GPS standard positioning using Kalman filter

Seiji Yamaguchi, Toshiyuki Tanaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

At present GPS is applied to various situations because of its confidence and usefulness. Position calculated by GPS makes some errors caused from many different factors which GPS signals made. The greatest error factor which affects the accuracy and the precision of positioning by GPS is lack of the number of satellites you can see in the sky. To reduce this error factor and to improve the precision and accuracy of GPS positioning many projects are carried out research, such as QZSS, pseudolite system. These systems have potentiality to make the precision of GPS positioning under worse situation that you can see few GPS satellites because they increase the number of satellites which are available to use for position calculating. However, they require much time and expensive device for their infrastructure. We paid attention to GPS calculating method itself. We adapted Kalman filter to GPS positioning calculation. We improved the precision and accuracy of SPS positioning in stand-alone mode under worse situation adapted the Kalman filter parameter.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages1351-1354
Number of pages4
DOIs
Publication statusPublished - 2006 Dec 1
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: 2006 Oct 182006 Oct 21

Publication series

Name2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period06/10/1806/10/21

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Keywords

  • GPS
  • Kalman filter
  • Least-squares method
  • SPS
  • Stand-alone mode

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Yamaguchi, S., & Tanaka, T. (2006). GPS standard positioning using Kalman filter. In 2006 SICE-ICASE International Joint Conference (pp. 1351-1354). [4109175] (2006 SICE-ICASE International Joint Conference). https://doi.org/10.1109/SICE.2006.315572