A Wearable Pedestrian Localization and Gait Identification System Using Kalman Filtered Inertial Data

In this article, we introduce a pedestrian dead reckoning (PDR)-based navigation device that does not require global navigation satellite system (GNSS) signals or beacons and works with an inertial measurement unit (IMU) mounted on its waist belt. The system identifies the individual by their walkin...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2021, Vol.70, p.1-8
Main Authors: Hajati, Nasim, Rezaeizadeh, Amin
Format: Article
Language:English
Subjects:
Accelerometers
Algorithms
Computational modeling
Dead reckoning
Estimation
Euler angles
extended Kalman filter (EKF)
Gait
Global navigation satellite system
Gyroscopes
Inertial platforms
Kalman filters
Legged locomotion
Navigation systems
pedestrian dead reckoning (PDR)
position estimation
random forest
Sensors
step detection
unscented Kalman filter (UKF)
user identification
Walking
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Description
Summary:In this article, we introduce a pedestrian dead reckoning (PDR)-based navigation device that does not require global navigation satellite system (GNSS) signals or beacons and works with an inertial measurement unit (IMU) mounted on its waist belt. The system identifies the individual by their walking pattern to use the proper gains in the computations, estimates the attitude by applying an unscented Kalman filter, and finally derives the position in three dimensions with the help of a step detection algorithm. The experimental results show an outdoor 4.7-km walk resulting in an error of 0.96%.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2021.3073440