Measuring fiber position errors from spectral data

Precise fiber positioning is crucial to a wide field,multi-fiber spectroscopic survey such as the Guoshoujing Telescope(the Large Sky Area Multi-Object Fiber Spectroscopic Telescope,LAMOST).Nowadays,most position error measurements are based on CCD photographic and image processing techniques.These methods only work for measuring errors orthogonal to the telescope optical axis,but there are also errors that lie parallel to the optical axis of the telescope,such as defocusing,and errors caused by the existing deviation angle between the optical axes of a fiber and the telescope.Directly measuring the two latter types of position errors is difficult for an individual fiber,especially during observations.Possible sources of fiber position errors are discussed in brief for LAMOST.By constructing a model of magnitude loss due to the fiber position error for a point source,we propose an indirect method to calculate both the total and systematic position errors for each individual fiber from spectral data.Restrictions and applications of this method are also discussed.     

The Richardson-Lucy deconvolution method to extract LAMOST 1D spectra

We use the Richardson-Lucy deconvolution algorithm to extract one-dimensional(1 D) spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST) spectrum images. Compared with other deconvolution algorithms, this algorithm is much faster. The application on a real LAMOST image illustrates that the 1 D spectrum resulting from this method has a higher signal-to-noise ratio and resolution than those extracted by the LAMOST pipeline. Furthermore, our algorithm can effectively suppress the ringings that are often present in the 1 D resulting spectra generated by other deconvolution methods.     

均值漂移算法在LAMOST动态选星中的应用

将均值漂移算法运用于LAMOST动态选星过程,用以寻找局部天区内观测目标密度最高的区域进行观测.通过模拟试验分析了在不同的天区覆盖方法对均值漂移算法观测效率的影响,并与使用最大密度算法得到的结果进行了比较,证实了均值漂移算法的优越性.     

LAMOST子镜镀膜研究进展

对大口径光学/红外天文望远镜而言,为保障其稳定高效运行,镜面镀膜是重要的维护环节之一.镀膜质量的好坏直接影响镜面光学反射率的高低,也严重影响到天文望远镜的成像质量、观测效率.国家重大科技基础设施—大天区面积多目标光纤光谱天文望远镜(Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST,又名郭守敬望远镜)自2009年6月通过国家竣工验收并逐步投入巡天观测,目前已进入第2个5 yr巡天计划阶段,取得近两千万的光谱产出和大批高显示度的科学成果. LAMOST共拥有24块施密特改正镜子镜和37块球面主镜子镜,为了确保在野外恶劣观测环境下镜面反射率维持在较高水平,每年要对大批子镜进行镀膜.主要介绍了镀膜需求、镀膜设备,并基于大量实验和多年的完善探索出一套可行的镀膜工艺流程,确保了LAMOST子镜极高的镀膜质量.镀膜后子镜平均反射率高达90%以上,满足了LAMOST光谱巡天的镜面反射率要求.     

Optical fiber positioning based on four-quadrant detector with Gaussian fitting method

With the development of large-scale spectral surveys, fiber positioning technology has been developing rapidly. Because of the performance advantages of a four-quadrant(4Q) detector, a fiber positioning and real-time monitoring system based on the 4Q detector is proposed. The detection accuracy of this system is directly determined by the precision of the center of the spot. A Gaussian fitting algorithm based on the 4Q detector is studied and applied in the fiber positioning process to improve the calculated accuracy of the spot center. The relationship between the center position of the incident spot and the detector output signal is deduced. An experimental platform is built to complete the simulated experiment. Then we use the Gaussian fitting method to process experimental data, compare the fitting value with the theoretical one and calculate the corresponding error.     

撞击坑识别方法综述

目前国内外有多种撞击坑识别方法,在一定程度上实现了对撞击坑的识别提取,但是其准确性以及对数据的适应性不尽相同。首先对撞击坑识别研究进展进行概述,再对撞击坑识别方法进行归纳总结,指出不同方法的优缺点和适用条件。最后,对撞击坑识别研究存在的问题进行分析,提出了研究撞击坑识别的重点及解决途径。     

Automatic Solar Filament Detection Using Image Processing Techniques

We present an automatic solar filament detection algorithm based on image enhancement, segmentation, pattern recognition, and mathematical morphology methods. This algorithm cannot only detect filaments, but can also identify spines, footpoints, and filament disappearances. It consists of five steps: (1) The stabilized inverse diffusion equation (SIDE) is used to enhance and sharpen filament contours. (2) A new method for automatic threshold selection is proposed to extract filaments from local background. (3) The support vector machine (SVM) is used to differentiate between sunspots and filaments. (4) Once a filament is identified, morphological thinning, pruning, and adaptive edge linking methods are used to determine the filament properties. (5) Finally, we propose a filament matching method to detect filament disappearances. We have successfully applied the algorithm to Hα full-disk images obtained at Big Bear Solar Observatory (BBSO). It has the potential to become the foundation of an automatic solar filament detection system, which will enhance our capabilities of forecasting and predicting geo-effective events and space weather.     

Active Optics in LAMOST

Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) is one of the major national projects under construction in China. Active optics is one of the most important technologies for new large telescopes. It is used for correcting telescope errors generated by gravitational and thermal changes. Here, however, we use this technology to realize the configuration of LAMOST, -a task that cannot be done in the traditional way. A comprehensive and intensive research on the active optics used in LAMOST is also reported, including an open-loop control method and an auxiliary closed-loop control method. Another important development is in our pre-calibration method of open-loop control, which is with some new features: simultaneous calculation of the forces and displacements of force actuators and displacement actuators; the profile of mirror can be arbitrary; the mirror surface shape is not expressed by a fitting polynomial, but is derived from the mirror surface shape formula which is highly accurat     

Estimating the Size of Hale-Bopp's Nucleus

A variety of independent methods have been used to estimate the size of the nucleus of comet Hale-Bopp. Several groups have analyzed optical and infrared images of the comet and claim to detect the signature of the nucleus, despite the presence of a strong coma. A detection of the nucleus was also claimed during mm- and cm-wave observations of Hale-Bopp shortly before perihelion. A team of observers detected the occultation of a star by the nucleus of Hale-Bopp in October 1996. The maximum observed gas production rate of the comet near perihelion can be used to place a lower limit on the size of the nucleus. This paper critically reviews the many different methods used to constrain the size of Hale-Bopp's nucleus. All of the techniques are affected by systematic errors that can be difficult to quantify precisely. Nevertheless, the available evidence strongly suggests that the nucleus of Hale-Bopp has an effective radius of at least 15 km and is probably in the range 20–35 km. Thus, the prodigious gas and production rates from this comet are naturally explained by its unusually large size. This revised version was published online in July 2006 with corrections to the Cover Date.     

主动光学─新一代大望远镜的关键技术

对主动光学技术在现代天文光学望远镜中的作用和工作原理作了较全面的介绍和评论。结合作者近十年的工作对薄镜面主动光学技术和拼接镜面主动光学技术的各个关键部分,如波前检测、波前拟合、校正力的确定、共焦和共面的检测作了较详细且深入的讨论和评述．也介绍了我国目前正在研制的同时采用薄镜面主动光学和拼接镜面主动光学技术的大天区面积多目标光纤光谱望远镜的主动光学系统。     

多波段巡天和LAMOST观测目标

综述了国际上多波段巡天工作的进展。其中，x射线波段列举了至今主要的x射线卫星，特别介绍了ROSAT、ASCA、Chandra和XMM—Newton的情况；光学波段主要介绍了SDSS、DEEP以及2df的星系和类星体巡天；红外波段主要介绍了2MASS和SWIRE巡天；射电波段主要介绍了NVSS和FIRST巡天。根据光谱能力和观测模式，提出了LAMOST的选题目标，分析讨论了LAMOST可以开展的交叉证认工作。     

一种新的基于2维傅里叶谱图像的恒星光谱特征提取方法和深度网络分类应用

天体光谱分类是天文学研究的重要内容之一,其关键是从光谱数据中选择和提取对分类识别最有效的特征构建特征空间.提出一种新的基于2维傅里叶谱图像的特征提取方法,并应用于LAMOST (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope)恒星光谱数据的分类研究中.光谱数据来源于LAMOST Data Release 5(DR5),选取30000条F、 G和K型星光谱数据,利用短时傅里叶变换(Short-Time Fourier Transform, STFT)将1维光谱数据变换成2维傅里叶谱图像,对得到的2维傅里叶谱图像采用深度卷积网络模型进行分类,得到的分类准确率是92.90%.实验结果表明通过对LAMOST恒星光谱数据进行STFT可得到光谱的2维傅里叶谱图像,谱图像构成了新的光谱数据特征和特征空间,新的特征对于光谱数据分类是有效的.此方法是对光谱分类的一种全新尝试,对海量天体光谱的分类和挖掘处理有一定的开创意义.     

由两块拼接反射镜组成的光学系统的衍射能量分布

LAMOST的光学系统由反射施密特改正板MA 和球面主镜MB 组成 ,MA 和MB 均为对角径 1 .1m的六角形子镜的拼镜面 .本文计算了星在子午圈上时望远镜观测不同的天区零视场和有视场时的光学系统衍射能量分布 ,还计算了MA 不变MB 改为整块的 6m镜以及MA 和MB 均为对角径 1 .5m的六角形子镜的拼镜面的衍射能量分布 .对这些计算结果进行分析 ,论证了六角形子镜尺寸选择的合理性     

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.     

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.     

Detection of Coronal Mass Ejections Using Multiple Features and Space–Time Continuity

Coronal Mass Ejections (CMEs) release tremendous amounts of energy in the solar system, which has an impact on satellites, power facilities and wireless transmission. To effectively detect a CME in Large Angle Spectrometric Coronagraph (LASCO) C2 images, we propose a novel algorithm to locate the suspected CME regions, using the Extreme Learning Machine (ELM) method and taking into account the features of the grayscale and the texture. Furthermore, space–time continuity is used in the detection algorithm to exclude the false CME regions. The algorithm includes three steps: i) define the feature vector which contains textural and grayscale features of a running difference image; ii) design the detection algorithm based on the ELM method according to the feature vector; iii) improve the detection accuracy rate by using the decision rule of the space–time continuum. Experimental results show the efficiency and the superiority of the proposed algorithm in the detection of CMEs compared with other traditional methods. In addition, our algorithm is insensitive to most noise.     

Microwave geodesy by interferometric radiometry

The aim of this paper is to establish a new method-first introduced by Soviet scientists in 1972 —for mapping the Earth in the microwave region passively using the interference pattern which results by correlating the signals from two radiometers which presumably can be mounted in two or more moving satellites. In such a procedure, the image is enhanced progressively by synthetic composition similar to that achieved by air-borne synthetic aperture radar. The only question left open by the Soviet originators is if the signal-to-backround ratio was sufficiently strong to think about implementing the system in more practical terms. By practical terms, I mean the construction of electronics to surmount instrumental noise and possible atmospheric interference. These two latter questions are not addressed at this stage of the analysis, but only the basic question of signal-to-backround. It appears that the signal-to-backround ratio can be reduced to a minimum level determined by the fringe spacing created which in turn is a function of satellite separation. It is shown that the signal-to-backround ratio becomes proportional to target area over resolution cell size and is enhanced by a mechanism of defocusing the interferometric radiometer. This reduction in the field of view suppresses background noise which surrounds the target within the foot-print size, to the enhancement of signal-to-background ratio. In addition, near field viewing in the Fresnel region permits the determination of cross range as well as range by measurement of the difference in the radii of curvature of the impinging wave front at the different vantage points of the two detectors. Thus near-field interferometric viewing permits two-dimensional range determination contrary to the usual astronomical applications which are far field and only one dimensional.     

一种基于主分量分析的减天光方法

天光是天体观测中的一种重要噪声源.减天光问题是制约多目标光纤光谱观测深度的重要因素.主分量分析(PCA)是统计学的一种分析方法,它可以用来寻找各个天光谱之间的关系,以进一步获得目标光谱中含有的天光成分.为了研究LAMOST的减天光方法,用SDSS的一组原始观测数据进行了仿真实验,实验结果表明,采用PCA方法比SDSS处理程序能够更有效地减天光.最后对PCA方法在LAMOST中的应用前景进行了展望.     

分离式靶标摄影测量在LAMOST中的应用

为了获取LAMOST焦面板上光纤的零位位置,提出了一种基于分离式标准靶标的高精度摄影测量方法。首先,根据Tsai摄像机标定参数模型介绍了CCD相机的标定原理。然后介绍了用光重心算法求取靶标发光点像面坐标及通过球面三角公式计算靶标发光点物面坐标。接着,利用最小二乘法导出了含标定参数的方程组。最后,介绍了标准靶标的放置方法以及提高光纤位置测量精度的靶标取法。实验结果表明:CCD相机的标定残差平均值为8.8μm;标定残差的标准差为5.3μm。测量方法简单易行,通过仔细分析,找出了残差偏大的原因,对后续进一步测量实验有重要指导意义。     

Blind Deconvolution of Astronomical Images with a Constraint on Bandwidth Determined by the Parameters of the Optical System

Atmospheric turbulence severely restricts the spatial resolution of astronomical images obtained by a large ground-based telescope. In order to reduce effectively this effect, we propose a method of blind deconvolution, with a bandwidth constraint determined by the parameters of the telescope's optical system based on the principle of maximum likelihood estimation, in which the convolution error function is minimized by using the conjugate gradient algorithm. A relation between the parameters of the telescope optical system and the image's frequency-domain bandwidth is established, and the speed of convergence of the algorithm is improved by using the positivity constraint on the variables and the limited-bandwidth constraint on the point spread function. To avoid the effective Fourier frequencies exceed the cut-off frequency, it is required that each single image element (e.g., the pixel in the CCD imaging) in the sampling focal plane should be smaller than one fourth of the diameter of the diffraction spot. In the algorithm, no object-centered constraint was used, so the proposed method is suitable for the image restoration of a whole field of objects. By the computer simulation and by the restoration of an actually-observed image of α Piscium, the effectiveness of the proposed method is demonstrated.