美国国家导弹防御系统

美国国家导弹防御系统已引起了世界的广泛关注。主要阐述该系统的主要组成、功能、特点、进展及系统部署设想     

有源干扰条件下基于NSGA-II的雷达网优化部署方法

雷达网的部署状态直接影响着网络的覆盖能力,尤其是在雷达辐射轨迹受到外力干扰条件下,对网络节点的优化部署更具意义。雷达对部署的任务区域有一定的能量覆盖,不同的任务区也具有不同的重要级别,在不针对特定任务的前提下,实现全方位全纵深的预警能力,雷达网的部署起着至关重要的作用。本文根据覆盖系数和重叠系数为主要优化目标,基于NSGA-II算法进行多目标优化。文章首先定义了覆盖系数和全局重叠系数两个指标,尤其是全局重叠系数打破了以往重叠系数的概念,从全局出发引导雷达网优化部署;同时,提出基于NSGA-II的多目标优化部署算法,采用诱导跳跃、基因到位、诱导交叉等候选解生成方式,保持种群多样性,提高算法收敛性。实验表明,部署优化算法耗时较低,不同干扰源部署态势使网络节点部署产生较大差异,多样的候选解生成方法明显提高了算法的收敛速度。     

选择防空兵群对空侦察配系部署方案的方法研究

部署高效、严密的对空侦察配系,是防空兵群获取空中情报,从而取得作战胜利的重要保障。引用模糊一致性矩阵判别法,对各个部署方案的优劣进行综合比较,从中选择最佳方案。     

基于QFD的武器装备使用需求映射方法

针对传统优化方法不能有效考虑部队需求的问题,提出了基于质量功能展开(Quality Function Deployment,QFD)的武器装备使用需求映射方法,给出了部队需求和武器装备性能指标自相关性的处理方法,并使用松弛系数法保证了最优解集的寻求与重点需求的优先实现。结合实例对该方法的实用性和反映部队需求的准确性进行了验证。结果表明:该方法既克服了传统需求分析侧重于论证人员的推理而对实际使用方的需求考虑不足的弊端,又充分体现了"用户"为主的思想。     

The effect of deployment on first‐ and second‐term re‐enlistment in the US active duty force

Why should deployment affect re‐enlistment? In our model, members enter the military with naïve beliefs about deployment and use actual deployment experience to update their beliefs and revise their expected utility of re‐enlisting. Empirically, re‐enlistment is related to the type and number of deployments, consistent with the learning model. Non‐hostile deployment increases first‐term re‐enlistment but hostile deployment has little effect except for the Army, where the effect is positive. Both types increase second‐term re‐enlistment. Interestingly, first‐term members with dependants tend to respond to deployment like second‐term members. In addition, deployment acts directly to affect re‐enlistment, not indirectly through time to promotion.     

ARMY RE‐ENLISTMENT DURING OIF/OEF: BONUSES,DEPLOYMENT, AND STOP‐LOSS

In 2004, stretched by wartime deployments, the US Army countered declining retention by increasing re‐enlistment bonuses and implementing stop‐loss to prevent soldiers from separating at the end of their enlistment. We estimate the effects of bonuses, deployment, and stop‐loss on re‐enlistment between FY 2002 and 2006. We estimate that the baseline propensity to re‐enlist fell by 20%. However, we find that deployed soldiers are more likely to re‐enlist and that the estimated effects of re‐enlistment bonuses are similar to those estimated in peacetime. We evaluate the reasons for our findings, and calculate the cost effectiveness of re‐enlistment bonuses.