Complexing of information channels of UAV detection and observation systems from the statistic solutions theory standpoint

Authors

DOI:

https://doi.org/10.30837/rt.2021.4.207.11

Keywords:

unmanned aerial vehicle, detection, observation, integration, radar station, integrated system, information channel, signal processing

Abstract

Currently, unmanned aerial vehicles (UAVs) provide a wide range of useful tasks for humanity, but, on the other hand, they pose a serious threat in economic, military and other areas of human activity. Difficulties in observing UAVs using modern technical means, as well as their relatively low cost, lead to an expansion of the scope of UAVs based illegal actions. Therefore, the protection of various objects against UAVs is a serious scientific and technical task of today.

Since the possibilities of the known methods of UAV detection are different, the joint use of systems of different types is realized in practice nowadays, in order to increase the informativeness of the obtained data by their joint (complex) processing.

The number of publications in this field is constantly increasing, and considerable attention is paid to integrated systems built on the basis of various physical sensors. However, the efficiency of multi-sensor systems with integrated processing of the output signals of the channels in practice remains insufficient.

This article is devoted to the study of methods for the synthesis of new, more efficient algorithms for complexing radar, acoustic, optical and infrared information channels of integrated UAV detection and recognition systems, which are performed from the standpoint of statistical theory of radio system optimization.

This approach allows synthesizing the optimal (according to the selected quality criterion) complex information processing system, which ensures obtaining the maximum amount of information from the vector process observed at the inputs of information channels. There shown the possibility of constructing an optimal UAV detector with the use of the late strategy of combining information at the level of decisions made in individual channels of the system.

References

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

Макаренко С., Тимошенко А., Васильченко А. Противодействие беспилотным летательным аппаратам. Ч. 1. Беспилотный летательный аппарат как объект обнаружения и поражения // Системы управления, связи и безопасности. 2020. №1. С. 109-146, doi: 10.24411/2410-9916-2020-10105.

Oleynikov V., Zubkov O., Kartashov V., Koryttsev I., Sheiko S. and Babkin S. Experimental Estimation of Direction Finding to Unmanned Air Vehicles Algorithms Efficiency by Their Acoustic Emission // 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T), 2019, pp. 175-178, doi: 10.1109/PICST47496.2019.9061337.

Sergiyenko O., Rodríguez-Quiñonez J. Developing and applying optoelectronics in machine vision // IGI Global, 2016.

Rivas-Lopez M., Sergiyenko O., Flores-Fuentes W. and Rodríguez-Quiñonez J. Optoelectronics in machine vision-based theories and applications // Hershey, PA: Engineering Science Reference (an imprint of IGI Global), 2019. pp. 373-391.

Murrieta-Rico F. et al. Pulse width influence in fast frequency measurements using rational approximations // Measurement, vol. 86. pp. 67-78, 2016, doi: 10.1016/j.measurement. 2016.02.032.

Avalos-Gonzalez D. et al. Constraints definition and application optimization based on geometric analysis of the frequency measurement method by pulse coincidence // Measurement. 2018. Vol. 126. Р. 184-193, 2018, doi: 10.1016/j.measurement. 2018. 05. 025.

Ivanov M. et al. Individual Scans Fusion in Virtual Knowledge Base for Navigation of Mobile Robotic Group with 3D TVS // IECON 2018 – 44th Annual Conference of the IEEE Industrial Electronics Society. 2018. Р. 3187-3192, doi: 10.1109/IECON.2018.8591442.

Avalos-Gonzalez D. et al. Application of Fast Frequency Shift Measurement Method for INS in Navigation of Drones // IECON 2018 – 44th Annual Conference of the IEEE Industrial Electronics Society, 2018, pp. 3159-3164, doi: 10.1109/IECON.2018.8591377.

Карташов В., Куля Д., Кушнир М., Толстых Ю. Выбор модели изменения скорости звука для оптимального линейного фильтра систем радиоакустического зондирования атмосферы // Радиотехника. 173. С. 63-78. Режим доступа: https://openarchive.nure.ua/handle/document/1130.

Карташов В., Куля Д., Пащенко С. Алгоритм автоматического слежения за изменением параметра сигнала радиоакустических информационных систем // Восточно-Европейский журнал корпоративных технологий. 2012. Вып. 4, №. 9(58), pp. 57-61. Режим доступа: http://journals.uran.ua/eejet/article/view/5747

Кащеев Б., Прошкин Е., Лагутин М. Дистанционные методы и средства изучения процессов в атмосфере Земли. Харьков : Бизнес Информ, 2002.

Сосулин Ю.В. Теоретические основы радиолокации и радионавигации. Москва : Радио и связь, 1992.

W. Koch, J. Koller and M. Ulmke. Ground target tracking and road map extraction // ISPRS Journal of Photogrammetry and Remote Sensing, vol. 61, no. 3-4, pp. 197-208, 2006, doi: 10.1016/j.isprsjprs.2006.09.013.

F. Kloeppel et al. Multimodal UAV detection: study of various intrusion scenarios // Electro-Optical Remote Sensing XI, 2017, doi: 10.1117/12.2278212.

F. Giovanneschi et al. An adaptive sensing approach for the detection of small UAV: first investigation of static sensor network and moving sensor platform // Signal Processing, Sensor/Information Fusion, and Target Recognition XXVII, 2018, doi: 10.1117/12.2304758.

S. Park et al. Combination of radar and audio sensors for identification of rotor-type Unmanned Aerial Vehicles (UAVs) // 2015 IEEE SENSORS, 2015, pp. 1-4, doi: 10.1109/ICSENS.2015.7370533.

G. L. Charvat, A. J. Fenn and B. T. Perry. The MIT IAP radar course: Build a small radar system capable of sensing range, Doppler, and synthetic aperture (SAR) imaging // 2012 IEEE Radar Conference, 2012, pp. 0138-0144, doi: 10.1109/RADAR.2012.6212126.

H. Liu, Z. Wei, Y. Chen, J. Pan, L. Lin and Y. Ren. Drone Detection Based on an Audio-Assisted Camera Array // 2017 IEEE Third International Conference on Multimedia Big Data (BigMM), pp. 402-406, 2017, doi: 10.1109/bigmm.2017.57.

Басов О., Карпов А. Анализ стратегий и методов объединения многомодальной информации // Обработка информации и управления. 2015. Вып. 2. С. 7-14, , doi: 10.15217/issn1684-8853.2015.2.7.

Фалькович С., Хомяков Е. Статистическая теория измерительных радиосистем. Москва : Радио и связь, 1981.

Ширман Ю., Манжос В. Теория и методика обработки радиолокационной информации на фоне помех. Москва : Радио и связь, 1981.

Published

2021-12-24

How to Cite

Kartashov, V. ., Pososhenko, V. ., Kolisnyk, V. ., Kapusta, A. ., Rybnykov, M. ., Pershyn, Y. ., & Kizka , V. . (2021). Complexing of information channels of UAV detection and observation systems from the statistic solutions theory standpoint. Radiotekhnika, 4(207), 102–112. https://doi.org/10.30837/rt.2021.4.207.11

Issue

Section

Articles