Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra

Yefeng Cai; Oleg Krasnov; Alexander Yarovoy

Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra

Yefeng Cai, Oleg Krasnov, Alexander Yarovoy

Microwave Sensing, Signals & Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

8 Citations (Scopus)

223 Downloads (Pure)

Abstract

This paper proposes to perform radar recognition of multi-propeller drones using micro-Doppler linear spectral pattern in long Doppler coherent processing interval (CPI) circumstances. It focuses on the investigation of the influence of geometry design and motion variables, such as blade number, blade shape, drone’s design geometry and propeller synchronisation, on the micro-Doppler spectral pattern. We propose suitable scalar features for the characterisation of these patterns measured within a long (relatively to propellers rotation period) CPI. A thin-wire model was used to simulate drones micro-Doppler spectra for various input variables. Proposed features are extracted from the simulated micro-Doppler spectra for further processing in a support vector machine (SVM), with the purpose of demonstrating the radar recognition of multi-propeller drones based on these features.

Original language	English
Title of host publication	EuRAD 2019 - 2019 16th European Radar Conference
Publisher	EuMA
Pages	185 – 188
Number of pages	4
ISBN (Electronic)	9782874870576
ISBN (Print)	978-2-87487-057-6
Publication status	Published - 4 Oct 2019
Event	16th European Radar Conference: in the framework of the European Microwave Week 2019 - Paris, France Duration: 1 Oct 2019 → 4 Oct 2019 https://www.eumweek.com/conferences/eurad.html

Publication series

Name	EuRAD 2019 - 2019 16th European Radar Conference

Conference

Conference	16th European Radar Conference
Abbreviated title	EuRAD 2019
Country/Territory	France
City	Paris
Period	1/10/19 → 4/10/19
Internet address	https://www.eumweek.com/conferences/eurad.html

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

CPI
Drone
Feature
Micro-Doppler
Radar

Access to Document

08904765Final published version, 2.96 MB

Cite this

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title = "Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra",

abstract = "This paper proposes to perform radar recognition of multi-propeller drones using micro-Doppler linear spectral pattern in long Doppler coherent processing interval (CPI) circumstances. It focuses on the investigation of the influence of geometry design and motion variables, such as blade number, blade shape, drone{\textquoteright}s design geometry and propeller synchronisation, on the micro-Doppler spectral pattern. We propose suitable scalar features for the characterisation of these patterns measured within a long (relatively to propellers rotation period) CPI. A thin-wire model was used to simulate drones micro-Doppler spectra for various input variables. Proposed features are extracted from the simulated micro-Doppler spectra for further processing in a support vector machine (SVM), with the purpose of demonstrating the radar recognition of multi-propeller drones based on these features.",

keywords = "CPI, Drone, Feature, Micro-Doppler, Radar",

author = "Yefeng Cai and Oleg Krasnov and Alexander Yarovoy",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 16th European Radar Conference : in the framework of the European Microwave Week 2019, EuRAD 2019 ; Conference date: 01-10-2019 Through 04-10-2019",

year = "2019",

month = oct,

day = "4",

language = "English",

isbn = "978-2-87487-057-6 ",

series = "EuRAD 2019 - 2019 16th European Radar Conference",

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booktitle = "EuRAD 2019 - 2019 16th European Radar Conference",

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}

Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra. / Cai, Yefeng; Krasnov, Oleg ; Yarovoy, Alexander.
EuRAD 2019 - 2019 16th European Radar Conference. EuMA, 2019. p. 185 – 188 8904765 (EuRAD 2019 - 2019 16th European Radar Conference).

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra

AU - Cai, Yefeng

AU - Krasnov, Oleg

AU - Yarovoy, Alexander

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2019/10/4

Y1 - 2019/10/4

N2 - This paper proposes to perform radar recognition of multi-propeller drones using micro-Doppler linear spectral pattern in long Doppler coherent processing interval (CPI) circumstances. It focuses on the investigation of the influence of geometry design and motion variables, such as blade number, blade shape, drone’s design geometry and propeller synchronisation, on the micro-Doppler spectral pattern. We propose suitable scalar features for the characterisation of these patterns measured within a long (relatively to propellers rotation period) CPI. A thin-wire model was used to simulate drones micro-Doppler spectra for various input variables. Proposed features are extracted from the simulated micro-Doppler spectra for further processing in a support vector machine (SVM), with the purpose of demonstrating the radar recognition of multi-propeller drones based on these features.

AB - This paper proposes to perform radar recognition of multi-propeller drones using micro-Doppler linear spectral pattern in long Doppler coherent processing interval (CPI) circumstances. It focuses on the investigation of the influence of geometry design and motion variables, such as blade number, blade shape, drone’s design geometry and propeller synchronisation, on the micro-Doppler spectral pattern. We propose suitable scalar features for the characterisation of these patterns measured within a long (relatively to propellers rotation period) CPI. A thin-wire model was used to simulate drones micro-Doppler spectra for various input variables. Proposed features are extracted from the simulated micro-Doppler spectra for further processing in a support vector machine (SVM), with the purpose of demonstrating the radar recognition of multi-propeller drones based on these features.

KW - CPI

KW - Drone

KW - Feature

KW - Micro-Doppler

KW - Radar

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M3 - Conference contribution

SN - 978-2-87487-057-6

T3 - EuRAD 2019 - 2019 16th European Radar Conference

SP - 185

EP - 188

BT - EuRAD 2019 - 2019 16th European Radar Conference

PB - EuMA

T2 - 16th European Radar Conference

Y2 - 1 October 2019 through 4 October 2019

ER -

Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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