Sensor Management Problems of Nuclear Detection

  • Tamra Carpenter
  • Jerry Cheng
  • Fred Roberts
  • Minge Xie
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)


Terrorist nuclear attack is a potentially devastating threat to homeland security. It is increasingly important to have the capability to intercept illicit nuclear materials entering the country and to monitor for nuclear threats emerging from within. The effective use of sensors for nuclear and radiological detection requires choosing the right type of sensor, putting it in the right place and activating it at the right time. It also involves interpreting the results of sensor alarms and making decisions that balance various types of risk and uncertainty based on those results. This article describes a variety of approaches to sensor management for nuclear detection that revolve around formulating the related problems using precise mathematical language and then developing tools of the mathematical sciences to solve them. It emphasizes a variety of approaches to sensor management in a multi-institution project on nuclear detection, which is based at Rutgers University and includes Princeton University and Texas State University-San Marcos.


Global Position System Mobile Sensor Radiation Sensor Sensor Management Nuclear Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank the members of our nuclear detection and port security project teams, especially those whose work is represented in this chapter: James Abello, Saket Anand, Tsvetan Asamov, Endre Boros, Xueying Chen, Siddhartha Dalal, Savas Dayanik, Elsayed Elsayed, Peter Frazier, Emilie Hogan, Paul Kantor, Mingyu Li, David Madigan, Sushil Mittal, Alantha Newman, Jason Perry, William Pottenger, Warren Powell, Ilya Rhyzov, Warren Scott, Kazutoshi Yamazaki, Christina Young, and Yada Zhu, Christopher Janneck, Adam Marzsalek, Christie Nelson. We also gratefully acknowledge support from the National Science Foundation under grants SES 05-18543, DMS 09-15139, and CBET 07-36134, from NSA under grant H98230-08-1-0104, ONR under grant N00014-07-1-0299, and the US Department of Homeland Security Domestic Nuclear Detection Office under grant 2008-DN-077-ARI012-02.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Tamra Carpenter
    • 1
  • Jerry Cheng
    • 1
  • Fred Roberts
    • 1
  • Minge Xie
    • 2
  1. 1.DIMACSRutgers UniversityPiscatawayUSA
  2. 2.Department of Statistics and Biostatistics RutgersThe State University of New JerseyPiscatawayUSA

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