An information gain driven search for a radioactive point source

Abstract

The paper presents an algorithm for detection and a subsequent information gain driven search for an unaccounted point source of relatively low-level gamma radiation. Source detection and parameter estimation are carried out jointly in the Bayesian framework using a particle filter. The observer control vector consists of the next sensor location and the exposure time. During the pre-detection search, the control vectors take predefined values. After detection, the optimal control vector is selected via a multiple-step ahead maximisation of the Fisher information gain.