Investigation of Visual Disappearance by Intelligent Illumination of Exterior Surfaces of Unmanned Aerial Vehicles

Abstract

Nowadays the elimination of the visual trace is very important, especially for the low altitude unmanned ait vehicles (UAVs) to protect from their enemy targets. For UAVs, which are widely used in both civil aviation and military fields, the issues of being undetected by visual and auditory and radar are have critical importance. For this reason, visual trace destruction has been taken into consideration at this work. For this purpose, the design of the UAV with the intelligent illumination system and disappearance technology in the desired environment has been discussed. For this purpose, a UAV with a weight of 2,5 kg, a wingspan of 1,3 m, a length of 1 m, with a brushless electric motor, mid-range, medium-height, and moderately hovering features has been produced. Lighting system equipment is placed on the fuselage, wing and tail structure of the UAV. Flight tests were carried out by installing the appropriate lighting system in order to give the UAV the ability to disappear. In the application study on the examination of the disappearance of UAV’s by intelligent illumination of the outer surfaces, the design of the Intelligent illumination system and the application of the outer surface lighting were carried out.

Keywords

• UAV
• Visual disappearance
• Flight tests
• Intelligent illumination

References

1. Austin, R. (2010), Unmanned Aircraft Systems. Wiltshire, United Kingdom: Wiley.
2. Avanzini, G. and Giulietti, F. (2013), Maximum Range for Battery-powered Aircraft, Journal of Aircraft, 50(1): 304-307.
3. Barrett, R. and Melkert, J. (2005), UAV Visual Signature Suppression Via Adaptive Materials, Proceedings of SPIE, 5762.
4. Blackwell, H. R., (1964), Contrast Thresholds of the Human Eye, Journal of the Optical Society of America, 36(11). Bo-Wen, W. and Fangb, Y. and Changa, L. (2009), Study on Human Vision Model of the Multi-parameter Correction Factor. Proc. of SPIE, 74-96.
5. Chamaidi, T. (2006), Calibrated Sky Luminance Maps for Daylight Simulation. Technical University Vienna-Continuing Education, Center, Austria.
6. Coban, S. and Oktay, T. (2018). Simultaneous Design of a Small UAV (Unmanned Aerial Vehicle) Flight Control System and Lateral State Space Model. Journal of Aviation , 2(2) , 70-76 .
7. Coban, S. and Oktay, T. (2018). Unmanned Aerial Vehicles (UAVs) According to Engine Type,. Journal of Aviation , 2 (2) , 177-184 .
8. Gordon, J., (1964), Visibility: Optical Properties of Objects and Backgrounds, Applied Optics, 3(5)

9. Gur, O. and Rosen, A. (2009), Optimizing Electric Propulsion Systems for Unmanned Aerial Vehicles, Journal of Aircraft, 46(4), 1340-1353.
10. Hambling, D. (2020), Cloak of Light Makes Drone Invisible. https://www.wired.com/2008/05/ invisible-drone/. [Access date: 15-June-2021]
11. Hsu, Y. and Thomas, L. and Boubacar, K. (2015) Extremely Thin Dielectric Meta Surface for Carpet Cloaking. Progress in Electromagnetics Research, 152, 33–40.
12. Igawa, N. and Hiroshi, N. and Kunio, M. (1999), Sky Luminance Distribution Model for Simulation of Daylit Environment. Proceedings of Building Simulation, Kyoto, Japan, 2, 969-975.
13. Kekec, E.T. and Konar, M. and Yildirim Dalkiran, F. (2020), Realization of Low Cost Useful Variometer Application for Sportive Aviation, Journal of Aviation, 4(1), 79-88.
14. Kekeç, E. T. and Konar, M. (2021). Investigation of Aerodynamic Calculations of Wingsuit Jumps with Fixed Angle of Attack . Journal of Aviation , 5 (1) , 1-8
15. Konar, M. (2020), Simultaneous Determination of Maximum Acceleration and Endurance of Morphing UAV with ABC Algorithm-based Model, Aircraft Engineering and Aerospace Technology, 92(4), 579-586.
16. Konar, M. (2019), Redesign of Morphing UAV’s Winglet using DS Algorithm Based ANFIS Model, Aircraft Engineering and Aerospace Technology, 91(9), 1214-1222.
17. Konar, M. and Turkmen, A. and Oktay T. (2020), Improvement of the Thrust-torque Ratio of an Unmanned Helicopter by using the ABC Algorithm, Aircraft Engineering and Aerospace Technology, 92(8), 1133-1139.
18. Macheret, J. and Teichman, J., and Kraig R., (2011), Conceptual Design of Low-Signature High- Endurance Hybrid-Electric UAV. Institute for Defense Analyses, Alexandria Virginia.
19. Koçkanat S., (2020), Acceleration Harmonics Estimation and elimination with MABC–RLS algorithm: Simulation and Experimental Analyses on Shaking Table, Applied Soft Computing Journal, 92(12).
20. Koçkanat S. and Karaboğa N. (2015), A Novel 2D-ABC Adaptive Filter Algorithm: A Comparative Study, Digital Signal Processing, 40, 140-153.
21. Oktay, T. and Konar, M. and Onay, M. and Aydin, M. and Mohamed, M. A. (2016), Simultaneous Small UAV and Autopilot System Design. Aircraft Engineering and Aerospace Technology, 88(6), 818-834.
22. Traub, L. W. (2011), Range and Endurance Estimates for Battery-powered Aircraft, Journal of Aircraft, 48(2), 703-707.
23. Y. Dalkiran, F. and Gencag, M. S. (2021), Increasing the Stabilization of Unmanned Aerial Vehicle in Global Navigation Satellite System Unavailable Areas, Journal of Aviation, 5(1), 36-44.