Aleksandar Lebl, Mladen Mileusnić, Dragan Mitić, Jovan Radivojević, Vladimir Matić

DOI Number
First page
Last page


Drones micro-Doppler signatures obtained by FMCW radars are an excellent procedure for malicious drone detection, identification and classification. There are a number of contributions dealing with recorded spectrograms with these micro-Doppler signatures, but very low number of them has analyzed possibility to calculate echo caused by drone moving parts. In this paper, starting from already existing mathematical apparatus, we presented such spectrograms as a function of changing drone moving parts characteristics: rotor number, blades number, blade length and rotor moving speed. This development is the part of a wider project intended to prevent malicious drone usage.


Malicious drone detection, FMCW radar, Spectrogram, Drone micro-Doppler signatures, calculation method

Full Text:



V. Matić, V. Kosjer, A. Lebl, B. Pavić and J. Radivojević, "Methods for Drone Detection and Jamming", In Proceedings of the 10th International Conference on Information Society and Technology (ICIST). Kopaonik, 2020, pp.16–21.

N. Eriksson, Conceptual study of a future drone detection system Countering a threat posed by a disruptive technology. Master thesis in Product Development, Chalmers University of Technology, Goethenburg, Sweden, 2018.

Advanced protection systems, Ctrl+sky drone detection and neutralization system, 2017,

Droneshield, "Product Information", 2018.

H. Liu, F. Qu, Y. Liu, W. Zhao and Y. Chen, "A drone detection with aircraft classification based on a camera array", In Proceedings of the 2018 IOP Conference Series: Materials Science and Engineering, vol. 322, p. 052005. 2018, pp. 1–7.

X. Shi, C. Yang, C. Liang, Z. Shi and J. Chen, "Anti-Drone System with Multiple Surveillance Technologies: Architecture, Implementation, and Challenges", IEEE Commun. Magaz., vol. 56, no. 4, pp. 68–74, 2018.

V. C. Chen, The Micro-Doppler Effect in Radar. Artech House, Second Edition, 2019, ISBN: 978-1-63081-546-2.

C. Zhao, G. Luo, Y. Wang, C. Chen and Z. Wu, "UAV Recognition Based on Micro-Doppler Dynamic Attribute-Guided Augmentation Algorithm", Remote Sensing, vol. 13, no. 6, p. 1205, pp. 1–17, 2021.

T. Šević, V. Joksimović, I. Pokrajac, R. Brusin, B. Sazdić-Jotić and D. Obradović, "Interception and Detection of Drones Using RF-based Dataset of Drones", Sci. Tech. Rev., vol. 70, no. 2, pp. 29–34, 2020.

S. Rahman and D. A. Robertson, "Radar micro-Doppler signatures of drones and birds at K-band and W-band", Sci. Rep., vol. 8, pp. 1–11, 2018.

Y. Cai, O. Krasnov and A. Yarovoy, "Simulation of Radar Micro-Doppler Patterns for Multi-propeller Drones", In Proceedings of the International Radar Conference (Radar-2019), Toulon, 2019, pp.1–5.

W. Wang, J. Du and J. Gao, "Multi-Target Detection Method Based on Variable Carrier Frequency Chirp Sequence", Sensors, vol. 18, p. 3386, pp. 1–12, 2018.

A. Coluccia, G. Parisi and A. Fascista, "Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review", Sensors, vol. 20, p. 4172, pp. 1–22, 2020.

M. Daković, M. Brajović, T. Thayaparan and Lj. Stanković, "An algorithm for micro-Doppler period estimation", In Proceedings of the 20th Telecommunications Forum (TELFOR), Belgrade, 2012, pp. 851–854.

P. Molchanov, Radar Target Classification by Micro-Doppler Contributions. Thesis for the degree of Doctor of Science in Technology, Publication 1255, Tampere University of Technology, Finland, October 2014, ISSN 1459-2045.

E. Hyun, Y.-S. Jin and J.-H. Lee, "Design and Implementation of 24 GHz Multichannel FMCW Surveillance Radar with a Software-Reconfigurable Baseband", J. Sensors, vol. 2017, p. 3148237, pp. 1–11, 2017.

B. Karlsson, Modeling multicopter radar return. Master’s thesis in Applied Physics, Chalmers University of Technology, Department of Electrical Engineering, Gothenburg, Sweden, 2017.

V. M. Milovanović, “On Fundamental Operating Principles and Range-Doppler Estimation in Monolithic Frequency-Modulated Continuous-Wave Radar Sensors", FU Elec. Energ., vol. 31, no. 4, pp. 547–570, 2018.

C. Iovescu and S. Rao, The fundamental of millimeter wave radar sensors. Texas Instruments, 2020.

J. Zhu, Low-cost, software defined FMCW radar for observations of drones. Master thesis, University of Oklahoma, Graduate College, 2017.

M. Passafiume, N. Rojhani, G. Collodi and A. Cidronali, "Modeling Small UAV Micro-Doppler Signature Using Milimeter-Wave FMCW Radar", Electronics , vol. 10, no. 6, pp. 1–16, 2021.

J. Park, J.-S. Park and S.-O. Park, "Small Drone Classification with Light CNN and New Micro-Doppler Signature Extraction Method Based on A-SPC Technique",, pp.1–5, 2020.

T. Tang and C. Wu, Design of new Frequency Modulated Continuous Wave (FMCW) target tracking radar with digital beamforming tracking. Defense Research and Development Canada, Scientific Report DRDC-RDDC-2019-R175, 2019.

M. Ahmadizadeh, An Introduction to Short-Time Fourier Transform (STFT). Sharif University of Technology, Department of Civil Engineering, 2014.

H. A. Gaberson, "A Comprehensive Windows Tutorial", Sound and Vibration, Instrumentation Reference Issue, pp. 14–23, 2006.


  • There are currently no refbacks.

ISSN: 0353-3670 (Print)

ISSN: 2217-5997 (Online)

COBISS.SR-ID 12826626