked threat sources. Multiple spectral anomaly detection algorithms have been developed by national laboratories and commercial vendors. For example, the Gamma Detector Response and Analysis Software (GADRAS) a one-dimensional deterministic radiation transport software capable of calculating gamma ray spectra using physics-based detector response functions was developed at Sandia National Laboratories. The nuisance-rejection spectral comparison ratio anomaly detection algorithm (or NSCRAD), developed at Pacific Northwest National Laboratory, uses spectral comparison ratios to detect deviation from benign medical and NORM radiation source and can work in spite of strong presence of NORM and or medical sources. RSL has developed its own wavelet-based gamma energy spectral anomaly detection algorithm called WAVRAD. Test results and relative merits of these different algorithms will be discussed and demonstrated.

Citation Download Citation

Sanjoy Mukhopadhyay, Richard Maurer, Ron Wolff, Paul Guss, and Stephen Mitchell "Radiation anomaly detection algorithms for field-acquired gamma energy spectra", Proc. SPIE 9593, Hard X-Ray, Gamma-Ray, and Neutron Detector Physics XVII, 95930S (26 August 2015); https://doi.org/10.1117/12.2185736

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KEYWORDS

Sensors

Gamma radiation

Detection and tracking algorithms

Algorithm development

Principal component analysis

Radioisotopes

Scintillators

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