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dc.contributor.authorChen, H.
dc.contributor.authorWan, Q.
dc.contributor.authorFan, R.
dc.contributor.authorWen, F.
dc.date.accessioned2015-05-21T12:36:00Z
dc.date.available2015-05-21T12:36:00Z
dc.date.issued2015-04cs
dc.identifier.citationRadioengineering. 2015 vol. 24, č. 1, s. 208-213. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/38752
dc.description.abstractTraditional direction-of-arrival (DOA) estimation techniques perform Nyquist-rate sampling of the received signals and as a result they require high storage. To reduce sampling ratio, we introduce level-crossing (LC) sampling which captures samples whenever the signal crosses predetermined reference levels, and the LC-based analog-to-digital converter (LC ADC) has been shown to efficiently sample certain classes of signals. In this paper, we focus on the DOA estimation problem by using second-order statistics based on the LC samplings recording on one sensor, along with the synchronous samplings of the another sensors, a sparse angle space scenario can be found by solving an $ell_1$ minimization problem, giving the number of sources and their DOA's. The experimental results show that our proposed method, when compared with some existing norm-based constrained optimization compressive sensing (CS) algorithms, as well as subspace method, improves the DOA estimation performance, while using less samples when compared with Nyquist-rate sampling and reducing sensor activity especially for long time silence signal.en
dc.formattextcs
dc.format.extent208-213cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2015/15_01_0208_0213.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectDirection-of-arrival estimationen
dc.subjectlevel crossingen
dc.subjectcompressive sensingen
dc.subjectdantzing selectoren
dc.subjectconvex optimizationen
dc.titleDirection-of-Arrival Estimation Based on Sparse Recovery with Second-Order Statisticsen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue1cs
dc.coverage.volume24cs
dc.identifier.doi10.13164/re.2015.0208en
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 3.0 Unported License