• DocumentCode
    2002914
  • Title

    Application of Dempster-Shafer theory of evidence to the correlation problem

  • Author

    Morelli, Michael ; DeSimone, Anthony J., Jr.

  • Author_Institution
    Naval Electron. & Surveillance Syst. Surface Syst., Lockheed Martin, Moorestown, NJ, USA
  • Volume
    2
  • fYear
    2002
  • fDate
    8-11 July 2002
  • Firstpage
    759
  • Abstract
    We apply the Dempster Shafer theory of evidence to the spatial correlation problem. Usually the correlation problem is solved using a Bayesian approach by evaluating the likelihood function for each possible assignment and choosing the maximum likelihood function as the correct assignment. A simulation comparison is then made between the decisions arrived at using the Dempster Shafer theory and those found using the (traditional) Bayesian approach. The results show (for the cases examined) that the decisions made by both theories are identical. Since the Dempster Shafer theory is much more computationally intensive than the Bayesian approach and there is no gain (or loss) in the outcome, one should be much more appreciative of the more traditional Bayesian solution to the problem.
  • Keywords
    Bayes methods; inference mechanisms; maximum likelihood estimation; sensor fusion; uncertainty handling; Bayesian approach; Dempster Shafer theory of evidence; correct assignment; decisions; maximum likelihood function; simulation; spatial correlation problem; Bayesian methods; Computational modeling; Contracts; Covariance matrix; Government; Measurement errors; Model driven engineering; Surveillance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2002. Proceedings of the Fifth International Conference on
  • Conference_Location
    Annapolis, MD, USA
  • Print_ISBN
    0-9721844-1-4
  • Type

    conf

  • DOI
    10.1109/ICIF.2002.1020882
  • Filename
    1020882