Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 70, Issue -, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2021.3073440
Keywords
Euler angles; extended Kalman filter (EKF); pedestrian dead reckoning (PDR); position estimation; random forest; step detection; unscented Kalman filter (UKF); user identification
Funding
- NOVE Company [Nafar-1398]
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This article presents a PDR-based navigation device that utilizes a pedestrian's walking pattern to identify individuals, does not rely on GNSS signals or beacons, and utilizes an IMU for attitude estimation and position calculation using a step detection algorithm. Experimental results show a 0.96% error for a 4.7km outdoor walk.
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%.
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