Hypothesis tests for the detection of constant speed radiation moving sources

As a complement to single and multichannel detection algorithms, inefficient under too low signal-to-noise ratios, temporal correlation algorithms have been introduced to detect radiological material in motion. Test hypothesis methods based on the mean and variance of the signals delivered by the different channels have shown significant gain in terms of a tradeoff between detection sensitivity and false alarm probability. This paper discloses the concept of a new hypothesis test for temporal product detection methods, taking advantage of the Poisson nature of the registered counting signals, and establishes a benchmark between this test and its empirical counterpart. The simulation study validates that in the two relevant configurations of a pedestrian source carrier under respectively high and low count rate radioactive backgrounds, the newly introduced hypothesis test ensures a significantly improved compromise between sensitivity and false alarm, while guaranteeing the stability of its optimization parameter regardless of signal-to-noise ratio variations between 2 to 0.8.

[1]  S.E. Bender,et al.  Time Series Evaluation of Radiation Portal Monitor Data for Point Source Detection , 2009, IEEE Transactions on Nuclear Science.

[2]  D. Stephens,et al.  Detection of moving radioactive sources using sensor networks , 2004, IEEE Transactions on Nuclear Science.

[3]  D. Torney,et al.  Radioactive source detection by sensor networks , 2005, IEEE Transactions on Nuclear Science.

[4]  Romain Coulon,et al.  Moving Sources Detection Algorithm for Radiation Portal Monitors Used in a Linear Network , 2014, IEEE Transactions on Nuclear Science.

[5]  Pramod K. Varshney,et al.  Distributed detection of a nuclear radioactive source using fusion of correlated decisions , 2007, 2007 10th International Conference on Information Fusion.

[6]  R.B. Vilim,et al.  Sensitivity Improvement In Low-Profile Distributed Detector Systems For Tracking Sources In Transit , 2007, 2007 IEEE Conference on Technologies for Homeland Security.

[7]  Stephane Normand,et al.  New monitoring system to detect a radioactive material in motion , 2013, 2013 3rd International Conference on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications (ANIMMA).

[8]  Lord Jopling Chemical , biological , radiological OR nuclear ( CBRN ) detection : A technological overview Special Report , .

[9]  D. Torney,et al.  Distributed sensor networks for detection of mobile radioactive sources , 2004, IEEE Transactions on Nuclear Science.