Detection and parameter estimation of multiple radioactive sources

Given an area where an unknown number of unaccounted radioactive sources potentially exist, and using gamma- radiation count measurements collected at known locations within this area, the problem is to estimate the number of sources as well as their locations and intensities. Two approaches are investigated. The first is based on the maximum likelihood estimation and the generalised maximum likelihood rule for multiple hypothesis testing. The second approach estimates the parameters and the number of sources in the Bayesian framework via Monte Carlo integration. Numerical analysis and the performance comparison of both approaches against the Cramer-Rao bound are carried out.