Evaluation of a regional real-time precise positioning system based on GPS/BeiDou observations in Australia

The performance of real-time (RT) precise positioning can be improved by utilizing observations from multiple Global Navigation Satellite Systems (GNSS) instead of one particular system. Since the end of 2012, BeiDou, independently established by China, began to provide operational services for users in the Asia-Pacific regions. In this study, a regional RT precise positioning system is developed to evaluate the performance of GPS/BeiDou observations in Australia in providing high precision positioning services for users. Fixing three hourly updated satellite orbits, RT correction messages are generated and broadcasted by processing RT observation/navigation data streams from the national network of GNSS Continuously Operating Reference Stations in Australia (AUSCORS) at the server side. At the user side, RT PPP is realized by processing RT data streams and the RT correction messages received. RT clock offsets, for which the accuracy reached 0.07 and 0.28?ns for GPS and BeiDou, respectively, can be determined. Based on these corrections, an accuracy of 12.2, 30.0 and 45.6?cm in the North, East and Up directions was achieved for the BeiDou-only solution after 30 min while the GPS-only solution reached 5.1, 15.3 and 15.5?cm for the same components at the same time. A further improvement of 43.7, 36.9 and 45.0 percent in the three directions, respectively, was achieved for the combined GPS/BeiDou solution. After the initialization process, the North, East and Up positioning accuracies were 5.2, 8.1 and 17.8?cm, respectively, for the BeiDou-only solution, while 1.5, 3.0, and 4.7?cm for the GPS-only solution. However, we only noticed a 20.9% improvement in the East direction was obtained for the GPS/BeiDou solution, while no improvements in the other directions were detected. It is expected that such improvements may become bigger with the increasing accuracy of the BeiDou-only solution.     

紧缩场测试扫描架平面度控制系统研制

扫描架是紧缩场现场校准系统的关键测试设备。扫描架扫描平面度是影响校准准确度的关键指标。本文针对自研的扫描区域为φ6m的大型极化扫描架，设计了一套扫描架平面度实时补偿系统。该实时补偿系统可以实时检测扫描架扫描平面相对于基准平面的位置偏差，并通过伺服补偿机构完成补偿。测试结果表明该实时补偿系统可以准确、快速完成平面度的补偿，与半实时补偿方式相比具有更高的效率及精度。目前，该系统已成功应用于紧缩场现场校准。     

分布式卫星系统仿真平台研究现状与技术分析

支持分布式卫星系统(DSS)开发和实验的仿真平台是DSS技术发展的关键技术之一,本文对DSS仿真平台现状和关键技术进行了分析。首先对比分析了现有3种典型的仿真平台,认为为追求尽可能高的逼真度,实时分布式仿真成为必然。继而从分布式计算角度分析了实时分布式仿真面临的分布性、实时性、仿真部件互操作性和可重用性的问题,而中间件技术可以很好地解决这些问题。最后讨论了中间件实现模式,并分析了中间件在DSS仿真中3种可能的应用方式。     

基于PCI总线的PC机再入遥测站设计

根据再入遥测的特点 ,提出基于 PCI总线和 Windows平台的 PC机再入遥测站的体系结构 ,重点对其关键技术即多通道高速数据的实时传输与存储技术进行研究     

实时精确定轨的自校准方法

实时精确定轨的迫切性越来越成为航天技术任务发展所关注的问题。本文将轨道约束“EMBET”自校准技术^[1,2]推广到实时轨道确定处理；在不断地获取对航天器轨道测量数据的过程中，递推地估算和修正观测数据的系统误差，又实时地为用户提供精确的轨道状态参数或轨道根数。     

知识作业的内涵辨析与界定

借鉴泰勒对工作（task）的定义，结合现代认知科学信息加工、问题解决等理论，在分析比较知识作业与操作作业、知识作业与脑力劳动以及知识作业与问题解决的基础上，适应知识经济时代生产率提高的要求，从管理工程与工效、信息加工、问题解决三个角度给出知识作业的内涵，分别为：知识作业是“一连串的动作”，心智操作是知识作业过程的“动素”；知识作业是人脑的信息加工和计算过程，心智操作是知识作业的“算法”；知识作业是根据作业目标所确定的心智操作序列，包括结果的规范化输出。     

飞机穿越微下击暴流起飞特性实时仿真研究

以大型客机为例，对飞机穿越微下击暴流的起飞飞行特性进行了实时数字，实时混合仿真及人机半物仿真研究，分析不同风场和不同进风高度对有，无人操纵飞行的航迹特性及相应状态变量响应特性的影响，探讨了飞机起飞飞行的安全性及正确操纵策略，最后给出了一些结论。     

实时数据处理技术在稳定裕度试飞中的应用

介绍了稳定裕度试飞流程和稳定裕度实时数据处理软件的设计思路,讨论了稳定裕度实时数据处理系统的数据流程和如何建立飞行试验数据库,最后给出了系统经过试飞验证后的几点结论。     

DSP的数学原理及在实时系统的应用

制造系统里所用的微处理器中，单片机只能做逻辑处理和简单数学计算，而数字信号处理器（DSP）可进行相当复杂的数学处理。本文概述DSP的数学原理及其技术特点，介绍了基于DSP智能控制器在制造业中实时测控系统的应用实例。     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.