Volume 50 Issue 6
Jun.  2024
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LIU H B,SHI X M,QU J B,et al. Design of Bayesian acceptance scheme for missile hit accuracy based on multinomial distribution[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(6):1991-2000 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0516
Citation: LIU H B,SHI X M,QU J B,et al. Design of Bayesian acceptance scheme for missile hit accuracy based on multinomial distribution[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(6):1991-2000 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0516

Design of Bayesian acceptance scheme for missile hit accuracy based on multinomial distribution

doi: 10.13700/j.bh.1001-5965.2022.0516
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  • Corresponding author: E-mail:sxm@nudt.edu.cn
  • Received Date: 20 Jun 2022
  • Accepted Date: 16 Sep 2022
  • Publish Date: 30 Sep 2022
  • The acceptance test of missile hit accuracy is an important step in verifying missile hit performance. Since the existing binomial distribution hit accuracy acceptance test method in GJB3400—1998 makes it difficult to describe the precision performance of the missile, the impact of the point target regions on its combat effectiveness was considered, and the hit accuracy was redefined as follows: The target was not regarded as the whole with the same damage effect but the multi-area target with different damage effects in different areas hit by the missile. In addition, the missile hit accuracy test was represented by a multinomial distribution. At the same time, the Bayesian method and the Dempster-Shafer (D-S) evidence theory could be used in the acceptance test to integrate multi-source prior information, and the Bayesian acceptance scheme design method of missile hit accuracy based on multinomial distribution was proposed. The example results show that compared with the method in GJB3400—1998, this method can test the accuracy performance of missiles from multiple criteria of hitting different important areas, which is beneficial to help users obtain missiles with more reliable hit accuracy and make full use of the prior information of hit accuracy, thus effectively reducing the risk of both sides involving in the acceptance. This study can provide a reference for the identification and acceptance design of missile hit accuracy.

     

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  • [1]
    徐德坤. 弹道导弹命中精度评定方法及其应用研究[D]. 长沙: 国防科学技术大学, 2007.

    XU D K. Ballistic missile hit accuracy evaluation method and its application [D]. Changsha: National University of Defense Technology, 2007 (in Chinese).
    [2]
    中国人民解放军总装备部.对空导弹武器系统制导精度评定方法:GJB3400-1998[S].北京:中国人民解放军总装备部,1998.

    General Armanent Department of the People' s Liberation Army. Guidance accuracy evaluation method of air-to-air missile weapon system: GJB3400-1998 [S]. Beijing: General Armanent Department of the People's Liberation Army, 1998 (in Chinese).
    [3]
    安明东, 伍惊涛. 高炮弹药炸点起爆方式毁伤效能研究[J]. 舰船电子工程, 2021, 41(6): 140-143.

    AN M D, WU J T. Research on the damage effectiveness of burst point initiation way of anti-aircraft gun[J]. Ship Electronic Engineering, 2021, 41(6): 140-143 (in Chinese).
    [4]
    王玮, 王军波, 黄景德. 一个可靠性二次抽样方案的分析及改进[J]. 兵工学报2006, 27(2): 360-362.

    WANG W, WANG J B, HUANG J D. Analysis and improvement of secondary sampling plan of the reliability[J]. Acta Armamentarii, 2006, 27(2): 360-362(in Chinese).
    [5]
    贠来峰, 缪云飞, 王国平, 等一种新的弹药产品密集度计量型抽样检验方法[J]. 弹道学报, 2020, 32(2): 50-55.

    YUN L F, MIAO Y F, WANG G P, et al. A new sampling inspection method of variables for dispersion of ammunition product[J]. Journal of Ballistics, 2020, 32(2): 50-55 (in Chinese).
    [6]
    谭尧, 赵骞, 王文峰, 等. 考虑专家信息的威布尔型产品定时截尾可靠性验收试验方案设计[J]. 系统工程与电子技术, 2022, 44(4): 1409-1416.

    TAN Y, ZHAO Q, WANG W F, et al. Type I censored reliability acceptence test plan for Weibull distributed products by considering expert information[J]. Systems Engineering and Electronics, 2022, 44(4): 1409-1416(in Chinese).
    [7]
    CHEN J W, LI K H, LAM Y. Bayesian single and double variable sampling plans for the Weibull distribution with censoring[J]. European Journal of Operational Research, 2007, 177(2): 1062-1073. doi: 10.1016/j.ejor.2005.11.023
    [8]
    MING Z, ZHANG Y, TAO J, et al. Selection and analysis of the number of Bayes identification tests for binomial distribution[J]. Journal of Systems Engineering and Electronics, 2008, 30(12): 2512-2515.
    [9]
    韩峰, 陆希成, 刘钰, 等. 二项分布中成功概率的贝叶斯序贯检验方法[J]. 航空动力学报, 2013, 28(2): 270-274.

    HAN F, LU X C, LIU Y, et al. Bayesian sequential test method for probability of success of binomial distribution based on posterior probability[J]. Journal of Aerospace Power, 2013, 28(2): 270-274 (in Chinese).
    [10]
    周阳, 李向东, 周兰伟, 等. 弹药对典型钢筋混凝土楼房毁伤评估方法研究[J]. 弹道学报, 2020, 32(4): 46-53.

    ZHOU Y, LI X D, ZHOU L W, et al. Research on assessment method of ammunition damaging typical reinforced concrete building[J]. Journal of Ballistics, 2020, 32(4): 46-53(in Chinese).
    [11]
    胡丽萍, 王和平, 王智慧, 等. 陶瓷复合装甲不同区域抗弹丸穿甲能力试验研究[J]. 弹箭与制导学报, 2010, 30(5): 90-92.

    HU L P, WANG H P, WANG Z H, et al. Experiment on ballistic property of different impact location of ceramic composite armor[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2010, 30(5): 90-92 (in Chinese).
    [12]
    LI K, SHI X M, LI J, et al. Bayesian estimation of ammunition demand based on multinomial distribution[J]. Discrete Dynamics in Nature and Society, 2021, 2021: 1-11.
    [13]
    LIGTVOET R. Exact Bayes factors for the comparison of multinomial distributions[J]. The American Statistician, 2021, 75(1): 7-14. doi: 10.1080/00031305.2019.1575773
    [14]
    MAHZARNIA A, GRABCHAK M, JIANG J C. Estimation of the minimum probability of a multinomial distribution[J]. Journal of Statistical Theory and Practice, 2021, 15(2): 24. doi: 10.1007/s42519-020-00163-y
    [15]
    CHENG Y B, CHEN X H, LI H L, et al. Analysis and comparison of Bayesian methods for measurement uncertainty evaluation[J]. Mathematical Problems in Engineering, 2018, 2018: 7509046.
    [16]
    XIAO N C, LI Y F, WANG Z L, et al. Bayesian reliability estimation for deteriorating systems with limited samples using the maximum entropy approach[J]. Entropy, 2013, 15(12): 5492-5509. doi: 10.3390/e15125492
    [17]
    VILA J P, WAGNER V, NEVEU P. Bayesian nonlinear model selection and neural networks: a conjugate prior approach[J]. IEEE Transactions on Neural Networks, 2000, 11(2): 265-278. doi: 10.1109/72.838999
    [18]
    NAJAR F, BOUGUILA N. Exact fisher information of generalized Dirichlet multinomial distribution for count data modeling[J]. Information Sciences: An International Journal, 2022, 586: 688-703.
    [19]
    ELFADALY F G, GARTHWAITE P H. Eliciting Dirichlet and Connor-Mosimann prior distributions for multinomial models[J]. Test: An Official Journal of the Spanish Society of Statistics and Operations Research, 2013, 22(4): 628-646.
    [20]
    OUIMET F. A precise local limit theorem for the multinomial distribution and some applications[J]. Journal of Statistical Planning and Inference, 2021, 215: 218-233. doi: 10.1016/j.jspi.2021.03.006
    [21]
    DI NARDO E, POLITO F, SCALAS E. A fractional generalization of the dirichlet distribution and related distributions[J]. Fractional Calculus and Applied Analysis, 2021, 24(1): 112-136. doi: 10.1515/fca-2021-0006
    [22]
    DEMIREL A K, ÇELIK H E. Dirichlet distribution and estimation of parameters[J]. Advances and Applications in Statistics, 2018, 53(4): 401-421. doi: 10.17654/AS053040401
    [23]
    郝志鹏, 曾声奎, 郭健彬, 等. 知识与数据融合的可靠性定量模型建模方法[J]. 北京航空航天大学学报, 2016, 42(1): 101-111.

    HAO Z P, ZENG S K, GUO J B, et al. Integrated method of knowledge and data for quantitative reliability modeling[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(1): 101-111(in Chinese).
    [24]
    苏敬, 何华锋, 何耀民, 等. 基于验前信息相容性与一致性的导弹命中精度Bootstrap评估[J]. 电光与控制, 2021, 28(7): 99-102.

    SU J, HE H F, HE Y M, et al. Bootstrap evaluation of missile hit accuracy based on compatibility and consistency of prior information[J]. Electronics Optics & Control, 2021, 28(7): 99-102 (in Chinese).
    [25]
    张忠占. 关于拟合优度检验的EDF统计量的若干评注(英语)[J]. 应用概率统计, 1996, 12(4): 361-368.

    ZHANG Z Z. Some commentaries on EDF statistics for goodness of fit test (English)[J]. Chinese Journal of Applied Probability and Statisties, 1996, 12(4): 361-368(in Chinese).
    [26]
    STARK A, SENETA E A N. Kolmogorov’s defence of Mendelism[J]. Genetics and Molecular Biology, 2011, 34(2): 177-186. doi: 10.1590/S1415-47572011000200002
    [27]
    TANG Y C, ZHENG J C. Generalized Jeffrey’s rule of conditioning and evidence combining rule for a priori probabilistic knowledge in conditional evidence theory[J]. Information Sciences:an International Journal, 2006, 176(11): 1590-1606. doi: 10.1016/j.ins.2005.04.005
    [28]
    ZHU C S, QIN B W, XIAO F Y, et al. A fuzzy preference-based Dempster-Shafer evidence theory for decision fusion[J]. Information Sciences: An International Journal, 2021, 570: 306-322.
    [29]
    孙伟超, 李文海, 李文峰. 融合粗糙集与D-S证据理论的航空装备故障诊断[J]. 北京航空航天大学学报, 2015, 41(10): 1902-1909.

    SUN W C, LI W H, LI W F. Avionic devices fault diagnosis based on fusion method of rough set and D-S theory[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1902-1909 (in Chinese).
    [30]
    WOMACK J M. Computing risk of pyrotechnic devices using lot acceptance testing[J]. Military Operations Research, 2021, 26(3): 65-77.
    [31]
    JOHN M C. An integrated quantitative approach to acceptance testing and related decisions[J]. INCOSE International Symposium, 2019, 29(1): 203-216. doi: 10.1002/j.2334-5837.2019.00598.x
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