Baseline drift occurs in various measured spectra, and the existence of a baseline signal will influence qualitative and quantitative analyses. Therefore, it is necessary to perform baseline correction or background elimination before spectral analysis. In this paper, a multiple constrained asymmetric least squares method based on the penalized least squares principle is proposed for baseline correction. The method takes both baseline and peak characteristics into account. Based on the prior knowledge that the left and right boundaries of characteristic peaks should be symmetrical, additional constraints of penalized least squares are added, which ensure the symmetry of spectra. The experimental results of the proposed method on simulated spectra are compared with existing baseline correction methods to verify the accuracy and adaptability of the proposed method. The method is also successfully applied to the baseline correction of real spectra. The results show that it can be effective for estimating the baseline. In addition, this method can also be applied to the baseline correction of other similar spectral signals.

中文翻译：

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用于频谱基线校正的多重约束重加权惩罚最小二乘法

基线漂移发生在各种测量光谱中，基线信号的存在将影响定性和定量分析。因此，有必要在光谱分析前进行基线校正或背景消除。本文提出了一种基于惩罚最小二乘原理的多约束非对称最小二乘法进行基线校正。该方法同时考虑了基线和峰特征。基于特征峰左右边界对称的先验知识，增加了惩罚最小二乘法的附加约束，保证了光谱的对称性。将所提方法在模拟光谱上的实验结果与现有的基线校正方法进行了对比，验证了所提方法的准确性和适应性。该方法也成功地应用于实际光谱的基线校正。结果表明，它可以有效地估计基线。此外，该方法还可应用于其他类似光谱信号的基线校正。