论文标题

通过最大似然和非参数bootstrap对光谱仪的线性表征和不确定性定量

Linearity Characterization and Uncertainty Quantification of Spectroradiometers via Maximum Likelihood and the Non-parametric Bootstrap

论文作者

Pintar, Adam L., Levine, Zachary H., Yoon, Howard W., Maxwell, Stephen E.

论文摘要

一种用于表征和纠正辐射仪器线性的技术,名称为“通量添加方法”和“组合技术”。在本文中,我们开发了一种与此技术一起使用的严格不确定性量化方法,并说明了与“光束互助”仪器的合成数据和实验数据的使用。我们提出了一个概率模型,该模型通过一组多项式系数将仪器读数与一组未知通量相关联。建议使用未知通量和多项式系数的最大似然估计(MLE),而非参数自举算法则可以实现不确定性定量(例如,它可以返回标准误差)。 合成数据代表辐射仪器的合理输出,并启用该方法的测试和验证。发现这些数据的MLE近似公正,并且发现自举重复措施得出的置信区间与其目标覆盖率为95%一致。对于多项式系数,相对偏置小于1%,观察到的覆盖率范围为90%至97%。实验数据集用于说明如何使用该方法加上一个众所周知的通量水平来实现不确定性的完整校准。归因于仪器非线性响应的估计的不确定性贡献比其大部分范围内的不到0.02%。

A technique for characterizing and correcting the linearity of radiometric instruments is known by the names the "flux-addition method" and the "combinatorial technique". In this paper, we develop a rigorous uncertainty quantification method for use with this technique and illustrate its use with both synthetic data and experimental data from a "beam conjoiner" instrument. We present a probabilistic model that relates the instrument readout to a set of unknown fluxes via a set of polynomial coefficients. Maximum likelihood estimates (MLEs) of the unknown fluxes and polynomial coefficients are recommended, while a non-parametric bootstrap algorithm enables uncertainty quantification (e.g., it can return standard errors). The synthetic data represent plausible outputs of a radiometric instrument and enable testing and validation of the method. The MLEs for these data are found to be approximately unbiased, and confidence intervals derived from the bootstrap replicates are found to be consistent with their target coverage of 95 %. For the polynomial coefficients, the relative bias was less than 1 % and the observed coverages range from 90 % to 97 %. The experimental data set is used to illustrate how a complete calibration with uncertainties can be achieved using the method plus one well-known flux level. The uncertainty contribution attributable to estimation of the instrument's nonlinear response is less than 0.02 % over most of its range.

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