空域窗射击毁歼概率解析计算模型

为提高未来空域窗射击技术对空中机动目标的毁伤概率,需要根据目标机动幅度对未来空域窗的大小进行动态设定,故提出“自适应射击窗”的概念.空域窗大小设定的依据是使毁歼概率最优.可以采用解析法来在线计算该毁歼概率值.在分析空域窗射击误差的基础上,演绎了均匀分布法与高斯和法两种毁歼概率解析计算方法的公式.以毁歼概率蒙特卡罗法仿真数据为基准值,对两种解析法的计算精度进行了对比分析.仿真结果表明,高斯和法的计算精度显著优于均匀分布法,且满足实时计算要求,适于在线评估空域窗的射击效能.     

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.     

改进熵系数法的预警机探测引导能力评估

引入欧氏距离来度量基于离差最大化法与熵系数法确定的两个权重向量的相似度,在相似度最大约束条件下,确定了熵系数法中参数ρ值,解决了参数ρ取值人为主观性的问题。采用区间数来表示专家对指标间的相对重要性,克服了实际中难于得到准确决策信息的问题。将区间数特征向量法确定的主观权重和改进的熵系数法确定的客观权重集成得到组合权重,采用加权算术平均算子对4种预警机的探测引导能力进行了计算。     

基于熵权多目标决策的战时物资运输方案优选研究

提出了战时物资运输方案优选问题,分析战时运输的影响因素,提出了评估战时物资运输方案的较有代表性的指标,并给出了具体计算方法.在没有指标权重的情况下,应用熵权多目标决策方法对多个合理方案进行优选评估,得出了可信度较高的优选方案.     

基于粗集和最大熵的模式识别方法

用基于属性约简的粗集理论找出条件属性的最小属性集。对属性间为不确定因果关系的模式,计算在最大熵情况下发生的概率,通过比较概率来进行模式识别,实例分析和结论部分说明这种方法是有效的。     

基于熵权-双基点法的战时野战维修装备编配方案优选研究

为解决战时野战维修装备编配多方案优选困难问题,实现编配方案的合理化选择;首先在分析优选编配方案的数据基础上,构建了多方案优选指标体系;然后利用熵权方法计算了优选指标的权重和标准化数据;最后利用双基点法构建了优选模型,并计算了各方案的优属度,确定了最优编配方案．     

粗糙集理论在装备保障训练效果评估中的应用

装备维修保障训练效果评估中最关键的步骤就是评估指标体系的构建及优化,为了克服传统评价方法中存在指标关联性大和权重确定主观性强的问题,将粗糙集和信息熵理论引入装备维修保障训练效果评估领域。采用信息熵的算法对连续指标离散化,基于粗糙集区分矩阵的方法对指标体系进行属性约简,降低了模型的复杂性;在此基础上提出了粗糙集属性重要度和AHP法相结合确定指标权重的方法,进而通过专家评议应用于训练效果评估实例,得到了较好的评估效果,为装备维修保障训练评估提供了新的参考方法。     

基于小波包分解和样本熵的电磁干扰分析方法

为了定量分析不同状态下电磁环境的变化,并有效提取电磁环境变化的干扰特征,提出了基于小波包分解和样本熵的电磁干扰分析方法.首先,时电磁环境的样本信号进行小波包分解,然后分别计算分解后备频带信号的能量谱系数和样本熵,通过能量谱系数和样本熵这两个指标的对比,综合判断电磁环境是否发生变化.仿真分析表明:样本熵可以弥补能量谱系数...     

Predictability of operational processes over finite horizon

Operational processes are usually studied in terms of stochastic processes. The main information measure used for predictability of stochastic processes is the entropy rate, which is asymptotic conditional entropy, thus not suitable for application over a finite horizon. We use the conditional entropy to study the predictability of stochastic processes over the finite horizon. It is well‐known that the conditional entropies of stationary processes decrease as the processes evolve, implying that, on average, their pasts become more informative about prediction of their future outcomes. Some important operational processes such as martingale, models for maintenance policies, nonhomogeneous Poisson, and mixed Poisson processes are nonstationary. We show that as a nonstationary process evolves, it may provide more information or less information about the future state of the system. We develop results for comparing the predictability of stochastic processes. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

基于自相关函数的信噪比估计方法

信噪比估计,作为衡量信道质量的标准,为许多自适应技术提供所需的信道信息。精确的信道质量估计值,可以有效提升这些技术的性能。研究表明,信号经过采样、发送波形成行后其自相关函数具有周期性。根据噪声和发送信号两者自相关函数的不同特性,提出一种利用自相关函数进行信噪比估计方法。仿真结果表明,该方法具有较高的估计精度。