Grouping Parallel Detection Method of UAV Based on Multi Features of Image Transmission Signal

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dc.contributor.authorXie, Yuelei
dc.contributor.authorJiang, Ping
dc.contributor.authorXiao, Xiao
dc.coverage.issue3cs
dc.coverage.volume30cs
dc.date.accessioned2021-11-08T10:24:40Z
dc.date.available2021-11-08T10:24:40Z
dc.date.issued2021-09cs
dc.description.abstractThe emergence of low, slow, and small civilian unmanned aerial vehicles (UAV) brings fun and convenience to life and work. However, with the widespread popularity of UAV, the illegal activities caused by them have gradually increased, causing great harm to social security. To solve this problem, in the paper, we propose a set of detection and recognition methods for UAV by UAV image transmission signal (ITS). The method is divided into two groups. In the first group, according to the signal characteristics in different transform domains such as spectrum and time-frequency spectrum, three sets of algorithms are proposed, which are time-frequency ridge double feature estimation (TFRDFE), segmented spectrum estimation (SSE) and cycle accumulation estimation of segmented spectrum (CAE-SS). Three sets of algorithms are estimated to perform blind detection on suspected UAV ITS. The second group uses the accurate recognition algorithm of UAV ITS to extract the periodic features in the signal, and completes the recognition of UAV through feature matching, decision criteria and other methods. The two groups of methods are implemented in parallel, and when the two groups both detect and recognize the flying target, it can be determined that there is UAV in the target airspace. The experimental results show that the recognition rate of the first group of suspected UAV ITS blind detection algorithm can reach 100% when the (signal-to-noise ratio) SNR is –22 dB. The second group of UAV ITS recognition algorithm can achieve 100% recognition rate when SNR is –4 dB. Therefore, this method can complete the multi-target recognition of UAVs and has practical application value.en
dc.formattextcs
dc.format.extent556-568cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 2021 vol. 30, č. 3, s. 556-568. ISSN 1210-2512cs
dc.identifier.doi10.13164/re.2021.0556en
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/201828
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttps://www.radioeng.cz/fulltexts/2021/21_03_0556_0568.pdfcs
dc.rightsCreative Commons Attribution 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectUnmanned aerial vehicle (UAV)en
dc.subjectimage transmission signalen
dc.subjecttime-frequency ridge double feature estimationen
dc.subjectsegmented spectrum estimationen
dc.subjectcycle accumulation estimation of segmented spectrumen
dc.subjectsignal characteristicsen
dc.titleGrouping Parallel Detection Method of UAV Based on Multi Features of Image Transmission Signalen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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