Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1437
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dc.contributor.authorHanumantharao, A D-
dc.contributor.authorPanigrahi, T-
dc.contributor.authorSahoo, U K-
dc.contributor.authorPanda, G-
dc.contributor.authorSuresh, B-
dc.date.accessioned2011-04-25T05:37:34Z-
dc.date.available2011-04-25T05:37:34Z-
dc.date.issued2011-03-
dc.identifier.citationInternational Conference on Emerging Technologies (ICET-2011) National Institute of Technology, Durgapur, March 28-31, 2011en
dc.identifier.urihttp://hdl.handle.net/2080/1437-
dc.descriptionCopyright belongs to proceeding publisheren
dc.description.abstractSource direction of arrival (DOA) estimation is one of the challenging problems in a variety of applications, such as communications, radar, sonar, and seismic exploration. Several methods based on maximum likelihood (ML) criteria has been established in literature. Generally, to obtain the exact ML (EML) solutions, the DOAs must be estimated by optimizing a complicated nonlinear multimodal function over a high-dimensional problem space. Bacteria foraging optimization (BFO) based solution is proposed here to compute the ML functions and explore the potential of superior performances over traditional PSO algorithm. Simulation results confirms that the BFO-EML estimator is significantly giving better performance at lower SNR compared to conventional method like MUSIC in various scenarios at less computational costs.en
dc.format.extent270883 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.subjectMUSICen
dc.subjectDirection-of-arrivalen
dc.subjectMaximum Likelihooden
dc.subjectPSOen
dc.subjectBFOen
dc.titleExact Maximum Likelihood Direction Of Arrival Estimation Using Bacteria Foraging Optimizationen
dc.typeArticleen
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