• The Korean Journal of Air & Space Law and Policy
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• v.35 no.1
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• pp.127-152
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• 2020

Despite growing international cooperation for maintenance of international peace and security, wars continue to occur due to conflicted state interests. Continuing conflicts has advanced development of various weapon systems such as global integrated intelligence, surveillance and reconnaissance. However, with a big increase in the number of civilian casualties caused by the weapon systems development, the international community has also advanced diplomatic efforts to minimize deaths of civilian and military personnel. Therefore, it is essential to observe the principle of discrimination between combatants and non-combatants when operating unmanned aerial vehicles (UAVs), better known as drones. Drones have become more capable of distinguishing combatants from non-combatants due to its high-tech prowess. In the operation of drones, any parties involved in combat or the war are responsible for mounting civilian casualties. In addition, it should comply with the principle of proportionality that calls for a balance between results of such action and expected military advantage anticipated from the attack. The rule of proportionality prohibits use of military force which may be expected to cause excessive civilian harm. Drones have been able to track and monitor targets for hours and select the accurate locations of the targets. The aim is to reduce civilian losses and damage to a minimum. Drones meet the standards of Article 51.4 of the Additional Protocol.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.936-939
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• 2022

As air combat system technologies developed in recent years, the development of air defense systems is required. In the operating concept of the anti-aircraft defense system, selecting an appropriate armament for the target is one of the system's capabilities in efficiently responding to threats using limited anti-aircraft power. Much of the flying threat identification relies on the operator's visual identification. However, there are many limitations in visually discriminating a flying object maneuvering high speed from a distance. In addition, as the demand for unmanned and intelligent weapon systems on the modern battlefield increases, it is essential to develop a technology that automatically identifies and classifies the aircraft instead of the operator's visual identification. Although some examples of weapon system identification with deep learning-based models by collecting video data for tanks and warships have been presented, aerial vehicle identification is still lacking. Therefore, in this paper, we present a model for classifying fighters, helicopters, and drones using a convolutional neural network model and analyze the performance of the presented model.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.41-49
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• 2014

Detection and processing techniques for small objects on seabed by the active synthetic aperture sonar can be increased the detection performance because it can be used by short sensor array in small unmanned underwater systems that are spatially constrained. But the limited conditions on constant speed and straight movement of the platform cause a large error in the number of external environmental factors and exact phase synthesis process. In this study, analyzed the applicability of active synthetic aperture processing that is mounted on such a system, and compared detection resolution change in accordance with the phase difference mismatch caused by the along track disturbance. Various simulations were performed as a coherently focus processing model by adding along track disturbance mismatched parameter on the configuring simulator. As the result, detection performance of active synthetic processing for small objects on seabed was found a number of changes by the phase difference mismatch errors according to track disturbances and S/N ratio variations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.215-222
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• 2017

An active synthetic aperture sonar mounted on small UUV is generated various trajectory disturbances in the traveling path by the influence of external underwater environments. That is the phase mismatch occurs in the synthetic aperture processing of the signals reflected from seabed objects and fetches the detection performance decreases. In this paper, we compensated deteriorated images by the active SAS autofocus processing using DPC and analyzed the effects of detection performance when the periodic trajectory disturbances occur in the side direction at a constant velocity and straight movement of UUV. Through simulations, the deteriorated images according to the periodic disturbance magnitudes and period variations in the platform were compensated using difference phases processing of the overlapping displaced phase centers on the adjacent transmitted ping signals, and we conformed the improved performance characteristics of azimuth resolution and detection images at 3dB reference point.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.409-416
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• 2020

Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

• The Korean Journal of Air & Space Law and Policy
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• v.28 no.2
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• pp.37-61
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• 2013

In modern international law, the absence of legal definition regarding drone(Unmanned Aerial Vehicle) has made legal scholars work on an typical analogy between aircraft codified in the international document and drone. The wording of the Convention on International Civil Aviation is limited to two categories of aircraft, such as civil aircraft and state aircraft, whereas military aircraft is not legally defined. As such it is, the current practices of the State regarding the drone flight over foreign territory have proven a hypothese that drone is being deemed as military aircraft. Principal usage of drone lies in reconnaissance and surveillance mission as well as so-called targeted killing, which is prohibited if the killing is treacherous. Claimed war against terrorism, however, is providing a legal rationale that targeted killing is not treacherous, and that the targeted person is not civilian but combatant. In such context, armed attack of drone is deemed legal and justified. Consequently, such attack is legal in the general context of the war. The rules that govern targeting do not turn on the type of weapon system used, and there is no prohibition under the laws of war on the use of technologically advanced weapons systems in armed conflict so long as they are employed in conformity with applicable laws of war. Drones may present interesting new challenges because of their sophistication and the technological advantage they convey to their operators.