一种小子样情况下的弹道一致性评定方法

doi:10.3969/j.issn.1000-1093.2014.12.028

兵工学报 ›› 2014, Vol. 35 ›› Issue (12): 2124-2128.doi: 10.3969/j.issn.1000-1093.2014.12.028

• 研究简报 • 上一篇

一种小子样情况下的弹道一致性评定方法

张领科¹，赵峰²，余永刚¹

(1.南京理工大学能源与动力工程学院，江苏南京 210094； 2.中国人民解放军63870部队，陕西华阴 714200)

收稿日期:2013-05-13 修回日期:2013-05-13 上线日期:2015-02-06
作者简介:张领科（1978—），男，副研究员
基金资助:
国家自然科学基金项目（51106075）

An Evaluation Method of Ballistic Consistency under Small Sample Circumstance

ZHANG Ling-ke¹, ZHAO Feng², YU Yong-gang¹

(1.School of Energy and Power Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China;2.Unit 63870 of PLA, Huayin 714200, Shaanxi, China)

Received:2013-05-13 Revised:2013-05-13 Online:2015-02-06

摘要/Abstract

摘要： 为在小样本情况下进行弹道一致性的评定，基于正态分布小样本相容性理论给出一种弹道一致性评定方法。该方法主要通过将计算的顺序统计量与计算机模拟的临界值进行比较判定。主要优点是不需计算位置-尺度估计值，从而减小由于样本容量小而带来的计算误差。通过算例分析表明：在样本数量较少(n≤5)的情况下，该方法与常规的配对t检验法和概率圆序贯检验法相比，都具有一定的优势。

关键词: 兵器科学与技术, 弹道试验, 弹道一致性, 小样本, 相容性, 评定方法

Abstract: In order to evaluate ballistic consistency under small sample circumstance, an evaluation method of ballistic consistency is proposed based on the normal distribution small sample compatibility theory. This method is to compare the calculated order statistics and the simulated critical value to determine the ballistic consistency. The main advantage is not necessary to calculate the position- scale estimate value, so it could decrease the calculation error due to small sample size. The calculation shows that this method is better than matched pair t test and probability circle sequential test under small sample circumstance (n≤5).

Key words: ordnance science and technology, ballistic test, ballistic consistency, small sample size, compatibility, evaluation method

中图分类号:

TJ012.36

张领科，赵峰，余永刚. 一种小子样情况下的弹道一致性评定方法[J]. 兵工学报, 2014, 35(12): 2124-2128.

ZHANG Ling-ke, ZHAO Feng, YU Yong-gang. An Evaluation Method of Ballistic Consistency under Small Sample Circumstance[J]. Acta Armamentarii, 2014, 35(12): 2124-2128.

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一种小子样情况下的弹道一致性评定方法

An Evaluation Method of Ballistic Consistency under Small Sample Circumstance

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