编队辐射源威胁估计研究

针对编队辐射源威胁估计结果在用途上的不同要求,以编队辐射源识别过程为依据,提出了便于编队指挥员把握战场电磁态势的宏观辐射源威胁等级划分方法,并以此为基础,利用多属性决策理论研究了微观编队辐射源威胁系数的计算方法,并以编队电子对抗中的融合识别为例给出了仿真实例。实例表明,该方法可实现编队辐射源威胁估计结果在宏观与微观使用上的统一。     

基于目标威胁规则的雷达情报按需分发

针对预警监视网络中信息过载的问题,为了提高情报分发的效率,提出了基于目标威胁规则的情报按需分发方法。依据目标特征以及保卫对象,利用模糊综合决策和层次分析法估计目标威胁值,在此基础上,通过设定阈值过滤,并与用户作战需求模型动态匹配,最终将所得到的目标情报信息分发给特定情报用户。仿真表明,该方法能够有效地实现情报的按需分发。     

IAHP和熵权相结合的TOPSIS法的空战目标威胁评估

针对空战目标威胁评估问题,提出了一种新的基于改进TOPSIS法的评估方法.该方法综合考虑了主观和客观因素,将运用区间层次分析法(Interval-based AHP,IAHP)求解出的威胁评估指标主观权重与运用熵权法求解出的威胁评估指标客观权重相融合得到组合权重.建立了改进的TOPSIS法评估空战目标威胁的数学模型.最后给出了评估实例,评估结果表明该方法是合理有效的.     

结合离差最大化的多属性群体决策TOPSIS威胁评估

针对传统理想解逼近排序法(TOPSIS)在确定多个属性权重系数上存在主观性和盲目性,并且所作决策多为单一决策,精确度不高等问题,提出结合离差最大化原理的多属性群体决策TOPSIS改进模型,利用离差最大化原理确定属性权值,同时引进群体决策方法。最后将该模型运用于机群协同空战的威胁评估中,建立了多目标威胁评估数学模型,并进行了全空战过程的动态仿真分析,结果表明所建立的扩展模型是合理可行的。     

坦克火力运用智能系统目标威胁度评估模块

随着科学技术的发展,未来战争将有更多的智能化武器出现,坦克火力运用智能化将是坦克火力系统的发展方向,而目标威胁度评估是该系统的核心模块.应用BP神经网络建立了坦克目标威胁度评估模型,对影响因素进行了分析与预处理,并构造了3组训练样本.利用MATLAB7.0中神经网络工具箱的图形用户界面GUI对样本和影响因素进行训练、仿真.结果表明,BP神经网络模型能很好地解决坦克目标威胁程度与影响因素之间的非线性关系,评估坦克目标威胁度有很强的客观性和科学性,对未来坦克火力运用智能系统的建设具有一定的借鉴作用.     

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。     

基于Vague集极值记分函数的装甲分队目标威胁评估

为了快速准确地对装甲分队作战单元面临的目标进行威胁度判断,提高信息化装甲分队作战辅助决策水平,建立了基于Vague集的极值记分函数评估模型,且构造了适合威胁评估的记分函数。实例分析表明,该模型可有效地完成目标威胁评估与排序,为分队火力优化控制提供重要数据支持。     

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.