利用BP网络校正跟踪接收机的相位漂移

针对跟踪接收机不同通道之间相位差的漂移问题,提出利用BP神经网络作为校正环节来消除此相位漂移。通过原理分析用数学方法描述跟踪接收机存在的相位漂移问题,介绍BP神经网络的网络模型和一种动态全参数自适应学习算法,进而提出基于BP神经网络的相位漂移校正算法。仿真结果表明,该方法的相位校正效果较好,不仅保证了系统的角跟踪精度,而且实现了高度的自动化。     

Application of neural networks to South African GPS TEC modelling

The propagation of radio signals in the Earth’s atmosphere is dominantly affected by the ionosphere due to its dispersive nature. Global Positioning System (GPS) data provides relevant information that leads to the derivation of total electron content (TEC) which can be considered as the ionosphere’s measure of ionisation. This paper presents part of a feasibility study for the development of a Neural Network (NN) based model for the prediction of South African GPS derived TEC. The South African GPS receiver network is operated and maintained by the Chief Directorate Surveys and Mapping (CDSM) in Cape Town, South Africa. Vertical total electron content (VTEC) was calculated for four GPS receiver stations using the Adjusted Spherical Harmonic (ASHA) model. Factors that influence TEC were then identified and used to derive input parameters for the NN. The well established factors used are seasonal variation, diurnal variation, solar activity and magnetic activity. Comparison of diurnal predicted TEC values from both the NN model and the International Reference Ionosphere (IRI-2001) with GPS TEC revealed that the IRI provides more accurate predictions than the NN model during the spring equinoxes. However, on average the NN model predicts GPS TEC more accurately than the IRI model over the GPS locations considered within South Africa.     

Comparison of standard TEC models with a Neural Network based TEC model using multistation GPS TEC around the northern crest of Equatorial Ionization Anomaly in the Indian longitude sector during the low and moderate solar activity levels of the 24th solar cycle

The highest Total Electron Content (TEC) values in the world normally occur at Equatorial Ionization Anomaly (EIA) region resulting in largest ionospheric range delay values observed for any potential Space Based Augmentation System (SBAS). Reliable forecasting of TEC is crucial for satellite based navigation systems. The day to day variability of the location of the anomaly peak and its intensity is very large. This imposes severe limitations on the applicability of commonly used ionospheric models to the low latitude regions. It is necessary to generate a mathematical ionospheric forecasting and mapping model for TEC based on physical ionospheric influencing parameters. A model, IRPE-TEC, has been developed based on real time low latitude total electron content data using GPS measurements from a number of stations situated around the northern crest of the EIA during 2007 through 2011 to predict the vertical TEC values during the low and moderate solar activity levels of the 24th solar cycle. This model is compared with standard ionospheric models like International Reference Ionosphere (IRI) and Parameterized Ionospheric Model (PIM) to establish its applicability in the equatorial region for accurate predictions.     

变体后缘的索网传动机构设计与分析

为了提高变体后缘的驱动效率,提出了一种可放大驱动力的索网传动机构.采用梁模型推导了单节点索网/基板弯曲变形的非线性微分方程,给出了基于有限差分法的迭代格式.数值模拟结果表明:索网机构比单索机构具有更高的驱动效率,降低了驱动器的最大驱动力;降低了基板的最大弯矩,且使最大弯矩点后移.最后,设计了单索和索网机构驱动钢板弯曲变形的实验装置,给出了钢板自由端垂直位移和外载关系的实验结果,结果表明当钢板等效偏转角的设计值为10°时,索网机构的最大驱动力比单索机构降低了41％.     

CCSDS高级在轨系统复接业务性能的分析

本论文分析了空间链路子网上的异步业务特别是复接业务的性能，建立了一种异步信息模型，从而解决了平均包延迟，帧效率的问题。这个结果也适用于各种不同的信息配置下可获得的系统性能的上、下限。而且，本文还讨论了一组与执行相关的参数，如帧完成暂停时间（ｆｒａｍｅｃｏｍｐｌｅｔｉｏｎｔｉｍｅ＿ｏｕｔｐｅｒｉｏｄ），分析了它们对系统性能的影响     

基于贝叶斯网络的民航安全分析研究

安全在民用航空领域占有举足轻重的地位,直接影响民航企业的生存和发展。科学合理的安全分析便于及时发现民航领域存在的安全问题,预防航空事故诱发因素的萌生,提高民航安全管理的科学性和可操作性。根据民航安全的特点,建立了基于故障树的多态贝叶斯网络系统安全分析模型,综合运用诊断推理和因果推理形式,实现了定性与定量相结合的民航安全分析,通过航空灾难的实例验证了方法的有效性。在此基础上,提出采用区间型贝叶斯网络进行民航安全分析,克服了其他方法只能分析计算单点概率值的局限性,比传统的安全评估更客观,更有说服力。     

认知无线电网络中基于几何规划的分布式功率控制

功率控制对于允许次用户和主用户之间频谱共享的认知无线电网络来说是关键的,针对具有干扰限制的认知网络最大总容量得到一种最优的分步式功率控制策略,对于系统效用的非凸性,引入几何规划把非凸最优化问题转换为凸最优化问题,引入辅助变量和额外等式约束,把效用之间的关联转化为约束之间的关联,提出了功率控制策略的解决方法,显示了整体最...     

基于神经网络的翼盒结构响应重构方法应用

翼盒结构复杂，航行中承载条件恶劣，利用有限测点信息重构其它位置响应对于实时健康监测具有很强的现实意义。通过误差反向传播神经网络训练得到响应之间的非线性关系，建立基于神经网络的响应重构方法，开展有限元分析对其进行数值仿真验证，并将该方法应用于实测随机激励环境下翼盒典型承力结构的响应重构及损伤定位与判断分析。结果表明：采用该方法重构出的预测响应功率谱密度的均方根相对误差不超过1.90 dB，主要频点误差小于10%；判断出翼盒关键测点e 的损伤或故障发生在所截取片段数据3 s 后，其故障特征频率为240 Hz 左右，该方法应用于响应重构预示及健康监测分析具有可行性。     

畸变信号重建的神经网络方法

分析了通信信道在传输信号时使信号发生畸变的现象，提出用径向基函数神经网络方法描述信道的畸变特征，并利用此方法作了仿真计算，结果表明用神经网络方法进行畸变信号重建效果较好。     

无线局域网中的核心技术及其应用

无线局域网对计算机网络技术的进一步发展起到了深刻的影响。该文着重介绍了无线局域网中的关键技术———直序扩频技术的工作原理和系统结构,讨论了无线局域网的协议结构。在此基础上给出了一个无线扩频通信局域网的典型设计方案。此设计方案主要对某大型企业无线局域网的扩频通信部分的各具体参数进行了详细设计,为实际工程应用提供了可行性技术指导。