Combination of terrestrial reference frames based on space geodetic techniques in SHAO:methodology and main issues

Based on years of input from the four geodetic techniques （SLR, GPS, VLBI and DORIS）, the strategies of the combination were studied in SHAO to generate a new global terrestrial reference frame as the material realization of the ITRS defined in IERS Conventions. The main input includes the time series of weekly solutions （or fortnightly for SLR 1983-1993） of observational data for satellite techniques and session-wise normal equations for VLBI. The set of estimated unknowns includes 3- dimensional Cartesian coordinates at the reference epoch 2005.0 of the stations distributed globally and their rates as well as the time series of consistent Earth Orientation Parameters （EOPs） at the same epochs as the input. Besides the final solution, namely SOL-2, generated by using all the inputs before 2015.0 obtained from short-term observation processing, another reference solution, namely SOL- 1, was also computed by using the input before 2009.0 based on the same combination of procedures for the purpose of comparison with ITRF2008 and DTRF2008 and for evaluating the effect of the latest six more years of data on the combined results. The estimated accuracy of the x-component and y-component of the SOL- 1 TRF-origin was better than 0.1 mm at epoch 2005.0 and better than 0.3 mm yr- 1 in time evolution, either compared with ITRF2008 or DTRF2008. However, the z-component of the translation parameters from SOL-1 to ITRF2008 and DTRF2008 were 3.4 mm and -1.0 ram, respectively. It seems that the z-component of the SOL-1 TRF-origin was much closer to the one in DTRF2008 than the one in ITRF2008. The translation parameters from SOL-2 to ITRF2014 were 2.2, -1.8 and 0.9 mm in the x-, y- and z-components respectively with rates smaller than 0.4 mmyr-1. Similarly, the scale factor transformed from SOL-1 to DTRF2008 was much smaller than that to ITRF2008. The scale parameter from SOL-2 to ITRF2014 was -0.31 ppb with a rate lower than 0.01 ppb yr-1. The external precision （WRMS） compared with IERS EOP 08 C04 of the combined EOP series was smaller than 0.06 mas for the polar motions, smaller than 0.01 ms for the UT1-UTC and smaller than 0.02 ms for the LODs. The precision of the EOPs in SOL-2 was slightly higher than that of SOL-1.

Improved astrometry of space debris with image restoration

In order to implement an observing strategy, image degradation that occurs during optical observation of space debris is ineluctable and has distinct characteris- tics. Image restoration is presented as a way to remove the influence of degradation in CCD images of space debris, based on assumed PSF models with the same F-WHM as images of the object. In the process of image restoration, the maximum entropy method is adopted. The results of reduction using observed raw CCD images indi- cate that the precision in estimating positions of objects is improved and the effects of degradation are reduced. Improving the astrometry of space debris using image restoration is effective and feasible.

Analysis of the geomorphology surrounding the Chang'e-3 landing site

Chang＇e-3 （CE-3） landed on the Mare Imbrium basin in the east part of Sinus Iridum （19.51°W, 44.12°N）, which was China＇s first soft landing on the Moon and it started collecting data on the lunar surface environment. To better understand the environment of this region, this paper utilizes the available high-resolution topography data, image data and geological data to carry out a detailed analysis and research on the area surrounding the landing site （Sinus Iridum and 45 km×70 km of the landing area） as well as on the topography, landform, geology and lunar dust of the area surrounding the landing site. A general topographic analysis of the surrounding area is based on a digital elevation model and digital elevation model data acquired by Chang＇e-2 that have high resolution; the geology analysis is based on lunar geological data published by USGS; the study on topographic factors and distribution of craters and rocks in the surrounding area covering 4km^4km or even smaller is based on images from the CE-3 landing camera and images from the topographic camera; an analysis is done of the effect of the CE-3 engine plume on the lunar surface by comparing images before and after the landing using data from the landing camera. A comprehensive analysis of the results shows that the landing site and its surrounding area are identified as typical lunar mare with flat topography. They are suitable for maneuvers by the rover, and are rich in geological phenomena and scientific targets, making it an ideal site for exploration.

A new lunar absolute control point: established by images from the landing camera on Chang'e-3

The establishment of a lunar control network is one of the core tasks in selenodesy, in which defining an absolute control point on the Moon is the most im- portant step. However, up to now, the number of absolute control points has been very sparse. These absolute control points have mainly been lunar laser ranging retrore- flectors, whose geographical location can be observed by observations on Earth and also identified in high resolution lunar satellite images. The Chang＇e-3 （CE-3） probe successfully landed on the Moon, and its geographical location has been monitored by an observing station on Earth. Since its positional accuracy is expected to reach the meter level, the CE-3 landing site can become a new high precision absolute control point. We use a sequence of images taken from the landing camera, as well as satellite images taken by CE-1 and CE-2, to identify the location of the CE-3 lander. With its geographical location known, the CE-3 landing site can be established as a new abso- lute control point, which will effectively expand the current area of the lunar absolute control network by 22%, and can greatly facilitate future research in the field of lunar surveying and mapping, as well as selenodesy.

An improved astrometric calibration technique for space debris observation

An optical survey is the main technique for detecting space debris. Due to the specific character- istics of observation, the pointing errors and tracking errors of the telescope as well as image degradation may be significant, which make it difficult for astrometric calibration. Here we present an improved method that corrects the pointing and tracking errors, and measures the image position precisely. The pipeline is tested on a number of CCD images obtained from a 1-m telescope administered by Xinjiang Astronomical Observatory while observing a GPS satellite. The results show that the position measurement error of the background stars is around 0.1 pixel, while the time cost for a single frame is about 7.5 s; hence the relia- bility and accuracy of our method are demonstrated. In addition, our method shows a versatile and feasible way to perform space debris observation utilizing non-dedicated telescopes, which means more sensors could be involved and the ability to perform surveys could be improved.

Contour detection in Cassini ISS images based on Hierarchical Extreme Learning Machine and Dense Conditional Random Field

In Cassini ISS(Imaging Science Subsystem)images,contour detection is often performed on disk-resolved objects to accurately locate their center.Thus,contour detection is a key problem.Traditional edge detection methods,such as Canny and Roberts,often extract the contour with too much interior details and noise.Although the deep convolutional neural network has been applied successfully in many image tasks,such as classification and object detection,it needs more time and computer resources.In this paper,a contour detection algorithm based on H-ELM(Hierarchical Extreme Learning Machine)and Dense CRF(Dense Conditional Random Field)is proposed for Cassini ISS images.The experimental results show that this algorithm’s performance is better than both traditional machine learning methods,such as Support Vector Machine,Extreme Learning Machine and even deep Convolutional Neural Network.The extracted contour is closer to the actual contour.Moreover,it can be trained and tested quickly on the general configuration of PC,and thus can be applied to contour detection for Cassini ISS images.

Fast compression and reconstruction of astronomical images based on compressed sensing

With the fast increase in the resolution of astronomical images, the question of how to process and transfer such large images has become a key issue in astronomy. We propose a new real-time compression and fast reconstruction algorithm for astronomical images based on compressive sensing techniques. We first reconstruct tile Original signal with fewer measurements, according to its compressibility. Then, based on the characteristics of astronomical images, we apply Daubechies orthogonal wavelets to obtain a sparse representation. A matrix representing a random Fourier ensembleis used to obtain a sparse representation in a lower dimensional space. For reconstructing the image, we propose a novel minimum total variation with block addptive sensing to balance the accuracy and eomputation time. Our experimental results show that the proposed algorithm can efficiently reconstruct colorful astronomicai images with high resolution and improve the applicability of compressed sensing.

Automated removal of stripe interference in full-disk solar images

The quality of full-disk solar Hα images is significantly degraded by stripe interference. In this paper, to improve the analysis of morphological evolution, a robust solution for stripe interference removal in a partial full-disk solar Hα image is proposed. The full-disk solar image is decomposed into a set of support value images on different scales by convolving the image with a sequence of multiscale support value filters, which are calculated from the mapped least-squares support vector machines （LS-SVMs）. To match the resolution of the support value images, a scale-adaptive LS-SVM regression model is used to remove stripe interference from the support value images. We have demonstrated the advantages of our method on solar Hα images taken in 2001-2002 at the Huairou Solar Observing Station. Our experimental results show that our method can remove the stripe interference well in solar Hα images and the restored image can be used in morphology researches.

A new segmentation algorithm for lunar surface terrain based on CCD images

Terrain classification is one of the critical steps used in lunar geomorphologic analysis and landing site selection. Most of the published works have focused on a Digital Elevation Model （DEM） to distinguish different regions of lunar terrain. This paper presents an algorithm that can be applied to lunar CCD images by blocking and clustering according to image features, which can accurately distinguish between lunar highland and lunar mare. The new algorithm, compared with the traditional algo- rithm, can improve classification accuracy. The new algorithm incorporates two new features and one Tamura texture feature. The new features are generating an enhanced image histogram and modeling the properties of light reflection, which can represent the geological characteristics based on CCD gray level images. These features are ap- plied to identify texture in order to perform image clustering and segmentation by a weighted Euclidean distance to distinguish between lunar mare and lunar highlands. The new algorithm has been tested on Chang＇e-1 CCD data and the testing result has been compared with geological data published by the U.S. Geological Survey. The result has shown that the algorithm can effectively distinguish the lunar mare from highlands in CCD images. The overall accuracy of the proposed algorithm is satisfactory, and the Kappa coefficient is 0.802, which is higher than the result of combining the DEM with CCD images.

A method and results of color calibration for the Chang'e-3 terrain camera and panoramic camera

The terrain camera （TCAM） and panoramic camera （PCAM） are two of the major scientific payloads installed on the lander and rover of the Chang＇e 3 mission re- spectively. They both use a Bayer color filter array covering CMOS sensor to capture color images of the Moon＇s surface. RGB values of the original images are related to these two kinds of cameras. There is an obvious color difference compared with human visual perception. This paper follows standards published by the International Commission on Illumination to establish a color correction model, designs the ground calibration experiment and obtains the color correction coefficient. The image qual- ity has been significantly improved and there is no obvious color difference in the corrected images. Ground experimental results show that： （1） Compared with uncor- rected images, the average color difference of TCAM is 4.30, which has been reduced by 62.1%. （2） The average color differences of the left and right cameras in PCAM are 4.14 and 4.16, which have been reduced by 68.3% and 67.6% respectively.

空间碎片跟踪图像序列的目标识别方法

自动化观测已成为目前空间碎片光学观测的发展趋势,相应的完全无人工干预的目标自动识别成为迫切需要研究的课题.开环跟踪依据历史根数引导望远镜进行碎片的跟踪观测,是一种实现简单并且很稳健的观测方法.针对开环跟踪获取的观测图像,开展了目标在像素空间内的点列特征分析,提出使用像点簇识别算法来进行目标的自动识别,并对3种不同的簇识别算法实现进行了比较.

Preliminary results of solving the problem of geometric distortion for the 2.4 m telescope at Yunnan Observatory

We observed the open clusters NGC 1664 （43 exposures） and M35 （42 ex- posures） by the Yunnan Faint Object Spectrograph and Camera in the 2.4 m telescope at Yunnan Astronomical Observatory on 2011 January 3, and processed them by a method recently proposed by us. The result shows that there is a geometric distortion effect in the field of view and the maximum distortion is - 0.25 （i.e. 1 pixel）. After correcting the geometric distortion, the precision of stellar positional measurement is significantly improved. The best precision in each direction is 6 mas for well-exposed stars.

基于图像位移叠加方法探测暗弱小行星

为了提高对太阳系内暗弱小天体的探测能力,将位移叠加方法应用于时序光学图像的处理,提高了暗弱小行星的识别效率.通过试位法预估动目标的视运动速度,确定动目标的存在性,进一步根据目标星象特征判据(信噪比和星象伸长率)迭代确定动目标的精确位置.将位移叠加方法运用在近地天体望远镜同一天区连续曝光的多幅图像的处理中,成功探测到暗于21 mag的单帧不可见动目标,验证了图像位移叠加方法探测暗弱动目标的可行性.

Cassini ISS图像可测性分类的初步研究

Cassini的光学成像系统(Imaging Science Subsystem,ISS)拍摄了大量的土星及其卫星的图像,其中一部分可以用来做天体测量工作,但是需要人工挑拣出来,这是一项繁重的工作.研究目的是将这种工作自动化.为此,将卷积神经网络(Convolution Neural Network,CNN)与支持向量机(Support Vector Machine,SVM)结合起来,提出了一种ISS图像可测性分类系统.系统首先通过深度卷积网络提取ISS图像的特征描述子,然后使用SVM分类器根据图像的特征描述子对图像进行分类.对比了3种有代表性的深度卷积网络:CNN-F、CNN-M-128和Very Deep-19,实验结果表明:CNN-F卷积网络加SVM可以提供较好的分类结果,其分类准确率在97%以上.研究不仅可用于Cassini ISS图像的天体测量工作,也可以推广到其他空间探测项目的类似工作中.

采用云量仪提高光电望远镜观测效率的探索

光电望远镜按编目次序对空间碎片进行跟踪,对于有云层分布的夜空,不能根据云量分布情况实时调整观测次序,造成望远镜资源浪费,影响探测目标数量.云量仪用于实时采集全天空的红外云量图像,测定云量分布与定位的同时,可以对望远镜的观测调度策略进行优化.实验测试表明云量仪优化的观测调度策略有效可行,能够充分利用现有资源,在多云条件下使望远镜实现见缝插针式的工作,显著提高观测设备效率.

Investigation of intergranular bright points from the New Vacuum Solar Telescope

Six high-resolution TiO-band image sequences from the New Vacuum Solar Telescope （NVST） are used to investigate the properties of intergranular bright points （igBPs）. We detect the igBPs using a Laplacian and morphological dilation algorithm （LMD） and automatically track them using a three- dimensional segmentation algorithm, and then investigate the morphologic, photometric and dynamic prop- erties of igBPs in terms of equivalent diameter, intensity contrast, lifetime, horizontal velocity, diffusion index, motion range and motion type. The statistical results confirm previous studies based on G-band or TiO-band igBPs from other telescopes. These results illustrate that TiO data from the NVST are stable and reliable, and are suitable for studying igBPs. In addition, our method is feasible for detecting and track- ing igBPs with TiO data from the NVST. With the aid of vector magnetograms obtained from the Solar Dynamics Observatory/Helioseismic and Magnetic Imager, the properties of igBPs are found to be strongly influenced by their embedded magnetic environments. The areal coverage, size and intensity contrast values of igBPs are generally larger in regions with higher magnetic flux. However, the dynamics of igBPs, includ- ing the horizontal velocity, diffusion index, ratio of motion range and index of motion type are generally larger in the regions with lower magnetic flux. This suggests that the absence of strong magnetic fields in the medium makes it possible for the igBPs to look smaller and weaker, diffuse faster, and move faster and further along a straighter path.

A solar radio dynamic spectrograph with flexible temporal-spectral resolution

Observation and research on solar radio emission have unique scientific values in solar and space physics and related space weather forecasting applications, since the observed spectral structures may carry important information about energetic electrons and underlying physical mechanisms. In this study, we present the design of a novel dynamic spectrograph that has been installed at the Chashan Solar Radio Observatory operated by the Laboratory for Radio Technologies, Institute of Space Sciences at Shandong University. The spectrograph is characterized by real-time storage of digitized radio intensity data in the time domain and its capability to perform off-line spectral analysis of the radio spectra. The analog signals received via antennas and amplified with a low-noise amplifier are converted into digital data at a speed reaching up to 32 k data points per millisecond. The digital data are then saved into a high- speed electronic disk for further off-line spectral analysis. Using different word lengths （1-32k） and time cadences （5 ms-10 s） for off-line fast Fourier transform analysis, we can obtain the dynamic spectrum of a radio burst with different （user-defined） temporal （5 ms-10 s） and spectral （3 kHz-320kHz） resolutions. This enables great flexibility and convenience in data analysis of solar radio bursts, especially when some specific fine spectral structures are under study.