Location of Things: Geospatial Tagging for IoT Using Time-of-Arrival

Ido Nevat 1 Gareth W. Peters 2 Karin Avnit 3 François Septier 4, 5 Laurent Clavier 6, 5
1 Institute for Infocomm Research - I²R [Singapore]
2 Department of Statistical Science
3 SIT - Singapore Institute of Technology [Singapore]
4 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
5 Institut TELECOM/TELECOM Lille1
6 CSAM
IEMN - Institut d’Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520, Institut TELECOM/TELECOM Lille1, IRCICA - Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancé
Abstract : We develop a new algorithm for geospatial tagging for Internet-of-Things (IoT) type applications, which we denote as location-of-things (LoT). The underlying idea of LoT applications is to use low-cost off-the-shelf two-way time-of-arrival (TW-ToA) ranging devices to perform localization of tags. We first demonstrate how conventional TW-ToA localization algorithms may experience performance degradation in cases where some of the access points (APs) are outside the communication range of the tags. We then show that we can make use of the audibility information (which indicates whether an AP is able or unable to communicate with the tags). By leveraging on this available information, we re-formulate the localization problem as a statistical nonlinear estimation problem. This information, coupled with ranging observations from audible AP leads to a new maximum likelihood estimation (MLE) algorithm for the tag's location. Our approach provides considerable improvement of the localization performance by mitigating the well-known ambiguity problem which arises when only a few AP are audible. In addition, we derive the Cramér-Rao bound (CRB) of the source location estimate under the proposed framework.
Type de document :
Article dans une revue
IEEE transactions on Signal and Information Processing over Networks, IEEE, 2016, 2 (2), pp.174-185. 〈10.1109/TSIPN.2016.2531422〉
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https://hal-imt.archives-ouvertes.fr/hal-01359099
Contributeur : François Septier <>
Soumis le : jeudi 1 septembre 2016 - 17:58:21
Dernière modification le : vendredi 13 avril 2018 - 01:23:14

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INRIA | CRISTAL-SIGMA | IMT-LILLE-DOUAI

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Ido Nevat, Gareth W. Peters, Karin Avnit, François Septier, Laurent Clavier. Location of Things: Geospatial Tagging for IoT Using Time-of-Arrival. IEEE transactions on Signal and Information Processing over Networks, IEEE, 2016, 2 (2), pp.174-185. 〈10.1109/TSIPN.2016.2531422〉. 〈hal-01359099〉

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