Heading Drift Reduction for Foot-Mounted Inertial Navigation System via Multi-Sensor Fusion and Dual-Gait Analysis

Foot-mounted inertial navigation is an important issue in areas such as pedestrian localization, gait analysis, and sport training. However, low-cost inertial sensors suffer from several errors that make the navigation results less convincing. In this paper, a multi-sensor approach with one sensor o...

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Published inIEEE sensors journal Vol. 19; no. 19; pp. 8514 - 8521
Main Authors Zhao, Hongyu, Wang, Zhelong, Qiu, Sen, Shen, Yanming, Zhang, Luyao, Tang, Kai, Fortino, Giancarlo
Format Journal Article
LanguageEnglish
Published New York IEEE 01.10.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Cost analysis
Drift
Dual-gait analysis
Feet
Foot
foot-mounted inertial navigation system (INS)
Force
Gait
Gait recognition
inertial measurement unit (IMU)
Inertial navigation
Inertial sensing devices
Mathematical model
multi-sensor fusion
Multisensor fusion
Navigation systems
Pendulums
Position measurement
Position sensing
Sensors
Subsystems
Velocity measurement
zero velocity updates (ZUPT)
Online AccessGet full text
ISSN1530-437X
1558-1748
DOI10.1109/JSEN.2018.2866802

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Abstract Foot-mounted inertial navigation is an important issue in areas such as pedestrian localization, gait analysis, and sport training. However, low-cost inertial sensors suffer from several errors that make the navigation results less convincing. In this paper, a multi-sensor approach with one sensor on each foot is presented to reduce the system heading drift. Through dual-gait analysis, gait parameters between two feet are employed to make the non-collocated and uncoupled subsystems be related to each other. A step length estimator based on an inverted pendulum model is developed to derive a relative position vector between the two foot-mounted sensors rather than a distance scalar. A Kalman-type filter with one time update and two measurement updates is developed to fuse the velocity and position observations at foot and person levels, respectively. Experiments were conducted by four healthy subjects, and experimental results show that the proposed sensor fusion method can effectively reduce the heading drift of inertial navigation and make the captured dual-foot motion closer to its actual process.
AbstractList Foot-mounted inertial navigation is an important issue in areas such as pedestrian localization, gait analysis, and sport training. However, low-cost inertial sensors suffer from several errors that make the navigation results less convincing. In this paper, a multi-sensor approach with one sensor on each foot is presented to reduce the system heading drift. Through dual-gait analysis, gait parameters between two feet are employed to make the non-collocated and uncoupled subsystems be related to each other. A step length estimator based on an inverted pendulum model is developed to derive a relative position vector between the two foot-mounted sensors rather than a distance scalar. A Kalman-type filter with one time update and two measurement updates is developed to fuse the velocity and position observations at foot and person levels, respectively. Experiments were conducted by four healthy subjects, and experimental results show that the proposed sensor fusion method can effectively reduce the heading drift of inertial navigation and make the captured dual-foot motion closer to its actual process.
Author Shen, Yanming
Wang, Zhelong
Zhao, Hongyu
Fortino, Giancarlo
Zhang, Luyao
Qiu, Sen
Tang, Kai
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Snippet Foot-mounted inertial navigation is an important issue in areas such as pedestrian localization, gait analysis, and sport training. However, low-cost inertial...
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SubjectTerms Cost analysis
Drift
Dual-gait analysis
Feet
Foot
foot-mounted inertial navigation system (INS)
Force
Gait
Gait recognition
inertial measurement unit (IMU)
Inertial navigation
Inertial sensing devices
Mathematical model
multi-sensor fusion
Multisensor fusion
Navigation systems
Pendulums
Position measurement
Position sensing
Sensors
Subsystems
Velocity measurement
zero velocity updates (ZUPT)
Title Heading Drift Reduction for Foot-Mounted Inertial Navigation System via Multi-Sensor Fusion and Dual-Gait Analysis
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Volume 19
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