高分辨率雷达目标一维距离像的编码识别算法

文中提出了一种高分辨率雷达目标一维距离像的识别算法。该算法借用图像处理方法,先对雷达目标的一维距离像进行编码,经过傅里叶变换提取一组形状特征。这组特征精确地描述了一维距离像曲线的走向。而后,利用人工神经网络技术对一定姿态角变化范围内的这组形状特征进行识别。实验结果表明,可以获得良好的识别效果。该算法为雷达目标一维距离像识别算法的实时处理提供了一条有效途径。     

跟踪雷达超低空目标捕获距离的精确估算方法

根据比较精确的数学模型,考虑到海情、地球曲率、海水反射特性及极化方式等各种因素影响,对应不同雷达截面积的目标,我们可计算出低仰角时接收机输出信噪比与距离的关系曲线。根据雷达的积累信噪比,可用该曲线比较精确地估算出跟踪雷达对超低空目标的最大捕获距离。     

微型计算机在复合材料强度准则研究中的应用

文中论述了运用微型计算机(IBM-PC)进行复合材料强度准则研究的方法,包括强度包络线绘制、双向加载数据采集及实验数据处理等,同时还研究了如何确定双向试验中的破坏载荷值,并在分析实例中提供了较详细的数据。     

燃烧室前缘扩张角对旋转爆震冲压发动机的影响

针对圆柱形隔离段-燃烧室构型的旋转爆震冲压发动机,开展了总温为860 K、马赫数为2的来流条件下的直连式试验,探讨了燃烧室前缘扩张角(θ=30°,45°,60°,90°)对爆震波传播特性、工况范围及压力分布的影响。结果表明:当燃烧室前缘扩张角为90°时,燃烧模态均为爆燃燃烧;随着扩张角的减小,燃烧模态将会向锯齿波和混合模态(包含单波阶段)转换。当燃烧室前缘扩张角为30°时,旋转爆震的自持工况范围最宽且燃烧室压力最高;同时,随着燃烧室前缘扩张角减小,实现混合模态的当量比下限降低。此外,分析了燃烧模态对来流的影响,发现:锯齿波/混合模态燃烧室内存在的周期性高频压力扰动会使隔离段内的激波串位置前移;混合模态对超声速来流的影响最为显著。     

Controlled warfare: how directed-energy weapons will enable the US Military to fight effectively in an urban environment while minimizing collateral damage

US military operations are increasingly conducted within urban environments and with these operations come the risk of increasing the number of civilian casualties and infrastructure damage. The use of non-lethal weaponry, such as directed-energy weapons, is one method for minimizing collateral damage. This method enables US military forces to effectively fight within urban environments through force escalation capabilities. Using a series of historical examples and future scenarios for urban warfare, this article highlights deficiencies affecting military capabilities in military urban operations, addresses the consequences of collateral damage, assesses the effectiveness of directed-energy weapons in military urban operations and encourages further funding, research and integration of non-lethal weaponry, such as directed-energy weapons, within the US military.     

嵌入式装备测试系统设计研究

针对现代装备测试性需求,利用ARM微处理器构建了基于CAN总线网络的多路嵌入式数据采集系统,介绍了嵌入式数据采集系统硬件组成、硬件模块实现以及软件设计;检测数据经过CAN总线存入SD卡存储器,并进行后期数据的存取和处理．实验结果表明,该系统能够可靠、准确地对多路信号进行采集,实现对火炮装备的检测．     

面向实体的作战行动数据采集系统研究与设计

为满足基地对作战行动数据的实际需求,针对作战行动数据的特点,提出了以作战实体为中心的数据组织方式和作战行动的模板描述方法;运用软件工程技术对系统进行了需求分析和方案设计,并结合主流的web技术构建了系统解决方案。系统能够对训练、演习中的作战行动进行标准化数据描述并记录形成作战行动数据库,为演习评估、裁决等实际应用提供数据支撑。经过长期的数据积累和数据挖掘,能够对部队的作战行动进行合理的评价与预测,为建立长效的数据采集、使用机制提供保障。     

The rising unit cost of defence equipment — The reasons and the results

This paper constructs a conceptual model for the selection of defence equipment providing best value for money. It then shows how the unit cost of the chosen equipment increases between one generation of equipment and its successor because of developments in the perceived threat, the available technology and industrial productivity, and demonstrates that unit cost increases can arise from a logical and rational procurement policy and are not necessarily caused by technological chimeras and military vainglory. The resulting persistent rise in unit cost is unlikely to be significantly slowed by any of the counter‐measures yet proposed.

The paper then discusses the policies which nations have adopted to accommodate past increases in unit cost, and the options which confront any nation at the point when it can no longer afford to re‐equip a particular element of its armed forces.     

近程舰炮武器系统拦截高速目标发展研究

反舰导弹的超声速特性使得现役近程舰炮武器系统的反应时间严重不足,毁伤能力明显下降.针对高速目标,分析了目标对系统的随动性能需求,研究了系统情报处理、传感器捕获跟踪及火控解算等时间特征参数、及系统毁伤能力,并提出了解决问题的初步想法.分析结果表明,可以提高近程舰炮武器系统对超高声速目标的跟踪毁伤能力,实现对该类目标的有效拦截.     

3D laser scanning strategy based on cascaded deep neural network

A 3D laser scanning strategy based on cascaded deep neural network is proposed for the scanning system converted from 2D Lidar with a pitching motion device. The strategy is aimed at moving target detection and monitoring. Combining the device characteristics, the strategy first proposes a cascaded deep neural network, which inputs 2D point cloud, color image and pitching angle. The outputs are target distance and speed classification. And the cross-entropy loss function of network is modified by using focal loss and uniform distribution to improve the recognition accuracy. Then a pitching range and speed model are proposed to determine pitching motion parameters. Finally, the adaptive scanning is realized by integral separate speed PID. The experimental results show that the accuracies of the improved network target detection box, distance and speed classification are 90.17%, 96.87% and 96.97%, respectively. The average speed error of the improved PID is 0.4239°/s, and the average strategy execution time is 0.1521 s. The range and speed model can effectively reduce the collection of useless information and the deformation of the target point cloud. Conclusively, the experimental of overall scanning strategy show that it can improve target point cloud integrity and density while ensuring the capture of target.