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A reliable and accurate indoor localization method using phone inertial sensors

Published: 05 September 2012 Publication History

Abstract

This paper addresses reliable and accurate indoor localization using inertial sensors commonly found on commodity smartphones. We believe indoor positioning is an important primitive that can enable many ubiquitous computing applications. To tackle the challenges of drifting in estimation, sensitivity to phone position, as well as variability in user walking profiles, we have developed algorithms for reliable detection of steps and heading directions, and accurate estimation and personalization of step length. We've built an end-to-end localization system integrating these modules and an indoor floor map, without the need for infrastructure assistance. We demonstrated for the first time a meter-level indoor positioning system that is infrastructure free, phone position independent, user adaptive, and easy to deploy. We have conducted extensive experiments on users with smartphone devices, with over 50 subjects walking over an aggregate distance of over 40 kilometers. Evaluation results showed our system can achieve a mean accuracy of 1.5m for the in-hand case and 2m for the in-pocket case in a 31m×15m testing area.

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cover image ACM Conferences
UbiComp '12: Proceedings of the 2012 ACM Conference on Ubiquitous Computing
September 2012
1268 pages
ISBN:9781450312240
DOI:10.1145/2370216
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 05 September 2012

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Author Tags

  1. indoor localization
  2. inertial tracking
  3. pedestrian model

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Ubicomp '12
Ubicomp '12: The 2012 ACM Conference on Ubiquitous Computing
September 5 - 8, 2012
Pennsylvania, Pittsburgh

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UbiComp '12 Paper Acceptance Rate 58 of 301 submissions, 19%;
Overall Acceptance Rate 764 of 2,912 submissions, 26%

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  • (2025)Particle filter-based BLE and IMU fusion algorithm for indoor localizationTelecommunications Systems10.1007/s11235-024-01230-688:1Online publication date: 1-Mar-2025
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