• DocumentCode
    2820933
  • Title

    A Nonlinear Kalman Smoothing Method for Ballistic Target Tracking

  • Author

    Wu, Panlong ; Kong, Jianshou ; Bo, Yuming ; Li, Bing

  • Author_Institution
    Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • Volume
    2
  • fYear
    2009
  • fDate
    24-26 April 2009
  • Firstpage
    160
  • Lastpage
    162
  • Abstract
    In order to track the ballistic target more accurate, a suitable model of ballistic target motion is developed and a new nonlinear smoothing method is presented in this paper. The new nonlinear smoothing method named UKS is based on the combination of unscented Kalman filter (UKF) and Rauch-Tung-Striebel (RTS)smoothing method. The UKS method improves the tracking accuracy, and enhances the filtering convergence. The simulation of the application of UKS and UKF methods to track Ballistic target is done separately. The simulation results show that the new method outperforms UKF in terms of tracking accuracy and filter credibility.
  • Keywords
    Kalman filters; ballistics; military computing; smoothing methods; target tracking; Rauch-Tung-Striebel smoothing method; ballistic target motion; ballistic target tracking; nonlinear Kalman smoothing method; unscented Kalman filter; Automation; Convergence; Equations; Filtering; Iterative methods; Kalman filters; Optimization methods; Radar tracking; Smoothing methods; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-0-7695-3605-7
  • Type

    conf

  • DOI
    10.1109/CSO.2009.70
  • Filename
    5193921