最大互信息准则下的认知MIMO雷达波形设计

针对杂波背景下对认知多输入多输出(MIMO)雷达波形设计研究较少的问题,提出了一种基于最大互信息准则的波形设计方法。该方法结合一般认知雷达波形设计模型,以雷达发射功率作为约束条件,以最大化目标与接收回波间的互信息为目标,对认知MIMO雷达的波形设计问题进行建模,并采用卡尔曼滤波一步预测的方法对快速运动扩展目标的冲激响应进行预测,实现对目标的精准估计;同时,基于上述分析采用最大能量分配的方法进行波形设计。仿真实验表明,与传统的线性调频信号(LFM)相比,文中所提方法可以获得更多的信息量。     

基于神经网络的动态规划检测前跟踪算法

针对低信噪比条件下的目标探测问题,提出基于神经网络的动态规划检测前跟踪算法。首先,从原始观测数据中选择训练样本,对神经网络进行权值训练;然后,全部原始观测数据归为两类,将归入杂波集合的数据幅值置零,将归入目标集合的数据进行幅值缩放,改善后续值函数积累效果;最后,提出一种多目标决策航迹回溯算法,对初步回溯的航迹集合进行二次提取,有效降低了航迹回溯过程中的虚假航迹率。仿真结果验证了所提算法的有效性。     

MEC业务连续性技术研究与应用

分析了当前移动性面临的难题以及可行的解决思路,同时研究了3GPP网络侧现有的业务连续性能力和关键特性,包括会话和服务连续模式、超高可靠与低时延通信、流量引导等。提出了一种基于网络侧和应用侧协同机制,满足低时延业务在边缘快速移动涉及跨MEC切换场景下的业务连续性要求。并探讨了移动性管理后续研究的总体思路和分阶段实施路径。     

电磁计算在飞机隐身设计中的应用及未来需求

随着飞机隐身技术的发展,对电磁计算提出了更高的要求,文中分析了国内外技术基础,梳理了电磁计算在飞机雷达隐身设计中的切入点和应用点,阐述了设计过程中利用电磁仿真手段重点开展的分析研究内容.在此基础上,分析了目前电磁计算在飞机隐身设计领域存在的技术难点以及未来技术需求,并结合飞机研制工程经验,指出未来电磁计算将重点突破超电大尺寸目标快速计算、隐身结构材料仿真等问题.     

Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine

In the application of Wireless sensor net-works (WSNs), effective estimation for link quality is a basic issue in guarantying reliable data transmission and upper network protocol performance. A link quality es-timation mechanism is proposed, which is based on Sup-port vector machine (SVM) with multi-class classification. Under the analysis of the wireless link characteristics, two physical parameters of communication, Receive sig-nal strength indicator (RSSI) and Link quality indicator (LQI), are chosen as estimation parameters. The link qual-ity is divided into five levels according to Packet recep-tion rate (PRR). A link quality estimation model based on SVM with decision tree is established. The model is built on kernel functions of radial basis and polynomial re-spectively, in which RSSI, LQI are the input parameters. The experimental results show that the model is reason-able. Compared with the recent published link quality es-timation models, our model can estimate the current link quality accurately with a relative small number of probe packets, so that it costs less energy consumption than the one caused by sending a large number of probe packets. So this model which is high efficiency and energy saving can prolong the network life.     

基于喘振谱分析的压缩机故障智能检测技术研究

为了实现对压缩机故障的准确诊断和实时检测,保证天然气压缩机的稳定运行,提出一种基于喘振谱分析的压缩机故障智能检测技术.对在故障工况下的天然气压缩机喘振时间序列进行样本数据采集,对采集的样本数据进行故障信号特征提取,采用小波变换方法进行压缩机故障信号的时频分解,运用喘振谱分析方法提取故障特征参量,以提取的故障特征参量为测试样本集,通过故障分类器实现故障智能检测识别.仿真结果表明,采用该方法进行压缩机故障检测的准确检测概率较高,对故障点的定位识别性能较好,实现天然气压缩机故障的智能诊断.     

"互联网+"时代的宿舍智能用电监控系统——以广东培正学院为例

随着"互联网+"行动计划的发展,高校进行学生宿舍大功率电器的人工检查即将成为过去式,而错误率低,更快速,更准确,效率高,采用电脑计量电费,让学生实时了解用电详情,可以节省学校对于检查大功率所耗费的人力、物力及财力的"互联网+高校学生宿舍智能电表"将会普遍高校.本文将从研究背景与意义、系统设计和数据监控三个方面以广东培正学院为例进行研究分析.     

基于FPGA的TIADC并行采样系统设计

介绍一种基于多片ADC的时间交替并行采样设计方法以及在FPGA平台上的实现.着重阐述TIADC并行采样的增益误差、时间误差校正算法及实现.实验结果表明,TIADC并行数据采集系统的结构设计和预处理算法,能较好抑制因相位偏移、时钟抖动等造成的非均匀误差.     

Energy‐Dissipative Matrices Enable Synergistic Toughening in Fiber Reinforced Soft Composites

Tough hydrogels have shown strong potential as structural biomaterials. These hydrogels alone, however, possess limited mechanical properties (such as low modulus) when compared to some load‐bearing tissues, e.g., ligaments and tendons. Developing both strong and tough soft materials is still a challenge. To overcome this obstacle, a new material design strategy has been recently introduced by combining tough hydrogels with woven fiber fabric to create fiber reinforced soft composites (FRSCs). The new FRSCs exhibit extremely high toughness and tensile properties, far superior to those of the neat components, indicating a synergistic effect. Here, focus is on understanding the role of energy dissipation of the soft matrix in the synergistic toughening of FRSCs. By selecting a range of soft matrix materials, from tough hydrogels to weak hydrogels and even a commercially available elastomer, the toughness of the matrix is determined to play a critical role in achieving extremely tough FRSCs. This work provides a good guide toward the universal design of soft composites with extraordinary fracture resistance capacity.     

Redox‐Responsive and Drug‐Embedded Silica Nanoparticles with Unique Self‐Destruction Features for Efficient Gene/Drug Codelivery

The development of advanced gene/drug codelivery carriers with stimuli‐responsive release manner for complementary cancer therapy is desirable. In this study, novel disulfide‐bridged and doxorubicin (DOX)‐embedded degradable silica nanoparticles (DS‐DOX) with unique self‐destruction features are synthesized by a facile one‐pot method. In order to realize codelivery of genes and drugs, the surface of DS‐DOX nanoparticles is readily functionalized with the assembled polycation (CD‐PGEA), comprising one β‐cyclodextrin core and two ethanolamine‐functionalized poly(glycidyl methacrylate) arms, to achieve DS‐DOX‐PGEA. The redox‐responsive self‐destruction behavior of DS‐DOX imparts DS‐DOX‐PGEA with a better ability to release anticancer drug DOX, while the low‐toxic hydroxyl‐rich CD‐PGEA brushes can efficiently deliver genes for cancer treatment. Very interestingly, the degradation process of DS‐DOX starts from the outside, while the destruction of the degradable silica (DS) nanoparticles without DOX begins from the center of the nanoparticles. The embedded DOX inside the DS‐DOX nanoparticles can significantly influence the structures and facilitate the cellular uptake and the subsequent gene transfection. The as‐developed DS‐DOX‐PGEA nanostructure with coordinating biodegradability, stimuli‐responsiveness, and controlled release manner might be desirable gene/drug codelivery carriers for clinical cancer treatment.