Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar

Daniel White; Mohammed Jahangir; Michail Antoniou; Christopher Baker; Jeyan Thiyagalingam; Stephen Harman; Cameron Bennett

doi:10.1109/RadarConf2248738.2022.9764352

Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar

Daniel White
, Mohammed Jahangir
, Michail Antoniou
, Christopher Baker
, Jeyan Thiyagalingam
, Stephen Harman
, Cameron Bennett

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, three simple models of a multi-rotor drone's timeseries radar returns were derived, and by populating the equation parameters with genuine drone motor speed recordings, a synthetic spectrogram was generated that accurately captures the characteristic uDoppler sidebands caused by the rapidly rotating propeller blades. Deficiencies in the model's amplitude modulation were identified and phenomenologically treated. The synthetic drone data was injected into a real radar background enabling a direct comparison of synthetic and real spectrograms of rotary-wing drones with an L-band staring radar.

Original language	English
Title of host publication	2022 IEEE Radar Conference (RadarConf22)
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9781728153681
ISBN (Print)	9781728153698 (PoD)
DOIs	https://doi.org/10.1109/RadarConf2248738.2022.9764352
Publication status	Published - 3 May 2022
Event	2022 IEEE Radar Conference, RadarConf 2022 - New York City, United States Duration: 21 Mar 2022 → 25 Mar 2022

Publication series

Name	Proceedings of the IEEE Radar Conference
Publisher	IEEE
ISSN (Print)	1097-5764
ISSN (Electronic)	2640-7736

Conference

Conference	2022 IEEE Radar Conference, RadarConf 2022
Country/Territory	United States
City	New York City
Period	21/03/22 → 25/03/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

Drone
HERM
Radar
Simulation

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing
Instrumentation

Access to Document

10.1109/RadarConf2248738.2022.9764352

3rd Place Student Paper Competition
White, D. (Recipient), 21 Mar 2022
Prize: Prize (including medals and awards)

Cite this

White, D., Jahangir, M., Antoniou, M., Baker, C., Thiyagalingam, J., Harman, S., & Bennett, C. (2022). Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar. In 2022 IEEE Radar Conference (RadarConf22) Article 9764352 (Proceedings of the IEEE Radar Conference). IEEE. https://doi.org/10.1109/RadarConf2248738.2022.9764352

@inproceedings{c69b75eeb945455baa80bc0ffd14deef,

title = "Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar",

abstract = "In this paper, three simple models of a multi-rotor drone's timeseries radar returns were derived, and by populating the equation parameters with genuine drone motor speed recordings, a synthetic spectrogram was generated that accurately captures the characteristic uDoppler sidebands caused by the rapidly rotating propeller blades. Deficiencies in the model's amplitude modulation were identified and phenomenologically treated. The synthetic drone data was injected into a real radar background enabling a direct comparison of synthetic and real spectrograms of rotary-wing drones with an L-band staring radar.",

keywords = "Drone, HERM, Radar, Simulation",

author = "Daniel White and Mohammed Jahangir and Michail Antoniou and Christopher Baker and Jeyan Thiyagalingam and Stephen Harman and Cameron Bennett",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Radar Conference, RadarConf 2022 ; Conference date: 21-03-2022 Through 25-03-2022",

year = "2022",

month = may,

day = "3",

doi = "10.1109/RadarConf2248738.2022.9764352",

language = "English",

isbn = "9781728153698 (PoD)",

series = "Proceedings of the IEEE Radar Conference",

publisher = "IEEE",

booktitle = "2022 IEEE Radar Conference (RadarConf22)",

}

White, D, Jahangir, M , Antoniou, M, Baker, C, Thiyagalingam, J, Harman, S & Bennett, C 2022, Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar. in 2022 IEEE Radar Conference (RadarConf22)., 9764352, Proceedings of the IEEE Radar Conference, IEEE, 2022 IEEE Radar Conference, RadarConf 2022, New York City, United States, 21/03/22. https://doi.org/10.1109/RadarConf2248738.2022.9764352

Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar. / White, Daniel; Jahangir, Mohammed ; Antoniou, Michail et al.
2022 IEEE Radar Conference (RadarConf22). IEEE, 2022. 9764352 (Proceedings of the IEEE Radar Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar

AU - White, Daniel

AU - Jahangir, Mohammed

AU - Antoniou, Michail

AU - Baker, Christopher

AU - Thiyagalingam, Jeyan

AU - Harman, Stephen

AU - Bennett, Cameron

PY - 2022/5/3

Y1 - 2022/5/3

N2 - In this paper, three simple models of a multi-rotor drone's timeseries radar returns were derived, and by populating the equation parameters with genuine drone motor speed recordings, a synthetic spectrogram was generated that accurately captures the characteristic uDoppler sidebands caused by the rapidly rotating propeller blades. Deficiencies in the model's amplitude modulation were identified and phenomenologically treated. The synthetic drone data was injected into a real radar background enabling a direct comparison of synthetic and real spectrograms of rotary-wing drones with an L-band staring radar.

AB - In this paper, three simple models of a multi-rotor drone's timeseries radar returns were derived, and by populating the equation parameters with genuine drone motor speed recordings, a synthetic spectrogram was generated that accurately captures the characteristic uDoppler sidebands caused by the rapidly rotating propeller blades. Deficiencies in the model's amplitude modulation were identified and phenomenologically treated. The synthetic drone data was injected into a real radar background enabling a direct comparison of synthetic and real spectrograms of rotary-wing drones with an L-band staring radar.

KW - Drone

KW - HERM

KW - Radar

KW - Simulation

UR - https://www.scopus.com/pages/publications/85146199371

U2 - 10.1109/RadarConf2248738.2022.9764352

DO - 10.1109/RadarConf2248738.2022.9764352

M3 - Conference contribution

AN - SCOPUS:85146199371

SN - 9781728153698 (PoD)

T3 - Proceedings of the IEEE Radar Conference

BT - 2022 IEEE Radar Conference (RadarConf22)

PB - IEEE

T2 - 2022 IEEE Radar Conference, RadarConf 2022

Y2 - 21 March 2022 through 25 March 2022

ER -

Multi-rotor Drone Micro-Doppler Simulation Incorporating Genuine Motor Speeds and Validation with L-band Staring Radar

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Prizes

3rd Place Student Paper Competition

Cite this