Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket
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 i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-08-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/15/9/21518 |
| _version_ | 1828277915839627264 |
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| author | Zhi-An Deng Guofeng Wang Ying Hu Di Wu |
| author_facet | Zhi-An Deng Guofeng Wang Ying Hu Di Wu |
| author_sort | Zhi-An Deng |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T07:22:08Z |
| format | Article |
| id | doaj.art-2025c98a79874e86b3fd9e25e7ca97f5 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T07:22:08Z |
| publishDate | 2015-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2025c98a79874e86b3fd9e25e7ca97f52022-12-22T02:56:35ZengMDPI AGSensors1424-82202015-08-01159215182153610.3390/s150921518s150921518Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the PocketZhi-An Deng0Guofeng Wang1Ying Hu2Di Wu3School of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaSchool of Information Science and Technology, Dalian Maritime University, Dalian 116026, ChinaHeading 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.http://www.mdpi.com/1424-8220/15/9/21518indoor navigationheading estimationrotation matrixprincipal component analysissmartphone sensors |
| spellingShingle | Zhi-An Deng Guofeng Wang Ying Hu Di Wu Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket Sensors indoor navigation heading estimation rotation matrix principal component analysis smartphone sensors |
| title | Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket |
| title_full | Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket |
| title_fullStr | Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket |
| title_full_unstemmed | Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket |
| title_short | Heading Estimation for Indoor Pedestrian Navigation Using a Smartphone in the Pocket |
| title_sort | heading estimation for indoor pedestrian navigation using a smartphone in the pocket |
| topic | indoor navigation heading estimation rotation matrix principal component analysis smartphone sensors |
| url | http://www.mdpi.com/1424-8220/15/9/21518 |
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