Models and Algorithm for Radiation Detection

Accepted for presentation at “DHS-S&T: Workshop on Grand Challenges in Modeling, Simulation, and Analysis for Homeland Security (MSAHS-2010)”, March 2010

K. Mani Chandy, Julian J. Bunn and Annie H. Liu

Abstract: The objective of this work is to develop systems,  models and algorithms that help distinguish signatures of dangerous radiation material from background and normal (e.g.,  medical) sources of radiation. The challenge is to do so rapidly and with an extremely low probability of false alarms. Radiological detection architectures will be deployed in a variety of settings such as monitoring political rallies and Coast Guard maritime boarding parties. This paper presents models and algorithms by which sensor networks and mobile agents collaborate to detect dangerous radiation sources. Extensive simulations using the algorithms have been carried out and some results are presented  here. The paper explores ways in which the models can be extended from radiation detection to detecting other types of  threats such as chemical threats.