Sparsity based off-grid blind sensor calibration

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buir.contributor.authorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.citation.epage92en_US
dc.citation.spage80en_US
dc.citation.volumeNumber84en_US
dc.contributor.authorÇamlıca, S.en_US
dc.contributor.authorYetik, I. S.en_US
dc.contributor.authorArıkan, Orhanen_US
dc.date.accessioned2020-01-28T11:13:36Z
dc.date.available2020-01-28T11:13:36Z
dc.date.issued2019en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractCompressive Sensing (CS) based techniques generally discretize the signal space and assume that the signal has a sparse support restricted on the discretized grid points. This restriction of representing the signal on a discretized grid results in the off-grid problem which causes performance degradation in the reconstruction of signals. Sensor calibration is another issue which can cause performance degradation if not properly addressed. Calibration aims to reduce the disruptive effects of the phase and the gain biases. In this paper, a CS based blind calibration technique is proposed for the reconstruction of multiple off-grid signals. The proposed technique is capable of estimating the off-grid signals and correcting the gain and the phase biases due to insufficient calibration simultaneously. It is applied to off-grid frequency estimation and direction finding applications using blind calibration. Extensive simulation analyses are performed for both applications. Results show that the proposed technique has superior reconstruction performance.en_US
dc.embargo.release2022-01-01
dc.identifier.doi10.1016/j.dsp.2018.10.005en_US
dc.identifier.issn1051-2004
dc.identifier.urihttp://hdl.handle.net/11693/52874
dc.language.isoEnglishen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttps://dx.doi.org/10.1016/j.dsp.2018.10.005en_US
dc.source.titleDigital Signal Processing: A Review Journalen_US
dc.subjectBlind calibrationen_US
dc.subjectSparseen_US
dc.subjectCompressive sensingen_US
dc.subjectOff-griden_US
dc.subjectDirection findingen_US
dc.subjectFrequency estimationen_US
dc.titleSparsity based off-grid blind sensor calibrationen_US
dc.typeArticleen_US

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