Methods for detection-recognition of radar, acoustic, optical and infrared signals of unmanned aerial vehicles

Authors

DOI:

https://doi.org/10.30837/rt.2021.2.205.15

Keywords:

unmanned aerial vehicle, detection, recognition, radar station, sodar, video camera, image, acoustic signal

Abstract

The protection of various objects against the impact of unmanned aerial vehicles (UAVs), which carry a potential threat in the military, economic and everyday areas of human activity, is one of the urgent tasks of our time. Currently, there are a large number of publications devoted to the description of methods and systems based on different physical principles designed to detect and observe UAVs against the background of existing interference. They consider the reception channels, methods of processing the received information signals and their subsequent intelligent analysis. It is shown, that the known methods of energy detection of UAV signals are insufficiently effective, since the operation is performed, as a rule, against a background of noise that has certain structural similarities with the UAV signal. Considerable attention is paid to the methods for interpreting the obtained data using trained neural networks. Since the number of publications in this area is constantly increasing, the task of analyzing, generalizing and systematizing the data available in the literature is relevant in accordance with this.

The article is an overview and it is devoted to the generalization and systematization of known methods of receiving and processing radar, acoustic, optical and infrared signals for detection-recognition, measurement of coordinates and parameters of UAV movement.

References

Кошкин Р.П. Беспилотные авиационные системы. Москва : Стратегические приоритеты, 2016. 676 с.

Макаренко С. И., Тимошенко А. В., Васильченко А. С. Анализ средств и способов противодействия беспилотным летательным аппаратам. Ч. 1. Беспилотный летательный аппарат как объект обнаружения и поражения // Системы управления, связи и безопасности. 2020. № 1. С. 109-146.

Kartashov V.M., Oleynikov V.N, Sheyko S.A., Koryttsev I.V., Babkin S.I., Zubkov O.V. Peculiarities of small unmanned aerial vehicles detection and recognition // Telecommunications and Radio Engineering, Vol. 78, Issue 9. P. 771-781.

Карташов В.М. и др. Обработка сигналов в радиоэлектронных системах дистанционного мониторинга атмосферы. Харьков : ХНУРЭ, 2014. 312 с.

Карташов В.М., Ситнік О.В. Радіотехнічні системи : навч. посібник. Харків : Сміт, 2009. 448 с.

De Wit J.M., Harmanny R., Premel-Cabic G. Micro-Doppler analysis of small UAVs // Proceedings of the 2012 9th European Radar Conference; Amsterdam, The Netherlands. 31 October–2 November 2012. P. 210–213.

Harmanny R., De Wit J., Cabic G.P. Radar micro-Doppler feature extraction using the spectrogram and the cepstrogram // Proceedings of the 2014 11th European Radar Conference; Cincinnati, OH, USA. 11–13 October 2014. P. 165–168.

Molchanov P., Harmanny R.I., de Wit J.J., Egiazarian K., Astola J. Classification of small UAVs and birds by micro-Doppler signatures // J. Microw. Wirel. Technol. 2014. 6:435–444.

De Wit J., Harmanny R., Molchanov P. Radar micro-Doppler feature extraction using the singular value decomposition // Proceedings of the 2014 International Radar Conference. Lille, France. 13–17 October 2014. P. 1–6.

Ren J., Jiang X. Regularized 2D complex-log spectral analysis and subspace reliability analysis of micro-Doppler signature for UAV detection // Pattern Recognit. 2017. 69:225–237.

24. Oh B.S., Guo X., Wan F., Toh K.A., Lin Z. Micro-Doppler mini-UAV classification using empirical-mode decomposition features // IEEE Geosci. Remote Sens. Lett. 2017. 15:227–231.

Szegedy C., Liu W., Jia Y., Sermanet P., Reed S., Anguelov D., Erhan D., Vanhoucke V., Rabinovich A. Going deeper with convolutions // Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Boston, MA, USA. 7–12 June 2015. P. 1–9.

Mendis G.J., Randeny T., Wei J., Madanayake A. Deep learning based doppler radar for micro UAS detection and classification // Proceedings of the MILCOM 2016-2016 IEEE Military Communications Conference. Baltimore, MD, USA. 1–3 November 2016. P. 924–929.

Freund Y., Schapire R.E. Large margin classification using the perceptron algorithm. Mach. Learn. 1999. 37:277–296.

Simonyan K., Zisserman A. Very deep convolutional networks for large-scale image recognition. arXiv. 20141409.1556.

Zeiler M.D., Fergus R. Visualizing and understanding convolutional networks // Proceedings of the European Conference on Computer Vision; Zurich, Switzerland. 6–12 September 2014. P. 818–833.

StrelkovaT., KartashovV., Lytyuga A.,StrelkovA. Theoretical Methods of Images Processing in Optoelectronic Systems. Chapter 6 // Developing and Applying Optoelectronics in Machine Vision. Oleg Sergiyenko and Julio C. Rodriguez-Quiñonez. (341p.) USA, Herhey, IGI Global, 2016. P.180-205.

StrelkovaT., KartashovV., Lytyuga A.,Strelkov A. Theoretical Methods of Images Processing in Optoelectronic Systems. Chapter 16 // Biometrics: Concepts, Methodologies, Tools, and Applications; Oleg Sergiyenko and Julio C. Rodriguez-Quiñonez. (341p.), IGI Global, 2017. P. 361-381.

Developing and Applying Optoelectronics in Machine Vision / O. Sergiyenko, J.C. Rodriguez-Quiñonez // IGI Global, 2016. 341p.

Schumann A., Sommer L., Klatte J., Schuchert T., Beyerer J. Deep cross-domain flying object classification for robust UAV detection // Proceedings of the 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). Lecce, Italy. 29 August–1 September 2017. P. 1–6.

Craye C., Ardjoune S. Spatio-temporal Semantic Segmentation for Drone Detection // Proceedings of the 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS); Taiwan, China. 18–21 September 2019.

Vasileios Magoulianitis D.A., Anastasios Dimou D.Z., Daras P. Does Deep Super-Resolution Enhance UAV Detection // Proceedings of the 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS); Taiwan, China. 18–21 September 2019.

Opromolla R., Fasano G., Accardo D. A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications. Sensors. 2018. 8:3391.

Gökçe F., Üçoluk G., Şahin E., Kalkan S. Vision-based detection and distance estimation of microunmanned aerial vehicles. Sensors. 2015. 15:23805–23846.

Ivanov M., Sergiyenko O., Mercorelli P., Tyrsa V., Kartashov V., Hernandez W., Sheiko S., Kolendovska M. Individual scans fusion in virtual knowledge base for navigation of mobile robotic group with 3D TVS // Proceedings of 44th Annual Conference of IEEE Industrial Electronics Society (IECON), Washington DC, USA. 2018. P. 3187-3192.

Ivanov M., Sergiyenko O., Mercorelli P., Hernandez W., Rodriguez Quinonez J.C., Kartashov V., Kolendovska M., Iryna T. Effective informational entropy reduction in multi-robot systems based on real-time TVS // IEEE International Symposium on Industrial Electronics, June, 8781209, 2019. P. 1162–1167.

Oleksandr Sotnikov, Vladimir Kartashov, Oleksandr Tymochko, Oleg Sergiyenko, Vera Tyrsa, Paolo Mercorelli, Wendy Flores-Fuentes. Methods for Ensuring the Accuracy of Radiometric and Optoelectronic Navigation Systems of Flying Robots in a Developed Infrastructure. Chapter 16 // Machine Vision and Navigation; Springer, Cham. P.537–578. Editors: Sergiyenko, Oleg, Flores-Fuentes, Wendy, Mercorelli, Paolo.

Lindner L., Sergiyenko O., Rivas-López M., Gurko A., Kartashov V.M. Machine vision system for UAV navigation // IEEE, 2016 International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles and International Transportation Electrification Conference, ESARS-ITEC, 2016. P.1–6.

Kartashov V., Oleynikov V., Zubkov O., Sheiko S. Optical detection of unmanned air vehicles on a video stream in a real-time // The Fourth International Conferenceon Information and Telecommunication Technologies and Radio Electronics (UkrMiCo’2019), 9–13 September 2019, Odessa, Ukraine, 4 p.

Aker C., Kalkan S. Using deep networks for drone detection // Proceedings of the 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS); Lecce, Italy. 29 August–1 September 2017. P. 1–6.

Карташов В.М., Олейников В.Н., Колендовская М.М., Тимошенко Л.П., Капуста А.И., Рыбников Н.В. Комплексирование изображений при обнаружении беспилотных летательных аппаратов // Радиотехника. 2020. Вып. 201. С. 120–129.

Müller T. Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras // Proceedings of the Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VIII, International Society for Optics and Photonics; Anaheim, CA, USA. 4 May 2017. P. 1019018.

Birch G.C., Woo B.L. Counter unmanned aerial systems testing: Evaluation of VIS SWIR MWIR and LWIR passive imagers. Sandia Rep. 2017.

Thomas A., Cotinat A., Gilber M. UAV localization using panoramic thermal cameras // Proceedings of the 12th International Conference on Computer Vision Systems (ICVS); Thessaloniki, Greece. 23–25 September 2019.

Samaras S., Diamantidou E., Ataloglou D., Sakellariou N., Vafeiadis A., Magoulianitis V., Lalas A., Dimou A., Zarpalas D., Votis K., Daras P., Tzovaras D. Deep Learning on Multi Sensor Data for Counter UAV Applications // A Systematic Review. Sensors (Basel). 2019 Nov 6. 19(22): 4837. Published online 2019, Nov 6.

Massey K., Gaeta R. Noise Measurements of Tactical UAVs. // Georgia Inst. of Technology / GTRI / ATAS, Atlanta. 16th AIAA / CEAS Aeroacoustics Conference. American Institute of Aeronautics and Astronautics, 2010. P. 1–16.

Marino L. Experimental analysis of UAV-propellers noise // 16th AIAA/CEAS Aeroacoustics Conference. University La Sapienza, Rome, Italy, American Institute of Aeronautics and Astronautics, 2010. P. 1–14.

Zaslavsky Yu. M., Zaslavsky V. Yu. Acoustic noise of a low flying quadrocopter // NOUSE Theory and Practice. V.5, №3, 2019. P. 21–27.

Sinibaldi G., Marino L. Experimental analysis on the noise of the propellers for small UAV // Applied Acoustics, 74 (2013). P. 79–88.

Intaratep N., Alexande W. N., Devenport W. J., Grace S. M., Dropkin A. Experimental Study of Quadcopter Acoustics and Performance at Static Thrust Conditions // Aeroacoustics Conferences 30 May 1 June, 2016, Lyon, France, 22nd AIAA/CEAS Aeroacoustics Conference. P. 1–6.

Moshkov P. M., Samokhin V. F. Assessment of the influence of the number of blades and diameter on the noise of the propeller // Vestnik Samarskogo universiteta. Aerokosmicheskaya tekhnika, tekhnologii i mashinostroyeniye, V. 15, No 3, 2016. P. 25–34. (In Rus.).

Карташов В.М., Олейников В.Н., Шейко С.А., Бабкин С.И., Корытцев И.В., Зубков О.В., Анохин М.А. Информационные характеристики звукового излучения малых беспилотных летательных аппаратов // Радиотехника. 2017. Вып. 191. С. 181-187.

Kartashov V.M., Tikhonov V.A., Voronin V.V. and Tymoshenko L.P. Complex model of random signal in problems of acoustic sounding of atmosphere // Telecommunications and Radio Engineering. 2016. V. 75. Iss. 20. P.1885–1892.

Карташов В.М., Харченко О.И., Чумаков В.И. Использование эффекта стохастического резонанса для анализа спектров акустического излучения малых беспилотных летательных аппаратов // Радиотехника. 2019. Вып. 197. С. 100-106.

Kartashov V.M., Oleynikov V.N, Sheyko S.A., Babkin S.I., Koryttsev I.V., Zubkov O.V., Anokhin M.A. Information characteristics of sound radiation of small unmanned aerial vehicles // Telecommunications and Radio Engineering. 2018. V.77 (10). P. 915–924.

Карташов В.М., Тихонов В.А., Воронин В.В., Тимошенко Л.П. Комплексные модели случайных сигналов в задачах акустического зондирования атмосферы // Радиотехника. 2016. Вып. 185. С. 81–86.

Oleynikov V. N., Zubkov O. V., Kartashov V. M., Korytsev I. V., Babkin S. I., Sheiko S. A. Investigation of detection and recognition efficiency of small unmanned aerial vehicles on their acoustic emission // Telecommunications and Radio Engineering, 2019. V. 78, Issue 9. P. 759–770.

Kartashov V., Oleynikov V., Koryttsev I., Zubkov O., Babkin S., Sheiko S. Processing and Recognition of Small Unmanned Vehicles Sound Signals // International Scientific-Practical Conference on Problems of Infocommunications Science and Technology, PIC S and T 2018 Proceedings 31 January 2019. P. 392–396.

Kartashov V., Oleynikov V., Koryttsev I., Sheyko S., Zubkov O., Babkin S., Selieznov I. 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), 25-29 Feb. 2020. P.1–4.

Chowdhury A.S.K. Master’s Thesis. University of Nevada. Las Vegas, NV, USA: 2016. Implementation and Performance Evaluation of Acoustic Denoising Algorithms for UAV.

Mezei J., Molnár A. Drone sound detection by correlation // Proceedings of the 2016 IEEE 11th International Symposium on Applied Computational Intelligence and Informatics (SACI); Timisoara, Romania. 12–14 May 2016. P. 509–518.

Bernardini A., Mangiatordi F., Pallotti E., Capodiferro L. Drone detection by acoustic signature identification // Electron. Imaging. 2017. P.60–64.

Liu H., Wei Z., Chen Y., Pan J., Lin L., Ren Y. Drone detection based on an audio-assisted camera array // Proceedings of the 2017 IEEE Third International Conference on Multimedia Big Data (BigMM); Laguna Hills, CA, USA. 19–21 April 2017. P. 402–406.

Kim J., Park C., Ahn J., Ko Y., Park J., Gallagher J.C. Real-time UAV sound detection and analysis system // Proceedings of the 2017 IEEE Sensors Applications Symposium (SAS); Glassboro, NJ, USA. 13–15 March 2017. P. 1–5.

Kim J., Kim D. Neural Network based Real-time UAV Detection and Analysis by Sound // J. Adv. Inf. Technol. Converg. 2018. 8:43–52.

Salamon J., Jacoby C., Bello J.P. A dataset and taxonomy for urban sound research // Proceedings of the 22nd ACM International Conference on Multimedia. ACM; Mountain View, CA, USA. 18–19 June 2014. P. 1041–1044.

Oleynikov V.N., Kartashov, V.M., Babkin, S. I., Zubkov, O.V., Korytsev I.V., Sheiko, S.A.,. Seleznov I.S. Structure and Parameter Unmanned Aerial Vehicles Sound Fields // Telecommunications and Radio Engineering. New York. 2020. Vol. 79, №17. P.1539-1550.

Park S., Shin S., Kim Y., Matson E.T., Lee K., Kolodzy P.J., Slater J.C., Scherreik M., Sam M., Gallagher J.C., et al. Combination of radar and audio sensors for identification of rotor-type unmanned aerial vehicles (uavs) // Proceedings of the 2015 IEEE SENSORS; Busan, Korea. 1–4 November 2015. P. 1–4.

A. Bernardini, F. Mangiatordi, E. Pallotti, L. Capodiferro, F. Ugo Bordoni. Drone detection by acoustic signature identification // Electronic Imaging, Imaging and Multimedia Analytics in a Web and Mobile World. 2017. P. 60–64.

Vasilchenko A., Kartashov V.M. Analysis of influence exerted by longitudinal Doppler effect upon output signal of sodar antenna array // Telecommunications and Radio Engineering. Vol. 66, Issue 9. P. 841–847.

Zelnio A.M. Detection of small aircraft using an acoustic array // Electrical Engineering.Wright State University, 2007. 55 p.

Kozeruk S. A., Korzhyk A.V. Identification of small aircraft by acoustic radiation // Visnyk NTUU KPI. Series Radiotekhnika Radiobuduvannia. 2019. Iss. 76. P. 15–20.

Sadasivan S., Gurubasavaraj M., Sekar S.R. Acoustis siqnature of an unmanned air vehicle exploitation for aircraft localisation and parameter estimation // Eronautical DEF SCI J. 2001 Vol. 51 №3. pр. 279–283.

Тихонов В.А., Карташов В.М., Олейников В.М., Леонидов В.И., Тимошенко Л.П., Селезнев И.С., Рыбников Н.В. Обнаружение-распознавание беспилотных летательных аппаратов с использованием составной модели авторегрессии их акустического излучения // Вісник НТУУ «КПІ». Радіотехніка. Радіоапаратобудування. 2020. Вип. №81. С. 38–46.

Semenets V. V., Kartashov V.M., Leonidov V. I. Registration of refraction Phenomenon in the Problem of acoustic Sounding of Atmosphere in Airport Zone // Telecommunications and Radio Engineering. 2018. Vol. 77, Iss. 5. P.461–468.

Карташов В.М., Тихонов В.А., Воронин В.В. Особенности построения и применения комплексних систем дистанционного зондирования атмосферы // Радиотехника. 2016. Вып. 186. С. 184-185.

Карташов В.М., Куля Д.Н., Кушнир М.В., Толстых Е.Г. Выбор модели изменения скорости звука для оптимального линейного фильтра систем радиоакустического зондирования атмосферы // Ра-диотехника. 2013. №173.С. 63–78.

Дистанционные методы и средства исследования процессов в атмосфере Земли ; под ред. Б.Л. Кащеева, Е.Г. Прошкина, М.Ф. Лагутина. Харьков : Бизнес Информ, 2002. 426 с.

Карташов В.М., Куля Д.Н., Пащенко С.В. Алгоритм автосопровождения изменений информационного параметра сигнала радиоакустических систем // Восточно-европейский журнал передовых технологий. 2012. №4/9(58). С. 57-61.

Олейников В.Н., Зубков О.В, Карташов В.М., Корытцев И.В., Бабкин С.И., Шейко С.А., Селезнев И.С. Экспериментальная оценка эффективности алгоритмов пеленгования беспилотных летательных аппаратов по акустическому излучению // Радиотехника. 2019. Вып. 199. С. 29–37.

Карташов В.М., Корытцев И.В., Олейников В.Н., Зубков О.В., Шейко С.А., Бабкин С.И., Левский Н.А., Селезнев И.С. Алгоритмы пеленгации беспилотных летательных аппаратов по их акустическому излучению // Радиотехника. 2019. Вып. 196. С. 22–31.

Oleynikov V., Zubkov O., Kartashov V., Koryttsev I., Sheiko S., Babkin S. Experimental estimation of direction finding to unmanned air vehicles algorithms efficiency by their acoustic emission // 2019 International Scientific-Practical Conference «Problems of Infocommunications Science and Technology, PIC S and T 2019 Proceeding», 2019. P.175–178.

Saqib M., Khan S.D., Sharma N., Blumenstein M. A study on detecting drones using deep convolutional neural networks // Proceedings of the 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). Lecce, Italy. 29 August–1 September 2017.

Mrunalini Nalamati A.K., Muhammed Saqib N.S., Blumenstein M. Drone Detection in Long-range Surveillance Videos // Proceedings of the 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS); Taiwan, China. 18–21 September 2019.

Aker C., Kalkan S. Using deep networks for drone detection // Proceedings of the 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS); Lecce, Italy. 29 August–1 September 2017. P. 1–6.

Kartashov V.M., Oleynikov V.N, Zubkov O.V., Korytsev I.V., Babkin S. I., Sheiko S.A., Kolendovskaya M.M. Spatial-temporal Processing of acoustic Signals of Unmanned Aerial Vehicles // Telecommunications and Radio Engineering. 2020. V. 79, №9. P.769–780.

Карташов В.М., Олейников В.Н., Воронин В.В., Рябуха В.П., Капуста А.И., Рыбников Н.В., Селезнев И.С. Методы комплексной обработки и интерпретации радиолокационных, акустических, оптических и инфракрасных сигналов беспилотных летательных аппаратов // Радиотехника. 2020. Вып. 202. С. 173-182.

Карташов В.М., Олейников В.Н., Леонидов В.И., Воронин В.В., Капуста А.И., Селезнев И.С., Першин Е.В. Комплексная обработка сигналов интегрированной системы наблюдения беспилотных летательных аппаратов с использованием целеуказания // Радіотехніка. 2020. Вип. 203. С. 148-161.

Карташов В.М., Корытцев И.В., Олейников В.Н., Зубков О.В., Шейко С.А., Бабкин С.И. Обработка сигналов при пеленгации и определении дальности до малоразмерных БПЛА в оптическом и инфракрасном диапазонах // Радиотехника. 2020. Вып. 202. С. 125-135.

Карташов В.М., Корытцев И.В., Олейников В.Н., Зубков О.В., Шейко С.А., Бабкин С.И. Оптико-электронные методы обнаружения воздушных объектов и измерения их координат // Радиотехника. 2020. Вып. 202. С. 153-159.

Карташов В.М., Корытцев И.В., Олейников В.Н., Зубков О.В., Шейко С.А., Бабкин С.И. Эффектив-ность детектирования и распознавания изображений дронов по видеопотоку стационарной видеокамеры // Радиотехника. 2020. Вып. 202. С. 136-146.

Semenets V.М., Kartashov V.M., Leonidov V.I. Features of Acoustic Noise of Small Unmanned Aerial Vehicles // Telecommunications and Radio Engineering. New York. 2020. Vol. 79, №11. P. 985-995.

Kartashov V., Oleynikov V., Koryttsev I., Sheiko S., Zubkov O., Babkin S.. Processing of Wide Band Acoustic Signals During Detection of Unmanned Aerial Vehicles // 2020 IEEE Ukrainian Microwave Week (UkrMW). Kharkiv, Ukraine, September 21 25, 2020. Vol. 1 on 2020 IEEE 12th International Conference on Antenna Theory and Techniques (ICATT). P. 35-39.

Koryttsev I., Sheiko S., Kartashov V., Zubkov O., Oleynikov V., Anohin M., Selieznov I. Practical Aspects of Range Determination and Tracking of Small Drones by Their Video Observation // 2020 International Scientific-Practical Conference. Problems of Infocommunications. Science and Technology. Kharkiv, Ukraine. October 6-9, 2020. 5 p.

Олейников В.Н., Зубков О.В., Карташов В.М., Шейко С.А., Бабкин С.И., Корытцев И.В. Исследова-ние эффективности обнаружения и распознавания малоразмерных беспилотных летательных аппаратов по их акустическому излучению // Радиотехника. 2018. Вып. 195. С. 209-217.

Карташов В.М., Олейников В.Н., Шейко С.А., Бабкин С.И., Корытцев И.В., Зубков О.В. Особенности обнаружения и распознавания малых беспилотных летательных аппаратов // Радиотехника. 2018. Вып. 195. С. 235-243.

Published

2021-07-02

How to Cite

Kartashov, V. ., Pososhenko, V. ., Voronin, V. ., Kolesnik, V. ., Kapusta, A. ., Rybnikov, N. ., & Pershin , E. . (2021). Methods for detection-recognition of radar, acoustic, optical and infrared signals of unmanned aerial vehicles . Radiotekhnika, 2(205), 138–153. https://doi.org/10.30837/rt.2021.2.205.15

Issue

Section

Articles

Most read articles by the same author(s)

1 2 > >>