Title: Detection of Gaussian signals via hexagonal sensor networks

Authors: Paolo Frasca, Paolo Mason, Benedetto Piccoli

Addresses: IAC-CNR Group c/o Dipartimento di Matematica, Universita di Roma 'Tor Vergata' via della Ricerca Scientifica, 1 00133 Rome, Italy. ' IAC-CNR Group c/o Dipartimento di Matematica, Universita di Roma 'Tor Vergata' via della Ricerca Scientifica, 1 00133 Rome, Italy. ' IAC-CNR Group c/o Dipartimento di Matematica, Universita di Roma 'Tor Vergata' via della Ricerca Scientifica, 1 00133 Rome, Italy

Abstract: This paper considers a special case of the problem of identifying a static scalar signal, depending on the location, using a planar network of sensors in a distributed fashion. Motivated by the application to monitoring wild fire spreading and pollutants dispersion, we assume the signal to be Gaussian in space. Using a network of sensors positioned to form a regular hexagonal tessellation, we prove that each node can estimate the parameters of the Gaussian from local measurements. Moreover, we study the sensitivity of these estimates to additive errors affecting the measurements. Finally, we show how a consensus algorithm can be designed to fuse the local estimates into a shared global estimate, effectively compensating the measurement errors.

Keywords: sensor networks; distributed computation; distributed decision making; consensus; hexagonal tessellation; fire detection; Gaussian signal; network optimisation; wild fires; pollutant dispersion; air pollution.

DOI: 10.1504/IJMMNO.2009.030086

International Journal of Mathematical Modelling and Numerical Optimisation, 2009 Vol.1 No.1/2, pp.39 - 55

Published online: 09 Dec 2009 *

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