• Title/Summary/Keyword: Pk(Probability of Kill)

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A Study on Pk(Probability of Kill) Calculation Method of the Direct Fire Weapon System using ANN (인공신경망을 적용한 직사화기 무기체계의 살상확률(Pk) 산출방법론 연구)

  • Jang, Young Cheon;Han, Hyun Jin;Lee, Ki Teak;Song, Mi Jin;Lee, Hwi Yeong;Kim, Jong Heon
    • Journal of the Korea Society for Simulation
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    • v.28 no.1
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    • pp.99-107
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    • 2019
  • Until now it has had the limitation of the target in the US JMEM to calculate the Pk with the existing method by our study. In this study, we focused on deriving a method to calculate the Pk of the actual targets except JMEM targets using ANN. We study the initial predictive model of ANN(Artificial Neural Network) from the targets data of the specification and the vulnerable area in the US JMEM(Joint Munitions Effectiveness Manuals), and calculate the actual targets vulnerable area by using this method. Finally, we propose a method to calculate the Pk by applying those data to the existing method of us.

A Study on Generating Meta-Model to Calculate Weapon Effectiveness Index for a Direct Fire Weapon System (직사화기 무기체계의 무기효과지수 계산을 위한 메타모델 생성방법 연구)

  • Rhie, Ye Lim;Lee, Sangjin;Oh, Hyun-Shik
    • Journal of the Korea Society for Simulation
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    • v.30 no.2
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    • pp.23-31
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    • 2021
  • Defense M&S(Modeling & Simulation) requires weapon effectiveness index which indicates Ph(Probability of hit) and Pk(Probability of kill) values on various impact and environmental conditions. The index is usually produced by JMEM(Joint Munition Effectiveness Manual) development process, which calculates Pk based on the impact condition and circular error probable. This approach requires experts to manually adjust the index to consider the environmental factors such as terrain, atmosphere, and obstacles. To reduce expert's involvement, this paper proposes a meta-model based method to produce weapon effectiveness index. The method considers the effects of environmental factors during calculating a munition's trajectory by utilizing high-resolution weapon system models. Based on the result of Monte-Carlo simulation, logistic regression model and Gaussian Process Regression(GPR) model is respectively developed to predict Ph and Pk values of unobserved conditions. The suggested method will help M&S users to produce weapon effectiveness index more efficiently.

A Study on Pk(Probability of Kill) Calculation Method of the Direct Fire Weapon System using Simulation (시뮬레이션 기반 직사화기 무기체계의 살상확률 산정 방법에 관한 연구)

  • Choi, Yun Ho;Lee, Ki Teak;Pyun, Jai Jeong;Jang, Young Cheon
    • Journal of the Korea Society for Simulation
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    • v.26 no.3
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    • pp.115-123
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    • 2017
  • Dispite the fact that our military has outwardly made notable accomplishments such as the development of weapon systems like tanks, self-propelled artillery, and missiles, there has been a lack of attention to producing weapon effectiveness data that suggests a standard as to what effects the developed weapons will demonstrate on the battlefield. For such reasons, most of the weapon effectiveness data utilizes JMEM data introduced by the United States and as for the rest of the data that cannot be acquired, respective branches create and utilize their own data through research. This research aims to develop a reliable methodology that can meet the requirements of the requesting branches in a short span of time and at a low cost by studying the existing weapon effectiveness data production methodologies such as that of JMEM. As a result I have developed a method that calculates the vulnerable area and the probability of kill of the weapon system that one wants to calculate by applying statistical technique and simulation technique based on weapon effectiveness data of similar weapon systems in JMEM and live test data.