低信噪比下短波授时信号的去噪方法研究

提出一种基于经验模态分解与改进型谱减法相结合的低信噪比短波时号语音增强方法,解决在复杂噪声环境下短波时号无法用于定时的问题.该方法的核心思想是利用希尔伯特-黄变换(HHT)算法对带噪短波时号进行经验模态分解,通过最大相关度筛选出含有短波时号的固有模态分量进行重构,再对重构之后的信号进行谱减,从而达到降噪的目的.实验表明:该方法的降噪效果优于传统方法.     

The CLEAN method of spectral analysis and its application to the oscillations of the cataclysmic variable TT Arietis

We studied the one-dimensional spectral analysis CLEAN applied to time series with unequal intervals, tested it with simulated signal, and showed it to be also applicable to noisy series, only the quality of the spectrum is closely correlated with the noise intensity. Applying this method to photometric data of the cataclysmic variable TT Ari quasi-periodic oscillations with periods around 20 min are recovered.     

使用小波技术自动搜寻天体谱线

使用小波技术对包括恒星、近邻星系和ＡＧＮ等不同的天体光谱进行了自动处理．用小波滤波的方法将光谱中的连续谱与诸线分离;然后使用小波域隐含马尔可夫模型（ＨＭＭ）,对已去掉连续谱的光谱进行降噪,同时得到了噪声在每个光谱中的分布;在训练ＨＭＭ的过程中,使用改进的Ｔｙｉｎｇ方法增加训练数据以保证训练的可靠性;利用噪声分布确定出谱线信号的局部阈值,在已经降噪的光谱中找到吸收线和发射线;用高斯函数拟会出谱线的形状,标出线心的波长值,作为自动证认的基础．     

Automated Detection of Oscillating Regions in the Solar Atmosphere

Recently observed oscillations in the solar atmosphere have been interpreted and modeled as magnetohydrodynamic wave modes. This has allowed for the estimation of parameters that are otherwise hard to derive, such as the coronal magnetic-field strength. This work crucially relies on the initial detection of the oscillations, which is commonly done manually. The volume of Solar Dynamics Observatory (SDO) data will make manual detection inefficient for detecting all of the oscillating regions. An algorithm is presented that automates the detection of areas of the solar atmosphere that support spatially extended oscillations. The algorithm identifies areas in the solar atmosphere whose oscillation content is described by a single, dominant oscillation within a user-defined frequency range. The method is based on Bayesian spectral analysis of time series and image filtering. A Bayesian approach sidesteps the need for an a-priori noise estimate to calculate rejection criteria for the observed signal, and it also provides estimates of oscillation frequency, amplitude, and noise, and the error in all of these quantities, in a self-consistent way. The algorithm also introduces the notion of quality measures to those regions for which a positive detection is claimed, allowing for simple post-detection discrimination by the user. The algorithm is demonstrated on two Transition Region and Coronal Explorer (TRACE) datasets, and comments regarding its suitability for oscillation detection in SDO are made.     

EChO spectra and stellar activity II. The case of dM stars

EChO is a dedicated mission to investigate exoplanetary atmospheres. When extracting the planetary signal, one has to take care of the variability of the hosting star, which introduces spectral distortion that can be mistaken as planetary signal. Magneticvariability has to be taken into account in particular for M stars. To this purpose, assuming a one spot dominant model for the stellar photosphere, we develop a mixed observational-theoretical tool to extract the spot’s parameters from the observed optical spectrum. This method relies on a robust library of spectral M templates, which we derive using the observed spectra of quiet M dwarfs in the SDSS database. Our procedure allows to correct the observed spectra for photospheric activity in most of the analyzed cases, reducing the spectral distortion down to the noise levels. Ongoing refinements of the template library and the algorithm will improve the efficiency of our algorithm.     

Impact of Galactic polarized emission on B-mode detection at low multipoles

We use a model of polarized Galactic emission developed by the Planck collaboration to assess the impact of foregrounds on B -mode detection at low multipoles. Our main interest is in applications of noisy polarization data and in particular in assessing the feasibility of B -mode detection by Planck . This limits the complexity of foreground subtraction techniques that can be applied to the data. We analyse internal linear combination techniques and show that the offset caused by the dominant E -mode polarization pattern leads to a fundamental limit of   r ∼ 0.1  for the tensor–scalar ratio even in the absence of instrumental noise. We devise a simple, robust, template fitting technique using multifrequency polarization maps. We show that template fitting using Planck data alone offers a feasible way of recovering primordial B -modes from dominant foreground contamination, even in the presence of noise on the data and templates. We implement and test a pixel-based scheme for computing the likelihood function of cosmological parameters at low multipoles that incorporates foreground subtraction of noisy data.     

10-GHz Tenerife cosmic microwave background observations at 8° resolution and their analysis using a new maximum entropy method

The complete set of data from the Tenerife 10-GHz (8° FWHM) twin-horn, drift scan experiment is described. These data are affected by both long-term atmospheric baseline drifts and short-term noise. A new maximum entropy procedure, utilizing the time invariance and spatial continuity of the astronomical signal, is used to achieve a clean separation of these effects from the astronomical signal, and to deconvolve the effects of the beam-switching. We use a fully positive/negative algorithm to produce two-dimensional maps of the intrinsic sky fluctuations. Known discrete sources and Galactic features are identified in the deconvolved map. The data from the 10-GHz experiment, after baseline subtraction with MEM, are then analysed using conventional techniques, and new constraints on Galactic emission are made.     

Shapiro effect as a possible cause of the low-frequency pulsar timing noise in globular clusters

A prolonged timing of millisecond pulsars has revealed low-frequency uncorrelated (infrared) noise, presumably of astrophysical origin, in the pulse arrival time (PAT) residuals for some of them. Currently available pulsar timing methods allow the statistical parameters of this noise to be reliably measured by decomposing the PAT residual function into orthogonal Fourier harmonics. In most cases, pulsars in globular clusters show a low-frequency modulation of their rotational phase and spin rate. The relativistic time delay of the pulsar signal in the curved spacetime of randomly distributed and moving globular cluster stars (the Shapiro effect) is suggested as a possible cause of this modulation. Extremely important (from an astrophysical point of view) information about the structure of the globular cluster core, which is inaccessible to study by other observational methods, could be obtained by analyzing the spectral parameters of the low-frequency noise caused by the Shapiro effect and attributable to the random passages of stars near the line of sight to the pulsar. Given the smallness of the aberration corrections that arise from the nonstationarity of the gravitational field of the randomly distributed ensemble of stars under consideration, a formula is derived for the Shapiro effect for a pulsar in a globular cluster. The derived formula is used to calculate the autocorrelation function of the low-frequency pulsar noise, the slope of its power spectrum, and the behavior of the σ_z statistic that characterizes the spectral properties of this noise in the form of a time function. The Shapiro effect under discussion is shown to manifest itself for large impact parameters as a low-frequency noise of the pulsar spin rate with a spectral index of n = −1.8 that depends weakly on the specific model distribution of stars in the globular cluster. For small impact parameters, the spectral index of the noise is n = −1.5.     

Astronomical Image Co-adding Method based on Wide-field Image Deconvolution

Due to the atmospheric turbulence, the static aberration, tracking and pointing errors of telescopes, the point spread functions (PSFs) in different fields of view are different. Meanwhile, there are different PSFs in the images obtained by different telescopes. The quality of co-adding image is limited by the image with the poorest quality, and finally the resolution and sensitivity of the quad-channel telescope will also be affected. Dividing the image into some regions with the same type of PSF, and deconvolving these regions can improve the quality of the co-adding image. According to this theory, an image restoration algorithm based on the PSF clustering is proposed. Firstly, this paper makes the PSF clustering analysis by using Self-Organizing Maps, and makes the image segmentation based on the result of the PSF clustering analysis, then using the clustered PSFs to make deconvolutions on the sub-images. Then, the restored sub-images after deconvolution are joined together. Finally, by through the image registration and co-adding, the image with a high signal to noise ratio can be obtained. The result shows that the signal to noise ratio of the astronomical images are improved with our method, and the detection capability on faint stars is also improved.     

Computing the Light Periods of Blazars with the Periodogram Spectral Analysis Method

The periodogram spectral analysis method applicable to equallyspaced time series is discussed, and the method is tested first with a simulated data series. It is confirmed that this method is effective for noisy series. Then, applying this method to the analysis of the light periods of the quasars 3C 279 and 3C 345 as well as the BL Lac objects OJ 287 and ON 231, we obtain their light periods to be 7.14 yr, 10.00 yr, 11.76 yr and 6.80 yr, respectively. These results obtained by periodogram spectral analysis are consistent with those obtained by the Jurkevich method in the literature. We have analyzed the effects of different window functions, and commented on their correct selection in practical applications.     

On the extraction of extended structure from Herschel-SPIRE scanning observations in the presence of 1/f noise

We present results from a study of the impact of uncorrelated 1/ f noise on the extraction of spatial structure, on a range of scales, from sky mapping observations made using the Herschel-SPIRE (the spectral and photometric imaging receiver) photometer in the scan-map mode. These studies were carried out using a detailed instrument simulator, and the output reduced using the map-making algorithm to be implemented in the SPIRE data pipeline. The influence of source size scale, telescope-scanning rate and 1/ f noise knee frequency is investigated, and operational bounds to the expected losses are presented, using the case of zero 1/ f (white) noise as a benchmark. Both cross-linked and non-cross-linked observing options are studied. The results presented here represent the best current estimate of the sensitivity of the SPIRE photometer to emission on arbitrary scales. The data presented are general and scalable to any SPIRE observation made using the scanning mode.     

Processing and compression of noise-dominated data: application to the cosmic microwave background data on board the Planck satellite

We address the problem of encoding and compressing data dominated by noise. Information is decomposed into 'reference' sequences plus arrays containing noisy differences susceptible to being described by a known probability distribution. One can then give reliable estimates of the optimal compression rates by estimating the corresponding Shannon entropy. As a working example, this idea is applied to an idealized model of the cosmic microwave background (CMB) data on board the Planck satellite. Data reduction is a critical issue in space missions because the total information that can be downloaded to Earth is sometimes limited by telemetry allocation. Similar limitations might arise in remotely operated ground based telescopes. This download-rate limitation could reduce the amount of diagnostics sent on the stability of the instruments and, as a consequence, curb the final sensitivity of the scientific signal. Our proposal for Planck consists of taking differences of consecutive circles at a given sky pointing. To a good approximation, these differences could be made independent of the external signal, so that they are dominated by thermal (white) instrumental noise, which is simpler to model than the sky signal. Similar approaches can be found in other individual applications. Generic simulations and analytical predictions show that high compression rates,     can be obtained with minor or zero loss of sensitivity. Possible effects of digital distortion are also analysed. The proposed scheme is flexible and reliable enough to be optimized in relation to other critical aspects of the corresponding application. For Planck , this study constitutes an important step towards a more realistic modelling of the final sensitivity of the CMB temperature anisotropy maps.     

Wavelet domain Bayesian denoising of string signal in the cosmic microwave background

An algorithm is proposed for denoising the signal induced by cosmic strings in the cosmic microwave background. A Bayesian approach is taken, based on modelling the string signal in the wavelet domain with generalized Gaussian distributions. Good performance of the algorithm is demonstrated by simulated experiments at arcminute resolution under noise conditions including primary and secondary cosmic microwave background anisotropies, as well as instrumental noise.     

Estimating the spectral indices of correlated astrophysical foregrounds by a second-order statistical approach

We present the first tests of a new method, the correlated component analysis (CCA) based on second-order statistics, to estimate the mixing matrix, a key ingredient to separate astrophysical foregrounds superimposed to the Cosmic Microwave Background (CMB). In the present application, the mixing matrix is parametrized in terms of the spectral indices of Galactic synchrotron and thermal dust emissions, while the free–free spectral index is prescribed by basic physics, and is thus assumed to be known. We consider simulated observations of the microwave sky with angular resolution and white stationary noise at the nominal levels for the Planck satellite, and realistic foreground emissions, with a position-dependent synchrotron spectral index. We work with two sets of Planck frequency channels: the low-frequency set, from 30 to 143 GHz, complemented with the Haslam 408 MHz map, and the high-frequency set, from 217 to 545 GHz. The concentration of intense free–free emission on the Galactic plane introduces a steep dependence of the spectral index of the global Galactic emission with Galactic latitude, close to the Galactic equator. This feature makes difficult for the CCA to recover the synchrotron spectral index in this region, given the limited angular resolution of Planck , especially at low frequencies. A cut of a narrow strip around the Galactic equator  (| b | < 3°)  , however, allows us to overcome this problem. We show that, once this strip is removed, the CCA allows an effective foreground subtraction, with residual uncertainties inducing a minor contribution to errors on the recovered CMB power spectrum.     

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article,we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the AsiaPacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particlefilter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.     

利用MUSIC算法分析BL Lac天体S5 0716+714光变周期

将基于多重信号分类的MUSIC谱估计算法引入BL Lac天体光变周期分析中.给出了MUSIC算法的基本原理,利用模拟信号检测了算法的频谱分辨率.从大量文献中收集了BL Lac天体S5 0716+714光学V、R、I 3个波段从1994年到2008年的有效观测数据,用MUSIC算法和平均周期图算法分别计算了它们的光变周期,发现存在两个主要光变周期:一个是(3.33±0.08)yr的周期,另一个是(1.24±0.01)yr的周期.对这两种算法的周期估计性能进行了比较,结果表明,MUSIC谱估计算法对样本长度要求较低,具有良好的分辨特性和抗噪声能力,能提高在样本长度较短情况下光变周期分析的准确性.     

Map making in small field modulated CMB polarization experiments: approximating the maximum likelihood method

Map making presents a significant computational challenge to the next generation of kilopixel cosmic microwave background polarization experiments. Years worth of time ordered data (TOD) from thousands of detectors will need to be compressed into maps of the T , Q and U Stokes parameters. Fundamental to the science goal of these experiments, the observation of B modes, is the ability to control noise and systematics. In this paper, we consider an alternative to the maximum likelihood method, called destriping , where the noise is modelled as a set of discrete offset functions and then subtracted from the time stream. We compare our destriping code (Descart: the DEStriping CARTographer) to a full maximum likelihood mapmaker, applying them to 200 Monte Carlo simulations of TOD from a ground-based, partial-sky polarization modulation experiment. In these simulations, the noise is dominated by either detector or atmospheric  1/ f   noise. Using prior information of the power spectrum of this noise, we produce destriped maps of T , Q and U which are negligibly different from optimal. The method does not filter the signal or bias the E- or B-mode power spectra. Depending on the length of the destriping baseline, the method delivers between five and 22 times improvement in computation time over the maximum likelihood algorithm. We find that, for the specific case of single detector maps, it is essential to destripe the atmospheric  1/ f   in order to detect B modes, even though the Q and U signals are modulated by a half-wave plate spinning at 5 Hz.     

基于图像相减和随机森林的AST3巡天暂现源及变源搜寻方法

AST3-2 (Antarctic Survey Telescopes)光学巡天望远镜位于南极大陆最高点冰穹A,其产生的大量观测数据对数据处理的效率提出了较高要求.同时南极通信不便,数据回传有诸多困难,有必要在南极本地实现自动处理AST3-2观测数据,进行变源和暂现源观测的数据处理,但是受到低功耗计算机的限制,数据的快速自动处理的实现存在诸多困难.将已有的图像相减方案同机器学习算法相结合,并利用AST3-2 2016年观测数据作为测试样本,发展一套的暂现源及变源的筛选方法成为可行的选择.该筛选方法使用图像相减法初步筛选出可能的变源,再用主成分分析法抽取候选源的特征,并选择随机森林作为机器学习分类器,在测试中对正样本的召回率达到了97%,验证了这种方法的可行性,并最终在2016年观测数据中探测出一批变星候选体.     

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。     

Decomposing the host galaxy from high-z QSOs using principal component analysis

High resolution deep imaging from space and adaptive optics techniques with large ground-based facilities have enabled studies examining faint host galaxies of high redshift quasi-stellar objects(QSOs).However, the related image processing techniques, especially for a precise point-spread function(PSF) reconstruction and characterization of the host galaxy light profiles, have yet to be optimized. We present here the scientific performance of a principal component analysis(PCA) based PSF subtraction of the central bright point source of high redshift QSO images, as well as further characterization of the host galaxy profile by directly fitting a S`ersic model to the residual image using the Markov Chain Monte Carlo(MCMC)algorithm. With a set of reference PSF star images which represent interleaving exposures between the QSO imaging, we can create an orthogonal basis of eigen-images and restore the PSF of QSO images by projecting the QSO images onto the basis. In this way, we can quantify the modes in which the PSF varies with time by a basis function that characterizes the temporal variations of the reference star as well as the QSO images. To verify the algorithm, we performed a simulation and applied this method to one of the high-z QSO targets from Mechtley et al. We demonstrate that the PCA-based PSF subtraction and further modeling of the galaxy's light profile using MCMC fitting would sufficiently remove the effects from central dominating point sources, and improve characterization ability for the host galaxies of high-z QSOs to the background noise level which is much better than previous two-component fitting procedures.