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Telecommunications and Radio Engineering
SJR: 0.203 SNIP: 0.44 CiteScore™: 1

ISSN Imprimer: 0040-2508
ISSN En ligne: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v78.i9.20
pages 759-770

INVESTIGATION OF DETECTION AND RECOGNITION EFFICIENCY OF SMALL UNMANNED AERIAL VEHICLES ON THEIR ACOUSTIC RADIATION

V. N. Oleynikov
Kharkiv National University of Radio Engineering and Electronics, 14 Nauka Ave, Kharkiv, 61166, Ukraine
O. V. Zubkov
Kharkiv National University of Radio Electronics, 14 Nauka Ave, Kharkiv 61166, Ukraine
V. M. Kartashov
Kharkov National University of Radio Engineering and Electronics, 14, Nauka Ave, Kharkiv, 61166, Ukraine
I. V. Koryttsev
Kharkiv National University of Radio Electronics, 14 Nauka Ave, Kharkiv 61166, Ukraine
S. I. Babkin
Kharkov National University of Radio Engineering and Electronics, 14, Nauky Ave, Kharkiv, 61166, Ukraine
S. A. Sheiko
Kharkiv National University of Radio Electronics, 14 Nauka Ave, Kharkiv 61166, Ukraine

RÉSUMÉ

The features of acoustic spectrum of UAVs, spectrum of natural and industrial acoustic noise, noise spectrum of automobile and rail transport, and human speech spectrum were investigated. The method for recognition of UAV sound based on the Mel-frequency cepstral coefficients was proposed. The universal method for detecting UAV based on characteristic features of acoustic spectrum was proposed as well. Both methods were tested using experimental recordings of UAVs and noise sounds and got close well results. The universal recognition method has some worse recognition reliability and false alarm probability, but does not need creation of sound and noise images base.

RÉFÉRENCES

  1. Oleynikov, V.N., Sheiko, S.A., and Babkin, S.I., (2017), The study of characteristics of the acoustic radiation of small unmanned aerial vehicles, Proc. VI International radio electronic forum on Applied radio electronics, State and development prospects (MYF-2017), International Scientific Conference.

  2. Kartashov, V., Oleynikov, V., Koryttsev, I., Zubkov, O. et al., (2018), Processing and recognition of small unmanned vehicles’ sound signals, International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T), Kharkiv, Ukraine, pp. 1-5.

  3. Kartashov, V.M., Oleynikov, V.N., Sheyko, S.A., Babkin, S.I. et al., (2017) , Information characteristics of the sound signals of small unmanned aerial vehicles, Radiotekhika, 91, pp. 181-187, (in Russian).

  4. Kartashov, V.M., Oleynikov, V.N, Sheyko, S.A., Babkin, S.I. et al., (2018), Information characteristics of sound radiation of small unmanned aerial vehicles, Telecommunications and Radio Engineering, 77(10), pp. 915-924.

  5. Zhuravlev, V., (2007) , Analysis of the information parameters and characteristics of speech masking signals using the objects of information activity, Legal, normative and metrological supply of the information security system in Ukraine, 1(14), pp. 170-176.

  6. Ostanin, S.A., (2011), The increase in the signal-to-noise ratio by the method of sequential calculation of the autocorrelation function, Journal of Radio Electronics, 12, pp.17-26, (in Russian).

  7. Zakovryashin, A.S., Malinin, P.V., and Lependin, A.A., (2007), The use of distributions of Mel- frequency cepstral coefficients for a person voice identification, Control, computer technology and computer science, 5, pp. 156-160, (in Russian).

  8. Bernardini, A., Mangiatordi, F., Pallotti, E., Capodiferro, L., and Ugo Bordoni, F., (2017), Drone detection by acoustic signature identification, Electronic Imaging, Imaging and Multimedia Analytics in a Web and Mobile World, pp. 60-64.


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