基于知识的红移测量和谱线证认方法

该文给出了一种基于知识的天体光谱的红移测量和谱线证认方法。首先，利用特征谱线的相关知识对红移候选和特征谱线候选进行了定义，并根据定义交叉确认红移候选和特征谱线候选；然后，利用Parzen窗法对所得到的红移候选集进行密度估计；最后，确定密度最大的红移候选，将落入其Parzen窗内的所有红移候选值进行平均得到红移，与这些红移候选值相对应的特征谱线候选即为特征谱线。与现有的基于谱线匹配的方法相比，该方法对谱线提取效果的依赖程度较低。实验结果表明：该方法的鲁标性较好，正确牢较其它基于谱线匹配的方法有较大提高。

Red Shift Determination and Spectral Line Identification Based on Knowledge

A novel method for redshift determination and spectral line identification of celestial spectra is presented, which is based on the knowledge of feature spectral lines. Firstly, definition of redshift candidate and feature spectral line candidate is given, and the candidates are cross-validated according to the definition; Secondly, the density is estimated at every redshift candidate by using the Parzen window technique; Finally, the average of redshift candidates in Parzen window of the redshift candidate with maximum density is the redshift, and the feature spectral line candidates corresponding to those redshift candidates are feature spectral lines. Compared with other methods of the same kind, this method has a lower dependence on the quality of spectral line extraction. Experiments show that this method is robust and the correct rate is encouraging.