• DocumentCode
    1946150
  • Title

    Target passive tracking based on Strong Tracking Filter

  • Author

    Hua, Yu

  • Author_Institution
    Dept. of Command Autom., Naval Univ. of Eng., Wuhan, China
  • Volume
    9
  • fYear
    2010
  • fDate
    9-11 July 2010
  • Firstpage
    273
  • Lastpage
    275
  • Abstract
    We put forward Adaptive PLE (APLE) based on Strong Tracking Filter (STF) for bearing and frequency measure in order to rectify the bias of PLE. Furthermore, the APLE avoids filter divergence in that it is not necessary to linearize non-linear measure equation. Simulation demonstrate that the APLE has the ability to reduce estimate bias adaptively and estimate accuracy can be greatly improved.
  • Keywords
    adaptive Kalman filters; machine bearings; motion estimation; passive filters; target tracking; tracking filters; APLE; adaptive PLE; bearing; frequency measurement; strong tracking filter; target motion analysis; target passive tracking; Area measurement; Maximum likelihood estimation; Sonar measurements; adaptive filtering; passive tracking; strong tracking filter; target motion analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-5537-9
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2010.5564432
  • Filename
    5564432