Applications Of Wavelet To LAMOST Spectrum Processing

LAMOST, which is denoted to "Large Sky Area Multi-Object Fiber Spectroscopy Telescope", is one of the National Major Scientific Projects undertaken by the Chinese Academy of Science. LAMOST will be the one that possesses the highest spectrum acquiring rate in the world.LAMOST will obtain several ten-thousands of spectra per night and the data volume will be several gigabytes. It is planned to acquire ten-millions of spectra. Therefore, this paper introduces the process of LAMOST observation and data processing. Then based on learning the theory of wavelet analysis, we availably make use of wavelet to the pretreatment of spectra: denoising and continuum fitting. Finally the difficult issues-wavelength calibration and automatic classification for astronomical spectra are discussed. The main works are described as follows:1. Learning the process of LAMOST observation and data processing, then taking part in developing a series of procedures which can process a group of LAMOST observational data effectively and quickly.2. An improved automatic classification method of celestial spectra is proposed based on wavelet packet and the Support Vector Machines(SVM). Without regarding to the extraction of Spectral Line, the proposed method can effectively recognize the spectra of active objects with unknown red-shift values and low SNR from non-active objects. Experimental results show that the proposed method is effective and robust.3. A new method of wavelength calibration on the basis of the spectral line matching is presented. Through wavelet transform to get zero-crossings, we confirm the effective intervals corresponding with spectral line, and then realize data compression to significantly enhance the data processing speed.