CAJ | 학술논문

我国正在实施的大型巡天项目(LAMOST项目),急需恒星光谱自动识别与分类系统并给出了一种基于光谱特征的恒星自动识别方法.该方法由以下主要步骤组成:(1)利用谱线小波特征进行恒星游线整体估计和恒星Balmer线的检测;(2)利用吸收带小波特征进行吸收带位置和M型星特征频率检测;(3)根据以上检测结果进行发射线星、M型星和早型恒星识别.通过对(sloan digital sky survey,SDSS)(data release four,DR4)中的大量真实光谱数据实验表明,方法具有对噪声鲁棒等特点,发射线星识别率达到97.5%,M型星识别率达到98.1%,早型恒星识别率达到96.8%,类星体和星系的误识别率低于2%.该方法可对相对定标的巡大光谱进行自动识别,符合LAMOST数据的要求.
아국정재실시적대형순천항목(LAMOST항목),급수항성광보자동식별여분류계통병급출료일충기우광보특정적항성자동식별방법.해방법유이하주요보취조성:(1)이용보선소파특정진행항성유선정체고계화항성Balmer선적검측;(2)이용흡수대소파특정진행흡수대위치화M형성특정빈솔검측;(3)근거이상검측결과진행발사선성、M형성화조형항성식별.통과대(sloan digital sky survey,SDSS)(data release four,DR4)중적대량진실광보수거실험표명,방법구유대조성로봉등특점,발사선성식별솔체도97.5%,M형성식별솔체도98.1%,조형항성식별솔체도96.8%,류성체화성계적오식별솔저우2%.해방법가대상대정표적순대광보진행자동식별,부합LAMOST수거적요구.
The LAMOST project, the world's largest sky survey project being implemented in China, urgently needs an automatic stars recognition and classification system. This paper presents a method for auto-recognizing the stars based on spectral feature This method consists of three main steps: First, the integral information of spectral lines is calculated and the stellar Balmer lines are detected by using the wavelet features of spectral lines. Then, the characteristic frequency of M-type stars and the locations of absorption bands are obtained accurately through the wavelet features of absorption bands. Finally, based on the results of the former step, the emission-line stars, M-type stars and early-type stars can be recognized. The extensive experiments with real observed spectra from the SDSS DR4 show that the method can robustly recognize stellar spectra, the correct rate of the emission-line stars is as high as 97. 5%, the correct rate of M-type stars is as high as 98.1 % and the correct rate of early-type stars is as high as 96. 8%. The error rate of the quasars and the galaxies is less than 2%. This method is designed to automatically recognize stellar spectra with relative flux and low signal-to-noise ratio, which is applicable to the LAMOST data.