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Telecommunications and Radio Engineering

Publicado 12 números por año

ISSN Imprimir: 0040-2508

ISSN En Línea: 1943-6009

SJR: 0.185 SNIP: 0.268 CiteScore™:: 1.5 H-Index: 22

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PECULIARITIES OF SMALL UNMANNED AERIAL VEHICLES DETECTION AND RECOGNITION

Volumen 78, Edición 9, 2019, pp. 771-781
DOI: 10.1615/TelecomRadEng.v78.i9.30
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SINOPSIS

Review and analysis of methods for detection and recognition of unmanned aerial vehicles (UAVs) are carried out. The channels for the detection of UAVs - acoustic, optical, radar, infrared, radio channel are discussed. The advantages and disadvantages of the channels used are compared and appreciated. In the case of small UAVs, there are a number of significant difficulties and limitations. One of the directions in the UAVs detection is acoustic observation. The noise generated by the UAV propulsion system and the air propeller is a significant damasking feature. Creating and improving methods for detecting, guiding and recognizing small UAVs by the reception and processing their sound signals is an urgent task. When using such a method of detecting UAVs, frequency spectra, spectrograms, normalized autocorrelation functions, and phase portraits of acoustic signals are used. Estimates of spectral coefficients, determined by a discrete realization containing a predetermined number of samples, as well as parameters of autoregression models can serve as information signs of the UAVs sound image.

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CITADO POR
  1. Ciaburro Giuseppe, Iannace Gino, Improving Smart Cities Safety Using Sound Events Detection Based on Deep Neural Network Algorithms, Informatics, 7, 3, 2020. Crossref

  2. Kartashov Vladimir, Oleynikov Vladimir, Koryttsev Igor, Sheiko Sergiy, Zubkov Oleh, Babkin Stanislav, Processing of Wide Band Acoustic Signals During Detection of Unmanned Aerial Vehicles, 2020 IEEE Ukrainian Microwave Week (UkrMW), 2020. Crossref

  3. Tykhonov Vyacheslav, Kartashov Vladimir, Pososhenko Vitaliy, Kolisnyk Viktoriia, Sheiko Sergiy, Yegorov Andriy, Rybnykov Mykola, Detection and Recognition of Unmanned Aerial Vehicles by the Spectrum of Their Acoustic Signals, 2021 IEEE 16th International Conference on Computer Sciences and Information Technologies (CSIT), 2021. Crossref

  4. Zubkov Oleh, Sheiko Sergiy, Oleynikov Vladimir, Kartashov Vladimir, Investigation of the neural networks effectiveness in recognizing moving drones, 2021 IEEE 16th International Conference on Computer Sciences and Information Technologies (CSIT), 2021. Crossref

  5. Kartashov Vladimir, Oleynikov Vladimir, Koryttsev Igor, Sheiko Sergiy, Zubkov Oleh, Babkin Stanislav, Selieznov Ivan, Use of Acoustic Signature for Detection, Recognition and Direction Finding of Small Unmanned Aerial Vehicles, 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), 2020. Crossref

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