非线性随机动态系统学习建模方法

在动态神经网络及扩展卡尔曼滤波算法的基础上，提出了对非线性随机动态系统进行学习建模的迭代算法，用这种方法对非线性随机系统建模，可以获得更准确伯系统模型，并可对非线性随机系统进行状态估计。最后给出相应算法及仿真结果。     

编队飞行卫星群构型保持及初始化

导出了基于相对轨道要素的编队飞行卫星群轨道相对运动控制的轨道机动方程；提出了编队飞行卫星群轨道相对运动控制的轨道机动控制策略，利用不同方向的脉冲控制相对运动的轨道参数，包括轨道平面内机动和轨道平面外机动控制。根据相对轨道要素的变轨机动控制，进行编队飞行卫星群构型的初始化。这样的构型初始化可以视作一次特殊的变轨机动控制，很容易实现编队飞行构型的初始化机动。     

精密GPS卫星钟差的改正和应用

分析了GPS卫生钟差的变化特性，探讨了利用GPS地面跟踪站的观测数据估算GPS卫星钟差的可行性，建立了相应的算法和软件系统，并把由地面跟踪站的实测数据估算的卫星钟差用于星载GPS定轨计算，得到优于1m的定轨精度。     

基于连续覆盖特性分析的星座设计

研究了需要对地面目标进行连续覆盖的星座的设计问题．首先推导了对覆盖性能有重要影响的星间覆盖间隔时间和轨道面覆盖间隔时间的计算公式，通过算例针对不同配置的星座进行了计算，使用工程仿真软件STK验证了分析结果．通过理论分析、算例计算以及工程仿真为该类型星座设计提供了理论指导。     

无刷直流电动机的新型自适应模糊神经控制

 为无刷直流电动机提出了一种自适应模糊神经控制方法.这是一种建立在开关控制、模糊控制和自适应控制相结合基础上的控制方法,并用神经网络实现了模糊控制器和自适应机构.在无刷直流电动机的双闭环调速系统中,电流控制器是PI控制器;转速控制器是由1个开关控制器和1个包括自适应机构在内的模糊控制器相结合组成的,且用1个3层前向神经网络离线学习实现了模糊控制器,学习算法采用的是改进的BP算法.用1个单神经元通过在系统运行过程中的动态学习实现了自适应机构,学习算法选用了有监督的Hebb学习算法.由电机所处的运行阶段决定哪一个控制器工作.此控制算法的仿真结果说明,它使系统具有良好的动、静态特性和自适应性.     

浅议信息时代高校校报的发展

在以网络为代表的新媒体无孔不入的今天,传统的报纸面临着巨大的压力,同样新媒体对高校校报的冲击无疑也是巨大的。如何在竞争激烈的新媒体时代继续引领校园舆论,是所有高校校报人所引以深思的问题。列举了信息时代以网络为核心的新媒体对高校校报的冲击,特别是在读者获取信息的方式、读者阅读兴趣、读者阅读习惯等方面的巨大影响;分析了高校校报和网络媒体在内容、形式等方面各自的长处和特点,并初步提出了高校校报机构调整和加深内涵建设等应对措施。     

静止轨道卫星通信链路的预算与分析

星地链路计算作为卫星通信的重要技术，是卫星通信系统设计的基础和理论依据，直接决定了卫星通信系统的链路通信质量。由于影响卫星链路的因素很多，设计中存在一处不合理即使得整条星地链路不可用，造成巨大的损失。而且在实际设计中无法做到最理想的链路状态，往往需要在某方面有所取舍，这也是链路计算中的一大难点。基于目前国际通用的链路计算方法，将星地链路上下行拆分，独立计算，综合分析，再结合实际工程经验，分析和计算实际工程案例，针对不同的链路配置给出相应合理的设计方法，可作为静止轨道通信卫星星地链路计算分析的参考。     

Evaluation and improvement of coastal GNSS reflectometry sea level variations from existing GNSS stations in Taiwan

Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1?m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10?cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7?cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used.     

Global ionospheric scintillations revealed by GPS radio occultation data with FY3C satellite before midnight during the March 2015 storm

Global observations of S4 amplitude scintillation index by the GPS Occultation Sounder (GNOS) on FengYun-3 C (FY3C) satellite reveal global dynamic patterns of a strong pre-midnight scintillations in F-region of the ionosphere during the St. Patrick’s Day geomagnetic super storm of 17–19 March 2015. The observed strong scintillations mainly occurred in the low latitudes, caused by equatorial plasma bubbles. During the main storm phase (March 17), the scintillations were first triggered in the New Zealand sector near 160°E longitudes, extending beyond 40°S dip latitude. They were also enhanced in the Indian sector, but significantly suppressed in East Asia near 120°E longitude and in Africa around 30°E longitude. During the initial recovery phase (March 18–19), the global scintillations were seldom observed in GNOS data. During the later recovery phase (after March 19), the scintillations recovered to the pre-storm level in Indian, African, and American sectors, but not in East Asian and any of Pacific sectors. These results closely correlate with observations of the density depletion structures by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite, and ground-based instruments. Such consistency indicates reliability of our scintillation sensing approach even in a case-by-case comparison study. The prompt penetration electric field and disturbance dynamo electric field are suggested as the main factors that control the enhancement and inhibition of the scintillations during the storm, respectively.