Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning

<p/> <p>This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used fo...

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Main Authors: Evennou Fr&#233;d&#233;ric, Marx Fran&#231;ois
Format: Article
Language:English
Published: SpringerOpen 2006-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://dx.doi.org/10.1155/ASP/2006/86706
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author Evennou Fr&#233;d&#233;ric
Marx Fran&#231;ois
author_facet Evennou Fr&#233;d&#233;ric
Marx Fran&#231;ois
author_sort Evennou Fr&#233;d&#233;ric
collection DOAJ
description <p/> <p>This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.</p>
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spelling doaj.art-4eebf088f81545539e5f40b8a5f698c62022-12-22T03:21:55ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802006-01-0120061086706Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile PositioningEvennou Fr&#233;d&#233;ricMarx Fran&#231;ois<p/> <p>This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.</p>http://dx.doi.org/10.1155/ASP/2006/86706
spellingShingle Evennou Fr&#233;d&#233;ric
Marx Fran&#231;ois
Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
EURASIP Journal on Advances in Signal Processing
title Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
title_full Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
title_fullStr Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
title_full_unstemmed Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
title_short Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning
title_sort advanced integration of wifi and inertial navigation systems for indoor mobile positioning
url http://dx.doi.org/10.1155/ASP/2006/86706
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AT marxfran231ois advancedintegrationofwifiandinertialnavigationsystemsforindoormobilepositioning