Next Article in Journal
Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree
Previous Article in Journal
Fabrication and Characterization of a High-Performance Multi-Annular Backscattered Electron Detector for Desktop SEM
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(9), 3095; https://doi.org/10.3390/s18093095

Optimization-Based Wi-Fi Radio Map Construction for Indoor Positioning Using Only Smart Phones

1
Hainan Key Laboratory of Earth Observation, Sanya 572029, China
2
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
3
School of Public Administration and Mass Media, Beijing Information Science and Technology University, Beijing 100093, China
*
Author to whom correspondence should be addressed.
Received: 16 August 2018 / Revised: 8 September 2018 / Accepted: 11 September 2018 / Published: 14 September 2018
(This article belongs to the Section Intelligent Sensors)
Full-Text   |   PDF [4310 KB, uploaded 14 September 2018]   |  

Abstract

Fingerprinting-based Wi-Fi indoor positioning has great potential for positioning in GPS-denied areas. However, establishing a fingerprinting map (also called a radio map) prior to positioning (site survey) is normally a labor-intensive task. This paper proposes a method for easy site survey without need for any extra hardware. The user can conduct the site survey adopting only a smart phone. The collected inertial-based readings are processed using the pedestrian dead-reckoning algorithms to generate a raw trajectory. Then a factor graph optimization method is proposed to re-estimate the trajectory by adding constraints originated from collected Wi-Fi fingerprints and landmark positions. The proposed method is verified through an experiment in a mall. The mean positioning error is 1.10 m and the maximum error is 2.25 m. This level of positioning accuracy is considered sufficient for radio map generation purposes. A classical baseline algorithm, the k-Nearest Neighbor (kNN) algorithm, is adopted to test the positioning performance of the radio map (RM), which also validates the quality of the constructed RM from the proposed method. View Full-Text
Keywords: Wi-Fi indoor positioning; radio map; pedestrian dead reckoning; factor graph optimization Wi-Fi indoor positioning; radio map; pedestrian dead reckoning; factor graph optimization
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

Share & Cite This Article

MDPI and ACS Style

Tan, J.; Fan, X.; Wang, S.; Ren, Y. Optimization-Based Wi-Fi Radio Map Construction for Indoor Positioning Using Only Smart Phones. Sensors 2018, 18, 3095.

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