卫星天线热真空变形测量

针对在真空环境中进行高低温测量的难点和特点,提出了采用数字近景摄影测量技术在热真空中对卫星天线面板的高低温变形进行测量。成功地利用2台经过保护的专业像机组成双相机摄影测量系统,完成了天线热真空变形测量,解决了传统的测量手段无法在真空中进行测量的难题,型面变形测量精度达到0.1mm,满足了试验要求。     

Monitoring of the space system

We have performed monitoring of the space system that includes the Earth, the Moon, the Sun, and the GPS satellite group. We have discovered semi-diurnal and diurnal periodicities in the number of satellites detected as well as in the altitude, latitude and longitude by a GPS receiver. We have revealed tidal deformations related to changes in the Earth?s orientation with respect to the Moon and the Sun.     

Achievable debris orbit prediction accuracy using laser ranging data from a single station

Earlier studies have shown that an orbit prediction accuracy of 20 arc sec ground station pointing error for 1–2 day predictions was achievable for low Earth orbit (LEO) debris using two passes of debris laser ranging (DLR) data from a single station, separated by about 24 h. The accuracy was determined by comparing the predicted orbits with subsequent tracking data from the same station. This accuracy statement might be over-optimistic for other parts of orbit far away from the station. This paper presents the achievable orbit prediction accuracy using satellite laser ranging (SLR) data of Starlette and Larets under a similar data scenario as that of DLR. The SLR data is corrupted with random errors of 1 m standard deviation so that its accuracy is similar to that of DLR data. The accurate ILRS Consolidated Prediction Format orbits are used as reference to compute the orbit prediction errors. The study demonstrates that accuracy of 20 arc sec for 1–2 day predictions is achievable.     

Storm-time atmospheric density modeling using neural networks and its application in orbit propagation

Upper atmospheric densities during geomagnetic storms are usually poorly estimated due to a lack of clear understanding of coupling mechanisms between the thermosphere and magnetosphere. Consequently, the orbit determination and propagation for low-Earth-orbit objects during geomagnetic storms have large uncertainties. Artificial neural networks are often used to identify nonlinear systems in the absence of rigorous theory. In the present study, an attempt has been made to model the storm-time atmospheric density using neural networks. Considering the debate over the representative of geomagnetic storm effect, i.e. the geomagnetic indices ap and Dst, three neural network models (NNM) are developed with ap, Dst and a combination of ap and Dst respectively. The density data used for training the NNMs are derived from the measurements of the satellites CHAMP and GRACE. The NNMs are evaluated by looking at: (a) the mean residuals and the standard deviations with respect to the density data that are not used in training process, and (b) the accuracy of reconstructing the orbits of selected objects during storms employing each model. This empirical modeling technique and the comparisons with the models NRLMSIS-00 and Jacchia-Bowman 2008 reveal (1) the capability of neural networks to model the relationship between solar and geomagnetic activities, and density variations; and (2) the merits and demerits of ap and Dst when it comes to characterizing density variations during storms.     

Evaluation of three high-resolution satellite precipitation estimates: Potential for monsoon monitoring over Pakistan

Multi-sensor precipitation datasets including two products from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and estimates from Climate Prediction Center Morphing Technique (CMORPH) product were quantitatively evaluated to study the monsoon variability over Pakistan. Several statistical and graphical techniques are applied to illustrate the nonconformity of the three satellite products from the gauge observations. During the monsoon season (JAS), the three satellite precipitation products captures the intense precipitation well, all showing high correlation for high rain rates (>30 mm/day). The spatial and temporal satellite rainfall error variability shows a significant geo-topography dependent distribution, as all the three products overestimate over mountain ranges in the north and coastal region in the south parts of Indus basin. The TMPA-RT product tends to overestimate light rain rates (approximately 100%) and the bias is low for high rain rates (about ±20%). In general, daily comparisons from 2005 to 2010 show the best agreement between the TMPA-V7 research product and gauge observations with correlation coefficient values ranging from moderate (0.4) to high (0.8) over the spatial domain of Pakistan. The seasonal variation of rainfall frequency has large biases (100–140%) over high latitudes (36N) with complex terrain for daily, monsoon, and pre-monsoon comparisons. Relatively low uncertainties and errors (Bias ±25% and MAE 1–10 mm) were associated with the TMPA-RT product during the monsoon-dominated region (32–35N), thus demonstrating their potential use for developing an operational hydrological application of the satellite-based near real-time products in Pakistan for flood monitoring.     

基于人工神经网络的反射器型面精度预测

基于人工神经网络的预测方法,利用数量适当的有限元计算结果,建立人工神经网络模型,对反射器型面进行精度预测分析,得到在最小型面精度结果下的结构设计参数。计算结果显示训练好的神经网络模型能够较精确地预测格栅反射器的型面精度,节省计算时间,并且以型面精度最小为准则进行参数分析,能够指导反射器的结构设计。     

GRACE accelerometer calibration by high precision non-gravitational force modeling

The precise modeling and knowledge of non-gravitational forces acting on satellites is of big interest to many scientific tasks and missions. Since 2002, the twin GRACE satellites have measured these forces in a low Earth orbit with highly precise accelerometers, for about 15?years. Besides the significance for the GRACE mission, these measurement data allow the evaluation of modeling approaches and the improvement of force models. Unfortunately, before any scientific usage, the accelerometer measurements need to be calibrated, namely scale factor and bias have to be regularly estimated.In this study we demonstrate an accelerometer calibration approach, solely based on high precision non-gravitational force modeling without any use of empirically or stochastically estimated parameters, using our in-house developed satellite simulation tool XHPS. The aim of this work is twofold, first we use the accelerometer data and the residuals resulting from the calibration to quantitatively analyze and validate different non-gravitational force model approaches. In a second step, we compare the calibration results to three different calibration methods from different authors, based on gravity field recovery, GPS-based precise orbit determination, and based on modeled accelerations.We consider atmospheric drag forces and winds, as well as radiation forces due to solar radiation pressure, albedo, Earth infrared and thermal radiation (TRP) of the satellite itself. For TRP, we investigate different transient temperature calculation approaches for the satellite surfaces with absorbed power from the aforementioned radiation sources. A detailed finite element model of the satellite is utilized for every force, considering orientation, material properties and shadowing conditions for each element.For cross-track and radial direction, which are mainly affected by the radiative forces, our calibration residuals are quite small when drag is not super dominant (1–3?$\text{nm}/{\text{s}}^2$ for total accelerations around $\pm$50?$\text{nm}/{\text{s}}^2$). For these directions the calibration seems to perform better than the other compared methods, where some bigger differences were found. For the drag dominated along-track direction it is vice versa, here our method is not sensitive enough because the difference between modeled and measured drag is bigger (e.g. residuals around 10?$\text{nm}/{\text{s}}^2$ for total accelerations around $\pm$70?$\text{nm}/{\text{s}}^2$ for low solar activity). In along-track direction the orbit determination based methods are more sensitive and produce more reliable results. Results for the complete GRACE mission time span from 2003 to 2017 are shown, covering different seasonal environmental conditions.     

基于Pro/E特征造型技术的固体发动机装药燃面计算

以Pro／E软件为平台,借助Pro／E软件的特征造型功能及曲面论中的曲面插值法,完成了固体发动机装药燃面的推移模拟和燃面计算。通过比较计算所得的等速燃烧和不等速燃烧的燃面变化曲线。证明该方法具有较高的精度。     

卫星与地面测控系统协调设计研究

卫星运行需要地面测控系统的支持.通过对某些卫星运行与地面测控系统支持方面的实际分析,总结其设计研制和协调中不足,研究卫星系统与地面测控系统的协调设计,并提出相应建议,为我国的卫星发展作一些借鉴.     

“仿生学”沟槽减阻仿真分析及机理研究

"仿生学"沟槽结构在航空发动机叶片减阻和燃滑油系统减阻等领域有潜在的应用前景。为获得该结构构型参数和雷诺数对减阻效果的影响规律,通过对鲨鱼及海豚表皮特征进行仿生设计了横向和纵向沟槽,利用数值模拟方法对不同沟槽构型在不同雷诺数下的减阻效果开展了对比研究和机理分析。结果表明:横向和纵向沟槽构型减阻率均随雷诺数增大而减小,并且雷诺数影响占主导地位。对于横向沟槽构型,沟槽间距较大的构型沿程阻力占主导,在相对高雷诺数下减阻效果较好;沟槽数量较多的构型局部阻力占主导,在相对低雷诺数下减阻效果较好;无间距构型在相对低雷诺数下减阻效果最好,减阻率约为4.14%。对于纵向沟槽构型,减阻率比横向沟槽的高约1个百分点,雷诺数对减阻效果影响不大。