• DocumentCode
    2526772
  • Title

    Neural technologies for increasing the GPS position accuracy

  • Author

    Lecce, V. Di ; Amato, A. ; Piuri, V.

  • Author_Institution
    DIASS, Politec. di Bari, Bari
  • fYear
    2008
  • fDate
    14-16 July 2008
  • Firstpage
    4
  • Lastpage
    8
  • Abstract
    Aim of this paper is to present a method to improve the accuracy of a GPS receiver. It is well known that there are many factors affecting the accuracy of a GPS receiver. In this work, the authors point out that many of these factors, considered in a given geographic area, have a certain periodicity. An important example of this kind of factors is the sky satellite position relative to receiver. The proposed method uses a neural network to correct the position computed by the receiver. The neural network is trained to learn the errors introduced into the measuring system by the cyclic phenomenon in the various hours of the day.
  • Keywords
    Global Positioning System; learning (artificial intelligence); neural nets; radio receivers; telecommunication computing; GPS receiver position accuracy; neural network training; Clocks; Computational intelligence; Extraterrestrial measurements; Global Positioning System; Information technology; Neural networks; Position measurement; Satellite broadcasting; Satellite navigation systems; US Department of Defense; GPS position accuracy; neural network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Measurement Systems and Applications, 2008. CIMSA 2008. 2008 IEEE International Conference on
  • Conference_Location
    Istanbul
  • Print_ISBN
    978-1-4244-2305-7
  • Electronic_ISBN
    978-1-4244-2306-4
  • Type

    conf

  • DOI
    10.1109/CIMSA.2008.4595822
  • Filename
    4595822