Multi-layer protective armour for underwater shock wave mitigation

The effect of underwater shock wave on different target plates has been studied.An underwater shock wave generator(shock tube) was used to study the interactions between water and different constructed targets which act as shock wave mitigation.Target plates,composed of sandwich of two aluminum sheets with rubber and foam in between,were prepared and studied.For comparison,the target plates composed of triple aluminum sheets were tested.The study includes the testing of the selected plates in water under the effect of different peak pressures and the analysis of the results.The strain gauge data and displacement sensors results showed that the multi-layer plates have higher level of underwater shock wave mitigation than the triple aluminum plates with strain and deflection of nearly 50%.     

异步非平稳干扰抑制方法

为解决单通道条件下异步非平稳干扰抑制问题,提出基于数据驱动的稀疏分量分析干扰抑制方法,旨在从接收到的混叠信号中恢复期望信号。该方法利用深度卷积神经网络对输入/输出端数据间的复杂映射关系的强大建模能力,实现了目标信号稀疏域的自适应选择、稀疏域中目标信号稀疏表示的自适应学习以及目标信号的自动恢复。与以往干扰抑制算法不同,所提方法在时域上完成了“端到端”的信号波形恢复,且对混叠观测无先验要求,相比现有方法更具普适性。仿真实验验证了所提干扰抑制方法在不同环境噪声和干扰信号强度及泛化测试条件下的有效性,对干扰的抑制性能显著优于现有算法。     

对流层散射信道传递时间信号的抖动抑制模型

对流层散射信道传递时间同步信号过程中,信道的多径效应及噪声会引起信号抖动。为抑制抖动、提高时间同步精度,引入经验模态分解和小波阈值组合的抖动抑制模型。组合抖动抑制模型中,首先根据经验模态分解原理对原始信号进行分解,然后利用小波阈值对分解得到的各分量进行处理,最终利用处理结果重构信号。为提高组合模型的抖动抑制效果和原始信号的保持能力,利用连续性好、柔和度高的阈值函数对小波阈值中的传统阈值函数进行改进。利用实测数据验证模型的结果表明,在抖动抑制和信号保留方面,组合模型较单一模型以及常用的Kalman模型优势明显。     

GPS接收信号中线性扫频干扰的抑制

研究了阵列接收的GPS接收信号中线性扫频(LFM)干扰的抑制问题。LFM信号瞬时频率的估计是抑制干扰的关键,而要准确估计信号瞬时频率,必须抑制接收信号时频分布中交叉项干扰。本文对接收信号矢量进行白化,得到信号矢量白化后的空时频分布(STFD)矩阵。文中推出一个与传统方法获得的判决变量不同的判决变量,用该判决变量可以更加清晰地选出LFM信号在时频分布中的自项。根据时频脊点的分布估计LFM信号频率参数以及信号瞬时频率,之后即可根据瞬时频率构建陷波器滤除干扰。仿真表明该方法能够将受交叉项严重干扰的接收信号时频分布映射为清晰的接收信号自项的时频分布,在数据快拍数满足一定要求时可以很好地抑制掉LFM干扰。     

基于OpenFlow的SDN中链路层拓扑发现的优化

在基于OpenFlow的软件定义网络中,控制器需要对全局网络状态保持全面并且实时的掌握,怎样快速地获取当前网络的拓扑状态成为了重要前提。而SDN的拓扑发现协议OFDP虽然已经将控制权交给了控制器,但是仍采用洪泛式的拓扑发现消息发送机制来进行拓扑发现,没有达到全局最优,增加了不必要的开销。因此,提出一种基于OFDP的改进机制,在控制器中添加新的拓扑发现功能模块,通过减少重复端口发现的方式,来减少网络中的拓扑发现消息的数量。仿真实验结果表明,改进机制在加快了网络拓扑的生成的同时,减轻了控制器的负载。     

卫星导航接收机中快扫频干扰低复杂度抑制方法

针对卫星导航接收机中的快扫频干扰抑制问题,提出了一种基于脉冲置零的低复杂度干扰抑制方法,与传统基于时频分析的干扰抑制方法不同,该方法通过低通滤波将时域上连续的快扫频干扰转变为脉冲干扰,并通过脉冲检测与置零对干扰进行抑制。当快扫频干扰处于低通滤波器带内时,被当作脉冲干扰置零;当快扫频干扰处于低通滤波器带外时,被当成带外干扰滤除。理论分析与实验结果表明,该方法相对传统方法的运算复杂度降低了一个数量级,并且能得到与传统方法相近的干扰抑制效果。     

辅助通道参数模型估计射电天文抗干扰方法

针对单通道射电天文抗干扰方法在观测数据干噪比较低情况下的干扰消除性能降低甚至失效的问题,通过引入辅助天线观测提出了一种基于参数模型估计的抗干扰方法。该方法利用辅助天线所接收到的具有较高干噪比的观测数据建立干扰信号参数的估计模型,同时通过构建主辅通道参数差异性模型对估计模型进行修正,实现对干扰信号参数的精确估计,达到消除干扰信号的目的。仿真实验表明,相比于单通道方法,改进后的方法在解决低干噪比条件下的射电天文抗干扰问题方面具有更广泛的适用范围。     

Shock wave mitigation using zig-zag structures and cylindrical obstructions

The present study focuses on the mitigation of shock wave using novel geometric passages in the flow field. The strategy is to produce multiple shock reflections and diffractions in the passage with minimum flow obstruction, which in turn is expected to reduce the shock wave strength at the target location. In the present study the interaction of a plane shock front (generated from a shock tube) with various geometric designs such as, 1) zig-zag geometric passage, 2) staggered cylindrical obstructions and 3) zig-zag passage with cylindrical obstructions have been investigated using computational technique. It is seen from the numerical simulation that, among the various designs, the maximum shock attenuation is produced by the zig-zag passage with cylindrical obstructions which is then followed by zig-zag passage and staggered cylindrical obstructions. A comprehensive investigation on the shock wave reflection and diffraction phenomena happening in the proposed complex passages have also been carried out. In the new zig-zag design, the initial shock wave undergoes shock wave reflection and diffraction process which swaps alternatively as the shock front moves from one turn to the other turn. This cyclic shock reflection and diffraction process helps in diffusing the shock wave energy with practically no obstruction to the flow field. It is found that by combining the shock attenuation ability of zig-zag passage (using shock reflection and diffraction) with the shock attenuation ability of cylindrical blocks (by flow obstruction), a drastic attenuation in shock strength can be achieved with moderate level of flow blocking.     

基于PCA与FCM的入侵检测样本数据压缩方法

采用行列双向压缩的数据处理策略,提出了一种基于主成分分析与模糊C-均值聚类算法的入侵检测样本数据压缩方法。该方法首先采用主成分分析法对数据冗余特征进行压缩,然后采用模糊C-均值聚类算法对冗余样本进行压缩,由此可挖掘入侵检测样本数据中的关键特征和关键样本。通过KDD CUP99数据集测试证明:数据双向压缩可减少入侵检测分类器的计算量,进而可提高其实时检测性能和检测推断的准确性。     

级联结构的阵列天线导航接收机抗干扰及多径抑制方法

阵列信号处理技术因其能够提供空域分辨能力已被广泛应用于卫星导航接收机领域以实现抗干扰和多径抑制。根据干扰和多径信号对导航接收机基带处理影响的不同提出了一种以数字相关器为界线划分的抗干扰与多径抑制两级处理结构:第一级处理在解扩前估计阵列接收数据的空时协方差矩阵,根据干扰信号功率远大于导航信号及噪声的特点利用子空间投影技术实现抗干扰;第二级处理在解扩后进行空间平滑解相干处理,利用基于Householder变换的广义旁瓣相消技术进行波束形成以实现多径抑制。理论分析和仿真结果表明,该级联处理技术能够有效地压制强干扰,并显著减小多径信号对导航接收机伪码测量的影响。     

Experimental investigation on weak shock wave mitigation characteristics of flexible polyurethane foam and polyurea

In recent years, explosion shock wave has been considered as a signature injury of the current military conflicts. Although strong shock wave is lethal to the human body, weak shock wave can cause many more lasting consequences. To investigate the protection ability and characteristics of flexible materials and structures under weak shock wave loading, the blast wave produced by TNT explosive is loaded on the polyurethane foam with the density of 200.0 kg/m3(F-200) and 400.0 kg/m3(F-400), polyur...     

联合特征累积分析的压缩域运动对象检测

依据H.264压缩域中能够反映景物运动变化的MV和DCT系数特征,本文提出了一种多特征联合累积分析的压缩域运动对象检测方法。该方法对压缩码流中各宏块的运动信息进行时空域滤波,并使用雅克比矩阵描述全局运动参数和宏块MV之间的关系,简化参数求解过程,通过比较局部运动和全局运动之间的差异初步检测运动对象;选取宏块周围可靠的运动特征用于宏块DCT系数能量的投影累积,并通过熵能原理在压缩域中选取各个宏块的自适应阈值,检测运动对象的边缘及纹理显著区域;通过一定的逻辑准则将MV和DCT系数的检测结果结合起来,最终检测出视频中运动对象。实验结果表明,本文算法可准确地检测压缩视频中的运动对象,且检测结果具有较高的查全率和查准率。     

带限信道中准相干码相关参考波形技术多径抑制性能分析

码相关参考波形(CCRW)技术以其设计灵活、抗多径性能优异等特点成为卫星导航多径抑制研究的热点,但目前相关文献在分析CCRW技术时常假设单边信道带宽无限或远大于扩频码率,且仅研究特定参考波形的性能,缺乏具有工程指导意义的定量结论.根据CCRW技术一般原理,推导了在无限带宽时任意参考波形的鉴别曲线计算公式,给出了满足稳定跟踪的波形约束条件.分析了不同带宽和闸宽参数的W2/W4/W5三类参考波形的准相干多径误差包络性能,仿真表明带限信道中W4、W5波形抗多径性能优于W2波形;以GPS L5和Galileo E5a/E5b的QPSK(10)信号为例进行原理样机试验,结果表明W2、W5算法比窄相关技术的3dB衰减多径误差包络面积减小达63％和72％.结论可用于现代化导航接收机的多径抑制设计.     

An approach for predicting digital material consumption in electronic warfare

Electronic warfare is a modern combat mode, in which predicting digital material consumption is a key for material requirements planning (MRP). In this paper, we introduce an insensitive loss function (ε) and propose a ε-SVR-based prediction approach. First, we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set, and preprocess it to construct the sample space. Subsequently, we establish the ε-SVR-based prediction model based on “wartime influencing factors - material consumption” and perform model training. In case study, we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach. The results illustrate its higher accuracy and more convenience compared with other current approaches. Taking data acquisition controller prediction as an example, our model has better prediction performance (RMSE = 0.575 7, MAPE (%) = 12.037 6 and R² = 0.996 0) compared with BP neural network model (RMSE = 1.272 9, MAPE (%) = 23.577 5 and R² = 0.980 3) and GM (1, 1) model (RMSE = 2.095 0, MAPE (%) = 24.188 0 and R² = 0.946 6). The fact shows that the approach can be used to support decision-making for MRP in electronic warfare.     

基于人工智能的微反应识别与处理

随着时代发展,人工智能研究运用取得一定的成果,比如苹果公司的siri、Google的搜索引擎、卡内基·梅隆大学的Intra Face应用系统等,都为人工智能条件下的机器人更像真实人类率先布局。如何实现机器人更像真实人类的目标,尽快研究并解决人工智能的微反应识别和处理显得尤为紧迫和重要。本文将以面部微表情和映射心理状态肢体动作的微反应为主,重点介绍人工智能微反应的探测、识别及处理的方式,旨在不断提高机器识别、表达微反应的能力,推动人工智能从感知层面向认知层面演进,实现发展人工智能的终极目标。     

结合多视角学习与一致性表征的人脸伪造检测

现有的人脸伪造检测方法通常在已知域上表现较好,但面临过拟合的风险,在应对未知场景时无法保持良好的检测能力。为解决此问题,提出一种结合多视角学习与一致性表征的人脸伪造检测框架。为捕获更全面的伪造痕迹,将输入图像转换为两种互补视角并采用双流骨干网络进行多视角特征学习。引入一致性度量,以补丁级监督的方式明确约束不同视角输出的局部特征的相似度。为提高检测精度,采用特征分解策略进一步优化伪造特征,减少不相关因素的干扰,并以伪造特征空间的决策作为最终的预测结果。在基准数据集上进行的大量实验表明,所提出的方法优于现有的主流模型,具备良好的跨域泛化能力。     

A closed-from approach for multi-item inventory grouping

The problem of optimally coordinating the replenishments of the many items in stock with one another is dealt with in this article. Specifically, it considers this coordination based on classifying the items into a few groups with common order cycles for all the items in a particular group. Assuming that the cumulative distribution by value of the inventory can be characterized by a Pareto function of the type f(n) = n/(an + b), (a, b > 0), it establishes that the optimal boundaries of the groups can be obtained as closed-form expressions by solving a system of simultaneous equations. The composition of the successive groups thus obtained is found to equipartition the total cost and to follow geometric sequences in relation to the number of items, the value of items, and the lengths of the order cycles. Graphs have been proposed to aid the implementation of the grouping scheme. Simple iterative schemes are outlined within the framework of the Pareto function to handle other relevant costs.     

初相未知信号联合检测与估计的序贯实现

在未知参数的充分统计量和再生概率密度函数的基础上,引入了联合检测与估计的序贯算法,给出了算法的实现框图,并将该算法应用于高斯噪声中初相位未知信号的联合检测与估计当中.仿真实验表明,新算法较传统算法有一定的性能改善.     

联合生成对抗网络和检测网络的SAR图像目标检测

针对合成孔径雷达图像目标检测中存在的样本获取困难且数量有限问题,提出了联合生成对抗网络和检测网络的学习模型。利用原始训练集对特别设计的超快区域卷积神经网络进行预训练;再通过基于注意力机制的深度学习生成对抗网络生成高质量合成样本,并输入检测网络进行预测;依据预测信息和概率等价类属标签分配策略为新生样本提供注释信息,并以一定占比对原始训练集进行扩充;利用扩充数据集对检测网络进行再训练。多组仿真实验证明,所提框架能够有效提升网络检测效率和性能。