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A Switched Approach for Smartphone-Based Pedestrian Navigation.

Shenglun Yi1, Mattia Zorzi1, Xuebo Jin2

  • 1Department of Information Engineering, University of Padova, Via Gradenigo 6/B, 35131 Padova, Italy.

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Summary

This study introduces a novel smartphone navigation method that works without Global Navigation Satellite System (GNSS) signals. It uses accelerometer data, denoised with an estimated bias, to maintain pedestrian navigation accuracy.

Keywords:
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Area of Science:

  • Mobile Sensing
  • Pedestrian Navigation
  • Sensor Fusion

Background:

  • Global Navigation Satellite System (GNSS) signals are often unavailable in urban or indoor environments, hindering smartphone-based pedestrian navigation.
  • Accurate pedestrian positioning is crucial for various location-based services.

Purpose of the Study:

  • To develop a novel switched approach for robust smartphone-based pedestrian navigation.
  • To enable navigation in environments with intermittent or unavailable GNSS signals.

Main Methods:

  • A switched approach is proposed, utilizing GNSS data when available to estimate position and accelerometer bias.
  • Estimated accelerometer bias is used to denoise sensor data during GNSS-denied periods.
  • Validation through a synthetic example and a real-world experiment on a 150m path.

Main Results:

  • The proposed method effectively denoises accelerometer measurements using the estimated average bias.
  • The approach demonstrates successful pedestrian navigation performance even when GNSS signals are unavailable.
  • Real-world experimental validation confirms the effectiveness of the navigation strategy.

Conclusions:

  • The novel switched approach enhances the reliability of smartphone-based pedestrian navigation in GNSS-challenged environments.
  • Denoising accelerometer data with estimated bias is a viable technique for continuous positioning.
  • This method offers a promising solution for ubiquitous pedestrian navigation.