• DocumentCode
    231454
  • Title

    Research on the algorithm of gravity aided Inertial Navigation based on CKF

  • Author

    Hao Xiong ; Xingshu Wang ; Jing Zhu ; Dongkai Dai

  • Author_Institution
    Coll. of Opto-Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2014
  • fDate
    19-23 Oct. 2014
  • Firstpage
    252
  • Lastpage
    257
  • Abstract
    Using the information of gravity filed for aided inertial navigation can ensure the system´s passive resistance and anti-jamming, and has become the hot topic of integrated navigation field. In this paper, we establish state-space model derived from the error equation of Inertial Navigation System (INS), and set the difference between indicated gravity anomaly and measured gravity anomaly which contains the information of position error as the measurement. After that, Cubature Kalman Filter (CKF) is introduced for estimation of navigation error online, which avoids the linearization of measurement. At last, the simulation system is realized based on the DNSC08 gravity model to inspect and verify the algorithm. The simulation results show that, the algorithm based on CKF for gravity aided navigation can strength the system´s performance effectively.
  • Keywords
    Kalman filters; gravity; inertial navigation; CKF; DNSC08 gravity model; INS; cubature Kalman filter; gravity aided inertial navigation system; gravity anomaly; state-space model; Gravity; Gravity measurement; Inertial navigation; Mathematical model; Measurement uncertainty; Position measurement; CKF; Gravity aided navigation; INS; gravity anomaly;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing (ICSP), 2014 12th International Conference on
  • Conference_Location
    Hangzhou
  • ISSN
    2164-5221
  • Print_ISBN
    978-1-4799-2188-1
  • Type

    conf

  • DOI
    10.1109/ICOSP.2014.7015007
  • Filename
    7015007