Improving orbit prediction accuracy through supervised machine learning

Due to the lack of information such as the space environment condition and resident space objects’ (RSOs’) body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs’ trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO’s orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.     

速率转台的角速率不确定度评定方法

利用不确定度的理论来评定速率转台的角速率不确定度。     

分布式数据采集控制系统的现状及发展趋势

综述了ＤＣＳ系统的形成，现状及今后的发展方向，阐明了应用远智能Ｉ／Ｏ改进ＤＣＳ系统的优越性及向ＦＣＳ系统的过渡。     

Co-registration of Chang’E-1 stereo images and laser altimeter data with crossover adjustment and image sensor model refinement

Topographic information is of fundamental importance for various scientific investigations in lunar and planetary exploration. To provide high-precision, seamless mapping capability, it is critical to co-register image and altimetry data, the two major data sources for topographic modeling. This paper presents a method for co-registration of Chang’E-1 (CE-1) stereo images and laser altimeter (LAM) data with crossover adjustment and refinement of the image sensor model. The crossover adjustment is tested in a larger area (0–60°N, 50–0°W); the image refinement and co-registration with LAM data are tested in an area (46.2–50.0°N, 31.8–28.8°W) within the larger area. Experimental results demonstrate that this co-registration reduces the mean differences of inconsistency from more than 200 m to just 3.21 m in the Z direction of object space. In image space, the mean errors of homologous points both in the column and row directions are reduced to below 0.1 pixel. This indicates that the proposed crossover adjustment of LAM data and refinement of the CE-1 stereo image model can effectively improve co-registration of the two data sets.     

基于航空货运网络结构的城市层级分析

航空货运网络是影响城市层级结构的重要因素之一,对其进行量化分析具有十分重要的理论和现实意义。根据2002—2008年中国航空货运数据库构建的中国航空货运网络,运用复杂网络分析的测度方法,以城市航空货运量比例为依据,将中国航空货运网络分成初始层级网络、中级层级网络和核心层级网络3个层次。基于航空货运网络视角,将中国通航城市分成核心、中级和边缘城市3类层级。通过对平均路径长度、聚类系数、度分布、密度等网络特征的分析,证明了3个层级城市所在的网络都具有小世界和无标度特性,研究表明中国城市层级结构具有金字塔特性,分布严重不均匀,值得关注。     

距离信息对DDFRC算法定位误差的影响与分析

在固定单站无源定位算法中,基于角度(Direct of Arrival)、角度变化率(Direct of Arrival Rate-of-Change)、多普勒频率(Doppler Frequency)和多普勒频率变化率(Doppler Frequency Rate-of-Change)4个观测信息实现定位(即DDFRC定位)算法仅通过单次观测即可实现对目标辐射源的定位。文中通过转移观测的卡尔曼滤波对定位结果进行平滑,较原有算法拥有更好的跟踪效果。同时,对定位误差进行了定量分析,并将距离信息引入算法的仿真分析之中,详细讨论了各个观测量误差在不同距离时对算法定位性能的影响,根据仿真结果,结合定位误差的定量分析对算法性能做出评价。通过仿真分析,得到了定位算法对不同距离下各参数的精度要求,从而为在实际系统中使用该定位算法提供了参考。     

基于TTE网络的分布式系统分区通信方法

针对新一代分布式IVMS及高可靠航电系统对通信网络的确定性通信要求，分析了符合ARINC653标准的分区间通信原理，研究TTE端系统缓冲方案，设计了分区间TTE通信映射配置，实现了分区间TTE通信驱动，建立了分区间TTE通信测试平台，通过实际测试表明，基于TTE网络的分布式系统分区通信方案有效可靠。     

一种PowerPC和FPGA结构的远程接口单元设计方法

远程接口单元（ RIU）已经是综合化模块化航空电子系统的重要组成部分。分析了分布式IMA架构下航空电子系统对远程接口的新需求,提出了一种基于PowerPC ＋FPGA结构的远程接口单元设计方法。通过设计方法不仅实现了单元综合多种I／O资源,还保证了单元具有一定的容错和可配置特性,并在远程接口关键技术方面取得了实质性的突破。     

国内常用分散式数据采集器的性能介绍

介绍了三种数据采集器，并对其性能进行比较。     

一种新型的分布式数据采集器(二)

4 系统结构和工作原理 900系列分布式数据采集系统由900系列数据采集模块、电源、通讯电缆、主机构成.可以在1.2 km的范围内,根据现场使用需要随意组成最少1个模块、20个测量点;最多不超过99个模块、1980个测量点(取决于模块)的测量系统.前端传感器输入信号可以是模拟信号(如温度、压力、电压、电流、应变等);也可以是数字信号(如开关状态监测、事件捕获、测频计数等).测量结果经模块内部A/D转换后,用RS485通讯方式,经屏蔽双绞线送至主计算机进行采集,并以固定的数据格式输出,用户可根据需要,采用相应的软件对采集到的信号进行处理.典型测量系统组成如图1所示.