Method of pedestrian navigation based on robust filter

Rui Xu, Yong Rong Sun, Wu Chen, Jian Ye Liu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Since the positional method of pedestrian navigation system (PNS) is usually assisted by global positioning system (GPS) and dead reckoning (DR) system integrated navigation algorithm, the PNS positional accuracy tend to be diminished by the GPS positional errors, especially positional outliers. To reduce the tendency and improve the accuracy of the pedestrian navigation system, a method of GPS and DR integrated navigation algorithm based on robust filter is presented. The Kalman filter model of PNS is obtained through modeling DR systematic errors and DR sensor errors first. Then, the positional difference between GPS and DR is used to estimate the extent to which the latest observation error meets their prior statistics. Based on the extent, the observed weight is renewed by an equivalent weight to restrict the negative effect of GPS positional error on integrated navigation. Finally, the result of real data from the experimental prototype shows that, in the case of GPS performing badly, the robust method is much more effective than Kalman filter in reducing the influence of the GPS positional error and could improve the positional accuracy by about 5 m. Thus, the positional accuracy of PNS based on GPS/DR integrated navigation is improved without additional hardwares.
Original languageEnglish
Pages (from-to)1506-1508
Number of pages3
JournalXi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Issue number7
Publication statusPublished - 1 Jul 2010


  • Dead reckoning
  • Global positioning system
  • Integrated navigaiton
  • Kalman filter
  • Pedestrian navigation
  • Robust filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Method of pedestrian navigation based on robust filter'. Together they form a unique fingerprint.

Cite this