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Sensors 2016, 16(9), 1455; doi:10.3390/s16091455

Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field

1
Department of Robotics and Virtual Engineering, University of Science and Technology (UST), Daejon 305-333, Korea
2
Robotics R & BD Group, Korea Institute of Industrial Technology (KITECH), Ansan 426-791, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Jörg F. Wagner
Received: 4 June 2016 / Revised: 29 August 2016 / Accepted: 5 September 2016 / Published: 9 September 2016
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)

Abstract

Pedestrian navigation systems (PNS) using foot-mounted MEMS inertial sensors use zero-velocity updates (ZUPTs) to reduce drift in navigation solutions and estimate inertial sensor errors. However, it is well known that ZUPTs cannot reduce all errors, especially as heading error is not observable. Hence, the position estimates tend to drift and even cyclic ZUPTs are applied in updated steps of the Extended Kalman Filter (EKF). This urges the use of other motion constraints for pedestrian gait and any other valuable heading reduction information that is available. In this paper, we exploit two more motion constraints scenarios of pedestrian gait: (1) walking along straight paths; (2) standing still for a long time. It is observed that these motion constraints (called “virtual sensor”), though considerably reducing drift in PNS, still need an absolute heading reference. One common absolute heading estimation sensor is the magnetometer, which senses the Earth’s magnetic field and, hence, the true heading angle can be calculated. However, magnetometers are susceptible to magnetic distortions, especially in indoor environments. In this work, an algorithm, called magnetic anomaly detection (MAD) and compensation is designed by incorporating only healthy magnetometer data in the EKF updating step, to reduce drift in zero-velocity updated INS. Experiments are conducted in GPS-denied and magnetically distorted environments to validate the proposed algorithms. View Full-Text
Keywords: pedestrian navigation system; drift reduction in INS; magnetic anomaly detection; multi-sensor fusion pedestrian navigation system; drift reduction in INS; magnetic anomaly detection; multi-sensor fusion
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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

Ilyas, M.; Cho, K.; Baeg, S.-H.; Park, S. Drift Reduction in Pedestrian Navigation System by Exploiting Motion Constraints and Magnetic Field. Sensors 2016, 16, 1455.

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