Indoor navigation using Wi-Fi fingerprinting combined with pedestrian dead reckoning

Shan Jung Yu, Shau Shiun Jan, David S. De Lorenzo

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

11 Citations (Scopus)

Abstract

This paper presents a method by which to calibrate the Wi-Fi fingerprinting database with less effort using smartphone based Pedestrian Dead Reckoning (PDR) without any a-priori knowledge. Because the accumulated errors from PDR will decrease the quality of the database, we employ a quaternion based orientation extended Kalman filter (EKF) to deal with the pedestrian heading and to narrow down the PDR positioning error to 2.2 meters for a 270 meter path. Furthermore, we implement the Walkie-Markie method to enhance the accuracy of the PDR step positions used to replace the reference points (RPs) built into the Wi-Fi fingerprinting database. The method defines the Wi-Fi landmarks according to the trend of the Receive Signal Strength (RSS) collected by PDR and converges the pathway map using the Wi-Fi Marks (WMs). In a simulation scenario, the WMs and PDR pathway errors is nearly 0 meters.

Original languageEnglish
Title of host publication2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages246-253
Number of pages8
ISBN (Electronic)9781538616475
DOIs
Publication statusPublished - 2018 Jun 5
Event2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Monterey, United States
Duration: 2018 Apr 232018 Apr 26

Publication series

Name2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018 - Proceedings

Other

Other2018 IEEE/ION Position, Location and Navigation Symposium, PLANS 2018
Country/TerritoryUnited States
CityMonterey
Period18-04-2318-04-26

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Control and Optimization

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