复杂环境空地电视遥控制导导弹作战效能仿真

在复杂的背景环境中,如何有效地提高电视遥控制导导弹的抗干扰能力,提取目标信息,从而发现并识别目标,最大可能地提高对目标的作战效能是电视遥控制导导弹发展过程中必须要解决的关键技术。通过对影响电视遥控制导导弹作战效能的背景环境的分析研究,结合仿真计算,给出了各种背景环境下的效能指标,对电视遥控制导导弹的作战使用和设计研制具有指导意义。     

气动弹性影响下高超声速飞行器动力学建模与分析

高超声速飞行器通常采用轻质材料和细长升力体设计,导致受控刚体运动频率与结构振动频率趋于接近,给飞行器制导控制系统设计带来了巨大挑战。基于假设模态下建立了考虑变截面效应的高超声速飞行器自由梁结构动力学模型,对比了横截面梁和变截面梁模态振型和频率;考虑变截面效应后,振型变化较大,同时二、三阶模态频率均变小。给出了耦合气动弹性和飞行动力学的高超声速飞行器运动方程。在典型工况下,对比分析了刚体、常截面梁和变截面梁高超声速飞行器的平衡和动态特征,结果说明:变截面梁在平衡状态下附加攻角更大,系统在平衡点处开环不稳定性更大,同时非最小相位行为基本不变。     

车辆液力机械传动系统建模及动态特性仿真

建立了具有液力传动的履带车辆动力传动系统及整车的仿真模型,对车辆的加速性进行了仿真研究并与试验结果进行了比较,应用该仿真模型,分析了履带车辆换挡过程中发动机与涡轮转速、系统元件转速等的变化规律,结果表明该仿真模型能够方便的应用于车辆的性能分析与预测.     

装甲车辆电传动技术现状、关键技术与发展

介绍了目前世界上装甲车辆电传动发展的现状和趋势,分析了国外相关研究成果,阐述了装甲车辆电传动中的关键技术,并对我国装甲车辆电传动的发展,提供了参考性建议.     

改革装甲装备动用制度势在必行

通过对装甲装备和其它武器装备动用制度的对比分析与探讨,提出了改进装甲新装备动用制度的初步设想。     

What you should know about the vehicle routing problem

In the Vehicle Routing Problem (VRP), the aim is to design a set of m minimum cost vehicle routes through n customer locations, so that each route starts and ends at a common location and some side constraints are satisfied. Common applications arise in newspaper and food delivery, and in milk collection. This article summarizes the main known results for the classical VRP in which only vehicle capacity constraints are present. The article is structured around three main headings: exact algorithms, classical heuristics, and metaheuristics. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于QFD的动能反卫装备体系技术需求分析

动能反卫装备体系涉及技术领域众多,高精尖技术相对集中。利用质量功能展开(QFD)方法,建立了QFD在装备体系需求分析中的质量屋(HOQ)结构,并且将德尔菲和头脑风暴法相结合确定了顾客需求权重,重点分析了QFD在动能反卫装备体系技术需求分析中的需求转换过程,将动能反卫装备体系的作战能力需求转化为装备体系技术需求,得到了动能反卫装备体系关键技术的重要度排序。     

小型电动垂直起降飞行器推进系统性能分析

小型电动垂直起降飞行器的悬停续航性能取决于推进系统的性能。基于电池、电机、电调的质量模型和螺旋桨的推力-功耗关系,利用电池的恒流放电模型建立了垂直起降飞行器的续航时间评估模型,分析了推进系统参数和有效载荷对飞行器续航性能的影响规律,研究结论可用于电动垂直起降飞行器的总体设计和推进系统选型。     

无人机飞行训练资源配置效率的AHP-Arena综合评价方法

为降低传统层次分析法(analytic hierarchy process,AHP)赋权过程主观片面性影响,提出了一种综合AHP与Arena仿真建模技术的无人机训练资源配置效率评价方法。基于飞行训练流程分析,确定了训练资源配置效率影响因素和效率评价指标,建立了层次型综合评价体系,概括了AHP-Arena综合评价步骤。利用Arena建模软件构建训练流程动态仿真系统并验证有效性,采用单变量数值仿真法、均方差决策法完成了影响因素客观赋权,通过线性加权综合法得出综合评价系数,实现资源配置效率评价与方案优选。实例应用说明了该方法的有效性,同时,该方法可推广至其他类似的训练过程中,亦可为其他多因素、多指标评价决策过程提供借鉴。     

Autonomous maneuver decision-making for a UCAV in short-range aerial combat based on an MS-DDQN algorithm

To solve the problem of realizing autonomous aerial combat decision-making for unmanned combat aerial vehicles (UCAVs) rapidly and accurately in an uncertain environment, this paper proposes a decision-making method based on an improved deep reinforcement learning (DRL) algorithm: the multi-step double deep Q-network (MS-DDQN) algorithm. First, a six-degree-of-freedom UCAV model based on an aircraft control system is established on a simulation platform, and the situation assessment functions of the UCAV and its target are established by considering their angles, altitudes, environments, missile attack performances, and UCAV performance. By controlling the flight path angle, roll angle, and flight velocity, 27 common basic actions are designed. On this basis, aiming to overcome the defects of traditional DRL in terms of training speed and convergence speed, the improved MS-DDQN method is introduced to incorporate the final return value into the previous steps. Finally, the pre-training learning model is used as the starting point for the second learning model to simulate the UCAV aerial combat decision-making process based on the basic training method, which helps to shorten the training time and improve the learning efficiency. The improved DRL algorithm significantly accelerates the training speed and estimates the target value more accurately during training, and it can be applied to aerial combat decision-making.