一种基于等高线的小型撞击坑识别方法

撞击坑自动识别是行星探测任务中重要的研究热点之一。由于数据精度和算法局限性等问题,以往的方法往往针对识别尺度较大的撞击坑。基于目前国际上精度最高、覆盖最全的嫦娥二号数字高程模型数据,提出一种基于等高线自动识别小型撞击坑的方法。首先,分析小型撞击坑模型的等高线特征,确定特征参数,建立指标体系;其次,提取实验区等高线信息,筛选出符合特征参数的等高线;最后,利用霍夫变换拟合撞击坑边界,提取撞击坑位置和大小信息。通过对实验区域的小型撞击坑识别结果分析表明,该方法可针对不同尺度的小型撞击坑设置不同的参数,分批次识别提取,综合识别正确率达90%以上,说明该方法对于自动识别小型撞击坑是有效的。该方法弥补现有自动识别方法针对尺度较大撞击坑的缺陷,识别结果补充月球撞击坑数据库中的小尺度撞击坑,为今后建立全月球撞击坑数据库打下基础。     

月表撞击坑形貌特征和几何形态关系分析

在已有研究的基础上,利用月表撞击坑数据库LU60645GT．深入分析了月表撞击坑深径比随直径变化以及深度随直径变化的特点．并给出了全月范围内新鲜撞击坑这两组形态参数之间的关系式。此外,通过统计风暴洋克里普岩地体、高地斜长岩地体、南极艾肯地体三大地体下不同形貌类型、不同尺度撞击坑的深径比,对比分析得出不同地体下各类撞击坑几何形态关系的差异。研究表明（1）对较为新鲜的撞击坑而言,深径比随着直径的增加呈现先增加后减小的趋势,在直径5km附近出现极大值;深度随着直径的增加而增加的趋势并不均匀,在18km和30km附近出现拐点：15km以下撞击坑的深度一直径之间呈现较高的线性相关关系,而15km以上撞击坑的深径比一直径之间呈现较高的幂相关关系。（2）高地斜长岩地体下各类撞击坑的平均深径比均大于另两类地区同类撞击坑深径比。     

高重复率卫星激光测距中一种回波实时识别方法

高重复率卫星激光测距(SLR)采用低能量激光,回波率较低且探测器暗噪声数明显增多,尤其在白天测距强背景噪声时,回波信号更是难于识别。该文提出了两次滤波的回波实时识别方法。为验证此方法的可行性,使用了Graz激光站2kHz实际测距数据,模拟了高重复率测距过程。结果表明,此方法在对高重复率激光测距回波识别中是有效的,为开展kHz激光测距打下了技术基础。     

基于DEM的月表典型撞击坑形态特征的指标因子量化关系模拟

在激光测高方法获取的100 m分辨率的全月数字高程模型数据基础上,选取1 407个不同形态的撞击坑,提取多视角刻画撞击坑形态的地形因子指标,并进行撞击坑形态特征分析。在此基础上,采用数理统计与地理建模的方法,重点探讨地形因子间的关联性,进一步构建基于多因子的量化模型,以解释地形因子信息与撞击坑形态发育的内在联系。结果表明,深径比(y)与直径(x_1)、体积(x_2)、圆度(x_3)、体态比(x_4)以及坑壁坡度(x_5)能较好地刻画撞击坑形态发育特征,通过多元线性回归拟合构建指标间的函数关系,且拟合模型在0.05置信水平下的显著性F=492.037F_a,拟合模型的显著性极好,y=(7.941e-007)x_1+(8.063e-016)x_2+0.082x_3+0.012x_4+0.007x_5-0.042为其模拟函数关系式,拟合优度达0.637。该模拟方法在月表撞击坑形态发育研究中有重要意义,是撞击坑形态特征的数字地形模拟与信息挖掘的一次有益实践。     

射电天文台址常驻电磁干扰检测与识别方法

为有效统计射电天文台址常驻电磁干扰的变化,提高实时电磁环境监测效率,提出一种基于先验信息的常驻电磁干扰信号检测与识别方法.首先通过信噪分离,信号能量估值从电磁环境历史监测数据中提取移动通信,地面数字电视等常驻大信号的中心频率、极化方式、来波方向等特征,经对无线信号传播信道的衰落方式进行分析,提出信号能量模型服从的分布函数假设并采用K-S检验验证该假设,合理设置能量阈值,建立信号模板库.其次,根据信号模板库中的信号特征对实时频谱数据进行双门限能量检测、信号相关性识别,从而提高信号检验的准确率,实现了常驻信号的快速统计.针对射电天文台址实测频谱,运用该方法能够有效识别并统计频谱中的常驻信号,从而为台址干扰缓解策略制定提供重要依据.     

基于日球物理学事件知识库的太阳活动识别

太阳图像中包含明显的太阳活动区域,以及无现象的太阳宁静区。从太阳图像中识别有效的太阳活动区域,是图像处理技术在天文研究中的典型应用。得益于美国太阳动力学天文台的日球物理学事件知识库提供的实时太阳观测数据,提出了一种基于日球物理学事件知识库的太阳活动识别方法。此方法获取6种太阳活动的信息(发生时间、位置、区域面积),建立对应时间的全日面图像的尺度变换模型。结合位置与区域面积信息,对不同太阳活动进行梯度阈值分割,边界识别方法被用来定位和识别太阳活动的区域。然后,对太阳图像特征参数相关性的研究,得到每种太阳活动的最佳特征参数组合。方法实现了对太阳活动的精确定位和有效识别,为后续工作的开展提供了便利。此外,对不同太阳活动区域提取特定组合的特征,可以为基于内容的图像检索系统建立精简的图像特征集提供一种可行办法。     

太阳活动预报中的模糊识别综合指数

在太阳活动预报中,预报因子的选取和处理对预报效果影响甚大。本文在云台原有的平均综合指数基础上,运用模糊识别方法,给出了一种模糊识别综合指数,它能更好地表征太阳日面活动区的活动特征。这种方法简单、方便,较充分地利用了预报因子中所含有的有用信息,从而使识别预报率有所提高。     

宽带频谱序列干扰信号识别与统计方法

随着科学技术的不断进步,射电天文台站趋于自动化,各类电子设备的广泛使用使得射电天文台站的电磁环境变得尤为复杂,如何有效识别和统计复杂频谱中的干扰信号是当前射电天文台站亟需解决的问题,故提出一种宽带频谱序列干扰信号识别与统计方法.首先,对每组宽带频谱进行信噪分离、识别频谱中的干扰信号;然后,对第1组宽带频谱信号识别结果及信号特征建立模板库,后续每组频谱的信号识别结果与模板库中对应频率的信号进行相似性分析,根据相似性分析结果,统计信号次数,更新模板库;实现宽带频谱序列干扰信号的识别与统计.针对QTT (QiTai Radio Telescope)台站实测频谱,运用该方法进行干扰信号识别与统计,能够有效识别并标记频谱中的干扰信号,并统计干扰信号随时间、方向的变化趋势.     

双链DNA片段的碱基空间模式BSP——基因组调控区的一种可能的信息编码方式

生物体可看作是一种特殊的信息处理系统 ,论文的第二章从这种观点出发讨论了生物细胞内最大的信息源基因组DNA序列的信息编码问题。首先探讨了基因组蛋白质编码区的信息编码问题 ;简要回顾转录水平的基因表达调控后 ,讨论了基因组基因表达调控区的信息编码问题。第三章介绍了我们利用internet上可获取的开放的生物信息学资源 ,对基因组DNA调控区的一种可能的编码方式所进行的理论研究。这种可能的编码方式我们称之为双链DNA上的碱基空间模式BSP (BaseSpatialPattern)。首先 ,我们发现了由三联体BSP介导的一种 4与 2 0的关系 ,称为 4 -BSP -2 0关系。并推测 4 -BSP -2 0关系也许是某些DNA—蛋白质相互作用中的一种识别密码 ;第二 ,研究真核细胞转录调控中的DNA—蛋白质相互作用的实验数据表明 :某些DNA结合蛋白质对双螺旋核酸的专一性识别可能与BSP有关。并找到了 7组由其他生物学家公开发表的实验数据支持这一猜测 ;第三 ,研究了BSP的形式化描述问题 ,找到了一种基于等价类的BSP描述方法 ,并开发了相应的计算机处理算法。该描述方法简明且便于用计算机进行处理 ,更重要的是它提供了一种研究途径 ,可把BSP和 4 -BSP -2 0关系推广到单链DNA (ssDNA)和ssDNA -蛋白质相互作用的研究中 ,从而可进一步推广到RN     

一种基于MUSIC算法的天地波识别方法

基于我国BPL长波脉冲信号的特征,利用MUSIC(多信号分类)算法对BPL天、地波延迟进行估计,实现天、地波识别。对传统谱估计IFFT(快速傅里叶逆变换)算法和现代谱估计MUSIC算法进行了仿真和比较,结果表明,这两种方法在较低信噪比条件下可有效分离天、地波,且识别误差都能控制在±5μs内,但MUSIC算法比IFFT算法具有更高的精度和分辨率。     

Defocus spot detection of astronomical optical system

Defocusing spot size detection is especially essential for aberration analysis and correction of optical systems. In the case of far defocusing, the celestial forms a pupil image on the detector, and the size of the image is linearly changed with the defocusing distance, and can be used to correct the optical system and analyze the image quality. Based on the focal plane attitude detection of Large Sky Area MultiObject Fiber Spectroscopy Telescope(LAMOST), this paper uses a variety of methods to detect the size of the defocusing spot of LAMOST telescope. For the particularity of the spot, the average value spacing algorithm, the peak value spacing algorithm, the ellipse fitting algorithm, and the multi-peak Gaussian fitting algorithm are used to detect the spot size. This paper will introduce these four methods, in which the average value spacing algorithm is proposed by the author of this paper. The advantages and disadvantages of the four methods are compared. The experimental results show that the average value spacing algorithm can achieve better accuracy of spot size detection in the four algorithms.     

Map-projection-independent crater size-frequency determination in GIS environments—New software tool for ArcGIS

Statistical analysis of crater size-frequency distributions (CSFDs) of impact craters on planetary surfaces is a well-established method to derive absolute ages on the basis of remotely-sensed image data. Although modelling approaches and the derivation of absolute ages from a given CSFD have been described and discussed in considerable depth since the late 1960s, there is no standardised methodology or guideline for the measurement of impact-crater diameters and area sizes that are both needed to determine absolute ages correctly. Distortions of distances (i.e., diameters) and areas within different map projections are considerable error sources during crater and area measurements.In order to address this problem and to minimize such errors, a software extension for Environmental Systems Research Institute's (ESRI's) ArcMap (ArcGIS) has been developed measuring CSFDs on planetary surfaces independently of image and data frame map projections, which can also be theoretically transferred to every Geographic Information System (GIS) capable of working with different map projections.Using this new approach each digitized impact crater is internally projected to a stereographic map projection with the crater's central-point set as the projection center. In this projection, the circle is defined without any distortion of its shape (i.e., conformality). Using a sinusoidal map projection with a center longitude set to the crater's central-point, the diameter of the impact crater is measured along this central meridian which is true-scale and does not show any distortion. The crater is re-projected to the map projection of the current data frame and stored as vector geometry with attributes. Output from this workflow comprises correct impact-crater diameters and area sizes in sinusoidal map projections and can be used for further processing, i.e. absolute age determinations (e.g., using the software CraterStats). The ArcMap toolbar CraterTools developed in this context significantly helps to improve and simplify the crater size-frequency (CSF) measurement process. For GIS-based measurements, we strongly recommend our procedure as the standard method for determining CSFDs on planetary surfaces to minimize map distortion effects for further analysis.     

Short-term solar flare prediction using image-case-based reasoning

Solar flares strongly influence space weather and human activities,and their prediction is highly complex. The existing solutions such as data based approaches and model based approaches have a common shortcoming which is the lack of human engagement in the forecasting process. An image-case-based reasoning method is introduced to achieve this goal. The image case library is composed of SOHO/MDI longitudinal magnetograms, the images from which exhibit the maximum horizontal gradient, the length of the neutral line and the number of singular points that are extracted for retrieving similar image cases. Genetic optimization algorithms are employed for optimizing the weight assignment for image features and the number of similar image cases retrieved. Similar image cases and prediction results derived by majority voting for these similar image cases are output and shown to the forecaster in order to integrate his/her experience with the final prediction results. Experimental results demonstrate that the case-based reasoning approach has slightly better performance than other methods,and is more efficient with forecasts improved by humans.     

Simulated Annealing and Bayesian Posterior Distribution Analysis Applied to Spectral Emission Line Fitting

Spectral-line fitting problems are extremely common in all remote-sensing disciplines, solar physics included. Spectra in solar physics are frequently parameterized by using a model for the background and the emission lines, and various computational techniques are used to find values to the parameters given the data. However, the most commonly-used techniques, such as least-squares fitting, are highly dependent on the initial parameter values used and are therefore biased. In addition, these routines occasionally fail because of ill-conditioning. Simulated annealing and Bayesian posterior distribution analysis offer different approaches to finding parameter values through a directed, but random, search of the parameter space. The algorithms proposed here easily incorporate any other available information about the emission spectrum, which is shown to improve the fit. Example algorithms are given and their performance is compared to a least-squares algorithm for test data – a single emission line, a blended line, and very low signal-to-noise-ratio data. It is found that the algorithms proposed here perform at least as well or better than standard fitting practices, particularly in the case of very low signal-to-noise ratio data. A hybrid simulated annealing and Bayesian posterior algorithm is used to analyze a Mg x line contaminated by an O IV triplet, as observed by the Coronal Diagnostic Spectrometer onboard SOHO. The benefits of these algorithms are also discussed.     

赋形旋转抛物面天线母线自适应分段拟合

赋形旋转抛物面天线母线拟合常用的方法包括多项式整体拟合和等间隔分段拟合,多项式整体拟合结果阶次高、计算量大,且高阶多项式在边缘处拟合的结果容易振荡;而等间隔分段拟合则是对母线数据按等间隔分段,分段方式具有一定的盲目性,容易造成拟合参数多、光滑性差等问题.针对上述问题,提出了一种基于母线拟合残差分布的自适应分段拟合方法,该方法包括初始整体拟合和分段拟合两步,初始整体拟合用以确定各离散点的拟合残差分布,分段拟合先参照残差分布情况对离散点数据分段,然后采用低阶多项式对各段数据进行拟合.经过实例拟合对比,该方法可避免高阶拟合的不稳定性,减少了分段数,更适用于赋形旋转抛物面天线母线的拟合.     

Automated Detection of EUV Prominences

We present methods to detect automatically off-limb prominences in the extreme ultraviolet (EUV), using synoptic images taken by the extreme-ultraviolet imaging telescope (EIT) on board SOHO. The 304 Å line is essential for the detection of EUV prominences, but the optimal detection is achieved through a combined image processing of the four synoptic EIT images. In addition, the difference between consecutive 304 Å images serves to identify erupted prominences. Representation maps of the quiescent EUV prominences for a given Carrington rotation are generated and used for further analysis of the detected structures. Longitudinal profiles of long-lived prominences are investigated for three examples at different latitudes, in conjunction with on-disk intensity profiles in the EUV. The observations coincide with theoretically predicted apparent longitudinal profiles, which can be distinguished from the profile of a prominence rising before eruption. The developed algorithms may be relevant to study the 3D geometry of features seen in the EUV and may facilitate the analysis of data from the future STEREO mission.     

基于图像的天体搜索研究与自动化集成软件开发

天体搜索是天文数据处理流程的一个重要环节,也是以平方公里阵列射电望远镜(Square Kilometre Array, SKA)为代表的下一代射电望远镜在面向海量数据处理中的挑战之一.现今天体自动搜索算法、软件已日趋成熟并投入应用,不过在自动化、兼容性等方面仍具有提升空间.以更自动化、更适应海量数据需求的天体搜索算法研究为宗旨,以现有算法为研究基础,天体自动搜索软件系统得到设计和开发.该系统包含友好的交互式用户操作界面,具备可视化输出数据显示、兼容不同数据输入和输出并包含为实际应用服务的文件管理功能.该系统对于大天区图以及图像集,均能够很好地进行自动化处理.测试结果显示,上述方法对于天体搜索的改进有一定成效.后续将在此基础上对该集成系统做进一步的改进开发,以适应更多的需求.     

Image processing of globular clusters - Simulation for deconvolution tests (GlencoeSim)

This paper presents an algorithmic approach for efficiency tests of deconvolution algorithms in astronomic image processing. Due to the existence of noise in astronomical data there is no certainty that a mathematically exact result of stellar deconvolution exists and iterative or other methods such as aperture or PSF fitting photometry are commonly used. Iterative methods are important namely in the case of crowded fields (e.g., globular clusters). For tests of the efficiency of these iterative methods on various stellar fields, information about the real fluxes of the sources is essential. For this purpose a simulator of artificial images with crowded stellar fields provides initial information on source fluxes for a robust statistical comparison of various deconvolution methods. The “GlencoeSim” simulator and the algorithms presented in this paper consider various settings of Point-Spread Functions, noise types and spatial distributions, with the aim of producing as realistic an astronomical optical stellar image as possible.     

A novel hybrid algorithm for lucky imaging

Lucky imaging is a high-resolution astronomical image recovery technique with two classic implementation algorithms, i.e. image selecting, shifting and adding in image space, and data selecting and image synthesizing in Fourier space. This paper proposes a novel lucky imaging algorithm where with space-domain and frequency-domain selection rates as a link, the two classic algorithms are combined successfully, making each algorithm a proper subset of the novel hybrid algorithm. Experimental results show that with the same experiment dataset and platform, the high-resolution image obtained by the proposed algorithm is superior to that obtained by the two classic algorithms. This paper also proposes a new lucky image selection and storage scheme, which can greatly save computer memory and enable lucky imaging algorithm to be implemented in a common desktop or laptop with small memory and to process astronomical images with more frames and larger size. In addition, through simulation analysis,this paper discusses the binary star detection limits of the novel lucky imaging algorithm and traditional ones under different atmospheric conditions.     

The SumThreshold Method for Radio Frequency Interference Detection

Radio frequency interference (RFI) is one of the main challenges in the search of radio targets and their accurate analysis. The efficient RFI detection and mitigation techniques are required in the radio data processing. Existing RFI mitigation algorithms typically fall into three categories: component decomposition methods, threshold-based methods, and machine learning methods. The threshold-based algorithms are widely used in real applications because of its clear principle, simple structure, and easily implementation. Especially, the SumThreshold method is becoming more concerned for its good performance in RFI detection. Therefore, this work investigates the principles and algorithm of SumThreshold, and discusses its characteristics and applicability.