摘要
大天区面积多目标光纤光谱望远镜(简称LAMOST)是中国正在建造的一台大型光纤光谱天文望远镜,它的建成将使我国天文学在大规模光学光谱观测以及大视场天文学研究上,居于国际领先地位。
LAMOST一个观测夜将观测到上万条天体的光谱,属于海量数据,因此迫切需要一个全自动的观测运行和数据处理系统。依此为目的,本文介绍了LAMOST的观测和数据处理流程,并针对其中抽谱算法处理时间过长的缺点,对其进行了有效的改进,提高了计算效率。然后对LAMOST光谱预处理中的难点问题——光谱去噪和拟合连续谱做了详细的分析,具体做了以下几方面的工作:
1.提出了基于稀疏表示的小波去噪方法。该方法先对天体光谱进行小波变换得到不同尺度上的小波系数,通过对各个尺度上的小波系数进行稀疏化处理来去除噪声。其优点是在处理小波系数时虽然将其作为整体进行考虑,但依然能保持小波系数的局部特性不变,所以在去噪的同时很好地保持了特征谱线的信息。
2.提出了小波变换和其它方法相结合的连续谱拟合新方法,该方法在做小波变换的过程中,尽量将强谱线扣除掉,并且对所得到的连续谱进行多项式插值或样条拟合,使其尽量逼近真实的连续谱。
3.利用本文提出的去噪和拟合连续谱算法,对传统的减天光和谱线提取方法进行了合理有效的改进,实验结果表明了改进算法的优越性。
Large Sky Area Multi-Object Fiber Spectroscopy Telescope(LAMOST) is one of the National Major Scientific Projects undertaken by the Chinese Academy of Sciences. The set-up of it will make our country a leading role in the research field of large scale spectrum observation and large field astronomy.
LAMOST will obtain several ten-thousands of spectra per night. Therefore an automatically observational controlling and data processing system is in urgent need. This paper firstly introduces the process of observation and data processing as well as methods to improve the algorithm of spectrum flux extraction which solves the disadvantage of processing slowly, making the calculation more effective. Then the difficult issues—spectrum de-nosing and continuum fitting are analyzed in detail. The concrete works are described as follows:
1. A new wavelet de-noising scheme based on sparse representation is presented in this paper. This method removes noise by means of dealing with the wavelet coefficients of each scale based on sparse representation. The method not only takes the structure properties in the wavelet coefficients into consideration, but also can maintain the local characteristics of wavelet coefficients. Therefore it can effectively keep the information of featured spectral lines during the process of de-noising.
2. A combined method of wavelet transform and spine fitting is proposed for continuum fitting. This method removes strong spectral lines during the process of wavelet transform, trying to approximate it to real continuum spectrum.
3. The traditional methods for sky spectrum subtraction and spectral line extraction are improved reasonably and effectively by means of the presented algorithms for de-noising and continuum fitting. Experimental results show the superiority of our improved algorithms.
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