Next Article in Journal
Control and Guidance of Low-Cost Robots via Gesture Perception for Monitoring Activities in the Home
Previous Article in Journal
Energy-Efficient Algorithm for Multicasting in Duty-Cycled Sensor Networks
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(12), 31244-31267; doi:10.3390/s151229850

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones

1
Institute of Remote Sensing and GIS, Peking University, No. 5 Yiheyuan Road, Haidian District, Beijing 100871, China
2
National Remote Sensing Center of China, No. 8A, Liulinguan Nanli, Haidian District, Beijing 100036, China
3
Beijing Aerospace Unmanned Vehicles System Engineering Research Institute, No. 1 Fengyingdong Road, Haidian District, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 5 October 2015 / Revised: 3 December 2015 / Accepted: 4 December 2015 / Published: 11 December 2015
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [8222 KB, uploaded 11 December 2015]   |  

Abstract

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move. View Full-Text
Keywords: indoor positioning; Wi-Fi; PDR; multi-sensor fusion; TCPF indoor positioning; Wi-Fi; PDR; multi-sensor fusion; TCPF
Figures

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

Li, H.; Chen, X.; Jing, G.; Wang, Y.; Cao, Y.; Li, F.; Zhang, X.; Xiao, H. An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones. Sensors 2015, 15, 31244-31267.

Show more citation formats Show less citations formats

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