防空导弹反TBM作战指挥中目标分配关键问题研究

依据防空反导作战理论和目标分配的要求,对防空导弹反TBM作战指挥中目标分配的关键问题进行了研究。分别对威胁排序方法、拦截可行性条件、目标分配原则和目标分配算法进行了分析,提出了一种反TBM作战指挥中目标分配问题的算法,最后讨论了目标分配的评价问题。通过实际应用表明此方法是切实可行的。     

Pakistan’s nuclear weapons: how safe is safe enough? Transparency versus opacity

Due to expanding and increasing religious extremism and terrorism coupled with political instability in Pakistan, most western observers believe that Pakistan's nuclear weapons are not secure and could be taken over by terrorists. This would have adverse implications for the region and for global peace, especially for the security of USA and Europe. This article argues that this perception is based on a flawed understanding and knowledge of how Pakistan's command and control setup has evolved and operates. Pakistan's nuclear weapons are as safe as any other state's nuclear weapons. Pakistan has also been active in supporting and participating in global efforts to improve nuclear safety and security. Over the years, Pakistan has been quite open in sharing information regarding how it is improving its command and control system with western governments as well as scholars. This article argues that the steps Pakistan has taken to secure its nuclear weapons are adequate and that Pakistan would continue to further strengthen these measures; however, it is the expanding religious extremism, terrorism and anti-Americanism in the country which make the international perception of Pakistan extremely negative and then seep into the perception of Pakistan's nuclear weapons safety and security.     

Optimization of steerable sensor network for threat detection

A Markov chain approach to detecting a threat in a given surveillance zone by a network of steerable sensors is presented. The network has a finite number of predetermined states, and transition from one state to another follows a Markov chain. Under the assumption that the threat avoids detection, two game theoretic problems for finding an optimal Markov chain (two surveillance strategies) are formulated: the first maximizes the probability of threat detection for two consecutive detection periods, whereas the second minimizes the average time of detection for the worst‐case threat's trajectory. Both problems are reduced to linear programming, and special techniques are suggested to solve them. For a dynamic environment with moving noise sources, the optimal Markov chain changes at each detection period, and the rate of convergence of the Markov chain to its stationary distribution is analyzed. Both surveillance strategies are tested in numerical experiments and compared one with another. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

反导作战中多TBM威胁评估模型研究

威胁评估模型是反导指挥控制系统中的关键模型之一.在分析和研究反导作战指挥控制问题的基础上,重点对TBM威胁评估的影响因素进行了分析总结;对各级反导指挥控制系统的威胁评估模型中的异同点进行了对比分析.最后结合层次分析法的相关理论给出了战区级反导指控系统威胁评估模型的求解过程.该算法在指控系统仿真应用中取得了较好的效果.对后续反导作战指挥控制问题的研究具有很高的参考价值.     

直觉模糊集在信息融合中的应用

直觉模糊集理论已获得广泛的应用。全面总结了直觉模糊理论在信息融合领域的应用情况。分析了直觉模糊理论的研究现状与研究进展,介绍了在态势估计与威胁评估方面的应用情况,研究了在信息融合第一级处理中应用的基本原理与方法,展望了在信息融合领域各级的应用前景。     

防空导弹作战复杂电磁环境威胁势研究

为了分析和把握防空导弹作战面临的复杂电磁环境(CEME)态势,分析并建立了防空导弹作战CEME威胁模型;提出了防空导弹作战CEME威胁势概念,从态和势两方面深入分析了防空导弹作战CEME威胁势内涵,建立了防空导弹作战CEME威胁势函数模型;提出了基于集对分析(SPA)的防空导弹作战CEME威胁势评估新方法。论文研究对防空导弹作战电磁态势评估和电子对抗进程推演具有非常重要的理论指导意义和军事应用价值。     

基于支持向量机的威胁判断模型

目标威胁判断是防空作战中一项重要内容,在建立目标威胁模型时,首先要挑选特征参数,分析了影响威胁度的若干因素.这里采用Rough理论中知识约简方法选择目标的特征参数;支持向量机是一类新型机器学习方法,由于其出色的学习能力,该技术已成为当前国际机器学习界的研究热点,利用支持向量机建立了威胁判断模型,给出了实例和解决此问题的支持向量机源程序.通过实例与神经网络法的结果进行了比较,结果表明支持向量机比较精确和简单.     

电子作战目标威胁评估方法初探

为了对电子作战目标进行威胁评估,主要立足于电子战环境,分析了电子作战目标威胁评估的内容与作用,并系统深入地研究了当前常用的目标威胁评估方法,对判断敌情及电子对抗作战指挥具有一定的指导意义。     

多因子动态加权威胁估计方法

在分析了以往威胁估计方法不足的基础上,提出了多因子动态加权威胁估计方法,该方法中给出了诸因子新的有作战背景的威胁隶属度函数,并运用层次分析法（ＡＨＰ）计算出权系数,而且随着作战环境的变化可动态调整之。     

采用时序多属性评价方法的空战威胁排序

鉴于空战中威胁目标的多属性及动态变化特点,提出采用时序多属性评价方法来解决空战目标动态威胁排序问题。在建立空战威胁指标体系基础上,采用熵权法确定目标属性权重,并通过指数分布法确定各时刻权重,最后综合依据威胁目标多时刻的属性信息,实现了空战动态威胁排序。仿真结果说明该方法的合理性。