Improving IMES localization accuracy by integrating dead reckoning information

Kenjiro Fujii, Hiroaki Arie, Wei Wang, Yuto Kaneko, Yoshihiro Sakamoto*, Alexander Schmitz, Shigeki Sugano

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Indoor positioning remains an open problem, because it is difficult to achieve satisfactory accuracy within an indoor environment using current radio-based localization technology. In this study, we investigate the use of Indoor Messaging System (IMES) radio for high-accuracy indoor positioning. A hybrid positioning method combining IMES radio strength information and pedestrian dead reckoning information is proposed in order to improve IMES localization accuracy. For understanding the carrier noise ratio versus distance relation for IMES radio, the signal propagation of IMES radio is modeled and identified. Then, trilateration and extended Kalman filtering methods using the radio propagation model are developed for position estimation. These methods are evaluated through robot localization and pedestrian localization experiments. The experimental results show that the proposed hybrid positioning method achieved average estimation errors of 217 and 1846 mm in robot localization and pedestrian localization, respectively. In addition, in order to examine the reason for the positioning accuracy of pedestrian localization being much lower than that of robot localization, the influence of the human body on the radio propagation is experimentally evaluated. The result suggests that the influence of the human body can be modeled.

Original languageEnglish
JournalSensors (Switzerland)
Issue number2
Publication statusPublished - 2016 Jan 27


  • Hybrid positioning
  • IMES
  • Indoor positioning
  • Pedestrian dead reckoning

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering


Dive into the research topics of 'Improving IMES localization accuracy by integrating dead reckoning information'. Together they form a unique fingerprint.

Cite this