Pedestrian Inertial Navigation: An Overview of Model and Data-Driven Approaches

Fuente: arXiv
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Autore principale: Klein, Itzik
Natura: Preprint
Pubblicazione: 2024
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author Klein, Itzik
author_facet Klein, Itzik
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2407_21676
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Pedestrian Inertial Navigation: An Overview of Model and Data-Driven Approaches
Klein, Itzik
Robotics
Signal Processing
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.
title Pedestrian Inertial Navigation: An Overview of Model and Data-Driven Approaches
topic Robotics
Signal Processing
url https://arxiv.org/abs/2407.21676