| 光谱学与光谱分析 |
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| The Automatic Recognition and Detection of Sky-Subtraction Residual Componentin the Stellar Spectra |
| AN Ran1, PAN Jing-chang1*, YI Zhen-ping1, WEI Peng2 |
1. School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, Weihai 264209, China
2. Key Laboratory of Optical Astronomy, National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China |
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Abstract The skylines, superimposing on the target spectrum as a main noise, will reduce the signal-to-noise ratio of the spectrum. If the spectrum still contains a large number of high strength skylight residuals after sky-subtraction processing, it will not be conducive to the follow-up analysis of the target spectrum. At present, the study on the automatic recognition of the abnormal sky-subtraction stellar spectra is limited in number. We can only find the abnormal sky-subtraction spectra by manual inspection, and this will reduce the speed of detection. This paper analyzes the influence factors of sky-subtraction results and finds the characteristics of the abnormal sky-subtraction spectra. A simple and effective method is proposed to automatic recognize the abnormal sky-subtraction stellar spectra which have been processed with the LAMOST Pipeline processing procedure and find the positions of the abnormal skylines. In this method, all the spectra are normalized first; the abnormal skyline is determined by detecting whether there exits any high strength skyline residuals which are similar to the emission line or absorption line. Finally, all the abnormal skyline positions in the spectra are obtained in this method. The experimental results with the LAMOST spectroscopic dataset show that this method can recognize the abnormal sky-subtraction spectra and find the abnormal skyline positions of different residual strength effectively. In addition, the method is simple and has high recognition efficiency, and can be applied to the automatic detection of abnormal sky-subtraction of large number of spectra.
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Received: 2015-12-15
Accepted: 2016-04-12
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Corresponding Authors:
PAN Jing-chang
E-mail: pjc@sdu.edu.cn
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