战场环境下无人车辆战术机动路径规划方法

针对不同类型威胁体存在的战场环境中无人车辆战术机动路径规划问题,提出了一种基于威胁代价地图的粒子群优化（Particle Swarm Optimization,PSO）方法。借助极坐标系中关键点的极角进行路径描述,并使用分段3次Hermite插值方法形成光滑路径,将路径规划问题转化为关键点极角的参数优化问题。针对基本PSO（BPSO）算法存在的早熟收敛和后期迭代效率低的缺陷,借鉴以群集方式生活的物种按照不同任务对种群进行分工的机制,提出了一种基于多任务子群协同的改进粒子群优化（Particle Swarm Optimization based on the Multi—tasking Subpopu—lation Cooperation,PSO-MSC）算法。借助该算法的快速收敛和全局寻优特性实现了最优路径规划。实验结果表明：该算法可以快速有效地实现战场环境下无人车辆的战术机动路径规划,且规划路径安全、平滑。     

载人登月软着陆制动段最优制导方法(英文)

提出一种解决软着陆制动段燃料最优制导以及闭环控制的方案.首先使用庞氏极大值原理将制动段燃料最优问题转化为一个初值问题,并使用遗传算法搜索求解;其次为了解决最优制导的闭环控制问题,将最优弹道作为标称弹道,使用RCS系统对轨道面内两个方向误差量进行解耦,分别使用极限环控制.仿真表明,所规划出的燃料最优弹道比阿波罗方案能节约159.7 kg的燃料,而闭环控制系统可以将初始1 000 m的位置误差和5 m/s的速度误差收敛到接近段入口误差要求以内,在闭环控制过程中,燃料消耗不大于87.75 kg,总体燃料消耗节约至少71.95 kg.     

Decommissioning and paramilitary strategy in Northern Ireland: A problem compared

This study examines the problems of paramilitary decommissioning in Northern Ireland. It analyses why decommissioning has become so contentious in the Northern Ireland peace process. Decommissioning, though, is not a unique or intrinsically insurmountable problem. This is demonstrated by highlighting the issue in international context. Three examples of decommissioning in conflict resolution processes are assessed: the Lebanon, El Salvador and Mozambique. These varied examples do supply some limited lessons for Northern Ireland. This study argues that the explanation for the intractability of decommissioning in Northern Ireland resides, to a greater extent, in the tactical and strategic reasoning of the main paramilitary groupings in Northern Ireland. The factors that condition their thinking, however, can be found in the nature of the peace process itself which provides the paramilitiaries with every incentive to retain possession of their weapons.     

Whose Hearts and Whose Minds? The Curious Case of Global Counter-Insurgency

Traditionally regarded as a secondary activity in military thinking and practice, the notion of counter-insurgency (COIN) has undergone a remarkable renaissance. This analysis traces the origins of this renaissance to two distinctive schools: a neo-classical school and a global insurgency school. The global insurgency school critiques neo-classical thought and presents itself as a more sophisticated appreciation of current security problems. An examination of the evolution of these two schools of counter-insurgency reveals how the interplay between them ultimately leaves us with a confused and contradictory understanding of the phenomenon of insurgency and the policies and strategies necessary to combat it.     

The Royal Navy and Mine Warfare, 1868-1914

Britain underestimated the importance of the naval mine in the years leading up to the First World War and entered the conflict unprepared for an extended mine campaign. Traditional interpretations of the mine's position are limited and neglect the broader political and economic factors influencing its development. The mine was a peripheral technology representative of the rapid technological change in the period, and its development was affected by financial constraints, international diplomacy and naval administration. Because of structural impediments, however, and despite significant resources devoted to the weapon, the mine faced obstacles which led to both limited stocks and inadequate plans for use at the opening of the First World War.     

多平台雷达有源干扰资源分配算法

根据现代干扰机特点,建立"多对多"雷达有源干扰资源分配数学模型,结合分配算法的具体应用环境,提出了基于多Agent分布协同拍卖的雷达干扰资源分配算法,实例表明该方法可行。     

时变环境下基于加速寿命试验的产品故障预测方法

针对传统可靠性模型及分析方法无法分析产品在时变环境下可靠性的缺陷,提出了时变环境应力下产品可靠性预测方法.引入比例风险模型描述产品可靠性与工作环境因素的关系,结合加速寿命试验数据,利用极大似然估计确定基准失效率函数及各环境因素协变量回归系数.在假设产品工作环境应力转换时间确定的情况下,建立了时变环境下可靠度分析模型.实例验证了该方法的有效性.     

基于仿真的竞争失效产品步降加速寿命试验优化设计

针对竞争失效产品加速寿命试验存在试验时间长、费用高、效率低的问题,提出了一种基于Monte-Carlo仿真的竞争失效产品步降加速寿命试验优化设计方法.采用Monte-Carlo对步降加速寿命试验进行仿真模拟,以正常使用应力下的p阶分位寿命渐进方差估计最小为目标,以各试验应力水平及对应应力下的试验截尾数作为设计变量,采用MIE理论进行统计分析,建立了基于仿真的竞争失效产品步降加速寿命试验优化设计模型.最后,通过实例分析表明:该方法具有可行性、有效性.     

改进型Voronoi图和动态权值A*算法的无人机航迹规划

针对实际作战环境中的不同威胁等级和不同威胁实体的威胁源,提出了改进型的Voronoi图,并建立了基于改进型Voronoi图的航迹规划空间;基于A*算法的估价函数在不同阶段对指标的敏感度不同,在传统的启发式A*搜索算法基础上提出了动态权值A*搜索算法,提高了航迹搜索的效率,实现了航迹搜索过程快速性和准确性的结合。最后通过Matlab仿真计算出由动态权值A*算法得到的最优航迹,并进行了航迹的平滑处理,仿真表明了该方法的可行性。