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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2016

24.06.2016

3D Localization and Frequency Band Estimation of Multiple Unknown RF Sources Using Particle Filters and a Wireless Sensor Network

verfasst von: Konstantinos A. Gotsis, Ioannis Kyriakides, John N. Sahalos

Erschienen in: Wireless Personal Communications | Ausgabe 4/2016

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Abstract

This paper presents a methodology for the 3D localization and the frequency band estimation of multiple unknown RF sources, using received signal strength (RSS) measurements from a wireless network of static sensors and a moving sensor. Using a particle filter based Bayesian approach, the static sensor network is used to continuously monitor an urban area and provide an estimate of the probability distribution for the states of the unknown sources. Based on this probability distribution, a moving sensor is guided towards locations where it is more likely to find an unknown source. The RSS measurements in the vicinity of the unknown source are used to provide the final estimation and confirmation of the source state. The method is analytically developed and evaluated in terms of accuracy in estimating the number, the 3D location and the frequency band of the unknown sources under different Monte Carlo simulation scenarios.
Vorheriger Artikel A Residual Energy Aware Schedule Scheme for WSNs Employing Adjustable Awake/Sleep Duty Cycle
Nächster Artikel NADS: Neighbor Assisted Deployment Scheme for Optimal Placement of Sensor Nodes to Achieve Blanket Coverage in Wireless Sensor Network

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Metadaten
Titel
3D Localization and Frequency Band Estimation of Multiple Unknown RF Sources Using Particle Filters and a Wireless Sensor Network
verfasst von
Konstantinos A. Gotsis
Ioannis Kyriakides
John N. Sahalos
Publikationsdatum
24.06.2016
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2016
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-016-3429-z

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