• DocumentCode
    3314584
  • Title

    A novel maneuvering target passive tracking algorithm with multiple infrared observers

  • Author

    Wu, Panlong ; Li, Xingxiu

  • Author_Institution
    Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    8-11 Aug. 2009
  • Firstpage
    357
  • Lastpage
    359
  • Abstract
    A novel algorithm of UKF-IMM(unscented Kalman filter-interacting multiple model) is proposed to track a maneuvering target with two infrared observers. This algorithm use Markov process to describe switching probability among the models, while weighting means of inputs and outputs of UKF. The simulations of the application of UKF-IMM and EKF-IMM algorithm to maneuvering target tracking using dual infrared sensors are done separately. The simulation results show that the new algorithm outperforms EKF-IMM in terms of tracking accuracy and filter credibility.
  • Keywords
    Kalman filters; Markov processes; infrared detectors; probability; target tracking; Markov process; UKF-IMM; dual infrared sensors; filter credibility; infrared observers; multiple infrared observers; switching probability; target passive tracking algorithm; unscented Kalman filter-interacting multiple model; Automation; Covariance matrix; Equations; Filtering algorithms; Infrared sensors; Kalman filters; Markov processes; Passive filters; Predictive models; Target tracking; UKF-IMM; infrared observers; passive tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-4519-6
  • Electronic_ISBN
    978-1-4244-4520-2
  • Type

    conf

  • DOI
    10.1109/ICCSIT.2009.5234699
  • Filename
    5234699