• 제목/요약/키워드: Military training

검색결과 439건 처리시간 0.034초

차기 군 위성통신체계 OMS/MP 분석 및 운용개념으로부터의 RAM 목표값 산출 제안 (A Proposal on Analyzing Operational Mission Summary/Mission Profile and RAM Goal Setting from Operational Concepts on the Next-MILSATCOM)

  • 박흥순;권태욱;이철화;박대현
    • 한국군사과학기술학회지
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    • 제16권3호
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    • pp.295-303
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    • 2013
  • The Operational Mode Summary/Mission Profile(OMS/MP) is a document which describes how a system or training device will be used in wartime and/or peacetime at the time it is field with focus on the future. OMS/MP is also typically used for the RAM goal setting in an early phase of weapon system development. This paper provides OMS/MP and RAM goal of the Next-MILSATCOM which is following military satellite system after ANASIS. We propose operational concepts, user-side OMS/MP model and RAM goal.

M & S 신용성 향상을 위한 VV & A 적용 모델 (VV & A Application for the Assurance of Defense M & S Credibility)

  • 최상영
    • 한국군사과학기술학회지
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    • 제9권1호
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    • pp.60-71
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    • 2006
  • With the increased reliance on M & S(Modeling & Simulation) in military training, defense analysis, and system acquisition. The credibility of M & S becomes even more critical issue in the M & S application community. In this paper, we have introduced the VV & A(Verification, Validation and Accreditation) concept of M & S for the assurance of its credibility, and proposed the VV & A model applicable to a military simulator development with the illustrative example of MSAM(Medium range-Surface to Air Missile) system simulator.

공개된 토지피복도를 활용한 위성영상 분류 (Image Classification for Military Application using Public Landcover Map)

  • 홍우용;박완용;송현승;정철훈;어양담;김성준
    • 한국군사과학기술학회지
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    • 제13권1호
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    • pp.147-155
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    • 2010
  • Landcover information of access-denied area was extracted from low-medium and high resolution satellite image. Training for supervised classification was performed to refer visually by landcover map which is made and distributed from The Ministry of Environment. The classification result was compared by relating data of FACC land classification system. As we rasterize digital military map with same pixel size of satellite classification, the accuracy test was performed by image to image method. In vegetation case, ancillary data such as NDVI and image for seasons are going to improve accuracy. FACC code of FDB need to recognize the properties which can be automated.

공산오차를 고려한 국내 포병사격장 안전기준 분석 연구 (A Study on Safety Standards for the Interior of an Artillery Firing Range Considering Probable Error)

  • 김주희;성기은
    • 한국군사과학기술학회지
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    • 제26권2호
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    • pp.139-148
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    • 2023
  • Safety standards for long-range artillery ammunition test and training sites follow the US artillery shooting range safety zone standards. Although the South Korean geographical conditions of shooting ranges are different from those of the United States, there is no safety standard reflecting the South Korean topographical characteristics. Probable error associated with the shooting range, trajectory should be considered in establishing the safety standards. In this study, we present the safety standards for the ammunition testing site suitable for the Korean situation, with applying a concept of trajectory and probable error differed by ammunition type, which are currently confirmed by the South Korean Army's artillery shooting.

적록색맹 모사 영상 데이터를 이용한 딥러닝 기반의 위장군인 객체 인식 성능 향상 (Performance Improvement of a Deep Learning-based Object Recognition using Imitated Red-green Color Blindness of Camouflaged Soldier Images)

  • 최근하
    • 한국군사과학기술학회지
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    • 제23권2호
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    • pp.139-146
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    • 2020
  • The camouflage pattern was difficult to distinguish from the surrounding background, so it was difficult to classify the object and the background image when the color image is used as the training data of deep-learning. In this paper, we proposed a red-green color blindness image transformation method using the principle that people of red-green blindness distinguish green color better than ordinary people. Experimental results show that the camouflage soldier's recognition performance improved by proposed a deep learning model of the ensemble technique using the imitated red-green-blind image data and the original color image data.

국방 표준화 정책 로드맵에 관한 연구 (A Study on the Defense Standardization Policy Roadmap)

  • 김진철;최석철
    • 한국군사과학기술학회지
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    • 제11권1호
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    • pp.33-42
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    • 2008
  • Many advanced countries including the U.S. consider defense standardization as a critical task for the efficient acquisition and effective operation of weapon systems and have implemented the appropriate standardization policy by synchronizing the defense acquisition strategies and nation standardization policy with defense standardization. It is required to develop the long-term defense standardization policy that can cope with the future domestic and international defense environmental changes. Therefore, it is an inevitable task to investigate the standardization trends and strategy in the domestic and international perspectives. The study aims to provide the vision of defense standardization policy, act/regulation, organization/personnel, education/training and information system.

효율적인 트래픽 처리를 위한 능동 메커니즘 응용 방안 (Active Mechanism for Efficient Traffic Processing)

  • 이직수;이원구;이성현;이재광
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2004년도 춘계 종합학술대회 논문집
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    • pp.429-433
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    • 2004
  • 컴퓨터 시뮬레이션을 통해 실제 전투 자산을 가동하지 않고 실전과 같은 전투경험을 부여하기 위해서는 데이터베이스를 포함한 페더레이트(federate)간의 연동(federation)이 네트워크상에서 잘 수행되어야 한다. 이에 본 논문에서는 전장 데이터(이하 액티브 패킷)의 신속한 전달을 필요로 하는 실제상황과 유사한 전장공간을 구축할 수 있도록 액티브 네트워크 상에서 페더레이트(혹은 액티브 노드) 간의 효율적인 트래픽 처리가 가능한 가상 전장 환경을 구성하고, 이에 대한 유효성을 모의 실험을 통하여 검증하였다.

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모델 변환기를 이용한 전투 21과 K1 전차 시뮬레이터의 연동 방안 (Interoperability between Combat 21 and K1 Tank Simulators using a Converter)

  • 고성길;이태억;김대규;최미선
    • 한국군사과학기술학회지
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    • 제13권5호
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    • pp.841-851
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    • 2010
  • We examine interoperability for integrated training simulation of a mechanized infantry battalion that uses a war game model of Korean army, Combat 21, and virtual simulators of K1 tanks. We discuss issues and problems for integrated simulation of the virtual and constructive models, including differences between the model scopes, model resolutions, engagement algorithms, and data consistency and training audiences of the war game model and virtual simulators. From these, we identify interoperability requirements. We propose ways of resolving the problems using a model converter.

전이학습을 활용한 군집제어용 강화학습의 효율 향상 방안에 관한 연구 (Study on Enhancing Training Efficiency of MARL for Swarm Using Transfer Learning)

  • 이슬기;김권일;윤석민
    • 한국군사과학기술학회지
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    • 제26권4호
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    • pp.361-370
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    • 2023
  • Swarm has recently become a critical component of offensive and defensive systems. Multi-agent reinforcement learning(MARL) empowers swarm systems to handle a wide range of scenarios. However, the main challenge lies in MARL's scalability issue - as the number of agents increases, the performance of the learning decreases. In this study, transfer learning is applied to advanced MARL algorithm to resolve the scalability issue. Validation results show that the training efficiency has significantly improved, reducing computational time by 31 %.