Optimization of the location of the center for receiving and controlling reconnaissance UAVS, taking into account the reflections of the signal from urban areas

Аuthors

Akhmedov E. M.

National Aerospace Agency of Azerbaijan Republic, NASA, Baku, 8th mkr., Suleiman Sani Akhundov 1

e-mail: emil.ahmadov21@gmail.com

Abstract

The issues of optimizing the choice of the location of the UAV reception and control center, taking into account the reflections of the signal from nearby urban areas, are investigated. The success of the reconnaissance UAV mission as a whole depends on the possibility of solving such a problem as signal attenuation during the flight. One of the most important tasks to be solved in order to increase the effectiveness of reconnaissance UAVs is to take into account the effects of various attenuations of the transmitted signal on the "UAV-center" or "center-UAV" routes. Signal attenuation in these communication channels manifests itself in the form of amplitude fluctuations in time or frequency. Additional components of attenuation include attenuation due to multipath. In the case of a UAV flying over a city at low altitude and when communicating at frequencies below 5 GHz, the signal multipath resulting from multiple reflections from various urban structures may have the most significant impact. Multipath consists in the arrival at the receiving center of numerous reflected signals with different phases, leading to interference effects. The problem of choosing the location of the flight control center in an urban environment in which noise due to multipath would be minimized is formulated and solved. Solving the problem using the mathematical apparatus of unconditional variational optimization showed that multipath noise can be minimized if reflective structures near the center are located in such a way that the delays of the reflected signal from buildings are inversely proportional to the square of the signal coming from these buildings, i.e. strongly reflective buildings should be located closer to the center than weakly reflective objects. 

Keywords:

multipath, UAV, optimization, signal reflection, interference

References

1. Horcher A., Visser R.J.M. Unmanned aerial vehicles: applications for natural resource management and monitoring. Council on Forest Engineering Annual Meeting, Hot Springs (AR), USA, 2004. 
2. Sugiura R., Noguchi N., Ishii K. Remote-sensing technology for vegetation monitoring using an unmanned helicopter. Biosystems Engineering. 2005. V. 90 (4), P. 369-379. DOİ: 10.1016/j.biosystemseng.2004.12.011
3. Egbert J., Beard R.W. Road following control constraints for low altitude miniature air vehicles. American Control Conference, New York, 2007. P. 353-358. 
4. Αlbrigtsen A. The application of unmanned aerial vehicles for snow avalanche search and rescue. Faculty of Science and Technology, Department of Engineering and Safety. The Artic University of Norway. 2016.
5. Andriluka M., Schnitzspan P., Meyer J., Kohlbrecher S., Petersen K., von Stryk O., Roth S., Schiele B. Vision based victim detection from unmanned aerial vehicles. In Conference on Intelligent Robots and Systems (IROS). 2010. P. 1740–1747. DOI: 10.1109/IROS.2010.5649223
6. Bernard M., Kondak K. Generic slung load transportation system using small size helicopters. Proceedings of the IEEE International Conference on Robotics and Automation. 2009. P. 3258– 3264. DOİ: 10.1109/ROBOT.2009.5152382
7. R. Raz, A. Rosen, T. Ronen. Active aerdynamic stablization of a helicopter/sling-load system. Journal of Aircraft. 1989. V. 26, P. 822-828. DOI: 10.2514/3.45847
8. Kusyk J., Uyar M.U., Ma K., Plishka J., Bertoli G., Boksiner J. AI and game theory based autonomous uav swarm for cybersecurity. In Proceedings of the MILCOM 2019 IEEE Military Communications Conference (MILCOM), Norfolk, VA, USA, 12–14 November 2019. P. 1–6. DOI: 10.1109/MILCOM47813.2019.9020811
9. Lim W.Y.B., Garg S., Xiong Z., Zhang Y., Niyato D., Leung C., Miao C. UAV-Assisted Communication Efficient Federated Learning in the Era of the Artificial Intelligence of Things. IEEE Network. 2021. V. 35, P. 188–195. DOI: 10.1109/MNET.002.2000334
10. Semsch E., Jakob M., Pavlicek D., Pechoucek M. Occlusion-aware multi-UAV surveillance. 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14 2010. V. 1-3. DOI: 10.1145/1838206.1838405
11. New America. Drones and aerial observat http://drones.newamerica.org/primer/ion: new technologies for property rights, human rights and global development. A primer. URL: http://drones.newamerica.org/primer/
12. Yan C., Fu L., Zhang J., Wang J. A comprehensive survey on UAV communication channel modeling. IEEE Access. 2019.V. 4. DOI: 10.1109/ACCESS.2019.2933173
13. Mozaffari M., Saad W., Bennis M., Debbah M. Efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage. IEEE Communications Letters, 2016. V. 20, No. 8. P. 1647–1650. DOI: 10.1109/LCOMM.2016.2578312
14. Bui Chi Tkhan', Marin D.V., Rastorguev V.V. Comparison of attenuation of electromagnetic waves in the millimeter and infrared wave range in hydrometeor and dust. Trudy MAI. 2015. No. 84. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=63128
15. Burenko E.A. Substantiation of the effectiveness of the use of signals with orthogonal frequency division multiplexing in aviation radio systems of information transmission. Trudy MAI. 2022. No. 127. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=170344. DOI: 10.34759/trd-2022-127-14
16. Alieva A.D., Guseinova M.V. et al. Issues of attenuation of the inter-electronic electromagnetic impact of the warring parties. Trudy MAI. 2023. No. 133. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=177667
17. Tikhomirov A.V., Omel'yanchuk E.V., Semenova A.Yu., Mikhailov V.Yu. Prediction of radio waves propagation parameters when employing low-lying antennas in conditions of urban development. Trudy MAI. 2017. No. 97. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=87308
18. Yudin V.N., Kamnev E.A. Principles of creation of anti-navigation interference field. Trudy MAI. 2015. No. 83. (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=62310
19. Kakar J.A. UAV communications spectral requirements, MAV and SUAV channel modelling, OFDM waveform parameters, performance and spectrum management. URL: https://vtechworks.lib.vt.edu/server/api/core/bitstreams/a4ec2d22-7a08-40e1-91e9-efbbee7c10f4/conten...
20. El'sgol'ts L.E. Differentsial'nye uravneniya i variatsionnoe ischislenie (Differential equations and calculus of variations). Moscow, Nauka Publ., 1974. 432 p.

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