Pedestrian inertial navigation: An overview of model and data-driven approaches

Research output: Contribution to journalArticlepeer-review

Abstract

The task of indoor positioning is fundamental to several applications, including navigation, healthcare, location-based services, and security. An emerging field is inertial navigation for pedestrians, which relies only on inertial sensors for positioning. In this paper, we present inertial pedestrian navigation models and learning approaches. Among these, are methods and algorithms for shoe-mounted inertial sensors and pedestrian dead reckoning (PDR) with unconstrained inertial sensors. We also address three categories of data-driven PDR strategies: activity-assisted, hybrid approaches, and learning-based frameworks.

Original languageEnglish
Article number104077
JournalResults in Engineering
Volume25
DOIs
StatePublished - Mar 2025

Bibliographical note

Publisher Copyright:
© 2025 The Author

Keywords

  • Inertial sensors
  • Machine learning
  • Pedestrian dead reckoning

ASJC Scopus subject areas

  • General Engineering

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