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GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation
The urban setting is a challenging environment for GNSS receivers. Multipath and other anomalies typically increase the positioning error of the receiver. Moreover, the error estimate of the position is often unreliable. In this study, we detect GNSS trajectory anomalies by using similarity comparis...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165389/ https://www.ncbi.nlm.nih.gov/pubmed/30235863 http://dx.doi.org/10.3390/s18093165 |
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author | Peltola, Pekka Xiao, Jialin Moore, Terry Jiménez, Antonio R. Seco, Fernando |
author_facet | Peltola, Pekka Xiao, Jialin Moore, Terry Jiménez, Antonio R. Seco, Fernando |
author_sort | Peltola, Pekka |
collection | PubMed |
description | The urban setting is a challenging environment for GNSS receivers. Multipath and other anomalies typically increase the positioning error of the receiver. Moreover, the error estimate of the position is often unreliable. In this study, we detect GNSS trajectory anomalies by using similarity comparison methods between a pedestrian dead reckoning trajectory, recorded using a foot-mounted inertial measurement unit, and the corresponding GNSS trajectory. During a normal walk, the foot-mounted inertial dead reckoning setup is trustworthy up to a few tens of meters. Thus, the differing GNSS trajectory can be detected using form similarity comparison methods. Of the eight tested methods, the Hausdorff distance (HD) and the accumulated distance difference (ADD) give slightly more consistent detection results compared to the rest. |
format | Online Article Text |
id | pubmed-6165389 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61653892018-10-10 GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation Peltola, Pekka Xiao, Jialin Moore, Terry Jiménez, Antonio R. Seco, Fernando Sensors (Basel) Article The urban setting is a challenging environment for GNSS receivers. Multipath and other anomalies typically increase the positioning error of the receiver. Moreover, the error estimate of the position is often unreliable. In this study, we detect GNSS trajectory anomalies by using similarity comparison methods between a pedestrian dead reckoning trajectory, recorded using a foot-mounted inertial measurement unit, and the corresponding GNSS trajectory. During a normal walk, the foot-mounted inertial dead reckoning setup is trustworthy up to a few tens of meters. Thus, the differing GNSS trajectory can be detected using form similarity comparison methods. Of the eight tested methods, the Hausdorff distance (HD) and the accumulated distance difference (ADD) give slightly more consistent detection results compared to the rest. MDPI 2018-09-19 /pmc/articles/PMC6165389/ /pubmed/30235863 http://dx.doi.org/10.3390/s18093165 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 Peltola, Pekka Xiao, Jialin Moore, Terry Jiménez, Antonio R. Seco, Fernando GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
title | GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
title_full | GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
title_fullStr | GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
title_full_unstemmed | GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
title_short | GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
title_sort | gnss trajectory anomaly detection using similarity comparison methods for pedestrian navigation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165389/ https://www.ncbi.nlm.nih.gov/pubmed/30235863 http://dx.doi.org/10.3390/s18093165 |
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