A reliable and accurate indoor localization method using phone inertial sensors

TLDR

Indoor positioning is a key primitive enabling many ubiquitous computing applications. The study aims to provide reliable and accurate indoor localization using commodity smartphone inertial sensors. The authors developed step and heading detection algorithms, personalized step‑length estimation, and validated them with extensive experiments involving over 50 users covering more than 40 km. The resulting system delivers infrastructure‑free, phone‑position‑independent indoor localization with meter‑level accuracy—1.5 m in‑hand and 2 m in‑pocket—validated in a 31 m × 15 m area.

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.