基于知識的紅移測量和譜線證認(rèn)方法
Red Shift Determination and Spectral Line Identification Based on Knowledge
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摘要: 該文給出了一種基于知識的天體光譜的紅移測量和譜線證認(rèn)方法。首先，利用特征譜線的相關(guān)知識對紅移候選和特征譜線候選進(jìn)行了定義，并根據(jù)定義交叉確認(rèn)紅移候選和特征譜線候選；然后，利用Parzen窗法對所得到的紅移候選集進(jìn)行密度估計(jì)；最后，確定密度最大的紅移候選，將落入其Parzen窗內(nèi)的所有紅移候選值進(jìn)行平均得到紅移，與這些紅移候選值相對應(yīng)的特征譜線候選即為特征譜線。與現(xiàn)有的基于譜線匹配的方法相比，該方法對譜線提取效果的依賴程度較低。實(shí)驗(yàn)結(jié)果表明：該方法的魯棒性較好，正確率較其它基于譜線匹配的方法有較大提高。
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關(guān)鍵詞:
- 光譜分析;紅移測量;譜線證認(rèn);密度估計(jì)
Abstract: 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. -
段福慶, 吳福朝, 羅阿理等. 用于紅移測量的基于密度估計(jì)的模板匹配法[J].光譜學(xué)與光譜分析.2005, 25(11):1895-[6]羅阿理,趙永恒. 使用小波技術(shù)自動搜索譜線. 天體物理學(xué)報(bào).2000, 20(4):427.436.[8]邊肇祺，張學(xué)工等. 模式識別. 北京清華大學(xué)出版社, 2000, 65:70[9]Kinney A L, Calzetti D, Bohlin R C, et al. Template ultraviolet to near-infrared spectra of star-forming galaxies and their application to k-corrections[J].Astrophysical Journal.1996, 467(8):38- -
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