Improvements in accurate GPS positioning using time series analysis

Koyama Yuichiro, Tanaka Toshiyuki

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

4 Citations (Scopus)


Although the Global Positioning System (GPS) is used widely in car navigation systems, cell phones, surveying, and other areas, several issues still exist. We focus on the continuous data received in public use of GPS, and propose a new positioning algorithm that uses time series analysis. By fitting an autoregressive model to the time series model of the pseudorange, we propose an appropriate state-space model. We apply the Kalman filter to the state-space model and use the pseudorange estimated by the filter in our positioning calculations. The results of our positioning experiment show that the accuracy of our proposed method is much better than that of the standard method. In addition, as we can obtain valid values estimated by time series analysis using the state-space model, the proposed state-space model can be applied in several other fields.

Original languageEnglish
Title of host publicationProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
PublisherSociety of Instrument and Control Engineers (SICE)
Number of pages4
ISBN (Print)9784907764364
Publication statusPublished - 2010

Publication series

NameProceedings of the SICE Annual Conference


  • Armodel
  • GPS
  • Kalman filter
  • Time series analysis

ASJC Scopus subject areas

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


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