基于APS的微型星跟踪器

JPL实验室已经就如何设计未来小型化星跟踪器的问题安排了一个研究课题。该研究项目推荐发展以APS为核心的超低功耗(70mW)、超轻质量(42g)的高速(50Hz)微型星跟踪器(MAST)。当数据更新率为50Hz时，这种MAsT的精度约为7．5”。对于所有轻质量与低功耗的微型卫星来说，MAST都是不可缺少的，因为在这些卫星上，质量与功耗参数是人们特别关心的。MAST仅由两个芯片组成——一个是为星跟踪器应用而优化的CMOS有源像元敏感器(APS)图像探测器，这是一项技术突破；另一个是包含内部集成电路(I^2C)接口、存储器和一个8051微控制器的专用集成电路(ASIC)芯片。MAST的强大功能使它可从几个小窗口同时输出像元数据，而由星上计算机执行处理任务。     

全天球实时星光模拟器的设计与标定

本文论述了全天球实时星光模拟器设计中的几个重要指标及其实现方法，提出了一种软件提高星模拟器的星点位置精度的方法，给出了星模拟器的系统标定以误差补偿的方案和算法。     

机载小型化星敏感器遮光罩设计

针对机载小型化星敏感器的消杂光系统进行了研究。以点源透射比(PST)为标准,根据机载小型化星敏感器成像系统自身的特性与遮光罩设计原则,在尽量不增加系统长度的前提下,对消杂光结构进行了设计。利用Matlab计算出遮光罩的尺寸,确定挡光环的位置,结合CAD作图软件进行建模,并使用光学软件TracePro对遮光罩的消杂光效果进行了仿真和分析,在太阳规避角30°时的点源透射比达到了5.536×10-10,达到系统要求的性能指标。设计的遮光罩能够成功地抑制杂散光,可以满足机载小型化星敏感器的使用要求。     

基于区域生长法的星图中星的提取方法

针对扫描法和矢量法抗噪能力不强、提取精度不高的问题,将区域生长法引入到星提取中,提出了基于区域生长法的星图中星的提取方法.该方法根据星体目标具有较强相关性的特点,制定相似性准则,对星体目标进行生长判断、提取.仿真结果表明:提出的星提取方法具有较强的抗噪能力和较高的提取精度.     

三视场星敏感器系统结构布局的优化

研究了三视场星敏感器的相关坐标系及旋转关系,讨论并给出计算视场内导航星数目的方法,指出优化三视场星敏感器结构布局的依据和途径。通过蒙特卡罗仿真,统计导航星捕获概率,给出了结构布局优化结果。从姿态测量精度、导航星捕获概率、光学系统设计难度方面折中考虑,选择极限星等、视场角和光学系统光轴仰角的最佳参数分别为5.0等、11°×11°和40°,此时捕获4颗以上导航星的概率达到99.43%。     

多星模拟器电路系统的设计

为了适应航天器的发展需求,需要研制小型轻量化的多星模拟器。提出了采用Sony公司的LCX023CMT液晶光阀为核心的多星模拟器构成方案。设计了相应的LCD显示驱动电路和光学系统。所设计的多星模拟器经过与星敏感器联调测试,达到了技术要求。     

星（船）载嵌入式软件的可靠性设计研究

本文分析了星（船）载嵌入式软件可靠性设计的现状及存在的问题，从软件工程和软件可靠性设计及软件测试三个方面论述了如何提高航天嵌入式星（船）载软件的可靠性。     

基于STK的卫星星敏感器视场仿真研究

研究卫星无陀螺姿态稳定性优化控制问题,针对在轨星敏感器可能会受到太阳光、月光、地气光等杂散光的干扰,从而降低星敏感器姿态测量精度以及有效姿态率等.首先建立了星敏感器视场遇杂散光的数学模型.为解决上述问题,提出用Satellite Tool Kit(STK)仿真软件进行了杂散光进入星敏感器视场的仿真,并给出了星敏感器遇杂散光的时间段、持续时长等信息.研究方法和仿真结果适用于对任意轨道卫星的星敏感器视场进行杂散光研究,并可用来优化星敏感器在星上的安装方位,对星敏感器的工程设计提供科学指导作用.     

高动态GPS/INS组合导航中一种新的选星算法

传统的GPS选星算法采用高度角对可用星进行判断,然后选择具有最佳几何精度因子的卫星组合进行导航;由于最佳几何精度因子法的运算量大,很难适用于高动态环境对实时性的要求;因此,通过建立可用星圆锥体,并结合模糊选星算法的思想,提出一种基于惯性导航系统辅助的GPS选星算法;仿真结果表明,新的算法能够根据载体姿态信息,有效地进行可见星判断和卫星组合选择,运算时间比最佳GDOP值法降低约80％,精度较模糊选星算法更优.     

基于K均值聚类的新型选星算法北大核心

在进行导航定位时,第一步是进行卫星的选取,选取卫星的合适与否直接决定了导航定位的准确性。为了提高选星的精确性和时效性,在计算卫星方位角和仰角的基础上,提出了一种新型选星算法——基于K均值聚类的新型选星算法。在选取最大仰角卫星的基础上利用K均值聚类算法对可见卫星的方位角进行聚类选星,并利用MATLAB软件进行仿真。仿真结果表明:上述算法选星的GDOP值与最佳几何精度因子法得到的GDOP值相差无几,具有较高的精确性,同时算法计算复杂度大大减小,提高了选星的时效性。     

Simulation of energy transport by charged thermonuclear particles in compressed laser targets with allowance for spontaneous magnetic fields

In specially designed compressed thermonuclear targets, spontaneous magnetic fields (SMF) ≥ 100 MG can be generated. We propose a conceptual design of the laser target for creating a magnetized hot (～10–100 million K) thermonuclear plasma to model “star matter” in a laboratory. The effect of SMF on the energy transport by charged thermonuclear particles in compressed plasma is studied by computer-aided computations.     

基于支持向量机的导航星选取算法研究

在星敏感器导航星表的建立过程中由于恒星的数量太多, 往往要进行筛选, 通常这种选择是一种基于枚举的大量反复的提取过程, 复杂费时而结果往往并不是最优的。而基于统计学习理论( SLT) 的支持向量机( SVM) 方法正好克服了这方面的不足。SLT 理论和SVM 方法为导航星选取过程的简化和结果的最优性的获得提供了新的途径。讨论了支持向量机在导航星选取优化中进行应用的分类算法, 构建了导航星分类器, 并以导航星的选取为例进行了试验论证。试验表明: 基于SVM 的导航星分类器对简化导航星的筛选过程优化导航星表的     

On compatible star decompositions of simple polygons

The authors introduce the notion of compatible star decompositions of simple polygons. In general, given two polygons with a correspondence between their vertices, two polygonal decompositions of the two polygons are said to be compatible if there exists a one-to-one mapping between them such that the corresponding pieces are defined by corresponding vertices. For compatible star decompositions, they also require correspondence between star points of the star pieces. Compatible star decompositions have applications in computer animation and shape representation and analysis. They present two algorithms for constructing compatible star decompositions of two simple polygons. The first algorithm is optimal in the number of pieces in the decomposition, providing that such a decomposition exists without adding Steiner vertices. The second algorithm constructs compatible star decompositions with Steiner vertices, which are not minimal in the number of pieces but are asymptotically worst-case optimal in this number and in the number of added Steiner vertices. They prove that some pairs of polygons require Ω(n²) pieces, and that the decompositions computed by the second algorithm possess no more than O(n²) pieces. In addition to the contributions regarding compatible star decompositions, the paper also corrects an error in the only previously published polynomial algorithm for constructing a minimal star decomposition of a simple polygon, an error which might lead to a nonminimal decomposition     

一种基于联合变换相关的PSF估计方法

针对弹体振动引起的星图成像质量退化的问题,提出了一种基于联合变换相关的PSF估计方法.首先,在低帧速CCD相机的曝光时间内,利用高帧速CCD相机拍摄得到振动条件下的连续平移星图序列,将星图序列的相邻帧拼接成联合输入星图;其次,采用联合变换光学相关器作为处理器并引入坐标变换进行相关运算,得到联合输入星图的相对位移矢量,插值处理后估计出模糊星图的连续PSF;最后进行仿真验证,仿真结果表明:联合变换相关法不仅有效克服了仅从单幅模糊星图估计PSF存在的多解问题,还较准确地估计出了由角振动引起的空间变化模糊星图的PSF.     

Optimal broadcasting on the star graph

The star graph has been show to be an attractive alternative to the widely used n-cube. Like the n-cube, the star graph possesses rich structure and symmetry as well as fault tolerant capabilities, but has a smaller diameter and degree. However, very few algorithms exists to show its potential as a multiprocessor interconnection network. Many fast and efficient parallel algorithms require broadcasting as a basic step. An optimal algorithm for one-to-all broadcasting in the star graph is proposed. The algorithm can broadcast a message to N processors in O(log₂ N) time. The algorithm exploits the rich structure of the star graph and works by recursively partitioning the original star graph into smaller star graphs. In addition, an optimal all-to-all broadcasting algorithm is developed     

An improved star test for implicit polynomial objects

For a given point set, a particular point is called a star if it can see all the boundary points of the set. The star test determines whether a candidate point is a star for a given set. It is a key component of some topology computing algorithms such as Connected components via Interval Analysis (CIA), Homotopy type via Interval Analysis (HIA), etc. Those algorithms decompose the input object using axis-aligned boxes, so that each box is either not intersecting or intersecting with the object and in this later case its center is a star point of the intersection. Graphs or simplicial complexes describing the topology of the objects can be obtained by connecting these star points following different rules. The star test is performed for simple primitive geometric objects, because complex objects can be constructed using Constructive Solid Geometry (CSG), and the star property is preserved via union and intersection. In this paper, we improve the method to perform the test for implicit objects. For a primitive set defined by an implicit polynomial equation, the polynomial is made homogeneous with the introduction of an auxiliary variable, thus the degree of the star condition is reduced. A linear programming optimization is introduced to further improve the performance. Several examples are given to show the experimental results of our method.     

混合星环交换结构的体系结构研究

弹性分组环是(RPR)是基于分组业务而优化的城域网络体系结构,针对环形结构传输星型业务的不足,出现了在环形结构中加入星型结构而形成的弹性分组星环网。弹性分组星环网成功地解决了RPR传输星型业务的问题。将弹性分组星环网的核心概念从物理结构中抽象出来用于交换结构,提出一种新型的适合高速分组交换结构混合星环交换结构。以排队论为工具对混合星环结构进行建模,分析星环结构的性能。结果表明混合星环结构是一种适合高速分组交换的结构。     

Two ranking schemes for efficient computation on the starinterconnection network

A node ranking scheme provides the necessary structural view for developing algorithms on a network. We present two ranking schemes for the star interconnection network both of which allow constant time order preserving communication. The first scheme is based on a hierarchical view of the star network. It enables one to efficiently implement order preserving ASCEND/DESCEND class of algorithms. This class includes several important algorithms such as the Fast Fourier Transform (FFT) and matrix multiplication. The other ranking scheme gives a flexible pipelined view of the star interconnection network and provides a suitable framework for implementation of pipelined algorithms     

A star network approach in heterogeneous multiprocessors system on chip

Multiprocessor System on Chip (MPSoC) platform plays a vital role in parallel processor architecture design. However, with the growing number of processors, interconnect on chip is becoming one of the major bottlenecks of MPSoC architecture. In this paper, we propose a star network based on peer to peer links on FPGA. The star network utilizes fast simplex links (FSL) as basic structure to connect the scheduler with heterogeneous processing elements, including processors and hardware IP cores. Blocking and nonblocking application interfaces are provided for high level programming. We built a prototype system on FPGA to evaluate the transfer time and hardware cost of the proposed star network architecture. Experiment results demonstrated that the average transfer time for each word could be reduced to 7 cycles, which achieves 14× speedup against state-of-the-art shared memory literatures. Moreover, the star network cost only 1.2?% Flip Flops and 2.45?% LUTs of a single FPGA.     

VLSI implementation of star detection and centroid calculation algorithms for star tracking applications

Nowadays, hardware implementation of image and video processing algorithms on application specific integrated circuit (ASIC) has become a viable target in many applications. Star tracking algorithm is commonly used in space missions to recover the attitude of the satellite or spaceship. The algorithm matches stars of the satellite camera with the stars in a catalog to calculate the camera orientation (attitude). The number of stars in the catalog has the major impact on the accuracy of the star tracking algorithm. However, the higher number of stars in the catalog increases the computation burden and decreases the update rate of the algorithm. Hardware implementation of the star tracking algorithm using parallel and pipelined architecture is a proper solution to ensure higher accuracy as well as higher update rate. Noise filtering and also the detection of stars and their centroids in the camera image are the main stages in most of the star tracking algorithms. In this paper, we propose a new hardware architecture for star detection and centroid calculation in star tracking applications. The method contains several stages, including noise smoothing with fast Gaussian and median filters, connected component labeling, and centroid calculation. We introduce a new and fast algorithm for star labeling and centroid calculation that needs only one scan of the input image.