Advancements in data processing for echelle spectrometers: a review

The echelle spectrometer is a sophisticated instrument used for high-resolution spectral analysis, with key applications in ICP, LIBS, and astronomy. Its accuracy in measuring wavelengths largely depends on the data processing methods employed, which have been continuously refined since the instrument's inception. This review provides an overview of the data processing workflow for echelle spectrometers, organized into three main steps: spectral model construction, spectral model optimization, and wavelength extraction. Each step is systematically reviewed, highlighting common methods and principles, along with their respective advantages and limitations. Additionally, the review explores anticipated trends in spectral model construction and optimization techniques. Efficient and precise data processing is essential, as it directly impacts the performance of echelle spectrometers and expands their range of applications.