Exploiting Arma 3 to Construct Synthetic Data for Military Target Detection on Remote Sensing Imagery

Yechan Kim, JongHyun Park, SooYeon Kim, Sihyun Kim, Sung Heon Kim, YeongMin Ko, Junggyun Oh, Dongho Yoon, Moongu Jeon

http://doi.org/10.5626/JOK.2025.52.1.9

Recently, satellite-based surveillance and reconnaissance systems have garnered significant attention in the military sector. However, the acquisition of large-scale satellite imagery for training military target detection models presents practical challenges, primarily due to high costs and security concerns. To tackle this issue, this paper proposes an algorithm for generating synthetic satellite imagery and annotations for military target detection using Arma 3, a well-known military simulation game. Arma 3 offers realistic military equipment and environments, which facilitates the creation of high-quality synthetic data. This study specifically validates the proposed method by demonstrating that our synthetic dataset can effectively complement real-world data, utilizing the DOTA dataset and web-scraped military images.