Enhancing Fingerprint-based Smartphone Localization Using Acoustic Time-of-Flight for Complex Indoors

Yukiya Mita, Hiroaki Murakami, Takuya Sasatani, Matthew Ishige, and Yoshihiro Kawahara

Abstract

Robust indoor positioning systems provide stable location-aware applications, enhancing our daily experiences. Fingerprint-based positioning techniques enable estimation of a user's position in complex indoor environments. While previous studies have used the received signal strength indicator or power spectral density as fingerprints, they typically achieved only submeter accuracy. This paper presents Geometric Sound Profile (GSP) as a novel location fingerprint to elevate the performance ceiling of fingerprint-based positioning. GSP is derived from the cross-correlation of transmitted and received signals based on transmission time, and a user's position is computed using weighted k-nearest neighbors. Our experiments demonstrate a median error of 0.66 m, marking a significant advancement over previous fingerprinting techniques.

Proceedings of the 21st ACM Conference on Embedded Networked Sensor Systems (ACM SenSys)

Published: April 2024

Pages: 548 - 549

City: Istanbul, Turkiye