坦克外壳对内部电磁波的影响及其振荡干扰波型的数值计算

在坦克的金属立方体盒子模型下,分析了坦克外壳对内部电磁波的影响,并对Lc型电路激发的电磁波在坦克内部形成的振荡波型进行了计算,分析了该类电磁振荡波对坦克内部其他电子元件产生电磁干扰的作用机理,对一种最低频率的谐振波型进行了仿真模拟,提供了对坦克内部电磁波电场分量及磁场分量的一种分析计算方法,为研究坦克内部电子设备的电磁干扰规律提供了思路,对提高坦克的电磁兼容性能具有一定参考意义。     

污水中重金属离子浓度软测量的BP算法

在重金属离子检测仪器及其工作原理研究的基础上,对污水中重金属离子浓度测量方法进行了分析研究,分析了采用软测量技术的可行性和必要性,针对水质测量具有非线性、大时变和多滞后的特点,提出了基于BP神经网络的污水中重金属离子浓度软测量建模方法,建立了软测量模型,并通过仿真分析和实验验证了该方法的实用性.     

基于遗传算法的跳频通信侦察技术

为了识别跳频序列,提出了采用遗传算法并结合跳频信号特点来完成跳频序列的分析与重组,从而实现跳频信号的侦察。在采用传统遗传算法的基础上,针对序列特点提出了5种改进手段,从而大大提高了算法的效率和可用性。最后利用采样的语音信号,对分析与重组过程进行模拟来验证算法的可行性。     

复杂电磁环境下电子系统仿生防护模式研究

阐述电磁防护工作中仿生研究所需要涉及的学科类型和基本内容,对所做工作在整个仿生领域中进行大致的定位;提出生物一电子研究的对等模型、总体构成和实现基础,细化具体研究的方向、设想和防护模式,并从原型实现的工程角度介绍实施策略,使得复杂电磁干扰环境下控制系统板卡及芯片级防护的仿生构想在技术上成为可能。     

融合神经网络与超像素的候选区域优化算法

为解决目标检测中候选区域召回率低的问题,提出融合神经网络与超像素的目标候选区域算法。该算法利用神经网络提取更能清楚表达目标边界的特征,并使用聚类、相似性等策略,计算每个滑动窗口所含有的边缘信息量;将待测图像使用简单线性迭代聚类算法分割成若干个超像素,并利用超像素的空间位置、完整性、相邻超像素间的对比度信息,计算各个超像素的显著性得分及每个滑动窗口的显著性得分;根据每个滑动窗口的边缘信息及显著性得分筛选滑动窗口。在PASCAL VOC 2007测试集上进行对比实验,其实验结果表明:所述算法能够快速产生定位质量高的候选区域。     

复杂海战场环境下AUV全局路径规划方法

针对无人自主水下航行器(Autonomous Underwater Vehicle, AUV)在复杂海战场环境中路径规划时环境模型复杂、约束条件多的情况,建立了包括战场地形、敌方威胁、障碍物和海流场等在内的比较完善的海战场环境模型。以AUV航行时间、威胁时间最短为优化目标,给出了一种基于振荡型入侵野草优化(Invasive Weeds Optimization, IWO)算法的AUV全局路径规划方法,并分别与标准IWO算法、全振荡型IWO算法以及粒子群算法等三种路径规划算法比较。仿真结果表明,所提方法具有较强的寻优能力和鲁棒性,可在复杂海战场环境下为AUV高效地规划出满足性能要求的航行路径。     

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.     

Visual SLAM in dynamic environments based on object detection

A great number of visual simultaneous localization and mapping (VSLAM) systems need to assume static features in the environment. However, moving objects can vastly impair the performance of a VSLAM system which relies on the static-world assumption. To cope with this challenging topic, a real-time and robust VSLAM system based on ORB-SLAM2 for dynamic environments was proposed. To reduce the influence of dynamic content, we incorporate the deep-learning-based object detection method in the visual odometry, then the dynamic object probability model is added to raise the efficiency of object detection deep neural network and enhance the real-time performance of our system. Experiment with both on the TUM and KITTI benchmark dataset, as well as in a real-world environment, the results clarify that our method can significantly reduce the tracking error or drift, enhance the robustness, accuracy and stability of the VSLAM system in dynamic scenes.     

知识图谱的预警探测体系探测效能贝叶斯评估方法

战争中,预警探测体系作为典型的复杂系统,其探测效能发挥情况的有效评估一直是亟需人们研究解决的重要现实问题.突破了传统效能评估方法的局限,在分析了知识图谱技术、贝叶斯评估方法基本原理的基础上,提出了基于两者综合运用的预警探测体系探测效能评估新方法,利用专家知识和实验数据构建知识图谱,并进一步使用贝叶斯网络方法实施知识推理...     

电磁屏蔽石墨混凝土电导率实验研究

石墨混凝土具有耐酸碱、成本低、性能稳定等优点。针对电导率是材料电磁屏蔽性能的重要影响参数,以获得最佳导电性能为方向设计了石墨混凝土的探索性制备方案,研究了其配合比对混凝土电导率性能的影响,采用四针电极法考察石墨混凝土的导电性能。实验结果表明,石墨混凝土中电导率存在不均匀性,其中粗颗粒石墨混凝土比细颗粒石墨混凝土具有更好的导电性能,其值约0．8 S/cm,表现出较好的性能一致性,为工程应用提供了条件。增加20%导电镍粉,对导电性能有改善,但水灰比较大。掺碳纤维石墨混凝土样品,针对石墨质量分数71%,相对石墨掺入碳纤维2%,电导率值由0．8 S/cm降为0．17 S/cm。其中材料的多孔性是材料导电性降低的主要因素。