Study on Sequential Bayesian Radionuclide Identification Approach: Threshold and Detection Capability

Radionuclide detection is a key step in the control of radioactive materials. Influenced by detector performance, ambient background noise and data analysis model, fast identification of radionuclides is a great challenge faced by traditional gamma-ray spectrometry analysis methods. This paper introduces the signal processing model and basic inspection strategy of nuclide recognition method based on statistical test, a Monte Carlo method to select the test threshold is proposed, and a radionuclide characteristic gamma-ray identifier for
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Cs based on Wald sequential probability ratio test is constructed. In the end, the detection performance of the identifier is analyzed through emulate experiment.