Chebychev moments based drone classification, recognition and fingerprinting
Clemente, Carmine and Pallotta, Luca and Ilioudis, Christos and Fioranelli, Francesco and Giunta, Gaetano and Farina, Alfonso (2021) Chebychev moments based drone classification, recognition and fingerprinting. In: International Radar Symposium, 2021-06-21 - 2022-06-22, Online.
Preview |
Text.
Filename: Clemente_etal_IRS_2021_Chebychev_moments_based_drone_classification_recognition_and_fingerprinting.pdf
Accepted Author Manuscript Download (111kB)| Preview |
Abstract
This paper introduces the use of a Chebychev moments' based feature for micro-Doppler based Classification, Recognition and Fingerprinting of Drones. This specific feature has been selected for its low computational cost and orthogonality property. The capability of the proposed feature extraction framework is assessed at three different levels of major classification steps, namely classification, recognition and fingerprinting, demonstrating the effectiveness of the proposed approach to discriminate drones from birds, fixed wings from multi-rotors and drones carrying different payloads on real measured radar data.
ORCID iDs
Clemente, Carmine ORCID: https://orcid.org/0000-0002-6665-693X, Pallotta, Luca, Ilioudis, Christos ORCID: https://orcid.org/0000-0002-7164-6461, Fioranelli, Francesco, Giunta, Gaetano and Farina, Alfonso;-
-
Item type: Conference or Workshop Item(Paper) ID code: 77935 Dates: DateEvent22 June 2021Published26 February 2021AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering
Strategic Research Themes > Measurement Science and Enabling Technologies
Strategic Research Themes > Ocean, Air and SpaceDepositing user: Pure Administrator Date deposited: 29 Sep 2021 15:41 Last modified: 11 Nov 2024 17:04 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/77935