ATD: Statistical Methods for Nuclear Material Surveillance Using Mobile Sensors

The research in this proposal outlines a robust system of a mobile sensor network and develops statistical algorithms and models to provide consistent, pervasive and dynamic surveillance for nuclear or biological materials in major cities. Specifically, the project proposes a novel design of sensor network, in which nuclear sensors and Global Position System (GPS) tracking devices are installed on a large number of vehicles such as taxicabs and police vehicles. Real time information from this network is processed at a central surveillance center, where mathematical and statistical analyses are performed. The proposed statistical approaches include multiple spatial cluster detection method using latent models and state-space model for real-time detection and tracking of possibly moving nuclear sources using sequential Monte Carlo method. The methods are general and flexible and can be used in other settings involving a massive network of sensors.

Threats to national and homeland security have become more dynamic and complex in the past decade due to global terrorism, increased opposition to U.S. interests, and increased access by adversaries to sophisticated technologies and materials. Among the threats, nuclear attacks is one of the most devastating acts, with severe losses of human lives as well as long term and large scale damages to infrastructures. As a result, there have been growing concerns regarding the prospect of detonating nuclear materials or dirty bombs in the populous metropolitan areas. It becomes more and more vital to have sophisticated nuclear surveillance and detection systems deployed in major cities in the U.S. to protect infrastructures and human lives. The proposed research on surveillance systems of a mobile sensor network can have broad impacts in advancing our detection capabilities of terrorist threats hence improving homeland security. During the course of the proposed project, activities related to education and training of graduate and undergraduate students will be actively engaged, in preparation for their possible careers in this area.