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Sensors 2014, 14(12), 22864-22890; doi:10.3390/s141222864

Magnetic, Acceleration Fields and Gyroscope Quaternion (MAGYQ)-Based Attitude Estimation with Smartphone Sensors for Indoor Pedestrian Navigation

IFSTTAR, GEOLOC Laboratory, Route de Bouaye CS4, Bouguenais 44344, France
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Received: 22 September 2014 / Revised: 11 November 2014 / Accepted: 25 November 2014 / Published: 2 December 2014
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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Abstract

The dependence of proposed pedestrian navigation solutions on a dedicated infrastructure is a limiting factor to the deployment of location based services. Consequently self-contained Pedestrian Dead-Reckoning (PDR) approaches are gaining interest for autonomous navigation. Even if the quality of low cost inertial sensors and magnetometers has strongly improved, processing noisy sensor signals combined with high hand dynamics remains a challenge. Estimating accurate attitude angles for achieving long term positioning accuracy is targeted in this work. A new Magnetic, Acceleration fields and GYroscope Quaternion (MAGYQ)-based attitude angles estimation filter is proposed and demonstrated with handheld sensors. It benefits from a gyroscope signal modelling in the quaternion set and two new opportunistic updates: magnetic angular rate update (MARU) and acceleration gradient update (AGU). MAGYQ filter performances are assessed indoors, outdoors, with dynamic and static motion conditions. The heading error, using only the inertial solution, is found to be less than 10° after 1.5 km walking. The performance is also evaluated in the positioning domain with trajectories computed following a PDR strategy. View Full-Text
Keywords: indoor navigation; MEMS; quaternion; attitude estimation; Kalman filter; magnetic angular rate update; acceleration gradient update; magnetometer indoor navigation; MEMS; quaternion; attitude estimation; Kalman filter; magnetic angular rate update; acceleration gradient update; magnetometer
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Renaudin, V.; Combettes, C. Magnetic, Acceleration Fields and Gyroscope Quaternion (MAGYQ)-Based Attitude Estimation with Smartphone Sensors for Indoor Pedestrian Navigation. Sensors 2014, 14, 22864-22890.

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