Robust Measurement Matrix Design Based on Compressed Sensing for DOA Estimation

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dc.contributor.authorHuang, Zhikai
dc.contributor.authorWang, Wei
dc.coverage.issue1cs
dc.coverage.volume28cs
dc.date.accessioned2020-04-23T06:56:46Z
dc.date.available2020-04-23T06:56:46Z
dc.date.issued2019-04cs
dc.description.abstractIt has been well known that Massive multiple-input-multiple-output (MIMO) radar can provide an excellent performance in direction of arrival (DOA) estimation. However, the significant increasing data size will seriously reduce the computational efficiency in practical application. Although compressed measurement can reduce data size and computational complexities, improper compression will enhance the environment noise. In this paper, a robust measurement matrix is designed to reduce data size and environment noise. Different from the general compressed sensing (CS) schemes, the optimization function is established by considering the overall mutual coherence of dictionary and the energy of measurement matrix, which is more suitable for noisy environment. The optimization function is highly non-convex due to the rank shrinkage of measurement matrix. To solve this problem, an alternating minimization scheme based on matrix factorization and Principal Component Analysis (PCA) is proposed. Moreover, the structure of measurement matrix is designed for massive MIMO receiver. Furthermore, numerous results demonstrate this scheme has a better estimation performance than random measurement method and general CS schemes in the noisy environment.en
dc.formattextcs
dc.format.extent276-282cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2019 vol. 28, č. 1, s. 276-282. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2019.0276en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/186855
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2019/19_01_0276_0282.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectcompressed sensingen
dc.subjectrobust measurement designen
dc.subjectDOA estimationen
dc.subjectsparse representationen
dc.subjectmassive MIMOen
dc.titleRobust Measurement Matrix Design Based on Compressed Sensing for DOA Estimationen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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