• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.152-163
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• 2022

In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.113-120
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• 2023

The purpose of this study was the accuracy of cardiac compression, fatigue, and physiological changes of the rescuer for different mask type in cardiopulmonary resuscitation(CPR). Data collection was from 9 to 12 May 2022, the participants were a total of 24 paramedic students with a BLS provider at D University. The students participated in an experiment in which 12 students each wore a surgical mask (Dental mask) and a fine particle 94% blocking mask (KF94 mask) and performed CPR for 2 minutes over a total of 7 times. As a result of the study, in the analysis of the quality of the rescuer's chest compression according to the type of mask, there was a significant difference in the compression speed (F=24.91, p<.001) and bad compression hand position (F=14.54, p=.024) in the group wearing the KF94, Fatigue showed significant differences in both the Dental mask group (F=51.16, p<.001) and the KF94 mask group (F=63.49, p<.001). Among the physiological changes, heart rate showed a significant difference between the Dental mask group (F=34.79, p<.001) and the KF94 mask group (F=35.55, p<.001), and the respiratory rate showed a significant difference between the Dental mask group (F=25.02, p=.001) and the KF94 mask group(F=23.02, p=.002). Therefore, in order to improve the quality of efficient chest compression and reduce the fatigue and physiological changes of rescuers, it will be necessary for rescuers to wear suitable personal protective equipment.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.214-224
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• 2024

Sonobuoys are disposable devices that utilize sound waves for information gathering, detecting engine noises, and capturing various acoustic characteristics. They play a crucial role in accurately detecting underwater targets, making them effective detection systems in anti-submarine warfare. Existing sonobuoy deployment methods in multistatic systems often rely on fixed patterns or heuristic-based rules, lacking efficiency in terms of the number of sonobuoys deployed and operational time due to the unpredictable mobility of the underwater targets. Thus, this paper proposes an optimal sonobuoy placement strategy for Unmanned Aerial Vehicles (UAVs) to overcome the limitations of conventional sonobuoy deployment methods. The proposed approach utilizes reinforcement learning in a simulation-based experimental environment that considers the movements of the underwater targets. The Unity ML-Agents framework is employed, and the Proximal Policy Optimization (PPO) algorithm is utilized for UAV learning in a virtual operational environment with real-time interactions. The reward function is designed to consider the number of sonobuoys deployed and the cost associated with sound sources and receivers, enabling effective learning. The proposed reinforcement learning-based deployment strategy compared to the conventional sonobuoy deployment methods in the same experimental environment demonstrates superior performance in terms of detection success rate, deployed sonobuoy count, and operational time.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.197-204
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• 2011

The authors adopt the Unmanned Undersea Vehicle(UUV), the shape of which is like a manta. They call here it Manta UUV. Manta UUV has been designed from the similar concept of the UUV called Manta Test Vehicle(MTV), which was originally built by the Naval Undersea Warfare Center of USA(Lisiewicz and French, 2000; Simalis et al., 2001; U.S. Navy, 2004). The present study deals with the effect of Reynolds numbers on hydrodynamic forces acting on Manta UUV at large angles of attack. The large angles of attack cover the whole range of 0 to ${\pm}$ 180 degrees in horizontal plane and in vertical plane respectively. Static test at large attack angles has been carried out with two Manta UUV models in circulating water channel. The authors assume that the experimental results of hydrodynamic forces (lateral force, yaw moment, vertical force and pitch moment) are analyzed into two components, which are lift force component and cross-flow drag component. First of all, Based on two dimensional cross-flow drag coefficient at 90 degrees of attack angle, the cross-flow drag component at whole range of attack angles is calculated. Then the remainder is assumed to be the lift force component. The only cross-flow drag component is assumed to be subject to Reynolds number.entstly the authors suggest the methodology to predict hydrodynamic derivertives acting on the full-scale Manta UUV.

• Journal of Korea Technology Innovation Society
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• v.18 no.2
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• pp.292-317
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• 2015

As modern science and technology and warfare become to be advanced and precise, the weapon systems becomes more complex based on state-of-the-art technology. Therefore, firms in the defense industry continue to accelerate research and development for up-to-date weapon systems with high complexity which urge the firms to collaborate with the external organizations to obtain the knowledge required and eventually to reduce costs and risk. This study tries an empirical study about the effect of collaboration on the innovation performances from the network analysis perspective. By surveying collaboration relationships among 530 firms in the Korean defense industry, we analyzed the alliance network of the defense industry. Network centrality including degree, closeness, and betweenness centralities is investigated and then the relationship among the network centrality property, internal R&D capabilities and innovation is analysed. The results show that firms with high internal R&D capabilities place the firm at center of the network. On the other hand, except for the firms with highly connected centrality, no relationship was found between the internal R&D capabilities and its performance and in turn. these capabilities had both direct and indirect effects on innovation performances through mediated collaboration among firms. This study implied that Korean firms with a high internal R&D capabilities in the defense industry which utilize knowledge, information and resources within the network more frequently show more innovative performance. This result claims the policy makers to participate more firms in fostering open innovation for the defense industry.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.105-117
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• 2020

Analysis of combat effectiveness is required to consider the concept of tactical cooperative engagement between manned-unmanned weapon systems, in order to predict the required operational capabilities of future weapon systems that meets the concept of 'effect-based synchronized operations.' However, analytical methods such as mathematical and statistical models make it difficult to analyze the effects of complex systems under nonlinear warfare. In this paper, we propose a combat simulation model that can simulate the concept of cooperative engagement between manned-unmanned combat entities based on wireless communications. First, we model unmanned combat entities, e.g., unmanned ground vehicles and drones, and manned combat entities, e.g., combatants and artillery, considering the capabilities required by the future ground system. We also simulate tactical behavior in which all entities perform their mission while sharing battlefield situation information through wireless communications. Finally we explore the feasibility of the proposed model by analyzing combat effectiveness such as target acquisition rate, remote control success rate, reconnaissance lead time, survival rate, and enemy's loss rate under a small-unit armor reconnaissance scenario. The proposed model is expected to be used in war-game combat experiments as well as analysis of the effects of manned-unmanned ground weapons.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.26-34
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• 2021

In the era of the Fourth Industrial Revolution, the future battlefield will carry out multi-area operations with hyper-connected, high-speed and mobile systems. In order to prepare for changes in the future, the Korean military intends to develop various weapons systems and form a multi-layer tactical network to support On The Move communication. However, current tactical networks are limited in support of On The Move communications. In other words, the operation of multi-beam antennas is necessary to efficiently construct a multi-layer tactical network in future warfare. Therefore, in this paper, we look at the need for multi-beam antennas through the operational scenario of a multi-layer tactical network. In addition, based on development consideration factors, features of rotary-wing and fixed-wing aircraft, we present the location and operation of airborne relay drone installations of multi-beam antennas.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.1-12
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• 2020

Low-Orbit satellite mobile networks can provide services through miniaturized terminals with low transmission power, which can be used as reliable means of communication in the national public disaster network and defense sector. However, the high traffic environment in the emergency preparedness situation increases the new call blocking probability and the handover failure probability of the satellite network, and the increase of the handover failure probability affects the QoS because low orbit satellites move in orbit at a very high speed. Among the channel allocation methods of satellite communication, the FCA shows relatively better performance in a high traffic environment than DCA and is suitable for emergency preparedness situations, but in order to optimize QoS when traffic increases, the new call blocking and the handover failure must be minimized. In this paper, we propose LEO-DBC (LEO satellite dynamic beam width control) technique, which improves QoS by adaptive adjustment of beam width of low-orbit satellites and call time of terminals by improving FCA-QH method. Through the LEO-DBC technique, it is expected that the QoS of the mobile satellite communication network can be optimally maintained in high traffic environments in emergency preparedness situations.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.