Next Article in Journal
DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field
Next Article in Special Issue
Anatomical Calibration through Post-Processing of Standard Motion Tests Data
Previous Article in Journal
Indoor Location Sensing with Invariant Wi-Fi Received Signal Strength Fingerprinting
Previous Article in Special Issue
Coarse Alignment of Marine Strapdown INS Based on the Trajectory Fitting of Gravity Movement in the Inertial Space
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(11), 1903; doi:10.3390/s16111903

Advanced Pedestrian Positioning System to Smartphones and Smartwatches

1
Telecommunications and Systems Engineering Department, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain
2
Institute of Communications and Navigation, German Aerospace Center, Oberpfaffenhofen 82234, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Jörg Wagner
Received: 19 August 2016 / Revised: 7 November 2016 / Accepted: 9 November 2016 / Published: 11 November 2016
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
View Full-Text   |   Download PDF [2532 KB, uploaded 11 November 2016]   |  

Abstract

In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user’s position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m 2 . View Full-Text
Keywords: inertial sensors and systems; smartphone navigation systems; aiding technology for INS; smartwatch; received signal strength inertial sensors and systems; smartphone navigation systems; aiding technology for INS; smartwatch; received signal strength
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

Correa, A.; Munoz Diaz, E.; Bousdar Ahmed, D.; Morell, A.; Lopez Vicario, J. Advanced Pedestrian Positioning System to Smartphones and Smartwatches. Sensors 2016, 16, 1903.

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