The political economy of drones

This paper provides a political economy analysis of the evolution of unmanned aerial vehicles (UAV), or ‘drones’ in the USA. Focus is placed on the interplay between the polity and private economic influences, and their impact on the trajectory of political, economic, and military outcomes. We identify the initial formation of the drone industry, trace how the initial relationships between the military and the private sector expanded over time, and discuss present relationships. Understanding the historical evolution of UAV technology, as well as the major players in the industry today, is important for ongoing policy debates regarding the use of drones both domestically and internationally.     

基于灰色关联投影法的空中加油机驻场选址评价

提出了一种基于灰色关联投影法的空中加油机驻场选址评价方法,分析了空中加油机驻场选址影响因素,设计了评价指标体系,并运用熵值理论客观赋权,构建了加权灰色关联决策矩阵。通过比较备选方案与理想方案灰色关联投影角,根据灰色关联投影值对备选方案进行优劣排序。算例分析结果符合现实场站选择条件,说明该方法能够有效解决空中加油机驻场选址问题。     

The view from above: how the Royal Air Force provided a strategic vision for operational intelligence during the Malayan Emergency

It has long been held that the Federation of Malaya’s counter-insurgency campaign during the First Malayan Emergency (1948–60) was determined by the use of intelligence. Special Branch — the Federation’s primary intelligence agency — dominates the prevailing paradigm of how the insurgent threat was tackled. Conversely, the role of the Royal Air Force (RAF) within this paradigm is very limited. Most observers simply dismiss the role of photoreconnaissance or airstrikes as being largely inconsequential to the counter-insurgency effort. This is perhaps understandable: the Emergency was after all a ‘policing action’ and the insurgents were largely hidden under Malaya’s jungle canopy and amongst the Chinese community. However, further scrutiny reveals that the RAF made a much more significant contribution to the intelligence element of the counter-insurgency campaign than previously realised. First, the RAF decided to locate their Advanced Headquarters with the Army’s General Headquarters. This led to the creation of the Land/Air Operations Room, through which intelligence, tasking and resources were coordinated. Moreover, the RAF put its intelligence teams into the field to provide a practical link between local units and theatre-level assets. Second, with the support of the Army, the RAF established at the beginning of the Emergency the Joint Air Photographic Intelligence Board (Far East). This coordinated all photographic intelligence requirements throughout the Emergency, which was then delivered via the Joint Air Photographic Centre (Far East). Hence, via Joint Operations Centre and JAPIB (FE), the RAF provided both the practical means for effective joint intelligence operations at theatre level throughout the Emergency.     

有人机/无人机协同空地攻击效能评估的综合指数模型

研究了未来有人机/无人机协同空地攻击的典型作战模式,然后根据混合编队的作战过程和特点,提出了一种建立有人机/无人机协同空地攻击效能评估的综合指数模型;同时确定了综合指数模型中各分系统和分项能力的评估模型。最后以6种有人机和6种无人机的协同空地攻击效能评估为例计算并检验了模型的可用性。     

基于因子分解和光束法平差从航空序列图像恢复三维结构

从航空序列图像恢复目标三维结构是航空摄影测量的基本问题。针对现有算法中精度与计算量的矛盾,提出一种基于因子分解与光束法平差的新算法。作为因子分解与光束法平差的桥梁,提出基于"R T"模式共线方程的概念,详细推导了其线性化公式。仿真实验和真实图像实验表明,新算法精度高、稳定性好,可应用于航空测绘、虚拟现实、军事侦察等工程实践。     

一种可实现TF/TA2的无人飞行器三维航迹规划方法

从规划空间的有效表达着手对无人飞行器三维航迹规划展开研究,基于地形和威胁提出的飞行器航迹规划方法将航迹规划分为学习阶段和查询阶段,环境信息和飞行器的大部分约束条件结合在路线图的构造过程中,航迹搜索在此路线图中进行并最终实现全部约束条件.试验结果显示,该方法可以实时获得实现TF/TA2的三维航迹.     

遥控式无人机多任务侦察监视/干扰系统技术

军用无人机是高性能信息化武器装备,对提高战场空间感知能力、电子战能力、压制敌防空系统能力、作战生存能力和联合作战能力与主宰战场能力等起重要作用,在未来战争中占突出的地位.主要对无人机的有效载荷系统、数据传输系统、测控控制站、数据处理等可能的技术途径、关键技术、作战使用进行描述.     

空中反恐中保卫目标重要度指标体系研究

空中恐怖袭击具有突然性和随意性的特点,其目的是通过制造恐怖事件引起巨大影响,带来社会恐慌。通过分析空中恐怖袭击对袭击目标选择的特点,剖析其规律性,从而建立空中反恐保卫目标重要度指标体系和保卫目标重要度评价模型,对保卫目标进行科学有效地划定与排序,便于在空中反恐作战中对保卫目标及早进行确定、实施空中警戒范围划定和战斗部署。     

无人动力伞建模及预测控制

建立了无人动力伞6自由度控制模型,依托该模型分析了系统的动力学特性与动态性能,阐述了基于预测控制算法的无人动力伞系统飞行控制律,并在实际飞行条件下,验证飞行控制系统的控制精度。     

OODA-L模式下的智能无人集群作战仿真建模框架

介绍了智能无人集群作战的相关概念,为反映智能无人仿真实体的自主能力和适应能力,提出将学习过程显性化的观察-判断-决策-行动-学习(Observe, Orient, Decide, Act and Learning, OODA-L)模式,并进一步扩展为适用于集群协同的Co-OODA-L模式。在智能无人仿真实体的总体描述上,采用马尔可夫决策过程进行数学抽象处理,提出智能无人Agent的三域分层结构。为体现智能无人集群作战的自主协同、分布式等特点,提出了利用人工神经网络将可变数量的智能无人Agent融合为同构或异构集群进行协同作战建模的体系结构。