基于态势预测的无人机防相撞控制方法

针对无人机自主飞行过程中,受空中非协作移动目标威胁较大,且空中移动威胁存在高机动性的特点,提出一种预测移动威胁情况下的无人机防撞控制方法,该方法采用交互多模(IMM)算法预测移动威胁的运动状态,同时利用滚动时域控制(RHC)思想建立无人机运动控制模型,构造有约束目标函数,运用微分进化算法(DE)求解目标函数,获取最优控制量,输入控制模型,完成防撞机动控制。仿真结果表明,该方法可以有效解决空中多架航空器同时入侵的防撞问题。     

一种基于单频GPS接收机的自迭代定位算法

随着通用航空及无人机产业的发展,低成本及小型化的导航解决方案将具有广泛的市场。提出了一种基于单频GPS接收机的自迭代定位算法,用于提高定位精度,增强定位收敛性。对该算法的基本原理进行了分析,并推导出该算法的数学模型,通过静态实验的方法对该算法的收敛性进行验证,并将该算法的位置信息与最小二乘法解出的位置信息进行对比,体现了自迭代定位算法的优势。     

基于粗糙集和支持向量机的火炮内膛疵病识别方法

火炮内膛疵病智能识别是火炮内膛窥测的最终目标,它涉及到内膛疵病的特征提取和疵病识别两方面。首先建立了包括疵病形状、纹理与颜色特征的火炮内膛疵病特征体系;并采用模糊粗糙集理论分析了各疵病特征对疵病识别的敏感性,由此优化了疵病特征体系,降低了疵病特征维数;建立了最小二乘支持向量机小样本、非线性数据特征的多疵病分类器,提高了疵病识别效率和质量。     

The role and capabilities of major weapon systems transferred between 1950 and 2010: Empirical examinations of an arms transfer data set

Arms transfers provide exporters an avenue to provide security to other states while gaining economic benefits. Arms transfers provide importers an avenue to gain security without having to rely on alliances. Past research uses aggregate measures of the monetary or security value of major weapon system transfers without accounting for strategic differences in possible use in interstate and civil conflict. This article presents a data set on interstate transfers of major weapon systems between 1950 and 2010 building upon Stockholm Peach Research Institute’s Arms Trade Register with several improvements. First, it disaggregates land weapons and air weapons into categories reflecting their strategic capabilities. Second, model level characteristics (e.g. age, speed, and range) are drawn from Jane’s Defence sources. Additionally, the data set covers a larger range of time and states than previous data sets categorizing arms. To demonstrate the usefulness, this article first presents summary statistics of the data set and then replicates an earlier test to show that the effect of human rights and regime types on United States transfers differs across the categories of arms compared to alternative measures of arms transfers.     

融合图嵌入的光滑主成分分析网络图像识别算法

主成分分析网络(principal component analysis network, PCANet)是一种简单的深度学习算法,在图像识别领域具有优秀的性能。将图嵌入思想融入PCANet,提出一种新的图像识别算法光滑主成分分析网络(Smooth-PCANet)。为了验证Smooth-PCANet算法的有效性,在人脸、手写体字符以及图片等不同数据集上构建实验,并将Smooth-PCANet与多种基于深度学习的图像识别算法作了对比。实验结果证明,Smooth-PCANet算法比PCANet获得了更高的识别性能,并且更有效地避免了过拟合,在小样本训练时具有显著优势。     

Stochastic framework for partially degradation systems with continuous component degradation‐rate‐interactions

Many conventional models that characterize the reliability of multicomponent systems are developed on the premise that for a given system, the failures of its components are independent. Although this facilitates mathematical tractability, it may constitute a significant departure from what really takes place. In many real‐world applications, system components exhibit various degrees of interdependencies, which present significant challenges in predicting degradation performance and the remaining lifetimes of the individual components as well as the system at large. We focus on modeling the performance of interdependent components of networked systems that exhibit interactive degradation processes. Specifically, we focus on how the performance level of one component affects the degradation rates of other dependent components. This is achieved by using stochastic models to characterize how degradation‐based sensor signals associated with the components evolve over time. We consider “Continuous‐Type” component interactions that occur continuously over time. This type of degradation interaction exists in many applications, in which interdependencies occur on a continuum. We use a system of stochastic differential equations to capture such “Continuous‐Type” interaction. In addition, we utilize a Bayesian approach to update the proposed model using real‐time sensor signals observed in the field and provide more accurate estimation of component residual lifetimes. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 286–303, 2014     

基于DPA的LED非线性部件逆向研究

在军事和商业应用中有很多密码算法是半公开或者不公开的,旨在证明算法保密对密码的安全性提高并没有明显帮助．针对轻型分组密码LED的未知非线性部件S盒,提出了一种基于差分功耗分析的逆向方法,该方法可以利用差分功耗曲线的极性信息来恢复未知算法结构．实验结果表明,在LED的S盒参数未知时,利用功耗采集平台采集算法运行时泄露的旁路功耗信息,可以成功逆向出全部s盒信息,验证了该方法的可行性．     

一种高效的不协调决策表约简算法

目前,不协调决策表的分布约简、最大分布约简和分配约简算法复杂度较高,不适合处理大数据集。在分析已有算法基础上,分析了基于相对可区分度的属性重要性度量的性质,解决了正域度量属性重要性的缺陷。针对不协调决策表,给出了多种简化协调决策表的定义,从而大大缩减了约简的实例数。以相对可区分度为启发函数构造了一种高效完备的不协调决策表约简算法。理论分析和实验结果表明,该约简算法解决了现有算法在复杂度和属性重要性度量上的缺陷,适合处理不协调的大数据集。     

面向产品配置的模块求解策略研究

针对模块化设计的产品配置阶段,提出了基于模块族特征参数模型的模块配置集生成流程。详细阐述利用质量功能配置(QFD)将用户需求定量映射为模块特征参数的方法,描述了依据相似度计算模型按照映射关系从模块库中检索模块的过程,从而为构建产品模块配置集、确定产品配置方案提供了完整的途径。     

基于粗糙集理论的武器系统效能评定

简述了各种武器效能评定方法。建立武器参数效能模型,首先要挑选特征参数,这里采用知识约简方法选择武器的特征参数。利用神经网络理论建立了参数效能模型,武器系统的效能与武器特征参数的关系可通过神经网络的阈值和权值得到体现。通过实例对神经网络法与指数法所得的结果进行了比较,结果表明神经网络法比指数法精确。