• DocumentCode
    731598
  • Title

    Modeling and filter algorithm analysis of all-optical atomic spin gyroscope´s random drift

  • Author

    Sheng Zou ; Hong Zhang ; Xiyuan Chen

  • Author_Institution
    Dept. of Instrum. Sci. & Eng., Southeast Univ., Nanjing, China
  • fYear
    2015
  • fDate
    4-5 June 2015
  • Firstpage
    367
  • Lastpage
    371
  • Abstract
    ARMA model is set up by using AIC method for all-optical atomic spin gyroscope´s random drift. The model is proven effective by the residual errors analysis. On the basis of the ARMA model, the results of conventional kalman filter, R-correction kalman filter, r-correction kalman filter and R-r correction kalman filter for analyzing gyroscope´s random drift have been compared in this paper. The results of actual datum analysis showed that R-correction kalman filter algorithm and R-r correction kalman filter algorithm performed better than others under high dynamic environment, conventional kalman filter algorithm performs better than others under low dynamic environment.
  • Keywords
    Kalman filters; gyroscopes; AIC method; R-correction kalman filter; R-r correction kalman filter; all-optical atomic spin gyroscope random drift; filter algorithm analysis; high dynamic environment; low dynamic environment; r-correction kalman filter; residual errors analysis; Algorithm design and analysis; Correlation; Data models; Gyroscopes; Heuristic algorithms; Kalman filters; ARMA; All-optica Atomic Spin Gyroscope; Dynamic Environment; Kalman Filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Metrology for Aerospace (MetroAeroSpace), 2015 IEEE
  • Conference_Location
    Benevento
  • Type

    conf

  • DOI
    10.1109/MetroAeroSpace.2015.7180684
  • Filename
    7180684