Wind Storm Estimation using a Heterogeneous Sensor Network with High and Low Resolution Sensors

Ido Nevat 1 Gareth W. Peters 2 François Septier 3, 4, 5 Tomoko Matsui 6
1 Institute for Infocomm Research - I²R [Singapore]
2 Department of Statistical Science, University College of London
3 Institut TELECOM/TELECOM Lille1
4 LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
5 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
6 ISM - Department of Statistical Modeling, Institute of Statistical Mathematics
Abstract : We develop a new algorithm for spatial field reconstruction in heterogeneous (mixed analog & digital sen- sors) wireless sensor networks (WSNs). We consider spatial physical phenomena which are observed by a heterogeneous WSN, meaning that it is partially consists of sparsely deployed high-quality sensors and partially of low-quality sensors. The high-quality sensors transmit their (continuous) noisy observations to the Fusion Centre (FC), while the low- quality sensors first perform a simple thresholding operation and then transmit their binary values over imperfect wireless channels to the FC. We develop a novel algorithm that is based on a multivariate series expansion approach resulting in a Saddle-point type approximation. We then present comprehensive study of the performance gain that can be obtained by augmenting the high-quality sensors with low- quality sensors using real data of insurance storm surge database known as the Extreme Wind Storms Catalogue.
Keywords : Kernel methods imperfect communication channels. Gaussian processes Wireless sensor networks Detection
Type de document :
Communication dans un congrès
IEEE International Conference on Communications (ICC), Jun 2015, London, United Kingdom. 2015
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https://hal-imt.archives-ouvertes.fr/hal-01144851
Contributeur : François Septier <>
Soumis le : mercredi 22 avril 2015 - 19:30:21
Dernière modification le : mardi 3 juillet 2018 - 11:49:16

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  • HAL Id : hal-01144851, version 1

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LAGIS | INRIA | CRISTAL-SIGMA | IMT-LILLE-DOUAI | CRISTAL

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Ido Nevat, Gareth W. Peters, François Septier, Tomoko Matsui. Wind Storm Estimation using a Heterogeneous Sensor Network with High and Low Resolution Sensors. IEEE International Conference on Communications (ICC), Jun 2015, London, United Kingdom. 2015. 〈hal-01144851〉

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