• DocumentCode
    916329
  • Title

    Estimation using subjective knowledge with tracking applications

  • Author

    Popoli, Robert ; Mendel, Jerry

  • Author_Institution
    Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
  • Volume
    29
  • Issue
    3
  • fYear
    1993
  • fDate
    7/1/1993 12:00:00 AM
  • Firstpage
    610
  • Lastpage
    623
  • Abstract
    Within the framework of classical estimation theory, there is no technically legitimate way to utilize knowledge that cannot be codified by either deterministic or strict probability models. The authors introduce a theoretically defensible approach called coordinated objective/subjective estimation (COSE) for the simultaneous incorporation of both objective and subjective knowledge in estimation. Also discussed is a technique, called heuristically constrained estimation (HCE) which is a particular interpretation of the Bayesian use of subjective priors. COSE, HCE, and classical maximum a posteriori probability (MAP) estimation are applied to a tracking problem
  • Keywords
    Bayes methods; estimation theory; heuristic programming; knowledge representation; probability; tracking; Bayesian method; coordinated objective/subjective estimation; data association; estimation theory; heuristically constrained estimation; maximum a posteriori probability; probability models; subjective knowledge; tracking; Assembly; Bayesian methods; Constraint optimization; Estimation theory; Frequency; Fuzzy sets; Fuzzy systems; Image processing; Knowledge engineering; Probability; Signal processing;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/7.220959
  • Filename
    220959