Electro-optical suppression of cameras on autonomous unmanned aerial vehicles with intelligent computer vision systems

This study focuses on countering autonomous unmanned aerial vehicles (UAVs) equipped with intelligent computer vision systems. The subject of the research comprises methods and techniques for countering modern UAVs. The aim is to advance methods for countering UAVs, specifically in the domain of electro-optical suppression of cameras on autonomous UAVs with computer vision systems by employing low-power lasers. The article presents experimental results confirming the feasibility of electro-optically suppressing optical devices using a low-power laser. Furthermore, an assessment is provided of the dazzling effect when a laser beam strikes a camera – capable of recognizing a human in the frame via custom-developed software based on a neural network model from the YOLO family – at various angles. The methodological basis of this research is formed by experiment and measurement. The work employs systems analysis methods. The authors describe the most significant malfunctions occurring during the electro-optical suppression of optical devices that utilize artificial intelligence algorithms. Based on the conducted analysis, a classification of failures during the blinding of cameras on UAVs with intelligent computer vision systems has been developed. A review of low-power laser systems, which can serve as technical means for the electro-optical suppression of autonomous UAVs, is presented. The results obtained in this work may form the basis for research aimed at creating new counter-UAV subsystems within physical protection systems. The scientific novelty of the work lies in its contribution to the development of a scientific and methodological framework for substantiating the physical protection systems of critical facilities, specifically regarding the enhancement of methods and techniques for countering modern unmanned aerial systems based on the application of low-power lasers for the electro-optical suppression of cameras on autonomous UAVs with computer vision systems.