Enhancing artificial radionuclides monitoring: a Bayesian statistical approach combined with the multi time-interval analysis method

This paper propose a binomial distribution model based on Bayesian statistics in the field of monitoring artificial radionuclides. A multi time-interval analysis method is adopted to extract the 214Bi–214Po correlated events counts in the 222Rn decay series. Then the model evaluates natural background using the ratio of correlated events counts to total α counts. The Beta distribution is used as the prior distribution of this model. We detailed discussed the process of posterior estimation, and compared the new approach with the conventional approaches. The results show the new approach has a more sensitive response to artificial radionuclides.