基于稳态遗传算法的间歇式覆盖天基雷达星座优化设计

针对天基雷达星座的构型优化设计,建立了能够反映星座重要工作性能的单双基地间歇式覆盖模型、星间链路模型、双基地雷达的动目标检测模型,得到了低轨道卫星星座星间链路判断准则,给出了统计评价特性和综合评估指标体系。在此基础上,建立星座设计的优化模型,采用基于可行解搜索法的协同演化遗传算法并融入稳态遗传进化策略,有效地处理带有复杂计算的目标函数和约束条件的星座优化问题,计算分析实例表明利用该方法进行星座设计是非常有效的。     

利用动态规划原理实现多冲量最优交会问题

多冲量最优交会问题是航天领域非常重要的一个研究方向,从运筹学角度将此问题转化为一个多阶段多维动态规划问题,并着重对多阶段二维动态规划进行分析研究。在给出状态方程及指标函数递推公式的基础上,得到了两冲量和三冲量交会问题最优解的求解算法,之后分别通过实例验证了算法的有效性。对于以地心角等参数为决策变量的更高维问题,讨论了利用进化算法等降维方法实现多维动态规划的思想。     

网络图的自动生成算法及其系统实现

研究了网络自动生成的实现算法和系统实现技术。该算法按路线来画结点 ,将其区分为不同的层 ,再绘制路径。先画出所有关键路 ,确定关键节点的坐标 ;然后对于未确定坐标的结点 ,寻找其由关键结点出发再回到关键结点的最短路径 ,将该路径上的结点画为一层 ,按不同的路线分为不同的层次进行绘制 ,直到所有结点均确定坐标。然后确定路线的层次 ,最后统一协调规整。以此算法开发的软件系统可节省时间 ,并可保证生成规范的网络图。     

基于Dijkstra算法的水平航迹规划

战术飞行任务的航迹规划是依靠地形信息和敌情信息,在某些约束条件下,找出作战飞机从起飞点到目标突防生存概率最大、航程最短的飞行轨迹的过程。采用简易方法建立了威胁模型,用Dijkstra算法实现了作战飞机整体最优水平航迹解算,并给出了具体算例,验证了算法的有效性和实用性。     

多传感器系统纯方位定位与可观测性分析

对多静止测向站系统的可观测性、定位方法进行了分析和研究。通过运动等效,将多静止站系统转化成一个特殊的单运动测向站问题。采用拟线性方法,建立了纯方位多传感器系统目标定位问题的数学描述,并分析了系统的可观测性条件。提出了两种目标被动定位的融合递推算法,它们可以以标量的形态递推计算,具有实时性高、可计算性好的优点。     

一座小型建筑空调动态负荷的ANN预测研究

人工神经网络(Artificial Neural Network,简称ANN)是一种崭新非线性建模和预测方法,具有良好的非线性品质和极高的拟合精度。在前人研究的基础上,针对一座小型建筑物建立了其空调动态负荷预测的BP模型。为克服常规BP训练算法的缺陷,提出了一种改进的遗传搜索算法,结果证明是一种高效实用的算法。     

基于遗传算法的红外图像增强研究

红外图像侦察是一种重要的航空侦察方式。遗传算法目前已在图像处理领域得到了很好的应用。本文将遗传算法引入红外图像增强,使用红外图像的参数模型将图像增强转化为参数的优化。实验结果表明,该方法是一种有效的图像增强方法。     

Estimating distribution functions from partially observed samples

Suppose that some components are initially operated in a certain condition and then switched to operating in a different condition. Working hours of the components in condition 1 and condition 2 are respectively observed. Of interest is the lifetime distribution F of the component in the second condition only, i.e., the distribution without the prior exposure to the first condition. In this paper, we propose a method to transform the lifetime obtained in condition 1 to an equivalent lifetime in condition 2 and then use the transformed data to estimate F. Both parametric and nonparametric approaches each with complete and censored data are discussed. Numerical studies are presented to investigate the performance of the method. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 521–530, 2000     

Investigation on the spatial distribution characteristics of behind-armor debris formed by the perforation of EFP through steel target

The behind-armor debris (BAD) formed by the perforation of an EFP is the main damage factor for the secondary destruction to the behind-armor components. Aiming at investigating the BAD caused by EFP, flash X-ray radiography combined with an experimental witness plate test method was used, and the FEM-SPH adaptive conversion algorithm in LS-DYNA software was employed to model the perforation process. The simulation results of the debris cloud shape and number of debris were in good agreement with the flash X-ray radiographs and perforated holes on the witness plate, respectively. Three-dimensional numerical simulations of EFP's penetration under various impact conditions were conducted. The results show that, an ellipsoidal debris cloud, with the major-to-minor axis radio (a/b) smaller than that caused by shaped charge jets, was formed behind the target. With the increase of target thickness (h) and decrease of impact velocity (v₀) and obliquity (θ), the value of a/b decreases. The number of debris ejected from target is significantly higher than that from EFP. Based on the statistical analysis of the spatial distribution of the BAD, An engineering calculation model was established considering the influence of h, v₀ and θ. The model can with reasonable accuracy predict the quantity and velocity distribution characteristics of BAD formed by EFP.     

强化学习框架下移动自组织网络分步路由算法

移动自组织网络是一种无基础设施、由移动通信节点组成的无线网络,具有高动态特性。传统的路由协议并不能适应节点移动性带来的频繁拓扑变化,简单的洪泛路由也会因开销过大降低网络的性能。针对如何在移动自组织网络中自适应地进行路由选择,提出强化学习框架下的分步路由选择算法。该算法以最小链路总往返时延为目标,基于强化学习进行路由搜寻,在筛选出符合目标需求节点集合的基础上,结合置信度选择路由。在链路变得不可靠时,数据包被广播给筛选出的邻居节点集以提升路由可靠性并降低开销。对提出的算法在分组到达率和路由开销等主要性能指标进行数值仿真分析。仿真结果表明,提出的分步路由算法相比于基于强化学习的智能鲁棒路由,在降低开销的同时,保持着相当的吞吐率。