Improving the Simulations of Radar Signatures of Small Drone

Fioranelli, F. , Krasnov, O., Cai, Y., Yarovoy, A., Yun, J. and Anderson, D. (2021) Improving the Simulations of Radar Signatures of Small Drone. In: MSG-SET-183 Specialists' Meeting on Drone Detectability: Modelling the Relevant Signature, 27-29 Apr 2021, ISBN 9789283723578

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Publisher's URL: https://www.sto.nato.int/publications/STO%20Meeting%20Proceedings/STO-MP-MSG-SET-183/MP-MSG-SET-183-01.pdf

Abstract

Small drones have attracted significant research interest from law enforcement and defence agencies due to the challenge in detecting, tracking, and classifying them with radar, because of their small size and high manoeuvrability. As collecting experimental data for all possible drone models and scenarios is unfeasible, modelling work to simulate accurately the signatures of these platforms is an important task. This paper presents some preliminary results of research effort to enhance modelling capabilities of the radar signatures of individual small drones, and multiple drones flying together in the scene of interest.

Item Type:Conference Proceedings
Keywords:Radar, drone.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Yun, Dr Joongsup and Anderson, Dr David and Fioranelli, Dr Francesco
Authors: Fioranelli, F., Krasnov, O., Cai, Y., Yarovoy, A., Yun, J., and Anderson, D.
Subjects:Q Science > Q Science (General)
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
College of Science and Engineering > School of Engineering
ISBN:9789283723578

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
305811Radar Analysis and Prediction of Intentions/Behaviour of small droners' swarmsDavid AndersonUS Office of Naval Research (ONR) (USANAVRE)N62909-19-1-2073ENG - Systems Power & Energy