Object prediction and detection of ground-based weapon with an improved YOLO11 approach

Hanyul Ryu, Mingyu Park, Dae-Yeol Kim — Mon, 30 Dec 2024 00:00:00 +0000

The utilization of UAV-based detection technologies in ground weapon system analysis plays a crucial role in supporting real-time tactical decision-making. While previous studies have primarily focused on improving the detection and classification performance of military objects using UAVs, the current study proposes a novel system that not only detects military objects in simulated UAV operational environments but also analyzes the elevation and azimuth angles of detected gun barrels. For object detection, the YOLO11 model was employed in conjunction with the BCEF loss function to enhance detection performance. The proposed system was validated across various environments using synthetically generated images simulating complex battlefield conditions, including rain, challenging terrain, and low-light environments. Even under these adverse conditions, the model demonstrated high detection accuracy and reliability. This study highlights the potential of UAV-based object detection technology as a tactical decision-making support tool, extending its utility from reconnaissance and identification to broader operational roles. Future research need to further evaluate the performance of the proposed model with experimental validation in real-world UAV operational conditions, emphasizing real-time data collection and analysis frameworks.

Exploring the critical factors of depot maintenance on weapon systems in South Korea

Yongdo Hur — Thu, 26 Dec 2024 00:00:00 +0000

Weapon system maintenance is essential for ensuring the operational availability of equipment while enhancing its performance and quality. Depot maintenance, as a core component of national defense logistics, involves the periodic disassembly, repair, and performance enhancement of weapon systems that have reached their endurance limits during the wear-out failure. It is critical for sustaining performance and achieving target operational rates. However, the current depot maintenance strategy in the Korean military primarily relies on the bathtub curve model, which may inadequately reflect variations in failure rates caused by differences in operating environments and sub-component characteristics. In addition, aging maintenance infrastructure and escalating costs of advanced weapon systems pose significant challenges to meeting operational targets. To overcome these limitations, a proactive approach is needed—one that prepares maintenance facilities and support equipment in advance, integrates depot maintenance with performance upgrades, and reduces unnecessary resource consumption. Enhancing the depot maintenance strategy is vital for improving the operational readiness of weapon systems and advancing the expertise of national defense operations. The current study identifies key factors affecting the effectiveness of depot maintenance and presents a research model designed to enhance weapon system operational rates and strengthen defense capabilities. By accurately determining equipment life cycles and incorporating performance improvements, the proposed model offers actionable insights for optimizing depot maintenance strategies in contemporary military operational environment.

Journal of Advances in Military Studies

Object prediction and detection of ground-based weapon with an improved YOLO11 approach

Exploring the critical factors of depot maintenance on weapon systems in South Korea