Analyzing Radar Cross Section Signatures of Diverse Drone Models at mmWave Frequencies

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorSemkin, Vasiliien_US
dc.contributor.authorHaarla, Jaakkoen_US
dc.contributor.authorPairon, Thomasen_US
dc.contributor.authorSlezak, Christopheren_US
dc.contributor.authorRangan, Sundeepen_US
dc.contributor.authorViikari, Villeen_US
dc.contributor.authorOestges, Claudeen_US
dc.contributor.departmentDepartment of Electronics and Nanoengineeringen
dc.contributor.groupauthorVille Viikari Groupen
dc.contributor.organizationUniversité Catholique de Louvainen_US
dc.contributor.organizationNew York Universityen_US
dc.date.accessioned2020-04-28T07:16:53Z
dc.date.available2020-04-28T07:16:53Z
dc.date.issued2020-01-01en_US
dc.description.abstractIn this work, we present quasi-monostatic Radar Cross Section measurements of different Unmanned Aerial Vehicles at 26-40 GHz. We study the Radar Cross Section signatures of nine different multi-rotor platforms as well as a single Lithium-ion Polymer battery. These results are useful in the design and testing of radar systems which employ millimeter-wave frequencies for superior drone detection. The data shows how radio waves are scattered by drones of various sizes and what impact the primary construction material has on the received Radar Cross Section signatures. Matching our intuition, the measurements confirm that larger drones made of carbon fiber are easier to detect, whereas drones made from plastic and styrofoam materials are less visible to the radar systems. The measurement results are published as an open database, creating an invaluable reference for engineers working on drone detection.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.extent48958-48969
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationSemkin, V, Haarla, J, Pairon, T, Slezak, C, Rangan, S, Viikari, V & Oestges, C 2020, ' Analyzing Radar Cross Section Signatures of Diverse Drone Models at mmWave Frequencies ', IEEE Access, vol. 8, 9032332, pp. 48958-48969 . https://doi.org/10.1109/ACCESS.2020.2979339en
dc.identifier.doi10.1109/ACCESS.2020.2979339en_US
dc.identifier.issn2169-3536
dc.identifier.otherPURE UUID: ff2c5116-2fff-4fcd-910f-e4d5998e9051en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/ff2c5116-2fff-4fcd-910f-e4d5998e9051en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85082391723&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/42188619/Semkin_Analyzing_Radar_IEEEAccess.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/43957
dc.identifier.urnURN:NBN:fi:aalto-202004282939
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartofseriesIEEE Accessen
dc.relation.ispartofseriesVolume 8en
dc.rightsopenAccessen
dc.subject.keywordDrone detectionen_US
dc.subject.keywordmillimeter-waveen_US
dc.subject.keywordradar cross sectionen_US
dc.subject.keywordunmanned aerial vehicleen_US
dc.titleAnalyzing Radar Cross Section Signatures of Diverse Drone Models at mmWave Frequenciesen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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