基于星间距离测量的高精度自主导航

研究利用地球卫星和月球卫星之间的测距信息进行自主导航的方法.基于三体摄动轨道动力学方程和星间测距信息,可以同时确定参与导航的地球卫星和月球卫星的绝对位置;但是在初始位置误差较大的情况下,导航系统的定位性能会受到影响.为了解决这一问题,提出基于"星间测距+紫外导航敏感器"的组合导航方法.采用该导航方法,能够在初始位置误差和紫外导航敏感器测量误差较大的情况下实现高精度自主导航.基于Cramer-Rao下界(CRLB)分析了组合导航系统的性能,并通过数学仿真验证了该导航方法的有效性.     

空间光学遥感器热控技术研究

分析了遥感器与卫星平台的热控差异,总结了近年来遥感器热控需求的变化,阐述了基于多学科集成的遥感器STOP设计模式,介绍了高精度/高稳定度温度控制、大功耗热量传输、深低温热量传输、Robust热控等适应遥感器热控需求的新技术研究及应用情况。对我国空间光学遥感器热控技术的研究具有一定借鉴意义。     

提高卫星导航性能的阵列参数估计算法

针对卫星导航信号参数估计性能严重影响导航定位精度,提出了一种利用电磁偶极子对提高信号波达方向和极化参数估计性能的方法。充分利用接收数据协方差矩阵,通过两次特征分解,由特征分解的特征值进行极化参数估计。利用小圆环子阵导向矢量得到波达方向的粗略而无模糊的估计,大圆环子阵导向矢量得到有模糊的估计,通过解模糊得到精确的无模糊的估计,从而大幅提高了到达角的估计精度。比较了单个圆环阵列和同心圆环阵列的参数估计性能,分析了参数估计精度对抗干扰性能的影响,仿真结果表明参数估计精度的提高有效改善了卫星导航抗干扰的性能。     

一种高动态卫星网络的拥塞控制算法

针对卫星网络通信路径发生改变引起往返时延突变,导致现有的拥塞控制机制中超时重传时间估计不准确,并对拥塞窗口计算产生不利影响的问题,提出一种基于链路长度的带宽估计TCPW\|BLC算法。该算法通过计算通信链路长度合理调整拥塞窗口、慢启动阈值及超时重传定时器中相关参数的增益因子,使拥塞控制算法在往返时延突变情况下仍保持较高吞吐量,适应卫星网络动态环境特性。NS2仿真结果表明,TCPW\|BLC算法相比TCPW算法在卫星网络中吞吐量性能提高了2.8%,有效降低了时延突变给拥塞控制机制造成的不利影响。     

运载火箭组装与测试远程协同信息平台技术

为适应未来高频度发射任务需求,在借鉴国内外远程协同及信息应用技术基础上,以中国运载火箭组装、测试及发射任务为背景,通过对功能需求和技术难点分析,设计了运载火箭组装与测试远程协同应用系统,对关键技术进行了分析和论述,为运载火箭远程测试、协同决策发射提供有效技术解决途径。     

基于labview的电涡流测距仪的设计

本文结合计算机等相关技术,提出了一种基于labview的电涡流传感器测量的方法。电涡流位移传感器存在非线性,人工标定存在误差,标定金属材料单一等矛盾,笔者通过实验与仿真研究来解决并在此基础上用labview软件实现了检测结果的界面显示。     

中国遥感卫星系统灾害监测能力研究

通过研究、归纳中国在气象、海洋、农业、减灾、资源、环境等方面的九类重大自然灾害的监测对空间遥感的应用需求,绘出了九类重大自然灾害在时间分辨率和空间分辨率上的相应分布图;介绍了中国遥感卫星系统的发展现状,绘制其对九类重大自然灾害监测的能力满足度曲线,在此基础上,预测了中国未来遥感卫星系统的灾害监测能力包线应具有的能力,提出了中国未来遥感卫星系统的能力配置及发展建议。     

Assessment of the impact of dimensionality reduction methods on information classes and classifiers for hyperspectral image classification by multiple classifier system

Identification of the appropriate combination of classifier and dimensionality reduction method has been a recurring task for various hyperspectral image classification scenarios. Image classification by multiple classifier system has been evolving as a promising method for enhancing accuracy and reliability of image classification. Because of the diversity in generalization capabilities of various dimensionality reduction methods, the classifier optimal to the problem and hence the accuracy of image classification varies considerably. The impact of including multiple dimensionality reduction methods in the MCS architecture for the supervised classification of a hyperspectral image for land cover classification has been assessed in this study. Multi-source airborne hyperspectral images acquired over five different sites covering a range of land cover categories have been classified by a multiple classifier system and compared against the classification results obtained from support vector machines (SVM). The MCS offers acceptable classification results across the images or sites when there are multiple dimensionality reduction methods in addition to different classifiers. Apart from offering acceptable classification results, the MCS indicates about 5% increase in the overall accuracy when compared to the SVM classifier across the hyperspectral images and sites. Results indicate the presence of dimensionality reduction method specific empirical preferences by land cover categories for certain classifiers thereby demanding the design of MCS to support adaptive selection of classifiers and dimensionality reduction methods for hyperspectral image classification.     

Characterization of lunar soils through spectral features extraction in the NIR

Recently launched hyper-spectral instrumentation with ever-increasing data return capabilities deliver the remote-sensing data to characterize planetary soils with increased precision, thus generating the need to classify the returned data in an efficient way for further specialized analysis and detection of features of interest. This paper investigates how lunar near-infrared spectra generated by the SIR-2 on Chandrayaan-1 can be classified into distinctive groups of similar spectra with automated feature extraction algorithms. As common spectral parameters for the SIR-2 spectra, two absorption features near 1300 nm and 2000 and their characteristics provide 10 variables which are used in two different unsupervised clustering methods, the mean-shift clustering algorithm and the recently developed graph cut-based clustering algorithm by Müller et al. (2012). The spectra used in this paper were taken on the lunar near side centering around the Imbrium region of the Moon. More than 100,000 spectra were analyzed.     

临近空间大气压力传感器现场校准装置研究

本文针对临近空间大气压力传感器现场校准需求,介绍了临近空间大气压力传感器现场校准装置工作原理, 进行理论分析与仿真,提出需突破的关键技术,给出了不确定度预估。