• DocumentCode
    3314473
  • Title

    Adaptive cubature particle filter algorithm

  • Author

    Qiurong Li ; Feng Sun

  • Author_Institution
    Coll. of Autom., Harbin Eng. Univ., Harbin, China
  • fYear
    2013
  • fDate
    4-7 Aug. 2013
  • Firstpage
    1356
  • Lastpage
    1360
  • Abstract
    Based on particle filter (PF) and cubature Kalman filter (CKF), with the maximum posterior principle (MAP), a new filter algorithm - the adaptive cubature particle filter (ACPF) is derivated. From the theory it can be seen, that ACPF algorithm not only has the strict mathematical derivation, but also can improve filtering accuracy in the system under the condition of high dimension. ACPF has the advantages of high reliability, low sensitivity, strong robustness, strong stability and convergence. The ACPF and several filter algorithms such as PF, UKF and CKF which are often used in recent years, are applied to the simulation of GPS/INS integrated navigation system, experiments show that ACPF is better than the others. The simulation results has proved the correctness of the theoretical derivation of the conclusion.
  • Keywords
    Global Positioning System; Kalman filters; adaptive filters; inertial navigation; maximum likelihood estimation; particle filtering (numerical methods); ACPF; CKF; GPS-INS integrated navigation system; Global Positioning System; MAP; adaptive cubature particle filter algorithm; cubature Kalman filter; filtering accuracy; inertial navigation system; maximum posterior principle; Estimation; Filtering algorithms; Filtering theory; Kalman filters; Mathematical model; Noise; Particle filters; Cubature Kalman filter(CKF); adaptive cubature particle filter (ACPF); particle filter (PF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2013 IEEE International Conference on
  • Conference_Location
    Takamatsu
  • Print_ISBN
    978-1-4673-5557-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2013.6618110
  • Filename
    6618110