基于加权D-S证据理论的辐射源目标识别

在目标识别中D-S证据理论应用较为广泛,该理论要求各传感器的重要程度相同,与作战使用相矛盾.就此提出了基于加权D-S证据理论的时空域目标识别方法,突出了不同传感器在目标识别中的地位和作用,使目标识别结果更接近作战实际.     

基于粗集理论证据加权的电子目标识别法

在对电子目标进行识别时,往往采取多传感器融合的D2S证据理论进行处理,但是由于传统的D2S证据理论中各传感器对识别结果的重要性没有区分,基于此将粗集理论属性重要度概念应用到各传感器的重要性上,从而实现加权融合的证据理论。仿真实验及其结果表明该方法对电子目标识别是有效的,尤其在传感器受到干扰时,具有较强的现实意义。     

多源目标识别中冲突证据的融合策略研究

随着防空反导作战环境的日益复杂,快速准确地进行真假目标识别显得尤为重要。针对多源目标决策级识别中冲突证据融合问题,在综合分析现有改进证据理论方法的基础上,引入新的冲突度量系数,提出了一种通过在融合流程中增加智能判断环节,以冲突系数为判断依据,对具有不同冲突系数证据选择不同组合规则进行证据组合的融合方法,并给出了策略的流程图。最后进行了实例验证,结果表明新策略能对不同未知信度和不同识别框架冲突证据进行快速有效的融合。     

一种RS码快速盲识别方法

为了获取数字通信中未知线路的纠错编码信息,提出了一种RS码快速盲识别方法.通过对RS码的二进制表示进行码根求解的方法来检测未知线路的RS码长、本原多项式阶数以及可能的本原多项式;进而遍历得到的本原多项式对RS序列进行伽罗华域的傅里叶变换(GFFT),通过连零位置和个数最终确定未知线路的真实本原多项式和生成多项式.实验验...     

美军作战实验室建设研究

简要回顾了美军作战实验发展的历史,从军种到联合详细阐述了美军作战实验室完整的体系,并简要介绍了各作战实验室所完成的典型实验,研究了美军作战实验室主要的实验方法和技术手段,剖析了美军作战实验室的运行机制,探讨了美军作战实验室建设带给我们的启示。     

超声辅助喷射电沉积Ni镀层的表面形貌及硬度

试验以直接超声方式,在喷射电沉积装置的基础上加载超声设备,分别在20℃和50℃两种镀液温度下在A3钢基体上制备了加载超声和不加载超声Ni镀层,研究了超声波及温度对Ni镀层表面形貌和硬度的影响。试验结果分析表明：在20℃条件下,超声可避免镀层裂纹的产生,提高镀层的硬度;在50℃条件下,超声可细化镀层的组织,且可显著提高镀层硬度;超声波对喷射电沉积层组织和性能的影响机理主要在于超声空化引起的析氢减少、细晶强化和加工硬度。     

电控共轨柴油机初始控制MAP研究

为合理快捷地获取电控柴油机的控制参数表MAP,进行了共轨柴油机电控初始MAP研究。分析了柴油机运行工况特点和试验获取特征工况数据的原则;引入了散点曲面拟合方法,简要说明了Shepard有理插值曲面理论和它的Lagrange插植的形式;根据柴油机运行工况的特点,提出了变步长试验点,减小试验量,引入均方根误差衡量不同试验点数拟合控制MAP的精度,结合实例给出了电控初始MAP的散点曲面拟合过程,并在493共轨柴油机上进行初始MAP的控制效果试验,试验数据表明：该方法能满足电控柴油机初始MAP的要求。     

一种基于ARM和DSP的信号处理平台

基于ARM和DSP芯片设计实现了一种信号处理平台。硬件方面,ARM作为主控制器,完成数据输入、输出、人机交互,并通过HPI接口访问和控制DSP芯片;DSP作为ARM芯片的协处理器,负责信号处理及算法运算。软件方面,实现了ARM芯片上的WINCE应用程序用于访问、控制DSP,设计基于HPI接口启动的DSP程序负责数据处理以及和ARM通信。通过在此平台上实现的一个声纹识别系统,验证了平台软硬件设计的正确性。     

Fuzzy recognition of missile borne multi-line array infrared detection based on size calculating

In order to improve the infrared detection and discrimination ability of the smart munition to the dy-namic armor target under the complex background, the multi-line array infrared detection system is established based on the combination of the single unit infrared detector. The surface dimension features of ground armored targets are identified by size calculating solution algorithm. The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target. According to the characteristics of the target signal, a custom threshold de-noising function is proposed to solve the problem of signal preprocessing. The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage. The method solves the disadvan-tages of wide scanning interval and low detection probability of single unit infrared detection. By reducing the scanning interval, the number of random rendezvous in the infrared feature area of the upper surface is increased, the accuracy of the size calculating is guaranteed. The experiments results show that in the fuzzy recognition method, the size calculating is introduced as the feature operator, which can improve the recognition ability of the ground armor target with different shape size.     

Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical-military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical-military experts.Both the design and the results of the evaluation are revealed in this article.