Laser-based Drone Vision Disruption

The capabilities of drones are increasing every day, followed by how easy it is for civilians to buy and fly drones. Most drones are equipped with a camera that is used as a point-of-view operator and, at the same time, can be used for image capture. A drone's use was also followed by a threat to privacy whereby anyone who can fly a drone can take pictures without permission. This study aims to create a 2-axis tracker system that can recognize drones and locate the position of the drone camera so that the laser beam can track and dazzle the drone camera. The depth camera is used to localize the part of the target and is created using the YOLOv5 algorithm as a deep learning detector model. Due to its small size, the drone camera is challenging to detect and calculate the detection range. The adaptive detection method approach combines drone detection and drone camera detection. The depth camera provides input in the form of a three-coordinate axis from the target. If only a drone is detected, the camera's predictive algorithm is used to determine its position and illuminate it with a laser. On the other hand, if the drone camera is detected, the laser can follow the target's movement more quickly. The green laser module with adjustable power is used in this study, and the dazzling range will be analyzed in detail. The computer vision detection algorithm can detect and localize the position of the drone camera up to 5 m with a confidence level of more than 0.7. If the target detection is in the center of the field of view, the accuracy of the target position can reach 98%. The tracker can follow the drone's movement from 2 m/s – 4 m/s with a maximum error of 1.9 cm from the center point of the drone camera for close range. For long range, the maximum error is 6.2 cm. The wavelength of a 520 nm green laser module with a power of 50mW can dazzle drone cameras.