Next Article in Journal
Assessing Motor Fluctuations in Parkinson’s Disease Patients Based on a Single Inertial Sensor
Next Article in Special Issue
GridiLoc: A Backtracking Grid Filter for Fusing the Grid Model with PDR Using Smartphone Sensors
Previous Article in Journal
Towards Automated Large-Scale 3D Phenotyping of Vineyards under Field Conditions
Previous Article in Special Issue
Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(12), 2135; doi:10.3390/s16122135

An Indoor Positioning Method for Smartphones Using Landmarks and PDR

1
Department of Computer Science and Technology, Ocean University of China, Qingdao 266100, China
2
Department of Computer Foundation, Ocean University of China, Qingdao 266100, China
3
Information Center, Administration for Industry and Commerce of Qingdao, Qingdao 266071, China
This paper is an extended version of our paper published in Wang, X.; Jiang, M.; Guo, Z.; Hu, N.; Sun, Z.; Liu, J. LaP: Landmark-Aided PDR on Smartphones for Indoor Mobile Positioning. In Big Data Computing and Communications; Springer: Berlin/Heidelberg, Germany, 2016.
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Yu Wang
Received: 31 August 2016 / Revised: 30 November 2016 / Accepted: 6 December 2016 / Published: 15 December 2016
View Full-Text   |   Download PDF [877 KB, uploaded 15 December 2016]   |  

Abstract

Recently location based services (LBS) have become increasingly popular in indoor environments. Among these indoor positioning techniques providing LBS, a fusion approach combining WiFi-based and pedestrian dead reckoning (PDR) techniques is drawing more and more attention of researchers. Although this fusion method performs well in some cases, it still has some limitations, such as heavy computation and inconvenience for real-time use. In this work, we study map information of a given indoor environment, analyze variations of WiFi received signal strength (RSS), define several kinds of indoor landmarks, and then utilize these landmarks to correct accumulated errors derived from PDR. This fusion scheme, called Landmark-aided PDR (LaP), is proved to be light-weight and suitable for real-time implementation by running an Android application designed for the experiment. We compared LaP with other PDR-based fusion approaches. Experimental results show that the proposed scheme can achieve a significant improvement with an average accuracy of 2.17 m. View Full-Text
Keywords: indoor positioning; PDR; landmarks; fusion indoor positioning; PDR; landmarks; fusion
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wang, X.; Jiang, M.; Guo, Z.; Hu, N.; Sun, Z.; Liu, J. An Indoor Positioning Method for Smartphones Using Landmarks and PDR. Sensors 2016, 16, 2135.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top