某型运载火箭1/5动力学缩比模型设计

缩比模型试验是获取大型运载火箭动特性的一种有效途径,其中一项重要内容是动力学缩比模型设计。本文以某型运载火箭为原型对象,首先根据其结构组成分别推导各部件的相似关系;然后,利用横向刚度和质量相似系数保持一致性,联立形成了运载火箭横向动特性相似关系;同时,考虑实际加工制造条件,分析了横向刚度和质量相似系数的约束;最后,根据上述相似关系和相似系数约束设计了1/5缩比模型,并对该缩比模型的动特性相似进行了有限元数值计算验证。验证结果表明,设计所得1/5缩比模型在动特性方面与原型具有较高的相似性,相关方法能够有效应用于运载火箭的动力学缩比模型设计。     

卫星导航抗干扰最优接收机与相关接收机性能分析

为减小抗干扰接收机硬件实现难度,深入研究单天线卫星导航抗干扰相关接收机的性能,并详细分析其频域响应、信干噪比损耗和相关输出函数。分析表明,抗干扰最优接收机与相关接收机信干噪比损耗随着干扰带宽和干扰强度的增加而增大,随干扰频率与中心频率偏差和噪声带宽的增加而减小。此外,干扰将引起抗干扰接收机匹配与相关输出主峰降低和旁瓣抬高,从而影响接收机捕获、跟踪和多径抑制性能。研究结果将为卫星导航抗干扰接收机的优化设计提供依据。     

基于灰关联分析和粗糙集的通信电台识别方法

通信侦察过程积累了大量电台通信记录,对这些数据进行分析、推理,可以识别电台的数量、装载平台等,为了提高识别正确率,提出了基于灰关联分析和粗糙集的通信电台识别方法。首先,依据粗糙集理论将信息表划分等价类,得到电台航迹;再根据灰关联分析计算雷达航迹和电台航迹的灰关联度,最后按照最大灰关联度原则进行通信电台关联。实验结果表明该方法适用范围更广,在多个平台的运动轨迹交叉且在交叉时刻各有电台通联、同一平台上的多个电台在不同时间通联这两种情况下,均能较好地对电台进行关联。     

周期平稳通信信号时差估计

研究了一种利用信号谱相关特性对周期平稳通信信号进行时差估计的方法。研究表明,谱相关时差估计方法较之经典的广义互相关(GCC)法具有更强的抗干扰能力,在多辐射源环境下,该方法可以无模糊地估计各个辐射源的时差。     

Equivalent accelerated life testing plans for log‐location‐scale distributions

Accelerated life testing (ALT) is widely used to determine the failure time distribution of a product and the associated life‐stress relationship in order to predict the product's reliability under normal operating conditions. Many types of stress loadings such as constant‐stress, step‐stress and cyclic‐stress can be utilized when conducting ALT. Extensive research has been conducted on the analysis of ALT data obtained under a specified stress loading. However, the equivalency of ALT experiments involving different stress loadings has not been investigated. In this article, a log‐location‐scale distribution under Type I censoring is considered in planning ALT. An idea is provided for the equivalency of various ALT plans involving different stress loadings. Based on this idea, general equivalent ALT plans and some special types of equivalent ALT plans are explored. For demonstration, a constant‐stress ALT and a ramp‐stress ALT for miniature lamps are presented and their equivalency is investigated. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

基于饱和信息维的信息资源聚焦的数学模型

运用饱和信息维的增减技术对信息获取子空间进行结构上的剖分,将饱和信息维的"值"的获取分解为"白"与"灰"两部分,用饱和信息维列作为因子列来构造灰色关联空间,用关联序来描述信息之间的相关联程度,得到信息资源聚焦的一种新的数学模型。     

图像质量主客观评价的相关性分析

图像质量的客观评价与人类主观感知之间一定存在必然的联系,并且这些客观评价方法应该取代主观评价。也就是说,这些客观评价方法允许在不征求任何用户意见的基础上,去评价一个给定系统的性能。本文研究了在变化的压缩体制下实施在若干图像上的一套客观测量和主观评价之间的相互关系,并给出了初步的分析结果。     

北斗RDSS系统新体制信号子载波间干扰产生机理与消除方法

为提高新一代北斗无线电测定卫星服务在有限带宽内的信息服务容量,借鉴了正交频分复用的理念,新体制无线电测定卫星服务信号设计采用多个子载波进行信号调制。以往针对多用户的分析主要考虑多址干扰,对载波频偏损耗和伪码损耗单独考虑,这不能解释新体制调制在相同的同步头的情况下其他子载波上信号在当前观测子载波上形成较大相关峰的问题,该问题对信号接收产生较大干扰。本文对该问题产生机理进行了分析,并提出了两种相关干扰的消除方法。     

一种基于灰关联分析的QoS服务选择方法

随着网络中可供选择QoS服务日益增多,在用户请求服务时,为了确保用户获得满足其功能与QoS要求的服务,提出了一种基于灰关联分析的QoS服务选择方法,根据用户对网络服务的QoS需求估计各项QoS指标的主观权重,以用户的偏好感知作为服务选择的约束条件;基于候选服务集合构建候选服务决策矩阵,采用灰关联分析方法从中获得用户QoS满意度最高的服务。仿真和分析表明,该服务选择策略能为服务质量敏感的用户提供有效的满足QoS需求的服务方案。     

Multivariate meta analysis with potentially correlated marketing study results

A univariate meta analysis is often used to summarize various study results on the same research hypothesis concerning an effect of interest. When several marketing studies produce sets of more than one effect, multivariate meta analysis can be conducted. Problems one might have with such a multivariate meta analysis are: (1) Several effects estimated in one model could be correlated to each other but their correlation is seldom published and (2) an estimated effect in one model could be correlated to the corresponding effect in the other model due to similar model specification or the data set partly shared, but their correlation is not known. Situations like (2) happen often in military recruiting studies. We employ a Monte‐Carlo simulation to evaluate how neglecting such potential correlation affects the result of a multivariate meta analysis in terms of Type I, Type II errors, and MSE. Simulation results indicate that such effect is not significant. What matters is rather the size of the variance component due to random error in multivariate effects. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 500–510, 2000.