A Test Method for the Static/Moving State of Targets Applied to Airport Surface Surveillance MLAT System

Due to the particularity of its location algorithm,there are some unique difficulties and features regarding the test of target motion states of multilateration(MLAT)system for airport surface surveillance.This paper proposed a test method applicable for the airport surface surveillance MLAT system,which can effectively determine whether the target is static or moving at a certain speed.Via a normalized test statistic designed in the sliding data window,the proposed method not only eliminates the impact of geometry Dilution of precision(GDOP)effectively,but also transforms the test of different motion states into the test of different probability density functions.Meanwhile,by adjusting the size of the sliding window,it can fulfill different test performance requirements.The method was developed through strict theoretical extrapolation and performance analysis,and simulations results verified its correctness and effectiveness.     

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.     

基于运动特征和中心环绕模型的空对地车辆检测方法

平台的移动基于空基车辆检测以其视野广、速度快、适应性强等优点,近些年成为了智能交通和航空应急救援等领域内的一个热点课题。然而,在城市背景的交通环境下,由于复杂背景造成的干扰、车辆运动的不规律性以及光照等条件变化带来的噪声,有效地获取运动对象特征是空对地视觉监视方法面临的一个难题。为有效解决这一问题,提出了结合运动特征的中心环绕模型进行空对地车辆检测的算法。现有的空对地车辆检测算法,大多是针对固定的摄像头的情况下,基于运动特征进行检测,例如光流法、背景差法等。这些方法在对高速公路等背景相对较为简单的环境下获得了良好的检测结果,但当面对城市复杂背景条件或摄像头自身运动的状况时,难以有效地检测出运动目标。而在对颜色、强度等静态特征进行显著度分析的基础上,加入了对运动特征的分析,可以解决在复杂环境下准确提取车辆目标有效特征的问题。试验表明,相较于基于图像相减的检测算法和单一显著度算法,该算法可以获得更高的检测率与更低的误报率。     

The role of volcanic aerosols and relativistic electrons in modulating winter storm vorticity

Small changes in the vorticity of winter storms, responding to solar wind variations, are found in winters from 1957 to 2011, and are greater for winters with higher levels of stratospheric volcanic aerosols. Using 1993–2011 data, the response of the vorticity area index (VAI) is shown to be of larger amplitude when the days of minima in the relativistic electron flux (REF) precipitating from the radiation belts are used, instead of heliospheric current sheet (HCS) crossings, as key days in superposed epoch analyses. The HCS crossings mostly occur within a few days of the REF minima. The VAI is an objective measure of the area of high cyclonic vorticity, and for the present work is derived from ERA-40 and ERA-Interim reanalyses of global meteorological data. The VAI dependencies on the stratospheric aerosol content (SAC) and the REF are consistent with a model in which the ionosphere-earth current density (J_z) affects cloud microphysics. One of the ways in which J_z is modulated is by changes in stratospheric column resistance (S), which is increased by stratospheric aerosols. Because S is in series with the tropospheric column resistance (T), J_z modulation by REF requires that S be not negligible with respect to T. So the J_z modulation and the VAI response appear when the SAC is very high, or the REF reductions (which also increase S) are very deep, and when the product of the SAC and the reciprocal of the REF exceeds a threshold value dependent on T.     

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。