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Sensors 2015, 15(12), 30759-30783; doi:10.3390/s151229827

A Hybrid Indoor Localization and Navigation System with Map Matching for Pedestrians Using Smartphones

1
College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
2
Department of Electrical and Computer Engineering, University of Auckland, Auckland 1010, New Zealand
3
Department of Information Science & Electronic Engineering, Zhejiang University, Hangzhou 310027, China
*
Author to whom correspondence should be addressed.
Academic Editors: Kourosh Khoshelham and Sisi Zlatanova
Received: 13 October 2015 / Accepted: 2 December 2015 / Published: 5 December 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
View Full-Text   |   Download PDF [2008 KB, uploaded 5 December 2015]   |  

Abstract

Pedestrian dead reckoning is a common technique applied in indoor inertial navigation systems that is able to provide accurate tracking performance within short distances. Sensor drift is the main bottleneck in extending the system to long-distance and long-term tracking. In this paper, a hybrid system integrating traditional pedestrian dead reckoning based on the use of inertial measurement units, short-range radio frequency systems and particle filter map matching is proposed. The system is a drift-free pedestrian navigation system where position error and sensor drift is regularly corrected and is able to provide long-term accurate and reliable tracking. Moreover, the whole system is implemented on a commercial off-the-shelf smartphone and achieves real-time positioning and tracking performance with satisfactory accuracy. View Full-Text
Keywords: pedestrian dead reckoning; hybrid; map matching; drift-free; particle filter pedestrian dead reckoning; hybrid; map matching; drift-free; particle filter
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).

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MDPI and ACS Style

Tian, Q.; Salcic, Z.; Wang, K.-K.; Pan, Y. A Hybrid Indoor Localization and Navigation System with Map Matching for Pedestrians Using Smartphones. Sensors 2015, 15, 30759-30783.

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