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Measurements and discrimination of drones and birds with a multi‐frequency multistatic radar system

Palamà, R; Fioranelli, F; Ritchie, M; Inggs, M; Lewis, S; Griffiths, H; (2021) Measurements and discrimination of drones and birds with a multi‐frequency multistatic radar system. IET Radar, Sonar & Navigation 10.1049/rsn2.12060. (In press). Green open access

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Abstract

This article presents the results of a series of measurements of multistatic radar signatures of small UAVs at L‐ and X‐bands. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter‐receiver and two bistatic receivers. NeXtRAD is capable of recording simultaneous bistatic and monostatic data with baselines and two‐way bistatic range of the order of a few kilometres. The paper presents an empirical analysis with range‐time plots and micro‐Doppler signatures of UAVs and birds of opportunity recorded at several hundred metres of distance. A quantitative analysis of the overall signal‐to‐noise ratio is presented along with a comparison between the power of the signal scattered from the drone body and blades. A simple study with empirically obtained features and four supervised‐learning classifiers for binary drone versus non‐drone separation is also presented. The results are encouraging with classification accuracy consistently above 90% using very simple features and classification algorithms.

Type: Article
Title: Measurements and discrimination of drones and birds with a multi‐frequency multistatic radar system
Open access status: An open access version is available from UCL Discovery
DOI: 10.1049/rsn2.12060
Publisher version: https://doi.org/10.1049/rsn2.12060
Language: English
Additional information: © 2021 The Authors. IET Radar, Sonar & Navigation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10126362
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