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Uncertainties in extracted parameters of a Gaussian emission line profile with continuum background

机译:具有连续背景的高斯发射谱线的提取参数的不确定性

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摘要

We derive analytical equations for uncertainties in parameters extracted by nonlinear least-squares fitting of a Gaussian emission function with an unknown continuum background component in the presence of additive white Gaussian noise. The derivation is based on the inversion of the full curvature matrix (equivalent to Fisher information matrix) of the least-squares error, (chi)~(2), in a four-variable fitting parameter space. The derived uncertainty formulas (equivalent to Cramer-Rao error bounds) are found to be in good agreement with the numerically computed uncertainties from a large ensemble of simulated measurements. The derived formulas can be used for estimating minimum achievable errors for a given signal-to-noise ratio and for investigating some aspects of measurement setup trade-offs and optimization. While the intended application is Fabry-Perot spectroscopy for wind and temperature measurements in the upper atmosphere, the derivation is generic and applicable to other spectroscopy problems with a Gaussian line shape.
机译:我们在存在加性高斯白噪声的情况下,导出了由具有未知连续谱背景分量的高斯发射函数的非线性最小二乘拟合所提取的参数中的不确定性的解析方程。该推导是基于四变量拟合参数空间中最小平方误差(chi)〜(2)的全曲率矩阵(等效于Fisher信息矩阵)的求逆。发现推导的不确定性公式(等效于Cramer-Rao误差范围)与来自大量模拟测量的数值计算的不确定性非常吻合。得出的公式可用于估计给定信噪比的最小可实现误差,以及用于调查测量设置的折衷和优化的某些方面。虽然预期的应用是用于高空风和温度测量的Fabry-Perot光谱,但该推导是通用的,适用于其他具有高斯线形的光谱问题。

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