DSpace@nitr >
National Institue of Technology- Rourkela >
Conference Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1365

Full metadata record

DC FieldValueLanguage
contributor.authorPanigrahi, T-
contributor.authorPanda, G-
contributor.authorMulgrew, B-
contributor.authorMajhi, B-
date.accessioned2011-02-01T15:25:41Z-
date.available2011-02-01T15:25:41Z-
date.issued2011-01-
identifier.citationInternational Conference on Electronics Systems (ICES-2011), 7-9th Jan 2011, National Institute of Technology, Rourkelaen
identifier.urihttp://hdl.handle.net/2080/1365-
descriptionCopyright belongs to proceeding publisheren
description.abstractWireless sensor networks have been proposed as a solution to environment sensing, target tracking, data collection and other applications. Source localization is one of the important problem in wireless sensor network. In literature a decentralized approach using strong antena arrays at each node or sensor arrays at different positions are used to localize the sources. In this paper a purely co-operative method where every node will participate in estimation. The network does the bearing estimation by optimizing maximum likelihood function by forming random array among all the nodes. Particle swarm optimization is used to optimize ML function because it is more efficient compared to other evolutionary algorithm like GA. Finally the results are compared with most analyzed MUSIC algorithm.en
format.extent432122 bytes-
format.mimetypeapplication/pdf-
language.isoen-
subjectWireless sensor networken
subjectMaximum Likelihood estimationen
subjectMUSICen
subjectParticle swarm optimizationen
titleMaximum Lilkelihood Source Localization in Wireless Sensor Network Using Particle Swarm Optimizationen
typeArticleen
Appears in Collections:Conference Papers

Files in This Item:

File Description SizeFormat
ICES2011.pdf421KbAdobe PDFView/Open

Show simple item record

All items in DSpace are protected by copyright, with all rights reserved.

 

Powered by DSpace Feedback