dc.contributor.author | Cao, Pan | |
dc.date.accessioned | 2022-03-30T16:30:01Z | |
dc.date.available | 2022-03-30T16:30:01Z | |
dc.date.issued | 2022-03-09 | |
dc.identifier.citation | Cao , P 2022 , ' Cellular Base Station Imaging for UAV Detection ' , IEEE Access , vol. 10 , pp. 24843-24851 . https://doi.org/10.1109/ACCESS.2022.3152534 | |
dc.identifier.issn | 2169-3536 | |
dc.identifier.uri | http://hdl.handle.net/2299/25450 | |
dc.description | © 2022 IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ | |
dc.description.abstract | As the use of unmanned aerial vehicles (UAVs) is greatly increasing, there is an emerging threat of using UAVs in infrastructure/cyber-attacks and data-eavesdropping. From the safety and security perspective, it is a timely need to build an air surveillance system that enables a seamless detection function for low-and-middle altitude flying targets. However, it is unrealistic to widely deploy classical radar stations due to the astronomical cost. Rethinking the role of cellular mobile communication networks, we desire to add a 'vision-like' capability to the widely deployed outdoor cellular base stations (BSs) to realize joint imaging and communication (JIAC) simultaneously through sharing the existing cellular communication infrastructure and spectrum. In this work, it is for the first time to systematically study and demonstrate the concept of cellular base station imaging for UAV detection, which allows a cellular BS to work like an inverse synthetic-aperture radar (ISAR) besides communication. Firstly, we provide the JIAC transmission signalling and systematic operation mechanism. Secondly, the feasibility of JIAC is investigated and analysed to support the idea of cellular base station imaging. Finally, numerical simulation evaluates the imaging performance of three typical types of cellular BSs operating at 900 MHz, 3.5 GHz and 28 GHz, respectively, which implies that cellular BS imaging works for UAV detection! Furthermore, the radar imaging function, as a new by-product, requires only a very little change to the current orthogonal frequency-division multiplexing (OFDM) communication signalling and has nearly no influence on the current communication operation and performance. | en |
dc.format.extent | 9 | |
dc.format.extent | 1297261 | |
dc.language.iso | eng | |
dc.relation.ispartof | IEEE Access | |
dc.subject | Cellular mobile communication | |
dc.subject | high resolution radar imaging | |
dc.subject | joint imaging and communication (JIAC) | |
dc.subject | unmanned aerial vehicles (UAVs) detection | |
dc.subject | General Computer Science | |
dc.subject | General Materials Science | |
dc.subject | General Engineering | |
dc.title | Cellular Base Station Imaging for UAV Detection | en |
dc.contributor.institution | Centre for Engineering Research | |
dc.contributor.institution | Communications and Intelligent Systems | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Department of Engineering and Technology | |
dc.description.status | Peer reviewed | |
dc.identifier.url | http://www.scopus.com/inward/record.url?scp=85125341474&partnerID=8YFLogxK | |
rioxxterms.versionofrecord | 10.1109/ACCESS.2022.3152534 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |