基于层次化分类器的遥感图像飞机目标检测

在大量航空航天遥感图像中,快速发现和统计飞机目标并对其进行准确定位,在军事和民用方面均具有重要意义。结合遥感图像特点,针对飞机目标的特征,文章设计了一种基于层次化的分类器的遥感图像飞机目标检测方法。首先用基于哈尔（Haar）特征的底层AdaBoost分类器快速去除大部分非目标区域;然后用基于梯度方向直方图（Histogram of Oriented Gradient,HOG）特征的顶层支持向量机（Support Vector Machine,SVM）分类器进行精细检测。在分辨率为1m的遥感图像数据集上的实验结果表明,层次化分类器在保证较高检测率的前提下,大大降低了虚警率,可以有效解决遥感图像飞机检测问题。     

中国无地面控制点摄影测量卫星追述（一）——返回式摄影测量卫星

以无地面控制点条件下的摄影测量为背景,回顾了中国第一代、第二代返回式摄影测量卫星的研制历程,给出了相机的主要技术参数,介绍了研制的技术难点。从地形图制作精度的角度评价了中国第一代、第二代返回式摄影测量卫星的技术水平,给出了制作的立体影像图和等高线图。最后,与美国、俄罗斯（前苏联）、欧空局同类型的返回式卫星进行了比较。     

同步串行总线在通信卫星转发器中的应用

提出了一种适用于通信卫星转发器分系统测控数据传输的5线制同步串行总线,支持30个终端同时接入,改变了通信卫星平台传统的点对点式的遥测遥控信息传输方式,大大减少了通信舱内电缆数量;并在某通信卫星载荷舱上进行了应用,使卫星载荷舱质量减少几十千克,提升了卫星平台的有效载荷能力。文章设计的串行总线提供标准的接口电路,有利于有效载荷设备的扩容,可以推广至更多的有效载荷设备,构成其之间的测控信息网络。     

卫星安全性设计的分析评价策略

卫星安全性设计往往采用故障模式与影响分析(FMEA)方法,与可靠性设计同时开展。文章分析了卫星可靠性和安全性设计的对立统一关系,以及FMEA方法在安全性设计应用时偏重功能故障分析的局限性,提出采用FMEA方法结合初步危险分析(PHA)和安全检查表分析(SCA)方法,开展卫星安全性设计综合分析评价的策略和安全性设计流程。以卫星在轨加注为例,采用安全性设计综合分析评价流程进行安全性设计研究,结果表明,文章提出的策略和流程可以帮助卫星设计师有效开展系统安全性设计,全面考虑故障模式和其他危险源引发的安全性风险,制定最优的卫星安全性设计方案。     

全球导航卫星系统互干扰评估分析及启示

介绍全球导航卫星系统(GNSS)信号互干扰问题的现状,总结卫星导航系统互干扰评估测试的两种方法,即多径误差评估方法和载噪比评估方法的基本理论和研究现状,结合卫星导航系统的发展需求,对比提出了方法之间的局限性。针对我国卫星导航系统的发展情况,提出基于频谱隔离系数的等效载噪比方法作为卫星导航系统信号互干扰评估方法,以及相关的发展建议。     

失效卫星再利用系统方案设想

为了实现在轨资源再利用,文章分析了失效卫星再利用的可能性,根据卫星不同的失效模式,包括入轨失败、部件失效、寿命末期,得出系统的4类轨道操作任务。论述系统的五大组成部分,并分析了各个系统间的关系;比较了货运飞船和搭载两种上行方案各自的优缺点;结合系统特点,在分析系统任务功能的基础上提炼出了6项相关关键技术。从系统角度提出了有利于失效卫星再利用系统可尽早实现的3条途径。     

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.     

Chaos and its avoidance in spinup dynamics of an axial dual-spin spacecraft

Attitude dynamics of a dual-spin spacecraft (DSSC) and a torque-free angular motion of a coaxial bodies system are considered. Some regimes of the heteroclinic chaos are described. The local chaotization of the DSSC is investigated at the presence of polyharmonic perturbations and small nutation restoring/overturning torques on the base of the Melnikov method and Poincaré Maps. Reasons of the chaotic regimes initiation at the spinup maneuver realization are studied. An approach for the local heteroclinic chaos escape/avoidance at the modification of the classical spinup maneuver is suggested.