适应拓扑变化的拥塞最小化网络更新策略

软件定义网络的出现推动了航空集群机载网络的发展，同时也为机载网络的一致性更新带来了挑战。针对拓扑变化导致的网络更新期间可用路径失效问题，提出适应拓扑变化的拥塞最小化网络更新策略。首先，为减少可用路径失效带来的数据包丢失，在更新之前采用重路由机制进行处理；然后，针对重路由机制可能引起的网络拥塞，设计了贪婪流迁移算法缓解拥塞；最后，通过瞬时拥塞最小化更新算法完成整个网络更新。仿真结果表明：与传统的拥塞一致性更新算法相比，所提更新策略用规则开销、瞬时网络拥塞方面的少量提高换取了网络更新期间数据包丢失的显著降低。     

基于可靠性分析的立方星网络维护架构优化

立方星编队或星座构成分布式空间传感器网络，可提高立方星执行复杂空间任务的能力。然而立方星易发生故障，其故障时间不确定性也导致了传感器网络性能的不稳定，这凸显了对立方星网络进行在轨维护的重要性。考虑立方星传感器网络的功能维持问题，描述了一种网络维护架构，通过定期发射、在轨备份立方星以及时更换故障立方星，从而提高网络对单星随机失效事件的快速响应与恢复能力。建立了该架构的运行成本模型，包括固定成本、储存成本和短缺成本。收集整理了真实的立方星寿命数据，并使用最大化拟合优度参数估计方法得到最优立方星寿命的随机模型。采用基于蒙特卡罗仿真的遗传算法优化备用立方星的补给时刻和补给数量，在备份成本与系统性能下降所带来的损失之间进行权衡，使得系统的综合收益最优。     

Evolution analysis of a UAV real-time operating system from a network perspective

With the flourishing development of Unmanned Aerial Vehicles (UAVs), the mission tasks of UAVs have become more and more complex. Consequently, a Real-Time Operating System (RTOS) that provides operating environments for various mission services on these UAVs has become crucial, which leads to the necessity of having a deep understanding of an RTOS. In this paper, an empirical study is conducted on FreeRTOS, a commonly used RTOS for UAVs, from a complex network perspective. A total of 85 releases of FreeRTOS, from V2.4.2 to V10.0.0, are modeled as directed networks, in which the nodes represent functions and the edges denote function calls. It is found that the size of the FreeRTOS network has grown almost linearly with the evolution of the versions, while its main core has evolved steadily. In addition, a k-core analysis-based metric is proposed to identify major functionality changes of FreeRTOS during its evolution. The result shows that the identified versions are consistent with the version change logs. Finally, it is found that the clustering coefficient of the Linux OS scheduler is larger than that of the FreeRTOS scheduler. In conclusion, the empirical results provide useful guidance for developers and users of UAV RTOSs.     

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。     

Crop parameters estimation by fuzzy inference system using X-band scatterometer data

Learning fuzzy rule based systems with microwave remote sensing can lead to very useful applications in solving several problems in the field of agriculture. Fuzzy logic provides a simple way to arrive at a definite conclusion based upon imprecise, ambiguous, vague, noisy or missing input information. In the present paper, a subtractive based fuzzy inference system is introduced to estimate the potato crop parameters like biomass, leaf area index, plant height and soil moisture. Scattering coefficient for HH- and VV-polarizations were used as an input in the Fuzzy network. The plant height, biomass, and leaf area index of potato crop and soil moisture measured at its various growth stages were used as the target variables during the training and validation of the network. The estimated values of crop/soil parameters by this methodology are much closer to the experimental values. The present work confirms the estimation abilities of fuzzy subtractive clustering in potato crop parameters estimation. This technique may be useful for the other crops cultivated over regional or continental level.     

先进通用飞机航电系统概述

阐述了通用飞机航空电子系统的发展及其综合化的系统架构,介绍了Smart Deck系统和Top Deck系统这两款先进通飞航电系统的设计特点、系统架构以及两款先进系统的共性,最后对通用飞机航电系统的发展提出了一些展望。     

RS-232、RS-485/USB转换器的最简设计

由于USB总线的诸多优点,以传统的RS-232接口为数据通信通道的外部设备正越来越多地朝着采用USB总线的方向发展,设计一种内置式或外挂式的双向RS-232/USB转换器很有必要。本文重点介绍一种以专用芯片FT8U232AM为转换控制器的最为简洁的RS-232/USB转换器设计方案。     

通用型舰载支援飞机的模块化布局设计概念

简要介绍了模块和模块化的基本概念，依据模块化设计的基本思想和步骤对通用支援飞机进行了系统分解和模块划分，详细地描述了通用型舰载支援飞机从系统分解、通用要素提取、非典型要素处理到模块组合的设计思路，从总体角度设计了一种模块化布局的通用型舰载支援飞机，并建立起三维模型。     

基于神经网络的精确末制导律研究

针对动能杀伤武器重量极小化问题，基于神经网络技术、动态逆补偿法和非线性优化法，研究了两种精确末制导律，一种采用FFBP神经网络学习一要制导方程动态逆实现精神制导，另一种采用FFBP神经网络学习非线性优化解实现精确制导，仿真分析表明，前者对目标加速度估计误差过于敏感，无法实现；而后者在目标加速度有误差时仍能实现精确制导，估于偏置比例导引，并可以使动能杀伤武器重量极小化。     

基于多层前向神经网络的模拟电路故障诊断

文中提出把一个神经网络应用到电路故障诊断的故障字典法中,以提高故障诊断的适应能力。这样,就使得字典法不仅适用于电路的故障情况,还提高了故障诊断的有效性。模拟结果显示这种方法是有效的。