• DocumentCode
    2437694
  • Title

    Algorithmic Research of Data Fusion in Mixed Navigation System Based on Least-Square Method

  • Author

    Yun, Chen ; Jijing, Wang

  • Author_Institution
    Sch. of Commun. & Transp. Eng., Changsha Univ. of Sci. & Technol., Changsha
  • Volume
    2
  • fYear
    2008
  • fDate
    19-20 Dec. 2008
  • Firstpage
    286
  • Lastpage
    289
  • Abstract
    To advance the vehicle setting accuracy, mixed navigation system emerges as the times require. The keystone of mixed navigation research is how to make use of multi-sensor´s locator data effectively. Multi-sensor data fusion technology is an innovation for data processing developed recently, and data fusion method research is paid close attention to generally. The classical linearity least-squares estimation is linearity unbiased and its variance identity. This paper presented a mixed navigation system data fusion method based on least-square estimation, which focused on multi-positioning system´s sense data. And it also demonstrated its effectiveness of algorithm through emulation counting.
  • Keywords
    least squares approximations; radionavigation; sensor fusion; data fusion; data processing; least-square method; mixed navigation system; multipositioning system; vehicle setting accuracy; Base stations; Filtering algorithms; Global Positioning System; Kalman filters; Least squares methods; Linearity; Navigation; Nonlinear equations; Sensor systems; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3490-9
  • Type

    conf

  • DOI
    10.1109/PACIIA.2008.331
  • Filename
    4756782