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Related Experiment Video

Updated: Mar 26, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

A Novel Pedestrian Navigation Algorithm for a Foot-Mounted Inertial-Sensor-Based System.

Mingrong Ren^1,2, Kai Pan^3,4, Yanhong Liu⁵

¹School of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, China. bjut_renmingrong@sohu.com.

Sensors (Basel, Switzerland)

|January 26, 2016

Summary

This summary is machine-generated.

This study introduces a new zero velocity update (ZUPT) method for pedestrian navigation systems (PNS). The novel approach achieves 0.89% mean relative accuracy, improving pedestrian tracking performance.

Keywords:

Kalman filter ZUPT foot-mounted PNS

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Last Updated: Mar 26, 2026

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

Home-Based Monitor for Gait and Activity Analysis

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

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Published on: November 7, 2014

Area of Science:

Robotics
Navigation Systems
Sensor Fusion

Background:

Pedestrian navigation systems (PNS) often suffer from accumulated errors.
Zero velocity updates (ZUPT) are crucial for mitigating drift in inertial navigation.
Existing ZUPT methods may lack robustness in diverse motion scenarios.

Purpose of the Study:

To propose a novel zero velocity update (ZUPT) method for foot-mounted pedestrian navigation systems (PNS).
To enhance the accuracy and reliability of pedestrian tracking.
To provide a robust ZUPT solution applicable across various motion modes.

Main Methods:

Development of a PNS error model and a corresponding Kalman filter.
Introduction of a novel zero velocity detection algorithm utilizing gait cycle speed variations.
Implementation of a finite state machine with three states to model gait cycles, using speed-based sliding window for state transitions.

Main Results:

Experimental validation of the proposed ZUPT method.
Demonstration of superior performance compared to existing methods.
Achieved a mean relative accuracy of 0.89% across various motion modes.

Conclusions:

The proposed ZUPT method significantly improves the accuracy of foot-mounted pedestrian navigation systems.
The novel zero velocity detection algorithm is effective in diverse dynamic conditions.
This approach offers a robust and accurate solution for pedestrian navigation.