• DocumentCode
    2780170
  • Title

    Improving performance of radar trackers by using H techniques

  • Author

    Atiullah, Tariq

  • fYear
    2005
  • fDate
    17-18 Sept. 2005
  • Firstpage
    163
  • Lastpage
    166
  • Abstract
    Kalman filters and extended Kalman filters are extensively used as observers in radar trackers in order to estimate the future position of the target. Kalman filters are linear filters while extended Kalman filters are non linear in nature. Extended Kalman filters therefore show better performance because A,B,C and D matrices are continuously updated. In both cases however basic LQR techniques are used to calculate the state space matrices. The aim of this paper is to design a H observer by robustifing the Blackman´s state space plant model through H loop shaping procedure so that it can tolerate maximum uncertainty. The paper also compares the performance of the designed observer with an extended Kalman filter in order to demonstrate the superiority of the H technique.
  • Keywords
    Kalman filters; observers; radar tracking; techniques; Blackman state space plant model; Kalman filters; extended Kalman filters; linear filters; radar trackers; Nonlinear filters; Predictive models; Radar tracking; Riccati equations; Robust control; Robustness; Stability; State-space methods; Target tracking; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies, 2005. Proceedings of the IEEE Symposium on
  • Print_ISBN
    0-7803-9247-7
  • Type

    conf

  • DOI
    10.1109/ICET.2005.1558873
  • Filename
    1558873