Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering

In order to overcome the poor observability of yaw measurement for foot-mounted inertial measurement unit (IMU), an integrated IMU+Compass scheme for self-contained pedestrian navigation is presented. In this mode, the compass measurement is used to provide the accurate yaw to improve the accuracy o...

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Main Authors: Meng Hou, Yuan Xu, Xiao Liu
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2018/8401967
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spelling doaj-ce6e85f8c5444127b11e168ca111cd842021-07-02T02:06:32ZengHindawi LimitedJournal of Electrical and Computer Engineering2090-01472090-01552018-01-01201810.1155/2018/84019678401967Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR FilteringMeng Hou0Yuan Xu1Xiao Liu2School of Electrical Engineering and Automation, Qilu University of Technology, Jinan 250353, ChinaThe School of Electrical Engineering, University of Jinan, Jinan 250022, ChinaSchool of Electrical Engineering and Automation, Qilu University of Technology, Jinan 250353, ChinaIn order to overcome the poor observability of yaw measurement for foot-mounted inertial measurement unit (IMU), an integrated IMU+Compass scheme for self-contained pedestrian navigation is presented. In this mode, the compass measurement is used to provide the accurate yaw to improve the accuracy of the attitude transformation matrix for the foot-mounted IMU solution. And then, when the person is in a stance phase during walk, a unbiased finite impulse response (UFIR) filter based on the self-contained pedestrian navigation scheme is investigated, which just needs the state vector size MU and the filtering horizon size NU, while ignoring the noise statistics compared with the Kalman filter (KF). Finally, a real test has been done to verify the performance of the proposed self-contained pedestrian navigation using the IMU and compass measurements via UFIR filter. The test results show that the proposed filter has robust performance compared with the KF.http://dx.doi.org/10.1155/2018/8401967
collection DOAJ
language English
format Article
sources DOAJ
author Meng Hou
Yuan Xu
Xiao Liu
spellingShingle Meng Hou
Yuan Xu
Xiao Liu
Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering
Journal of Electrical and Computer Engineering
author_facet Meng Hou
Yuan Xu
Xiao Liu
author_sort Meng Hou
title Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering
title_short Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering
title_full Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering
title_fullStr Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering
title_full_unstemmed Robust Self-Contained Pedestrian Navigation by Fusing the IMU and Compass Measurements via UFIR Filtering
title_sort robust self-contained pedestrian navigation by fusing the imu and compass measurements via ufir filtering
publisher Hindawi Limited
series Journal of Electrical and Computer Engineering
issn 2090-0147
2090-0155
publishDate 2018-01-01
description In order to overcome the poor observability of yaw measurement for foot-mounted inertial measurement unit (IMU), an integrated IMU+Compass scheme for self-contained pedestrian navigation is presented. In this mode, the compass measurement is used to provide the accurate yaw to improve the accuracy of the attitude transformation matrix for the foot-mounted IMU solution. And then, when the person is in a stance phase during walk, a unbiased finite impulse response (UFIR) filter based on the self-contained pedestrian navigation scheme is investigated, which just needs the state vector size MU and the filtering horizon size NU, while ignoring the noise statistics compared with the Kalman filter (KF). Finally, a real test has been done to verify the performance of the proposed self-contained pedestrian navigation using the IMU and compass measurements via UFIR filter. The test results show that the proposed filter has robust performance compared with the KF.
url http://dx.doi.org/10.1155/2018/8401967
work_keys_str_mv AT menghou robustselfcontainedpedestriannavigationbyfusingtheimuandcompassmeasurementsviaufirfiltering
AT yuanxu robustselfcontainedpedestriannavigationbyfusingtheimuandcompassmeasurementsviaufirfiltering
AT xiaoliu robustselfcontainedpedestriannavigationbyfusingtheimuandcompassmeasurementsviaufirfiltering
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