• DocumentCode
    3076889
  • Title

    Passive Multi-sensor Maneuvering Target Tracking Based on UKF-IMM Algorithm

  • Author

    Wu, Panlong ; Li, Xingxiu

  • Author_Institution
    Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    10-11 July 2009
  • Firstpage
    135
  • Lastpage
    138
  • Abstract
    For effectively improving the accuracy of tracking a maneuvering target by passive sensors, a novel passive multi-sensor maneuvering target tracking algorithm based on unscented Kalman filter-interacting multiple model (UKF-IMM) is proposed. In this algorithm UKF is used by all models. UKF can avoid linearization of the highly nonlinear equations, and achieve accuracy at least to the second order. This algorithm use Markov process to describe switching probability among the models, while weighting means of inputs and outputs of UKF. Simulation results in passive maneuvering target tracking using three infrared sensors show that the proposed algorithm is more stable and effective.
  • Keywords
    Kalman filters; Markov processes; nonlinear equations; sensor fusion; target tracking; Markov process; UKF-IMM algorithm; nonlinear equations; passive multisensor maneuvering target tracking; unscented Kalman filter-interacting multiple model; Automation; Covariance matrix; Filtering algorithms; Information filtering; Jacobian matrices; Kalman filters; Markov processes; Nonlinear systems; Sensor systems; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering, 2009. ICIE '09. WASE International Conference on
  • Conference_Location
    Taiyuan, Shanxi
  • Print_ISBN
    978-0-7695-3679-8
  • Type

    conf

  • DOI
    10.1109/ICIE.2009.182
  • Filename
    5211450