改进蚁群算法在DSR路由协议中的应用

针对移动Ad hoc网络节点移动频繁和单路径DSR路由协议不能均衡负载、网络健壮性低以及蚁群算法存在局部查询最优的问题,提出一种改进的蚁群算法,并把改进的蚁群算法应用到单路径路由协议DSR,设计出基于蚁群算法的多路径路由协议IDSR,通过仿真实验,从影响Ad hoc网络路由协议性能优劣的3个主要指标来比较IDSR、DSR路由协议和SMR路由协议的性能,实验结果表明,虽然改进协议IDSR路由开销比DSR、SMR稍有增加,但分组的投递率和平均端到端延时性能都有明显提高。     

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.     

Optimal path finding in direction,location, and time dependent environments

This article examines optimal path finding problems where cost function and constraints are direction, location, and time dependent. Recent advancements in sensor and data‐processing technology facilitate the collection of detailed real‐time information about the environment surrounding a ground vehicle, an airplane, or a naval vessel. We present a navigation model that makes use of such information. We relax a number of assumptions from existing literature on path‐finding problems and create an accurate, yet tractable, model suitable for implementation for a large class of problems. We present a dynamic programming model which integrates our earlier results for direction‐dependent, time and space homogeneous environment, and consequently, improves its accuracy, efficiency, and run‐time. The proposed path finding model also addresses limited information about the surrounding environment, control‐feasibility of the considered paths, such as sharpest feasible turns a vehicle can make, and computational demands of a time‐dependent environment. To demonstrate the applicability and performance of our path‐finding algorithm, computational experiments for a short‐range ship routing in dynamic wave‐field problem are presented. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

坦克实体智能机动路径模型

根据坦克机动作战的一般原则,首先对影响坦克实体机动的因素进行了分析和合理的假设;充分考虑战术模拟中的实际情况,将数字地图中各点间的空间距离转化为以各点间机动时间为权边的网图,通过求任意两点间的最短距离的方法,建立坦克实体机动最短时间路径的数学模型。并给出了人工智能算法,把问题求解过程简化,从而解决战术模拟系统中智能机动中的路径选择问题。     

基于公共燃气排导结构的共架发射系统武器选择与布局方法

公共燃气排导结构和同心筒结构的共架发射系统由于燃气排导机理不同,其对武器发射的影响及在武器选择、布局等方面均存在较大差异.针对公共燃气排导结构的共架发射系统分析了公共燃气排导对武器发射的影响,提出了武器选择与布局方法,通过算例进行了验证并得出结论:公共燃气排导结构的共架发射系统武器布局上应采取分散布局,武器选择上应优先选择“无发射活动、对应武器数量较多、烧蚀值较小”的模块,且按照模块编号依次交替在不同模块进行武器发射.     

基于核函数的自适应聚类背景提取

随着目标的检测与跟踪的广泛应用,移动物体分割问题成为研究热点,而解决这类问题的关键需为对图像背景的更新和提取。通过对目前已有的背景提取方法的研究,提出了一种新的基于核函数的背景提取方法:进行预处理,制定删选法则来自适应获取所需处理的视频序列;定义核函数来衡量模式间相似性,对2类聚类中心进行初始化;利用最小距离准则来灰度归并,采取实时的自适应阈值选择;最后通过比较满足条件的像素总数,获取所需背景。实验证明,该方法有效。     

基于复杂网络的防空武器系统目标选择研究

基于复杂网络的思想,通过对防空武器目标体系网络的拓扑参数分析,构建了防空武器目标体系网络,利用pajek软件,对网络进行了可视化分析,采用基于不同策略的攻击方式进行了模拟仿真,对仿真结果进行了分析。经过分析发现,基于节点度值和基于节点介数的攻击可以较好的降低网络效率,因此我们以节点度值和介数为主要依据,确定了目标打击顺序,为指挥决策人员进行防空目标选择提供了借鉴和参考。     

一种适用于拦截高速目标的末段导引律

基于在视线坐标系中的导弹-目标相对运动模型,以控制导弹-目标视线角速度趋于零为基本思想,设计了一种末制导律,用于拦截高超声速目标。以脱靶量和能量消耗为约束条件,以目标无机动时有很好的性能为目的,首先设计了最优制导律;然后,基于滑模控制理论,选择合适的滑模趋近律,对所设计的最优制导律进行改进得到最优滑模制导律;用李雅普诺夫理论证明了该制导律的稳定性,分析了该制导律参数选择条件。仿真结果表明,与最优制导律相比,所设计的制导律对目标机动有较强的鲁棒性,能以直接碰撞的方式拦截高超声速目标。     

星上路由查找设计与算法实现

针对星上路由器的路由查找功能展开研究。通过分析比较多种路由查找算法,利用软硬件协同设计的思想,给出了星上路由查找的设计与适合硬件查找的Trie树实现。给出了算法实现程序,通过实例分析了算法的优点。结果表明设计可以满足宽带卫星通信系统业务的需求。     

海上机动目标打击效果评估决策支持系统设计

针对海上机动目标打击效果评估的特点,运用遥感技术、人工智能技术和模糊评判的方法探索打击效果评估问题。提出一种基于高分辨率遥感图像的打击效果评估决策支持系统,融合人定性分析和机器定量分析的优点,核心是问题处理系统综合运用处理后的遥感信息和支持系统的模型、知识以及数据来评估打击效果,评估模型为二级综合评判模型。对尚处于理论研究阶段的海上机动目标打击效果评估问题有积极的参考意义。