• DocumentCode
    1854242
  • Title

    An incline alignment algorithm for vehicle-borne sensor system

  • Author

    Huang Jianjun ; Guo Junting ; Wang Juanjuan

  • Author_Institution
    ATR Key Lab., Shenzhen Univ., Shenzhen, China
  • Volume
    3
  • fYear
    2012
  • fDate
    21-25 Oct. 2012
  • Firstpage
    2016
  • Lastpage
    2019
  • Abstract
    Aiming at the problem of incline alignment for vehicle-borne sensor system, a UKF-LM based incline alignment algorithm is presented. Two Unscented Kalman Filters (UKF) are used to estimate a calibration target´s position in both sensor coordinate system and vehicle base-coordinate system, respectively. The nonlinear least-squares Levenberg-Marquardt (LM) algorithm is applied to estimate the incline angle and the incline vector between the two coordinate systems by the filtered target positions. Simulation results show that the proposed algorithm is effective and efficient.
  • Keywords
    Kalman filters; calibration; least squares approximations; nonlinear filters; sensors; UKF-LM-based incline alignment algorithm; calibration target position estimation; coordinate systems; filtered target positions; inclination angle; inclination vector; nonlinear least-squares LM algorithm; nonlinear least-squares Levenberg-Marquardt algorithm; sensor coordinate system; unscented Kalman filters; vehicle base-coordinate system; vehicle-borne sensor system; Levenberg-Marquardt(LM); Unscented Kalman Filter(UKF); incline alignment; vehicle-borne sensor system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2012 IEEE 11th International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2164-5221
  • Print_ISBN
    978-1-4673-2196-9
  • Type

    conf

  • DOI
    10.1109/ICoSP.2012.6491976
  • Filename
    6491976