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An Adaptive Zero Velocity Detection Algorithm Based on Multi-Sensor Fusion for a Pedestrian Navigation System.

Ming Ma1, Qian Song2, Yang Gu3

  • 1School of Electronic Science, National University of Defense Technology, Changsha 410073, China. maming@nudt.edu.cn.

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|October 3, 2018
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Summary
This summary is machine-generated.

This study introduces an adaptive zero velocity detection method using multi-sensor fusion for pedestrian navigation. The approach improves accuracy during high speeds and stair climbing, enhancing navigation system reliability.

Keywords:
ZUPTadaptive thresholdpedestrian navigation systemstairs recognitionzero velocity detection

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Area of Science:

  • Sensor Fusion
  • Pedestrian Navigation Systems
  • Algorithm Development

Background:

  • Zero velocity update (ZUPT) is crucial for pedestrian navigation accuracy.
  • Current ZUPT methods struggle with high gait speeds and stair climbing.
  • Accurate zero velocity interval detection is essential for ZUPT performance.

Purpose of the Study:

  • To develop an adaptive zero velocity detection approach for improved pedestrian navigation.
  • To enhance ZUPT algorithm performance across diverse motion modes.
  • To address limitations of existing zero velocity detection techniques.

Main Methods:

  • Multi-sensor fusion incorporating accelerometer, gyroscope, and pressure sensor data.
  • Development of an adaptive threshold for robust zero velocity detection.
  • Implementation of a stairs recognition method to mitigate height drift.

Main Results:

  • The proposed adaptive method accurately detects zero velocity intervals in various motion scenarios.
  • Improved detection performance at high gait speeds and during stair climbing.
  • Successful distinction between staircase and level walking movements.

Conclusions:

  • The adaptive multi-sensor fusion approach significantly enhances zero velocity detection for pedestrian navigation.
  • This method offers a more reliable solution for navigation systems operating in complex environments.
  • The developed technique effectively suppresses error growth in foot-mounted navigation systems.