Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2709
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dc.contributor.authorKumbul, Utku-
dc.contributor.authorHayvacı, Harun Taha-
dc.date.accessioned2019-12-25T14:03:32Z-
dc.date.available2019-12-25T14:03:32Z-
dc.date.issued2019
dc.identifier.citationKumbul, U., and Hayvaci, H. T. (2019). Multipath exploitation for knowledge-aided adaptive target detection. IET Radar, Sonar and Navigation, 13(6), 863-870.en_US
dc.identifier.issn17518784
dc.identifier.urihttps://hdl.handle.net/20.500.11851/2709-
dc.identifier.urihttps://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2018.5221-
dc.description.abstractThe authors consider the problem of multipath exploitation on adaptive radar detection of point-like targets in a multipath environment where a priori information is available. A new approach to exploit multipath returns with knowledge-aided adaptive target-detection regime is proposed. The authors model the received signal as the sum of direct-path and reflected-path return under the assumption of a zero-mean complex circular Gaussian noise with an unknown covariance matrix. The advantage of the proposed method is exploiting multipath returns with a priori knowledge of the reflecting environment, so that it has the knowledge of the reflected steering vector for a known actual direct-path steering vector. A Generalised Likelihood Ratio Test (GLRT) for the corresponding hypothesis testing problem is derived. It is shown that the devised detector also secures the Constant False Alarm Rate (CFAR) property regarding the unknown parameters of the noise. Performance comparison of the proposed detector with the existing well-known adaptive detectors is provided. It is presented that better-detection performance can be achieved by exploiting multipath with knowledge-aided adaptive radar. It is also observed that the devised detector has a small performance degradation in case of weak multipath return. © The Institution of Engineering and Technology 2019en_US
dc.language.isoenen_US
dc.publisherInstitution of Engineering and Technologyen_US
dc.relation.ispartofIET Radar, Sonar and Navigationen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClutter (information theory) en_US
dc.subject radar clutter en_US
dc.subject clutter covarianceen_US
dc.titleMultipath Exploitation for Knowledge-Aided Adaptive Target Detectionen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.volume13
dc.identifier.issue6
dc.identifier.startpage863
dc.identifier.endpage870
dc.authorid0000-0002-6717-5484-
dc.identifier.wosWOS:000498816400001en_US
dc.identifier.scopus2-s2.0-85066938354en_US
dc.institutionauthorHayvacı, Harun Taha-
dc.identifier.doi 10.1049/iet-rsn.2018.5221-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.5. Department of Electrical and Electronics Engineering-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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