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 |
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Title of host publication | 2022 IEEE Radar Conference (RadarConf22) |
Publisher | IEEE |
Number of pages | 6 |
ISBN (Electronic) | 9781728153681 |
ISBN (Print) | 9781728153698 (PoD) |
DOIs | |
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 |
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Publisher | IEEE |
ISSN (Print) | 1097-5764 |
ISSN (Electronic) | 2640-7736 |
Conference
Conference | 2022 IEEE Radar Conference, RadarConf 2022 |
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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