KEYWORDS: Signal to noise ratio, Sensors, Signal processing, Satellites, Digital signal processing, Design and modelling, Image processing, Process control, Spectroscopy, Quantum efficiency
Regarding crop production, which is the basis for food security, improving yields, using fewer materials through the appropriate use of nitrogen fertilizers and pesticides, and protecting the environment have become important global issues. This is part of the Green Food System Strategy announced by Japan's Ministry of Agriculture, Forestry, and Fisheries (MAFF) in May 2021. In this context, we plan to launch a miniature satellite with a hyperspectral sensor to observe Canopy Nitrogen Content (CNC) and Solar-Induced Fluorescence (SIF) in the mid-to the late 2020s. A miniature hyper spectrometer with a wide spectral range of 400 nm to 1700 nm and a narrow spectral resolution of 2nm to 10 nm, with a relatively medium Ground Sampling Distance (GSD) of 70m and Signal-to-Noise Ratio (SNR) of approximately 130 is currently under consideration. System optimization, such as the trade-off between the GSD and SNR under mass and envelope constraints, and the introduction of cutting-edge technologies, such as visible-enhanced InGaAs detectors, are both critical to the realization of specific mission objectives. A feasibility study and preliminary payload design are presented in this thesis.
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