Abstract
The requirements for the air reconnaissance system using unmanned aircraft systems are being studied. Problematic aspects of the air reconnaissance data processing process are analyzed from the point of view of ensuring the required level of operational efficiency and reliability of intelligence information. The possibility of automating the process of detecting aerial reconnaissance objects on video images is being investigated. A software-hardware module for automated detection and recognition of objects of interest is being developed to increase the level of processing efficiency and reliability of air reconnaissance data. Modern models of detection and recognition of objects of interest based on algorithms of the YOLO platform are studied. The software component of the module is being developed using the YOLOv8 algorithm architecture and a set of data formed in the conditions of air reconnaissance. The analysis of the results of experimental studies shows that: the developed model allows to ensure the required level of operational efficiency of video image processing and the reliability of aerial reconnaissance data; practical implementation of the developed model at ground command and control stations is possible without the use of additional computing equipment. The hardware component of the module is being developed using Raspberry Pi components. The analysis of quantitative evaluations of the efficiency of data processing using the developed software and hardware module on board the UAV of the studied class indicate an increase in time delays compared to the implementation at the command-and-control station, but it allows to ensure the required level of reliability. Further scientific research will be aimed at investigating the peculiarities of the implementation of the conceptual foundations of the developed module for various classes of UAV in order to increase the level of processing efficiency and reliability of aerial reconnaissance data.
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