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IECE Transactions on Intelligent Systematics, 2024, Volume 1, Issue 1: 19-29

Free Access | Research Article | Feature Paper | 26 May 2024
1 School of Computer Science and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China
* Corresponding author: Binbin Wang, email: [email protected]
Received: 03 February 2024, Accepted: 20 May 2024, Published: 26 May 2024  

Abstract
A pedestrian navigation system (PNS) that only relies on the foot-mounted IMU is useful for various applications, especially under some severe conditions, such as tracking of firefighters and miners. Due to the complexity of the indoor environment, signal occlusion problems could lead to the failure of certain positioning methods. In complex environments such as fire rescue and emergency rescue, the barometric altimeter fails because of the influence of air pressure and temperature. This paper used an improved zero velocity detection algorithm to improve the accuracy of gait detection. Then, combine the Kalman filter with the zero velocity update algorithm to recognize gait accurately and take corresponding actions. Finally, the trajectory involving both horizontal and vertical movement was obtained, and the 3D positioning accuracy reached 97.5%. The proposed method avoids the redundancy of data fusion and can be used in complex unknown environments.

Graphical Abstract
Pedestrian Trajectory Reconstruction for Indoor Movement Based on Foot-Mounted IMU

Keywords
Pedestrian Navigation
Zero-velocity Detection
Kalman Filter
Foot-mounted IMU

References

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Cite This Article
APA Style
Wang, Y., & Wang B. (2024). Pedestrian Trajectory Reconstruction for Indoor Movement Based on Foot-Mounted IMU. IECE Transactions on Intelligent Systematics, 1(1), 19–29. https://doi.org/10.62762/TIS.2024.136995

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