• DocumentCode
    1342991
  • Title

    Physics-Based Detection of Radioactive Contraband: A Sequential Bayesian Approach

  • Author

    Candy, J.V. ; Breitfeller, E. ; Guidry, B.L. ; Manatt, D. ; Sale, K. ; Chambers, D.H. ; Axelrod, M.A. ; Meyer, A.M.

  • Author_Institution
    Livermore Nat. Lab., Livermore, CA, USA
  • Volume
    56
  • Issue
    6
  • fYear
    2009
  • Firstpage
    3694
  • Lastpage
    3711
  • Abstract
    The timely and accurate detection of nuclear contraband is an extremely important problem of national security. The development of a prototype sequential Bayesian processor that incorporates the underlying physics of ¿-ray emissions and the measurement of photon energies and their interarrival times that offers a physics-based approach to attack this challenging problem is described. A basic radionuclide representation in terms of its ¿-ray energies along with photon interarrival times is used to extract the physics information available from the uncertain measurements. It is shown that not only does this approach lead to a physics-based structure that can be used to develop an effective threat detection technique, but also motivates the implementation of this approach using advanced sequential Monte Carlo processors or particle filters to extract the required information. The resulting processor is applied to experimental data to demonstrate its feasibility.
  • Keywords
    Monte Carlo methods; gamma-ray detection; germanium radiation detectors; national security; radioactivity measurement; radioisotopes; HPGe detector; Monte Carlo processors; gamma-ray detector; gamma-ray emissions; national security problem; nuclear detection; particle filters; photon energy measurement; prototype sequential Bayesian processor; radioactive contraband detection; radionuclide; Bayesian methods; Data mining; Energy measurement; Laboratories; Marketing and sales; Monte Carlo methods; National security; Object detection; Physics; Signal processing; Kalman filter; particle filter; physics-based approach; sequential Bayesian processor; sequential Monte Carlo; sequential radionuclide detection;
  • fLanguage
    English
  • Journal_Title
    Nuclear Science, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9499
  • Type

    jour

  • DOI
    10.1109/TNS.2009.2034374
  • Filename
    5341448