Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/7222
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Gürbüz, Sevgi Zübeyde | - |
dc.contributor.author | Erol, Barış | - |
dc.contributor.author | Çağlıyan, Bahri | - |
dc.contributor.author | Tekeli, Bürkan | - |
dc.date.accessioned | 2021-09-11T15:56:01Z | - |
dc.date.available | 2021-09-11T15:56:01Z | - |
dc.date.issued | 2015 | en_US |
dc.identifier.issn | 1751-8784 | - |
dc.identifier.issn | 1751-8792 | - |
dc.identifier.uri | https://doi.org/10.1049/iet-rsn.2015.0144 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/7222 | - |
dc.description.abstract | A key challenge for radar surveillance systems is the discrimination of ground-based targets, especially humans from animals, as well as different types of human activities. For this purpose, target micro-Doppler signatures have been shown to yield high automatic target classification rates; however, performance is typically only given for near-optimal operating conditions using a fixed set of features. Over the past few decades dozens of micro-Doppler features have been proposed, when in fact utilisation of all possible features does not guarantee the maximum classification performance and the selection of an optimal subset of features is scenario dependent. In this work, a comprehensive survey of micro-Doppler features and their dependence upon system parameters and operational conditions - such as transmit frequency, range and Doppler resolution, antenna-target geometry, signal-to-noise ratio, and dwell time - is given. Algorithms for optimising classification performance for a reduced number of features are presented. Performance gains achievable using adaptive feature selection are assessed for a case study of interest. | en_US |
dc.description.sponsorship | EU FP7 ProjectEuropean Commission [PIRG-GA-2010-268276]; TUBITAK ProjectTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [113E105] | en_US |
dc.description.sponsorship | This work was funded in part by the EU FP7 Project No. PIRG-GA-2010-268276 and TUBITAK Project No. 113E105. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Inst Engineering Technology-Iet | en_US |
dc.relation.ispartof | Iet Radar Sonar And Navigation | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | search radar | en_US |
dc.subject | feature selection | en_US |
dc.subject | Doppler radar | en_US |
dc.subject | radar signal processing | en_US |
dc.subject | signal classification | en_US |
dc.subject | object detection | en_US |
dc.subject | radar surveillance system | en_US |
dc.subject | ground-based target discrimination | en_US |
dc.subject | automatic target classification | en_US |
dc.subject | microDoppler feature adaptive selection | en_US |
dc.subject | transmit frequency | en_US |
dc.subject | range resolution | en_US |
dc.subject | Doppler resolution | en_US |
dc.subject | antenna-target geometry | en_US |
dc.subject | signal-to-noise ratio | en_US |
dc.subject | dwell time | en_US |
dc.title | Operational Assessment and Adaptive Selection of Micro-Doppler Features | en_US |
dc.type | Article | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Electrical and Electronics Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü | tr_TR |
dc.identifier.volume | 9 | en_US |
dc.identifier.issue | 9 | en_US |
dc.identifier.startpage | 1196 | en_US |
dc.identifier.endpage | 1204 | en_US |
dc.authorid | 0000-0002-6977-8801 | - |
dc.identifier.wos | WOS:000365855500009 | en_US |
dc.identifier.scopus | 2-s2.0-84949883105 | en_US |
dc.institutionauthor | Gürbüz, Sevgi Zübeyde | - |
dc.identifier.doi | 10.1049/iet-rsn.2015.0144 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | Q1 | - |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
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 |
CORE Recommender
SCOPUSTM
Citations
52
checked on Dec 21, 2024
WEB OF SCIENCETM
Citations
59
checked on Dec 21, 2024
Page view(s)
44
checked on Dec 23, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.