Improving the Productivity of UAV Operations Based on Granular Computing and Fuzzy Sets

The problem of assessing the quality of equipment of different unmanned aerial vehicles groups types based on fuzzy sets is considered. The growth in the number of unmanned aerial vehicles for various purposes and the expansion of their application in heterogeneous groups raises the question of developing new criteria for the effectiveness of their use. A new approach to increase the productivity of registration and information processing operations by determining the image quality based on the video camera's angle of inclination, altitude and flight speed of the unmanned aerial vehicle is proposed. Since the input information about the state of the scene and data from unmanned aerial vehicle sensors may be incomplete and poorly structured, the article proposes to apply the concept of granular calculations and fuzzy sets to build an air reconnaissance database. A new mathematical model (information granule) is proposed based on fuzzy data on the altitude and speed of flight and the angle of the camera, which allows obtaining a forecast of image quality that can be gotten by unmanned aerial vehicles while traveling along the route.