使用小波技术自动搜寻天体谱线

Astronomical Spectral Lines Auto-Searching using Wavelet Technology

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．

This paper puts forward an automatic method using wavelet analysis to deal with astronomical spectra of stars, nearby galaxies, and AGNs. The continuum is separated from the spectral lines through a wavelet filter bank. The spectral lines are segregated from the residual noisy data by the Hidden Markov Model on the wavelet domain. In the denoising step, we improve the 'tying method' in order to make the model training more robust and more reliable. We use the noise distribution to determine the local thresholds leading to the absorption and emission lines. The Gauss function is used to fit the spectral lines, marking the central wavelengths, as a basis for automatic identification.