• Title/Summary/Keyword: 소부대 전술 훈련

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Application of Augmented Reality Technology to small-unit's field training and Legal System Analysis (증강현실 기술의 소부대 야외 전술훈련 활용 방안 및 법제도에 관한 고찰)

  • Kim, Kyoung Min;Park, Sangjun;Kim, Jee Won;Kim, Hoedong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.7
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    • pp.963-969
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    • 2018
  • According to the dictionary definition Augmented Reality Technology is "an enhanced version of reality where live direct or indirect views of physical real-world environments are augmented with superimposed computer-generated images over a user's view of the real-world, thus enhancing one's current perception of reality". Since civilian property damages, noise and accidents during the field exercise by military or drills so that AR technology are indispensible with small units drills in Army. However because AR technology which Army has adopted are usually use for special units or need separate spaces which costs lots of budgets, those are not fit for small unit drills or tactics in regular Army. In this regards this paper suggests the AR technology which can apply small unit drill field and the efficiency and legal concerns thereof as well.

A Study on Integration between an Entity-based War Game Model and Tank Simulators for Small-Unit Tactical Training (소부대 전술 훈련을 위한 개체기반 워게임 모델과 전차시뮬레이터 연동에 관한 연구)

  • Kim, Moon-Su;Kim, Dae-Kyu;Kwon, Hyog-Lae;Lee, Tae-Eog
    • Journal of the Korea Institute of Military Science and Technology
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    • v.15 no.1
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    • pp.36-45
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    • 2012
  • In this thesis, we propose an integrated simulation method of virtual tank simulators and an entity-based constructive simulation model for small unit tactical training. To do this, we first identify requirements for virtual-constructive integrated simulation in a synthetic environment. We then propose a virtual and constructive interoperation method where individual combat entities of virtual-constructive models are interacting with each others. We develop a method of aggregating individual combat entities into a larger combat unit and disaggregating an unit into entities from time to time. We also present a way of sharing synthetic environment information between the models. Finally, we suggest that for more effective interoperability, virtual and constructive models should be developed by using common combat object models. The proposed interoperation method can be extended to further live-virtual-constructive models.

AR based Field Training System Algorithm for Small Units (증강현실 기반의 소부대 야외 전술훈련체계 알고리즘)

  • Park, Sangjun;Kim, Jee Won;Kim, Kyoung Min;Kim, Hoedong
    • Convergence Security Journal
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    • v.18 no.4
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    • pp.81-87
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    • 2018
  • Military training is being carried out to win the combats through the quick and accurate response exercise for changeable engagement situations on battle fields. However, practically, it is really difficult to do actual fight training. Even though ROK Army is doing effort for practical training in KCTC(Korea army advanced Combat Training Center) supplying such as MILES equipments but a single platoon is able to use KCTC facilities or MILES equipments only 10 days a year. In order to find solution on this problem many researches suggesting AR or VR technology are still on the way. Nevertheless these are not fully covered the training done in the real field. In this regard, this paper proposes how the AR technology algorithm to apply on small units during field training exercise.

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Analysis of scientific military training data using zero-inflated and Hurdle regression (영과잉 및 허들 회귀모형을 이용한 과학화 전투훈련 자료 분석)

  • Kim, Jaeoh;Bang, Sungwan;Kwon, Ojeong
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.6
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    • pp.1511-1520
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    • 2017
  • The purpose of this study is to analyze military combat training data to improve military operation and training methods and verify required military doctrine. We set the number of combat disabled enemies, which the individual combatants make using their weapons, as the response variable regarding offensive operations from scientific military training data of reinforced infantry battalion. Our response variable has more zero observations than would be allowed for by the traditional GLM such as Poisson regression. We used the zero-inflated regression and the hurdle regression for data analysis considering the over-dispersion and excessive zero observation problems. Our result can be utilized as an appropriate reference in order to verify a military doctrine for small units and analysis of various operational and tactical factors.