Application of Artificial Neural Networks for Efficient High-Resolution 2D DOA Estimation

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dc.contributor.authorAgatonovic, Marija
dc.contributor.authorStankovic, Zoran
dc.contributor.authorDoncov, Nebojsa
dc.contributor.authorSit, Leen
dc.contributor.authorMilovanovic, Bratislav
dc.contributor.authorZwick, Thomas
dc.coverage.issue4cs
dc.coverage.volume21cs
dc.date.accessioned2015-01-26T10:06:04Z
dc.date.available2015-01-26T10:06:04Z
dc.date.issued2012-12cs
dc.description.abstractA novel method to provide high-resolution Two-Dimensional Direction of Arrival (2D DOA) estimation employing Artificial Neural Networks (ANNs) is presented in this paper. The observed space is divided into azimuth and elevation sectors. Multilayer Perceptron (MLP) neural networks are employed to detect the presence of a source in a sector while Radial Basis Function (RBF) neural networks are utilized for DOA estimation. It is shown that a number of appropriately trained neural networks can be successfully used for the high-resolution DOA estimation of narrowband sources in both azimuth and elevation. The training time of each smaller network is significantly re¬duced as different training sets are used for networks in detection and estimation stage. By avoiding the spectral search, the proposed method is suitable for real-time ap¬plications as it provides DOA estimates in a matter of seconds. At the same time, it demonstrates the accuracy comparable to that of the super-resolution 2D MUSIC algorithm.en
dc.formattextcs
dc.format.extent1178-1186cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2012, vol. 21, č. 4, s. 1178-1186. ISSN 1210-2512cs
dc.identifier.issn1210-2512cs
dc.identifier.urihttp://hdl.handle.net/11012/37227
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2012/12_04_1178_1186.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectDOA estimationen
dc.subjectMLPen
dc.subjectRBFen
dc.subjectsectorisationen
dc.subjectURAen
dc.titleApplication of Artificial Neural Networks for Efficient High-Resolution 2D DOA Estimationen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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