Improvement of Automated Naval Gun-Alignment Procedure Assisted by AI

Naval guns are essential armaments installed on Republic of Korea Navy combat vessels, requiring the use of the Weapon Alignment Analysis System (WAAS) to correct discrep-ancies between sensors and armaments for engaging in air and sea combat. This paper aims to examine the current procedures of gun alignment and identify the associated challenges, proposing improvements through the application of Artificial Intelligence (AI) technologies. Particularly, the dynamic alignment of naval guns, performed in marine environments, is influenced by the ship's roll and pitch. As such, the task of calculating error values using alignment cameras is subject to inaccuracies dependent on the operator's skill level. Additionally, since operators manually input alignment measurements during the process, delays can lead to further inaccuracies. This paper proposes utilizing computer vision algorithms for image and video processing and deep learning-based AI models to enhance the image processing capabilities of gun alignment cameras. It also suggests an approach to automatically calculate the discrepancies between the actual armaments and their images, enhancing accuracy and efficiency in naval combat operations.