基于TTE端系统的时钟同步设计与实现

随着航空电子体系架构的日益更新,航空机载总线技术得到了飞速发展.时间触发以太网作为新一代的航空总线适合在分布式综合模块化电子系统中应用.时钟同步机制是该网络的核心技术,通过该技术建立的高精度全局同步时钟是保障TTE的数据通信强实时性和确定性的先决条件.本文在分析研究TTE时钟同步算法的基础上,提出了符合SAE AS6802协议标准的TTE端系统的时钟同步机制的设计方案,并在FPGA硬件上得以实现.     

基于时间触发架构的系统通信设计应用研究

本文详细介绍了基于时间触发架构的应用系统通信模型设计方法：结合某型飞机综合数据管理系统（IDMS）应用功能的通信需求,利用“PDevelopmentCluster系统设计工具,构建基于时间触发协议（TTP）的IDMS通信系统仿真模型。TTP精确的全局时钟同步可以为系统提供精确的时钟和单元之间的精确同步,协议的容错机制为...     

我国航天测控网发展构想

本文首先综述了我国测控网的发展过程和现状，然后根据我国航天发展规划，探讨了测控网所面临的挑战和问题。针对这些问题提出了诸如提高测控网精度、覆盖率、测控网运行效率的解决措施。     

具有相依特性的航天测控网稳定性分析

随着信息技术的不断提升,航天测控网各系统中的耦合和依赖变得越来越强烈。针对这种具有相依特性的测控网络的稳定性问题,提出借助于相依网络的分析方法,根据信息在测控网中所起的作用,对航天测控网相依特性进行分析、研究,特别是相依网络的级联失效过程进行稳定性分析。将航天测控网划分为具有相依特性的数据信息和控制信息,通过针对单侧网络进行蓄意攻击,研究不同控制信息模式下航天测控系统的稳定性,提出构建稳定、高效的测控网的方法。仿真结果表明,在数据信息遭受攻击时,合理规划控制信息形态并减小控制信息规模,能够有效保障航天测控系统的稳定性。     

基于局域网的分布式实时处理系统在航天测控领域中的应用研究

对TCP／IP网络技术及异步串行通信技术在航天测控领域中的应用进行了研究分析，并结合实际应用，介绍一个基于局域网的分布式实时系统软件的实现，介绍了该系统实现时钟同步、系统状态监视和多机调度、数据通信、扩充应用程序接口以及系统配置的情况。该软件的数据通信部分，可根据用户所填信息帧的信息路由码，实现用户信息在整个局域网的自动传输。实践证明，该方法正确可靠，使用方便，实时性强。     

船岸网络时延测量误差原因分析

简单介绍了测量船船岸通信网络组成,重点介绍了NTP（网络时间协议）和PTP（精密时间协议）这2种网络时间同步协议。针对改建后的船岸网络时延测量误差进行分析和研究,提出基于TWSTFT（卫星双向时间频率传输）技术模型的网络时延测量方法,测量结果误差小于3ms,满足测控任务实时性要求,为提高测控网的测控精度提供有益参考。     

量子密钥通信在分布式航天测控网中的应用研究

随着分布式航天测控网技术的不断发展,分布式航天测控网面临着信息安全问题.本文通过分析和研究各种信息加密技术,针对经典加密技术不能保证信息绝对保密性的弊端,考虑利用以量子力学为基础的量子密钥分配技术来保证测控信息传输的绝对安全.基于密钥这种"绝对保密"的方法与分布式航天测控网技术结合的思想,本文提出了量子密钥通信与分布式航天测控网相结合的密钥分配模型.     

飞行仿真系统网络传输与同步技术

网络通信是分布环境下飞行仿真系统需要解决的关键技术,包括网络传输量和时钟同步等。网络传输量方面,采用DR模型降低了网络数据更新频率,减少了数据通信量,并采用数据封包、解包的方法降低了网络频繁调用带来的时间损耗;时钟同步方面,采用了硬件同步电路和软件高性能时钟相结合的时钟同步方案,确保了飞行仿真系统时间推进的严格同步。在此基础上,构建了基于适配器模式的、支持多协议的通信引擎网络中间件,将顶层应用和底层通信进行有效隔离,降低了应用层开发量,加快了系统集成效率,在多型飞机模拟器中得到了应用。     

基于Internet的航天测控网中数据传输公平性仿真研究

随着Internet的不断发展,可以考虑利用Internet作为我国现有航天测控网的补充和扩展,对航天器进行测控,大幅度提高我国航天测控网的覆盖度。但是在数据传输方面,基于Internet的航天测控网则面临着传输不公平性问题。该问题是由UDP业务增长和TCP拥塞控制友好性原则及其他原因造成的,可能导致数据传输的流量过低。提出了两种简单方法来降低UDP对TCP造成的不公平性并试图改善TCP流量过低的情况。仿真结果表明,这种改进思路具有积极的意义,值得在该方向上作进一步探索。     

基于时钟同步的航空发动机分布式试验测控系统的研究

本文应用基于NTP协议的时钟同步方法和主从服务器方式的时钟同步实现策略，研究了基于时钟同步的航空发动机分布式试验测控系统的层次结构与系统集成，并在航空发动机高空试验台多前端测控系统试验中获得了成功的应用。     

基于随机网络演算的TTE网络时延分析

时间触发以太网(TTE)是一种新颖的混合型时间触发和事件触发的通信网络,通过引入时间触发(TT)流量,增强了航空电子全双工(AFDX)交换式以太网的确定性。虽然TT流量具有完全的时间确定性,但是与AFDX中虚拟链路(VL)兼容的速率约束(RC)流量仍具有一定非确定性。传统用于AFDX网络实时性能分析的方法在考虑TT流量固定分区调度时隙的影响下已不再适用,为了保障RC流量的实时性能,分别提出了基于确定性网络演算和随机网络演算两种延迟分析模型。在确定性网络演算下,通过构造TT流量的聚合到达曲线和RC流量的服务曲线以得到RC的确定性延迟上界;在随机网络演算下,通过切诺夫(Chernoff)边界定理构造RC流量的两状态伯努利分布模型,得到概率保证下的延迟上界。对比实验结果表明:随机网络演算模型可以有效减小确定性网络演算模型对RC流量性能分析的悲观性,同时从一定程度上验证了两种理论分析模型的正确性。     

AFIT neural network research

A brief summary of research done at the Air Force Institute of Technology (AFIT) in the area of neural networks is provided. It has been shown that backpropagation, used for feedforward artificial neural networks, is just a degenerate version of an extended Kalman filter, and that networks can do about as well as the optimum statistical classification technique. A method of finding the importance of features for use by a neural network classifier has been determined. Techniques for using neural networks for image segmentation have been developed. In optical pattern recognition, techniques that allow the processing of real FLIR (forward-looking infrared) images with existing binary spatial light modulators have been devised. An optical direction of arrival detector applicable to laser illumination direction determination has been designed and tested; the design is similar to a fly's eye. Coated mirrors for the optical confocal Fabry-Perot interferometer have been designed, specified, fabricated, and installed. Significant progress has been made in the use of neural networks for processing multiple-feature sets for speech recognition     

The network centric test system

Network topology is an important choice for the test system designer. There are several to choose from and each has benefits. A comparison of topologies is made based on the benefits and drawbacks for various usage situations. Some of the topologies of interest are: placing the instrumentation and the controller on the corporate intranet; using switching hubs for traffic isolation; using a second LAN connection in the test system controller as a private network for instrumentation; placing a router between the intranet and the test system controller; and widely distributing test assets. Test asset visibility to the rest of the network has both security and test integrity implications. Trading off the benefits of ready access and observation (which promotes collaboration) against system visibility needs to be carefully examined. Several use cases will be presented for examination: simply connected user; semi-automated test; fully automated test; and remote collaboration for system problem-solving.     

基于人工神经网络的静子叶片优化设计

采用NURBS参数化构型技术以及人工神经网络技术,对某两级风扇的第二级静子根部叶型进行优化改型。优化后,非设计点处该静子根部至中部流动得到较大改善,总压恢复系数有一定的提高。风扇总压比有较大增加,绝热效率基本不变。优化结果表明,该方法能够对静子叶片进行较好的优化改善,能够提高优化效率,减少优化时间,具有一定的实用价值。     

Service provision within the ATM network

Provision of ATM services has traditionally been seen as a function of government. Such a mechanism of provision is proving increasingly inadequate in the face of growing pressure of demand. This paper presents arguments for a radically new approach of European ATM, based upon a much greater private sector involvement.     

Percolation transition in temporal airport network

The air transportation system has a critical impact on the global economy. While the system reliability is essential for the operational management of air traffic, it remains challenging to understand the network reliability of the air transportation system. This paper focuses on how the global air traffic is integrated from local scale along with operational time. The integration process of air traffic into a temporally connected network is viewed as percolation process by increasing the integration time constantly. The critical integration time T_P which is found during the integration process can measure the global reliability of air traffic. The critical links at T_P are also identified, the delay of which will influence the global integration of the airport network. These findings may provide insights on the reliability management for the temporal airport network.     

航空发动机小波神经网络PID控制

提出了一种基于小波神经网络在线辨识的航空发动机比例-积分-微分(PID)控制算法.网络采用三层前向网络结构,以小波函数作为隐含层的激励函数.采用离线训练的方式训练出网络参数,以网络输出和输入之间的偏导数代替发动机模型输出和输入变量之间的偏导数,用以在线修正PID控制器的参数.阶跃响应测试表明,用小波神经网络整定的PID控制系统动态调节时间小于2s,稳态误差为零,在全飞行包线内均稳定正常工作.      

二值卷积神经网络综述

二值卷积神经网络（BNN）占用存储空间小、计算效率高,然而由于网络前向的二值量化与反向梯度的不匹配问题,使其与同结构的全精度深度卷积神经网络（CNN）之间存在较大的性能差距,影响了其在资源受限平台上的部署。至今,研究者已提出了一系列网络设计与训练方法来降低卷积神经网络在二值化过程中的性能损失,以推动二值卷积神经网络在嵌入式便携设备发展中的应用。因此,本文对二值卷积神经网络进行综述,主要从提高网络表达能力与充分挖掘网络训练潜力两大方面,给出了当前二值卷积神经网络的发展脉络与研究现状。具体而言,提高网络表达能力分为二值化量化方法设计、结构设计两方面,充分挖掘网络训练潜力分为损失函数设计与训练策略两方面。最后,对二值卷积神经网络在不同任务与硬件平台的实验情况进行了总结和技术分析,并展望了未来研究中可能面临的挑战。     

Neural network learning of low-probability events

In the problem of stationary target identification (STI) via millimeter wave (MMW) seeker radars in heavy clutter environments, it is often necessary to use nonparametric identification procedures, as detailed parametric models of clutter and target returns are generally unavailable. Neural networks provide an attractive approach to perform nonparametric identification. However, when identifying low-probability events, the computational overhead associated with training a neural network can become excessive. This is because low-probability events must be adequately represented in the training sample. We present a modified backpropagation training algorithm based on a likelihood ratio weighting function (LRWF) to train the neural network using a much smaller training set than that required using the standard backpropagation algorithm This algorithm is closely related to the importance sampling technique used in digital communication systems to obtain probability of error estimates by using a much smaller number of simulation runs than what is required with standard Monte Carlo simulation. The modified backpropagation technique results in a significant reduction in computational overhead in training the network, resulting from a substantial reduction in the size of the training set required to achieve a given level of performance. We demonstrate the performance of the algorithm on simulated data for the STI problem in MMW radar     

基于小波神经网络的PCBA检测

为了实现对PCBA的快速准确检测,提出了基于小波神经网络的检测模型,分析了网络的拓扑结构.仿真显示,该检测模型的误差小,精确度高,检测速度快,提高了SMT生产线上的一次通过率的可靠性.