Abstract
In Chinese new generation meteorological satellite, Hyperspectral greenhouse gas monitoring instrument is the first spectral observation load dedicated to the spectral detection of greenhouse gases, with the ability to track the total amount of greenhouse gases such as CO2, CH4 and CO in orbit. In order to realize high precision and quantitative remote sensing monitoring of greenhouse gases, the monitor should have the characteristics of high signal to noise ratio (SNR) when the signal is weak. Therefore, increasing the effective spectral information and eliminating the noise to increase the SNR is an important research content of the system.
In this paper, a set of on-board data processing method is proposed, which can effectively control the noise of electronic circuits and improve the SNR. The validity of the method is verified by analyzing and processing the data of the monitoring instrument, which provides a new idea and direction for the subsequent satellite application of hyperspectral observation load.
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Wang, Y., Nian, W. (2018). Research and Verification of Spatial Hyperspectral Data Processing Method. In: Urbach, H., Yu, Q. (eds) 4th International Symposium of Space Optical Instruments and Applications. ISSOIA 2017. Springer Proceedings in Physics, vol 209. Springer, Cham. https://doi.org/10.1007/978-3-319-96707-3_24
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DOI: https://doi.org/10.1007/978-3-319-96707-3_24
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