Current Status and Development Trend of Surface Penetrating Radarin the Application of Lunar and Deep Space Exploration

Surface Penetrating Radar(SPR)，a kind of geophysical method to survey the internal structure and change of properties of lossy dielectric material by using electromagnetic wave，is only able to penetrate the desolate surface of the planet for finding hidden signs of water ice.In addition，SPR is also the most eligible non destructive method for imaging planetary shallow layer soil structure and rock changes caused by electromagnetic discontinuous.This paper reviews the decades history of SPR in the application of extraterrestrial planetary exploration，and summarizes the scientific objectives，performance and results of SPRs configured in lunar and deep space missions.Then on this basis，combined with the latest news on radar technology，the main development trend of SPR in lunar and deep space exploration is given.     

Computer Vision on Mars

Increasing the level of spacecraft autonomy is essential for broadening the reach of solar system exploration. Computer vision has and will continue to play an important role in increasing autonomy of both spacecraft and Earth-based robotic vehicles. This article addresses progress on computer vision for planetary rovers and landers and has four main parts. First, we review major milestones in the development of computer vision for robotic vehicles over the last four decades. Since research on applications for Earth and space has often been closely intertwined, the review includes elements of both. Second, we summarize the design and performance of computer vision algorithms used on Mars in the NASA/JPL Mars Exploration Rover (MER) mission, which was a major step forward in the use of computer vision in space. These algorithms did stereo vision and visual odometry for rover navigation and feature tracking for horizontal velocity estimation for the landers. Third, we summarize ongoing research to improve vision systems for planetary rovers, which includes various aspects of noise reduction, FPGA implementation, and vision-based slip perception. Finally, we briefly survey other opportunities for computer vision to impact rovers, landers, and orbiters in future solar system exploration missions.     

利用序列ISAR图像获取空间目标3-D信息的方法

如何从空间目标序列性二维(2-D,Two-Dimentional)逆合成孔径雷达(ISAR,Inverse Synthetic Aperture Radar)成像获取目标的三维(3-D)信息,是目标特征自动识别(ATR,Automatic Target Recognition)技术的重要研究课题。利用双向射线跟踪(BART,Bidirectional Analytic Ray Tracing)方法,计算连续多角度观测条件下空间目标的电磁散射数据,并由此获取空间目标的ISAR序列2-D图像。再利用KLT(Kanade-Lucas-Tomasi)特征跟踪算法,跟踪提取2\|D序列ISAR图像中的特征点(强散射点),获得其2-D坐标。然后,基于正交因式分解法(OFM,Orthographic Factorization Method),计算强散射点的3\|D坐标,获取空间目标的3-D信息。通过简单六棱柱模型,验证重构算法的精度;并以ENVISAT卫星模型为例,给出强散射点的3-D重构结果。结果表明,本文对空间目标3\|D信息获取方法能有效地从ISAR序列2-D图像中重构目标的三维信息。     

Remote Sensing Image Scene Oriented Convolutional Neural Network Recursive Recognition Model

In order to solve low separability and rough details in scene recognition，remote sensing image scene oriented convolutional neural network recursive recognition model is presented.Firstly，deep convolutional neural network with multi\|convolutional layers and multi\|pooling layers is constructed by multi\|resolution scenes.Then quad\|grids are subdivided to DCNN scene recursive recognition based on Confusion Index (CI)by softmax probability，and multi\|sliding windows are used to tune recursively for accurately locating scene targets.Experimental results show that the proposed model can adapt scene recognition with different scale，and significantly improve the accuracy compared with the commonly used DCNN.     

基于多基态修正模型的空间探测数据管理技术研究与实现

传统的空间环境探测数据存储方式效率较低,且难于满足数据时空分析及深度挖掘,也不能基于三维特性开展时空可视化表达。设计了一种满足海量探测数据特点的多基态修正扩展的混合时空模型,并进行了管理系统软件的设计和开发。该系统能较好地组织管理空间环境数据,减少存储空间,并在一定程度上提高了时空数据操作的效率。     

NASA advances robotic space exploration

NASA's successful exploration of space has uncovered vast amounts of new knowledge about the Earth, the solar system and its other planets, and the stellar spaces beyond. To continue gaining new knowledge has required - and will continue to require - new capabilities in onboard processing hardware, system software, and applications such as autonomy. For example, initial robotic space exploration missions functioned, for the most part, as large flying cameras. These instruments have evolved over time to include more sophisticated imaging radar, multispectral imagers, spectrometers, gravity wave detectors, a host of prepositioned sensors and, most recently, rovers.     

基于遗传算法的深空探测天线综合

为了改善深空探测中共焦面阵列馈电抛物反射面天线的可视范围,提出一种基于遗传算法的扫描波束综合方法。基于物理光学法计算共焦面馈电阵中每个馈源照射反射面的次级远场方向图,利用遗传算法优化得到的权值对各次级方向图加权合成期望的波束。仿真和分析结果表明：提出的基于遗传算法的共焦面阵列馈电反射面方向图综合与传统共轭场匹配方法相比,可控制旁瓣电平,更精确综合出期望方向图,扩大深空探测天线的可视范围。     

深空探测航天器控制系统自主管理软件架构研究

深空探测航天器距离远、环境复杂,测控站遥测和遥控操作不能满足控制的实时性和安全性要求,自主管理技术是提高航天器对未知环境的应对能力、提升飞控实效性的主要手段。回顾了深空探测航天器自主管理技术发展的现状,分析了实现自主管理的关键技术,并结合深空探测工程实施和技术发展需求,提出了未来航天器自主管理系统体系结构和软件架构,并进行了仿真实验。     

基于图论的深空探测航天器故障可诊断性评价

为了衡量深空探测航天器的自主故障诊断能力,提出基于图论的故障可诊断性评价方法.在对加权有向图进行介绍的基础上,给出强可推导结点、依赖于故障的可推导结点以及解析冗余结点等定义;分别提出故障可检测性和可分离性判据并给出相关证明,考虑深空探测航天器的资源约束问题,研究解析冗余关系优选方法;分析深空探测航天器的故障诊断层次,并对系统级故障诊断能力进行评价;最后,利用深空探测航天器的数学仿真数据对所提方法的有效性进行验证.     

全极化SAR数据信息提取研究

全极化SAR(Synthetic Aperture Radar)测量的是每一像元的全散射矩阵,可合成包括线性极化、圆极化及椭圆极化在内的多种极化图像。因此与常规的单极化和多极化SAR相比,在雷达目标探测、识别、纹理特征的提取等方面全极化SAR具有很多优点。基于新疆和田地区的SIR-C L波段全极化雷达数据,介绍了极化合成的基本原理和数据处理流程,分析了几种典型地物全极化信号的特点,并在此基础上用监督分类法进行了全极化SAR数据的信息提取。结果表明:全极化SAR数据比单极化和多极化SAR数据具有更高的分类精度,并有效地的提取出地表信息,为利用SAR数据反演地表参数打下了基础。     

Systematic design space exploration using a template-based ontological method

The realization of complex engineered systems using models that are typically incomplete, inaccurate and not of equal fidelity requires the understanding and prediction of process behavior in design. This necessitates the need for extending designer’s abilities in making design decisions that are robust, flexible and modifiable particularly in the early stages of design. To address this requirement, we propose in this paper, an ontology for design space exploration and a template-based ontological method that supports systematic design space exploration ensuring the determination of the right combination of design information that meets the different goals and requirements set for a process chain. Using the proposed method, a designer is able to (1) systematically adjust the design space in due time to manage the risks of errors accumulating and propagating during the design of different stages of the process chain, (2) improve the ability to communicate and understand the interactions between design information in the process chain. We achieve the said through (1) procedure for design space exploration is identified to determine the sequence of activities needed for the systematic exploration of design space under uncertainty; (2) the decision-based design information flow is archived using the design space exploration process template and represented by utilizing frame-based ontology to facilitate the management of re-usable information. We demonstrate the efficacy of this template-based ontological method for design space exploration by carrying out the design of a multi-stage hot rod rolling system in steel manufacturing process chain.     

Piecewise Convex Mulutiple-model Hyperspectral Imagery ENDmember\|extraction based on Discrete Particle Swarm Optimization

Piecewise COnvex Multiple\|Model ENDmember(PCOMMEND) spectral unmixing can well solve unmixing of the nonconvex hyperspectral data，which improves the calculation accuracy of the standard linear mixed model based on the convex geometry model.the number of piecewise convex is not sure in the practical application，which limits the calculation ccuracy of unmixing and the wrong endmembers will sometimes extracted，in view of the situation，the Discrete Particle Swarm Optimization(D\|PSO)is proposed to unmix the piecewise convex mulutiple\|model hyperspectral imagery，D\|PSO is the intelligent algorithm of random search，and is able to find the global optimal solution of convex function，which reduce the unmixing error caused by the uncertainty number of the convex section，experiments on the simulative data and real data has indicate D\|PSO improves the accuracy of the extracting endmember and estimating the proportion.     

基于GeoAgent的数字地球自适应网络系统模型

数字地球是一个复杂,动态变化的自适应网络系统。通过类比人类对外界刺激的反应过程和数字地球的行为,提出了以一种具有学习和空间处理能力的智能实体－空间智能体ＧｅｏＡｇｅｎｔ作为数字作自适应网络中的基本处理单元,并给出了基于ＧｅｏＡｇｅｎｔ的数字地球自适应网络的系统模。     

The Comparison of Reflectance based on Different Terrain Correction

Selecting the Xinglong Mountain which locates in the southeast of Lanzhou city，GanSu province as an example.Using the Landsat8 satellite image as the data source，the Cosine method，C and the modified Minnaert methods were used for each band in the study area.Comparing with the results of the field measurement reflectance and the statistical characteristics of image，the result showed that the cosine method has a perfect correction in the visible and short wave infrared wavelength，the C correction has a serious over\|correct，however.In the Near Infrared Wavelength，the better result obtained by C correction，and the cosine method has over\|correct otherwise.Comparing with the correct effect of whole bands，the modified Minnaert method has an ideal correct effect.The comparison of before and after correction we found that there is a smaller difference for three methods in the smaller slope，and the over correct is mostly in the south.What’s more，with the increase of the slope，the over correct is more obviously，but，there is a little over correct which used the modified Minnaert method in the whole area，it’s more suitable in large slope and the complicated area.     

星载雷达观测分析亚洲季风区对流层顶附近的对流活动

为了加深理解东亚地区对流活动对于对流层顶部-平流层下部区域(UTLS)物质传输的影响,首个星载降雨雷达(Precipitation Radar,PR)观测资料用以研究该地区夏季对流活动特征及其对流穿越的概率分布特征。3年的PR数据分析结果显示,亚洲季风区夏季降水概率在孟加拉湾附近较高,其中对流性降水在印度地区最为显著,而我国对流性降水出现概率普遍偏低。深对流活动出现概率在印度最高,达到15%,其次是我国西南、华南地区和部分东南亚国家达到10%,其他大部分地区低于5%。此外,穿越14km高度的强对流活动在印度地区的出现概率最大(～2%),其次是我国西南和部分东南亚地区(～1%),其他大部分地区都没有出现穿越性对流;而强对流穿过NCEP资料提供的对流层顶高度的概率分布与前者类似,不过出现概率显著减低,最高也不足0.35%。这表明随着对流层顶参考高度增加,出现穿越性对流事件则急剧减少。此外,结合以往对流层顶层的研究,研究结果显示深对流穿过对流层顶层下边界的概率高达2％,而完全穿透整个对流层顶层的概率不足0.4％。     

Research on Extraction of Burned Area based on Saliency Enhancement

The information of burned area is significant for post disaster assessment，ecosystems protection and restoration.So far，the existing detection methods of burned areas are less practical.Based on the FY\|3C MERSI satellite data，various characteristics of the burned area are fully utilized and a new method of burned area mapping is created through saliency enhancement.Two burned areas in the northwestern United States were selected as research areas.Three burned\|area\|sensitive vegetation indices(NDVI，GEMI and NDVIT) were combined with the saliency features of the images to enhance and extract the burned areas.Visual interpretations are used to evaluate the experimental results of the proposed method，and compared with the results of NBR threshold method.The results show that the kappa coefficient of the saliency enhancement method in the two research areas reaches more than 0.68，0.2 higher than NBR threshold method.Experiments show that the saliency enhancement method for mapping burned area is high，and the influence of vegetation change caused by non\|burned has little influence on it，and the method has a certain stability compared with the NBR threshold method.     

A practical method for computing SAR satellite revisit times: application to RADARSAT‐1 and ENVISAT

Many geoscience applications of space‐borne Synthetic Aperture Radar (SAR) imagery require knowledge of the revisit time of the satellite at a location. In this paper, a practical method is presented for computing the revisit times of SAR satellites at any location on Earth. The method is based on the use of maps that give the number of imaging tracks, i.e. the number of satellite ground tracks from which a location can be imaged. With these maps and some basic equations, the revisit time of a SAR satellite or an arbitrary constellation of SAR satellites can be computed easily. As such, the presented method offers an alternative to computer programs that may not be available to everyone and often are tailored to the use of specific satellites. As an illustration of the method, maps with the number of imaging tracks have been computed for RADARSAT‐1 and ENVISAT and their ease of use is shown by means of an example.     

基于比例导引的深空撞击脉冲导引律设计

撞击探测是深空探测的一种重要探测手段.高精度的导引方法是实现撞击任务的关键.本文针对深空撞击任务的特点,推导了相对动力学方程,并据此设计了脉冲比例导引律.以某撞击任务为背景对比例导引方法进行了蒙特卡洛仿真验证.结果表明：该方法与传统预测制导方法相比撞击精度略低,但仍可满足任务需求,速度增量消耗基本相当,同时可满足不同轨道下任务的需求,避免了自主导航定位精度对预测制导的限制,具有较强的工程实用价值.     

基于全极化SAR影像的海岛地物分类

There are numerous islands with abundant resources in China.Due to the limited information included in common polarization features and the poor effect of traditional classification methods when there are few samples，nine polarization features are analyzed and classification is carried out using active deep learning.Firstly，multiple features are extracted from an original image.Then，the original features can be extracted by anto\|encoder and the initial classifier is trained and fine-tune the whole model with a small number of labeled samples.Finally，the most uncertain samples are selected to label with active learning algorithm and added to the training samples.Experiment comfirms that active deep learning can effectively improve the classification accuracy with less labeled samples and entropy shannon is a more effective feature to distinguish between seawater，mudflats and beaches.