Several calibration transfer methods require measurement of a subset of the calibration samples on each future instrument, which is impractical in some applications. Another consideration is that these methods model inter-instrument spectral differences implicitly rather than explicitly. The present work argues that explicit knowledge of the origins of inter-instrument spectral distortions can benefit calibration transfer during the fabrication and assembly of instrumentation, the formation of the multivariate regression, and its subsequent transfer to future instruments. In Part I of this work, a Fourier transform near-infrared system designed to perform noninvasive ethanol measurements was discussed and equations describing the optical distortions caused by self-apodization, retroreflector misalignment, and off-axis detector field of view were provided and examined using laboratory measurements. The spectral distortions were shown to be nonlinear in the amplitude and wavenumber domains, and thus cannot be compensated by simple wavenumber calibration procedures or background correction. Part II presents a calibration transfer method that combines in vivo data with controlled amounts of optical distortions in order to develop a multivariate regression model that is robust to instrument variation. Evaluation of the method using clinical data showed improved measurement accuracy, outlier detection, and generalization to future instruments relative to simple background correction.
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