Dirichlet分布的导弹命中精度贝叶斯估计
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1.海军工程大学 管理工程与装备经济系;2.海军工程大学管理工程与装备经济系;3.陆军工程大学石家庄校区

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E927

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国家自然科学基金项目(71501183)


Bayesian estimation of missile hit accuracy for Dirichlet distribution
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    摘要:

    基于弹着点空间分布对目标毁伤效能的差异化影响,构建导弹命中目标不同重要区域的概率分布模型,实现对传统命中精度概念的扩展。并针对导弹实打试验过程复杂、费用高、次数少的实际,采用贝叶斯方法融合多源信息,基于区域划分-分布确定-先验融合-后验求解的思路进行导弹命中精度估计。选取Dirichlet 分布作为命中精度参数的先验分布,运用Dempster-Shafer (D-S)证据理论对先验信息进行融合处理,基于马尔科夫链-蒙特卡洛 (Markov chain-Monte Carlo, MCMC) 方法对精度参数的后验分布进行求解。示例表明,该方法能够细致描述导弹命中目标不同重要区域的概率,并科学融合多源命中精度先验信息,为导弹命中精度估计方法及测试方案优化提供理论借鉴。

    Abstract:

    Based on the differential impact of the spatial distribution of impact points on target damage effectiveness, the probability distribution model of missile hitting different important areas of target was constructed to realize expansion of the traditional hit accuracy concept. Aimed at the reality of actual missile hitting targets with complex process, high cost and low frequency, Bayesian method was used to fuse multi-source information, and missile hit accuracy was estimated based on the idea of region division, distribution determination, prior fusion and posterior solution. The Dirichlet distribution was selected as the prior distribution of hit accuracy parameters, the Dempster-Shafer (D-S) evidence theory was used to fuse the prior information and the posterior distribution of accuracy parameters was solved by Markov chain-Monte Carlo (MCMC) method. Example results show that this method can describe the probability of missile hitting different important areas of the target in detail, and scientifically integrate multiple types of prior information about hit accuracy, which provides theoretical references for missile hit accuracy estimation methods and test schemes optimization.

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历史
  • 收稿日期:2023-02-13
  • 最后修改日期:2025-04-01
  • 录用日期:2023-11-02
  • 在线发布日期: 2025-04-03
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