• DocumentCode
    3222145
  • Title

    Maneuvering Target Tracking Based on ANFIS and UKF

  • Author

    Zhu, Anfu ; Jing, Zhanrong ; Chen, Weijun ; Yang, Yan ; Zhang, Anxue

  • Author_Institution
    Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´´an
  • Volume
    1
  • fYear
    2008
  • fDate
    20-22 Oct. 2008
  • Firstpage
    904
  • Lastpage
    908
  • Abstract
    A maneuvering target tracking algorithm is proposed to overcome the defects of poor filtering precision while using unscented Kalman filter (UKF). The method combines the merits of UKF and adaptive neuro-fuzzy inference system (ANFIS). ANFIS is used to adjust system noise covariance matrix in target tracking system. Fuzzy inference, neural networks and UKF are integrated effectively. The proposed method is applied to the simulation of radar target tracking. The simulation results show that the proposed method has advantages in higher precision, faster convergence, and stronger ability to track maneuvering targets.
  • Keywords
    Kalman filters; covariance matrices; fuzzy neural nets; fuzzy reasoning; radar computing; radar signal processing; radar tracking; target tracking; ANFIS; UKF; adaptive neuro-fuzzy inference system; neural networks; poor filtering precision; radar target tracking; system noise covariance matrix; target tracking maneuvering; target tracking system; unscented Kalman filter; Covariance matrix; Equations; Filtering algorithms; Fuzzy reasoning; Inference algorithms; Nonlinear filters; Radar tracking; Signal processing algorithms; State estimation; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation (ICICTA), 2008 International Conference on
  • Conference_Location
    Hunan
  • Print_ISBN
    978-0-7695-3357-5
  • Type

    conf

  • DOI
    10.1109/ICICTA.2008.145
  • Filename
    4659619