• DocumentCode
    2237671
  • Title

    Estimation Methods for GPS Kinematical Positioning and Simulation Analysis

  • Author

    Pan Xiong ; Kang Shuangshuang ; Yuan Shuanli ; Liu Lilong

  • Author_Institution
    Fac. of Inf. Eng., China Univ. of Geosci., Wuhan, China
  • fYear
    2009
  • fDate
    26-28 Dec. 2009
  • Firstpage
    845
  • Lastpage
    848
  • Abstract
    The characteristics of three GPS kinematical data processing models, Least Square, Kalman filtering, and Semiparametric model are discussed and their advantages and disadvantages are compared. With observational data and pertinent data processing software, the applicable condition, context and effect of the three models are experimented. Results show that when the mobile platform is in uniform motion, the accuracy of the three models are almost equal; when the mobile platform is in stochastic acceleration, the accuracy of Semiparametric model is superior to that of LS, and that of Kalman filtering is the worst.
  • Keywords
    Global Positioning System; Kalman filters; estimation theory; least squares approximations; GPS kinematical data processing; Kalman filtering; data processing software; estimation methods; least square; mobile platform; semiparametric model; stochastic acceleration; Analytical models; Data engineering; Data processing; Equations; Filtering; Global Positioning System; Kalman filters; Least squares approximation; Recursive estimation; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Engineering (ICISE), 2009 1st International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4909-5
  • Type

    conf

  • DOI
    10.1109/ICISE.2009.560
  • Filename
    5455728