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Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone

The ubiquity of sensor-rich smartphones provides opportunities for a low-cost method to track indoor pedestrians. In this situation, pedestrian dead reckoning (PDR) is a widely used technology; however, its cumulative error seriously affects its accuracy. This paper presents a method of combining in...

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Detalles Bibliográficos
Autores principales: Song, Xiyu, Wang, Mei, Qiu, Hongbing, Luo, Liyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308701/
https://www.ncbi.nlm.nih.gov/pubmed/30486301
http://dx.doi.org/10.3390/s18124143
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author Song, Xiyu
Wang, Mei
Qiu, Hongbing
Luo, Liyan
author_facet Song, Xiyu
Wang, Mei
Qiu, Hongbing
Luo, Liyan
author_sort Song, Xiyu
collection PubMed
description The ubiquity of sensor-rich smartphones provides opportunities for a low-cost method to track indoor pedestrians. In this situation, pedestrian dead reckoning (PDR) is a widely used technology; however, its cumulative error seriously affects its accuracy. This paper presents a method of combining infrastructure-free indoor acoustic self-positioning with PDR self-positioning, which verifies the rationality of PDR results through the acoustic constraint between a sound source and its image sources. We further determine the first-order echo delay measurements, thus obtaining the mobile user position. We verify that the proposed method can achieve a continuous self-positioning median error of 0.19 m, and the error probability below 0.12 m is 54.46%, which indicates its ability to eliminate PDR error, as well as its adaptability to environmental disturbances.
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spelling pubmed-63087012019-01-04 Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone Song, Xiyu Wang, Mei Qiu, Hongbing Luo, Liyan Sensors (Basel) Article The ubiquity of sensor-rich smartphones provides opportunities for a low-cost method to track indoor pedestrians. In this situation, pedestrian dead reckoning (PDR) is a widely used technology; however, its cumulative error seriously affects its accuracy. This paper presents a method of combining infrastructure-free indoor acoustic self-positioning with PDR self-positioning, which verifies the rationality of PDR results through the acoustic constraint between a sound source and its image sources. We further determine the first-order echo delay measurements, thus obtaining the mobile user position. We verify that the proposed method can achieve a continuous self-positioning median error of 0.19 m, and the error probability below 0.12 m is 54.46%, which indicates its ability to eliminate PDR error, as well as its adaptability to environmental disturbances. MDPI 2018-11-26 /pmc/articles/PMC6308701/ /pubmed/30486301 http://dx.doi.org/10.3390/s18124143 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Song, Xiyu
Wang, Mei
Qiu, Hongbing
Luo, Liyan
Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
title Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
title_full Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
title_fullStr Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
title_full_unstemmed Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
title_short Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone
title_sort indoor pedestrian self-positioning based on image acoustic source impulse using a sensor-rich smartphone
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308701/
https://www.ncbi.nlm.nih.gov/pubmed/30486301
http://dx.doi.org/10.3390/s18124143
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