Direction of Arrival Estimation by Using Artificial Neural Networks

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dc.contributor.authorUnlersen, Muhammes Fahri
dc.contributor.authorYaldiz, Ercan
dc.date.accessioned2024-02-23T14:23:51Z
dc.date.available2024-02-23T14:23:51Z
dc.date.issued2016
dc.departmentNEÜen_US
dc.description10th UKSim-AMSS European Modelling Symposium on Computer Modelling and Simulation (EMS) -- NOV 28-30, 2016 -- Pisa, ITALYen_US
dc.description.abstractIn the literature there are many algorithms for direction of arrival estimation like MUSIC, ESPRIT, First order forward prediction, Capon etc. These algorithms have heavy calculation operations. This situation could cause lags in response time of the algorithm, and may pose an important disadvantage in real time applications. To overcome this problem, artificial neural network (ANN) could he used. The training stage of an ANN needs significant time and sources but after training, the estimation by using ANN is very fast. In this study, an ANN approach has been proposed for direction of arrival estimation in uniform linear array antenna. In training, the whole pseudo spectrum is scanned by 10 degree steps. In the simulation process, it is accepted that a uniform linear array consists of 5 isotropic antenna elements and there are 1 to 4 arrival signals. Tests of the trained ANN have been done for various directions of arrival angles, and satisfactory results have been obtained.en_US
dc.description.sponsorshipNottingham Trent Univ,IEEE UK & RI Sect,UK Simulat Soc,Asia Modelling & Simulat Sect,IEEE Reg 8,Scuola Super Sant Anna,European Simulat Federat,European Council Modelling & Simulat,Manchester Metropolitan Univ,Univ Politecnica Madrid,Kingston Univ,Liverpool Univ,Univ Technol Malaysia,Univ Malaysia Pahang,Univ Malaysia Sabah,IEEE Comp Socen_US
dc.description.sponsorshipNecmettin Erbakan University [162518001-734]en_US
dc.description.sponsorshipThis study has been supported by Scientific Research Project of Necmettin Erbakan University with the project. number 162518001-734.en_US
dc.identifier.doi10.1109/EMS.2016.51
dc.identifier.endpage245en_US
dc.identifier.isbn978-1-5090-4971-4
dc.identifier.issn2473-3539
dc.identifier.startpage242en_US
dc.identifier.urihttps://doi.org/10.1109/EMS.2016.51
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13725
dc.identifier.wosWOS:000406227200038en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofUksim-Amss 10th European Modelling Symposium On Computer Modelling And Simulation (Ems)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDirection Of Arrivalen_US
dc.subjectUniform Linear Arrayen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectReal Time Applicationen_US
dc.titleDirection of Arrival Estimation by Using Artificial Neural Networksen_US
dc.typeConference Objecten_US

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