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Sensors 2015, 15(9), 21518-21536; doi:10.3390/s150921518

Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket

School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
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Author to whom correspondence should be addressed.
Academic Editor: Kourosh Khoshelham
Received: 26 June 2015 / Revised: 20 August 2015 / Accepted: 21 August 2015 / Published: 28 August 2015
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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Abstract

Heading estimation is a central problem for indoor pedestrian navigation using the pervasively available smartphone. For smartphones placed in a pocket, one of the most popular device positions, the essential challenges in heading estimation are the changing device coordinate system and the severe indoor magnetic perturbations. To address these challenges, we propose a novel heading estimation approach based on a rotation matrix and principal component analysis (PCA). Firstly, through a related rotation matrix, we project the acceleration signals into a reference coordinate system (RCS), where a more accurate estimation of the horizontal plane of the acceleration signal is obtained. Then, we utilize PCA over the horizontal plane of acceleration signals for local walking direction extraction. Finally, in order to translate the local walking direction into the global one, we develop a calibration process without requiring noisy compass readings. Besides, a turn detection algorithm is proposed to improve the heading estimation accuracy. Experimental results show that our approach outperforms the traditional uDirect and PCA-based approaches in terms of accuracy and feasibility. View Full-Text
Keywords: indoor navigation; heading estimation; rotation matrix; principal component analysis; smartphone sensors indoor navigation; heading estimation; rotation matrix; principal component analysis; smartphone sensors
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

Deng, Z.-A.; Wang, G.; Hu, Y.; Wu, D. Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket. Sensors 2015, 15, 21518-21536.

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