Titre :

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

Auteur(s) :

Nevat, Ido [Auteur]
Institute for Infocomm Research - I²R [Singapore]
Peters, Gareth W. [Auteur]
Avnit, Karin [Auteur]
Singapore Institute of Technology [Singapore] [SIT]
Septier, Francois [Auteur]
Institut TELECOM/TELECOM Lille1
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Clavier, Laurent [Auteur]
Institut TELECOM/TELECOM Lille1
Circuits Systèmes Applications des Micro-ondes - IEMN [CSAM - IEMN]

Titre de la revue :

IEEE Transactions on Signal and Information Processing over Networks

Pagination :

174-185

Éditeur :

IEEE

Date de publication :

2016-06

ISSN :

2373-776X

Discipline(s) HAL :

Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Statistiques [stat]/Applications [stat.AP]

Résumé en anglais : [en]

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 ...
Lire la suite >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.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Projet ANR :

PlateformE viRtuelle 3D pour la Simulation des rEseaux de caPTEURs

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL