A PDR Method Combining Smartphone and Smartwatch based on Multi-Scenario Map Matching

Tomoya Wakaizumi, Nozomu Togawa

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

Abstract

As smartphones are widely spread and used, the pedestrian navigation systems are utilized in our daily lives. A pedestrian dead reckoning method, or PDR method in short, is one of the positioning methods in indoor environments, which estimates user's positions by using sensors such as acceleration and angular velocity sensors. Particularly, by combining smartphone and smartwatch sensors, an effective PDR method has been proposed. This method can reduce drift errors even when the user carries his/her smartphone in various carrying modes without external infrastructures. However, the estimation errors tend to become large in the environments with many right and left turns. In this paper, we propose a PDR method combining smartphone and smartwatch sensors based on map information. In the proposed method, we generate walking nodes and walking edges from map information given and introduce multiple scenarios to effectively infer the user's current positions. Through experimental evaluation, we confirmed the effectiveness of the proposed method.

Original languageEnglish
Title of host publication2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages308-309
Number of pages2
ISBN (Electronic)9781665436762
DOIs
Publication statusPublished - 2021
Event10th IEEE Global Conference on Consumer Electronics, GCCE 2021 - Kyoto, Japan
Duration: 2021 Oct 122021 Oct 15

Publication series

Name2021 IEEE 10th Global Conference on Consumer Electronics, GCCE 2021

Conference

Conference10th IEEE Global Conference on Consumer Electronics, GCCE 2021
Country/TerritoryJapan
CityKyoto
Period21/10/1221/10/15

Keywords

  • PDR
  • carrying mode
  • indoor positioning
  • map matching
  • multi scenario
  • smartphone
  • smartwatch

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing
  • Biomedical Engineering
  • Electrical and Electronic Engineering
  • Media Technology
  • Instrumentation

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