Title: High accurate localisation using multipath effects via physical layer information

Authors: Yajun Zhang; Yawei Chen; Hongjun Wang; Meng Liu; Liang Ma

Addresses: School of Information Science and Engineering, Shandong University, Jinan, China; Computer Engineering Department, Changji College, ChangJi, China ' College of Culture and Art, Shaanxi Institute of International Trade and Commerce, Xi'an, China ' School of Information Science and Engineering, Shandong University, Jinan, China ' School of Information Science and Engineering, Shandong University, Jinan, China ' School of Information Science and Engineering, Shandong University, Jinan, China

Abstract: Device-free passive localisation (DFL) has shown great potentials to localising target(s) without carrying any device in the area of interests (AoIs). It is especially useful for many applications, such as hostage rescuing, wildlife monitoring, elder care, intrusion detection, etc. Current received signal strength (RSS) based DFL approaches, however, can only identify underlying the prerequisite that the signal collected is mainly conveying along a direct line-of-sight (LOS) path, but cannot perform well in a typical indoor building with multipath effects. This paper explains the fine-grained CSI-based localisation system that is effective to locate within multipath environment and non-line-of-sight scenarios. The intuition underlying our design is that channel state information (CSI) benefits from the multipath effect, because the received signal measurements at different sampling positions will be the combination of different CSI measurements. We adapt the improved maximum likelihood method to pinpoint single target's location. Final, we propose a prototype of our design utilising commercial IEEE 802.11n NICs. Results from the experimental scenes of a lobby and a laboratory of our university, comparing to RSS-based and CSI-based scheme, demonstrate that our design can locate best single target with the accuracy of 0.95 m.

Keywords: device-free passive localisation; DFL; channel state information; CSI; maximum likelihood method.

DOI: 10.1504/IJICT.2019.102044

International Journal of Information and Communication Technology, 2019 Vol.15 No.1, pp.15 - 30

Received: 11 Nov 2017
Accepted: 13 Jan 2018

Published online: 03 Sep 2019 *

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