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Pseudo-Zero Velocity Re-Detection Double Threshold Zero-Velocity Update (ZUPT) for Inertial Sensor-Based Pedestrian Navigation

Authors :
Mohammed Jalal Ahamed
Tianyi Zhao
Source :
IEEE Sensors Journal. 21:13772-13785
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

Zero-velocity update method (ZUPT) is widely used in inertial measurement unit (IMU)-based pedestrian navigation systems for mitigating sensor drifting error. In the basic pedestrian dead reckoning (PDR) system, especially in the foot-tie PDR system, zero-velocity update method with Kalman filter are two core algorithms. In the basic PDR system, ZUPT usually uses a single threshold to judge the gait of pedestrians. A single threshold, however, makes ZUPT unable to accurately judge the gait of pedestrians in different road conditions. In this paper, we propose a new, redesigned ZUPT method without using additional equipment and filter algorithms to further improve the accuracy of correction results. The method uses a sliding detection algorithm to help re-detect the zero-velocity intervals, aiming to remove the pseudo-zero velocity interval and the pseudo-motion interval, as well as improving the performance of the ZUPT method. The method was implemented in a shoe-mounted IMU-based navigation system. For walking step detection tests, the accuracy of the proposed modified ZUPT method reached 87.24%, 25% higher than the conventional methods. In a long-distance walking path tracking test, the mean error of the estimated path of our method is 0.61 m, an 81.69% reduction compared to the conventional ZUPT methods. The details of the improved ZUPT method presented in this paper not only enable the tracking technology to better track a pedestrian’s step changes during walking, but also provide better calculation conditions for subsequent filter operations.

Details

ISSN :
23799153 and 1530437X
Volume :
21
Database :
OpenAIRE
Journal :
IEEE Sensors Journal
Accession number :
edsair.doi...........dceaa90bdaaecc7726f19883773ecf8b