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dc.contributor.authorWei, Z.
dc.contributor.authorLi, X.
dc.contributor.authorWang, B.
dc.contributor.authorWang, W.
dc.contributor.authorLiu, Q.
dc.date.accessioned2020-04-30T12:16:42Z
dc.date.available2020-04-30T12:16:42Z
dc.date.issued2019-12cs
dc.identifier.citationRadioengineering. 2019 vol. 28, č. 4, s. 785-792. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/186924
dc.description.abstractDirection-of-arrival (DOA) estimation based on sparse signal reconstruction (SSR) is always vulnerable to off-grid error. To address this issue, an efficient super-resolution DOA estimation algorithm is proposed in this work. Utilizing the Taylor series expansion, the sparse dictionary matrix is constructed under the off-grid model. Then, a polynomial optimization function is established based on the orthogonality principle. By minimizing the given objective function, we derive an efficient closed-form solution of the off-grid errors. Using the estimated off-grid errors, the discretized grid can be iteratively learned and approaches the true DOAs. With the newly learned grid, accurate DOA estimations can be achieved through the SSR scheme. The proposed algorithm converges fast and achieves precise DOA estimations even the step size of the discretized grid is large. The superior performance of the proposed algorithm is demonstrated by the simulation results.en
dc.formattextcs
dc.format.extent785-792cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2019/19_04_0785_0792.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectDirection of arrival (DOA) estimationen
dc.subjectgrid learningen
dc.subjectsparse signal reconstruction (SSR)en
dc.subjectoff-grid modelen
dc.titleAn Efficient Super-Resolution DOA Estimator Based on Grid Learningen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue4cs
dc.coverage.volume28cs
dc.identifier.doi10.13164/re.2019.0785en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International license