风云二号卫星 CDAS 原始云图解调器

在传统四次方环基础上提出了一种适用于快捕的新方法——四次方环开关法;根据这一原理研制的风云二号ＣＤＡＳ原始云图解调器具有捕获快,捕捉带宽,误码率性能好等特点;经测试及实用证明,此解调器性能优良,完全能满足实际需要。     

卫星云图数据的同步技术

卫星云图的帧周期变化,数据是突发性的。为了提取帧同步信号,研制出“定位孔径技术”,可靠地提取帧同步信号。利用孔径技术的子帧保护,应用于实际系统,能连续、稳定、可靠的工作。     

结冰云雾参数对冰与固壁间剪切强度影响的初步研究

基于结冰风洞实验段,建立了冰与固壁间黏附界面剪切强度测量实验装置,获得了合理的剪切强度范围。在0.3 m×0.2 m结冰风洞实验段内开展了冰与固壁间黏附界面剪切强度的测量实验。掌握了结冰环境温度、平均水滴直径等结冰云雾参数对冰与固壁间黏附剪切强度的影响规律。研究表明:结冰环境温度为-15~-10 ℃间出现了剪切强度极大值。来流速度越大,水滴的惯性力越大,水滴间的间隙越容易被填充,冰与固壁间剪切强度也就越大。平均水滴直径(MVD)为35 μm附近出现了剪切强度极小值,水滴直径越小,水滴之间的间隙就越小,结冰就越致密。水滴直径越大,水滴越容易发生平铺,水滴之间的间隙就容易被填充,反而造成剪切强度增大。      

Real-time zenith tropospheric delays in support of numerical weather prediction applications

The Geodetic Observatory Pecný (GOP) routinely estimates near real-time zenith total delays (ZTD) from GPS permanent stations for assimilation in numerical weather prediction (NWP) models more than 12 years. Besides European regional, global and GPS and GLONASS solutions, we have recently developed real-time estimates aimed at supporting NWP nowcasting or severe weather event monitoring. While all previous solutions are based on data batch processing in a network mode, the real-time solution exploits real-time global orbits and clocks from the International GNSS Service (IGS) and Precise Point Positioning (PPP) processing strategy. New application G-Nut/Tefnut has been developed and real-time ZTDs have been continuously processed in the nine-month demonstration campaign (February–October, 2013) for selected 36 European and global stations. Resulting ZTDs can be characterized by mean standard deviations of 6–10 mm, but still remaining large biases up to 20 mm due to missing precise models in the software. These results fulfilled threshold requirements for the operational NWP nowcasting (i.e. 30 mm in ZTD). Since remaining ZTD biases can be effectively eliminated using the bias-reduction procedure prior to the assimilation, results are approaching the target requirements in terms of relative accuracy (i.e. 6 mm in ZTD). Real-time strategy and software are under the development and we foresee further improvements in reducing biases and in optimizing the accuracy within required timeliness. The real-time products from the International GNSS Service were found accurate and stable for supporting PPP-based tropospheric estimates for the NWP nowcasting.     

一种基于层次聚类的空间非合作目标重构方法

由于激光传感器内在的缺陷，获得的非合作目标原始点云数据往往处于一个分布不均匀的状态，这就对后续的高质量非合作目标表面重构带来了很大的挑战.提出了一种基于全局约束的局部层次聚类方法来提升非合作目标点云分布的连续性.该方法主要可分为两步：1.基于全局约束的自适应八叉树三维空间分解，2.基于全局约束的层次聚类.第一步的主要目的是为了降低算法的复杂度，第二步则将分布不均匀的点集转化为均匀分布的状态.本文在三个非合作目标模型上进行了实验.实验的可视化结果与定量计算结果均验证了该方法的有效性.     

Predicting the vulnerability of spacecraft components: Modelling debris impact effects through vulnerable-zones

The space environment around the Earth is populated by more than 130 million objects of 1 mm in size and larger, and future predictions shows that this amount is destined to increase, even if mitigation measures are implemented at a far better rate than today. These objects can hit and damage a spacecraft or its components. It is thus necessary to assess the risk level for a satellite during its mission lifetime. Few software packages perform this analysis, and most of them employ time-consuming ray-tracing methodology, where particles are randomly sampled from relevant distributions. In addition, they tend not to consider the risk associated with the secondary debris clouds. The paper presents the development of a vulnerability assessment model, which relies on a fully statistical procedure: the debris fluxes are directly used combining them with the concept of vulnerable zone, avoiding the random sampling the debris fluxes. A novel methodology is presented to predict damage on internal components. It models the interaction between the components and the secondary debris cloud through basic geometrical operations, considering mutual shielding and shadowing between internal components. The methodologies are tested against state-of-the-art software for relevant test cases, comparing results on external structures and internal components.     

充液挠性航天器姿态机动控制的多目标优化

针对充液挠性航天器姿态快速机动、快速稳定的控制要求,为减小姿态机动对挠性附件振动和液体晃动的激发,设计了一种基于正弦型加加速度的姿态机动路径规划方法。为进一步提高姿态控制性能,提出了一种基于云多目标粒子群算法的姿态控制器参数和机动路径参数联合优化方法。以最小化充液挠性航天器三轴姿态达到指定指向精度的时间以及三轴姿态稳定度,构建多目标优化模型,并应用云多目标粒子群算法求取姿态控制器参数和机动路径参数的Pareto最优解。仿真结果表明:采用多目标联合优化算法得到的控制器与路径参数,能够有效减小液体晃动和挠性附件振动,显著提高充液挠性航天器大角度姿态机动的快速性和稳定性。     

大型不规则椭球回转面的曲面重构与仿真加工

提出了大型不规则椭球回转面的一种新的曲面重构与仿真加工方法。基于GeomagicStudio软件,处理大型不规则椭球回转面的采集数据点云,重构了实测曲面的等距面模型;采用Pro/E对实测曲面的等距面模型进行等距操作,生成实测曲面模型;利用GeomagicQualify软件对实测曲面的等距面模型相对于原始数据点云,以及实测曲面模型相对于理论曲面模型进行误差分析;最后利用Pro/NC模块对实测曲面模型进行数控编程和仿真加工。研究结果表明,该方法提高了大型不规则椭球回转面的曲面重构精度,生成的标准数控加工程序具有可移植性,解决了原加工方法对专用设备的依赖。     

Systematic centroid error compensation for the simple Gaussian PSF in an electronic star map simulator

Simulated star maps serve as convenient inputs for the test of a star sensor, whose standardability mostly depends on the centroid precision of the simulated star image, so it is necessary to accomplish systematic error compensation for the simple Gaussian PSF（or SPSF, in which PSF denotes point spread function）. Firstly, the error mechanism of the SPSF is described, the reason of centroid deviations of the simulated star images based on SPSF lies in the unreasonable sampling positions（the centers of the covered pixels） of the Gaussian probability density function. Then in reference to the IPSF simulated star image spots regarded as ideal ones, and by means of normalization and numerical fitting, the pixel center offset function expressions are got, so the systematic centroid error compensation can be executed simply by substituting the pixel central position with the offset position in the SPSF. Finally, the centroid precision tests are conducted for the three big error cases of Gaussian radius r = 0.5, 0.6, 0.671 pixel, and the centroid accuracy with the compensated SPSF（when r = 0.5） is improved to 2.83 times that of the primitive SPSF, reaching a 0.008 pixel error, an equivalent level of the IPSF. Besides its simplicity, the compensated SPSF further increases both the shape similarity and the centroid precision of simulated star images, which helps to improve the image quality and the standardability of the outputs of an electronic star map simulator（ESS）.     

一种基于云模型优化的飞行器参数辨识算法

极大似然估计方法(ML)在飞行器参数辨识中得到了广泛应用,该方法需要预先推导灵敏度方程,进而求解灵敏度矩阵,在应用过程中比较繁杂,且容易陷入局部最优。提出一种基于云模型优化的飞行器参数辨识算法,根据极大似然估计原理,利用云模型的优化理论对极大似然函数进行优化,从而得到待辨识参数值。该算法不必推导灵敏度矩阵,对初值要求不高,应用便捷,且保留了云模型优化的特点,收敛速度较快、不易陷入局部最优。以Twin Otter飞机为例对算法进行验证。结果表明:算法易于实现、辨识结果精度较高、收敛速度较快,不易陷入局部最优。