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

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.
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Conference papers
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https://hal-imt.archives-ouvertes.fr/hal-01144851
Contributor : François Septier <>
Submitted on : Wednesday, April 22, 2015 - 7:30:21 PM
Last modification on : Saturday, March 23, 2019 - 1:25:20 AM

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  • HAL Id : hal-01144851, version 1

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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. ⟨hal-01144851⟩

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