Date of Award

Summer 2021

Publication Type

Thesis

Degree Name

M.A.Sc.

Department

Mechanical, Automotive, and Materials Engineering

First Advisor

J. Ahmed

Second Advisor

X. Chen

Third Advisor

A. Rahimi

Keywords

Inertial navigation, MEMS navigation, Path tracking, PDR, Sensors, Zero velocity update

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Zero-velocity update method is widely used in inertial measurement unit based pedestrian navigation systems for mitigating sensor drifting error. In the basic pedestrian dead reckoning system, especially in a foot-tie PDR system, zero-velocity update method and a 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 thesis paper, we propose a new, redesigned zero-velocity update method without using additional equipment and filter algorithms to further improve the accuracy of the 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 3-6 km/h walking speed step detection tests, the accuracy of the proposed ZUPT method has an average 23.7% higher than the conventional methods. In a long-distance walking path tracking test, the mean error of the estimated path for our method is 0.61 m, which is an 81.69% reduction compared to the conventional ZUPT methods. The details of the improved ZUPT method presented in this paper not only enables the tracking technology to better track a pedestrian's step changes during walking, but also provides better calculation conditions for subsequent filter operations.

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