Cargando…

Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion

In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positionin...

Descripción completa

Detalles Bibliográficos
Autores principales: Hellmers, Hendrik, Kasmi, Zakaria, Norrdine, Abdelmoumen, Eichhorn, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795943/
https://www.ncbi.nlm.nih.gov/pubmed/29300358
http://dx.doi.org/10.3390/s18010126
_version_ 1783297396355104768
author Hellmers, Hendrik
Kasmi, Zakaria
Norrdine, Abdelmoumen
Eichhorn, Andreas
author_facet Hellmers, Hendrik
Kasmi, Zakaria
Norrdine, Abdelmoumen
Eichhorn, Andreas
author_sort Hellmers, Hendrik
collection PubMed
description In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform’s altitude.
format Online
Article
Text
id pubmed-5795943
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-57959432018-02-13 Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion Hellmers, Hendrik Kasmi, Zakaria Norrdine, Abdelmoumen Eichhorn, Andreas Sensors (Basel) Article In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform’s altitude. MDPI 2018-01-04 /pmc/articles/PMC5795943/ /pubmed/29300358 http://dx.doi.org/10.3390/s18010126 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
Hellmers, Hendrik
Kasmi, Zakaria
Norrdine, Abdelmoumen
Eichhorn, Andreas
Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion
title Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion
title_full Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion
title_fullStr Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion
title_full_unstemmed Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion
title_short Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion
title_sort accurate 3d positioning for a mobile platform in non-line-of-sight scenarios based on imu/magnetometer sensor fusion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795943/
https://www.ncbi.nlm.nih.gov/pubmed/29300358
http://dx.doi.org/10.3390/s18010126
work_keys_str_mv AT hellmershendrik accurate3dpositioningforamobileplatforminnonlineofsightscenariosbasedonimumagnetometersensorfusion
AT kasmizakaria accurate3dpositioningforamobileplatforminnonlineofsightscenariosbasedonimumagnetometersensorfusion
AT norrdineabdelmoumen accurate3dpositioningforamobileplatforminnonlineofsightscenariosbasedonimumagnetometersensorfusion
AT eichhornandreas accurate3dpositioningforamobileplatforminnonlineofsightscenariosbasedonimumagnetometersensorfusion