• DocumentCode
    1339839
  • Title

    Update to the Hybrid Conditional Averaging Performance Prediction of the IMM Algorithm

  • Author

    Osborne, R.W. ; Blair, W.D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Connecticut, Fairfield, CT, USA
  • Volume
    47
  • Issue
    4
  • fYear
    2011
  • fDate
    10/1/2011 12:00:00 AM
  • Firstpage
    2967
  • Lastpage
    2974
  • Abstract
    Traditionally the performance evaluation of a target tracking algorithm is accomplished via Monte Carlo simulations for each specific scenario of interest. For some applications, the time and computational resource requirements of performing the necessary simulations for algorithm design is excessive; so the need for performance prediction becomes paramount. One method of performance prediction developed during the early 1990s is the hybrid conditional averaging (HYCA) technique, which can be used to predict the performance of the interacting multiple model (IMM) algorithm. Applying the HYCA technique to the IMM algorithm as originally developed leads to poor performance prediction in certain situations. A new extension used in these circumstances is shown to lead to superior performance prediction without an increase in computational complexity compared with the originally developed algorithm for such situations.
  • Keywords
    performance evaluation; signal processing; target tracking; IMM algorithm; computational complexity; computational resources; hybrid conditional averaging performance prediction; interacting multiple model algorithm; target tracking algorithm; Filtering algorithms; Mathematical model; Monte Carlo methods; Prediction algorithms; Trajectory; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Aerospace and Electronic Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9251
  • Type

    jour

  • DOI
    10.1109/TAES.2011.6034677
  • Filename
    6034677