Testing the efficiency of laser technology to destroy the rogue drones
[ 1 ] Computer science, Qatar University, University Street, Doha 3232, Qatar
2020
scientific article
english
- Security threats
- Rogue drones
- Anti-drone systems
- Laser weapon
- Laser attenuation
EN A large body of research shows the increasing numbers of drones attacks despite RF jammer systems and other technologies. This incredible increase in drone attacks means that the existing solutions are not enough to stop it. The objective of the article is to present a study on the combination of a laser beam with an optical focusing system to create a new cannon to crush rogue drones. The experimental method relies on an innovative design incorporating a laser module and groups of optical lenses to focus the power in one point to carbonize any target. Specifically, it is the laser with an adjustable lens position from 477mm to 617mm to focus the laser beam on the desired distant object. We measured the necessary time to burnt acrylic plastic, wood, and hard carton from a distance of 55 metres. It was noticed that the laser efficiency is proportional to the laser power and time the cannon is turned on. Tests on the laser cannon revealed that laser burner technology can destroy illegal drones. However, it was found that the laser is affected by adverse weather conditions, such as fog, rain, and clouds. Apart from that, the frailty of this technique is connected with the stabilizing system requirements, energy, overheating, and the time needed to destroy an object. Regardless of the drawbacks of the technique, the laser is the only solution with high efficiency that can ruin or intercept autonomously programmed drones, as this cannot be achieved by the RF jammer or any other solutions. The procedure can be repeated with new changeables to achieve a postive result, specifically, the use CO2 laser tube with a high-efficiency chiller to increase the laser power.
24.11.2020
31 - 38
CC BY-NC-ND (attribution - noncommercial - no derivatives)
open journal
final published version
24.11.2020
at the time of publication
20
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