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After January 13, 2012, FY-2F had successfully launched, the total number of the in orbit operating FengYun-2 geostationary meteorological satellites reached three. For accurate and efficient application of multi-satellite observation data, the study of the multi-satellites normalization of the visible detector was urgent. The method required to be non-rely on the in orbit calibration. So as to validate the calibration results before and after the launch; calculate day updating surface bidirectional reflectance distribution function (BRDF); at the same time track the long-term decay phenomenon of the detector's linearity and responsivity. By research of the typical BRDF model, the normalization method was designed. Which could effectively solute the interference of surface directional reflectance characteristics, non-rely on visible detector in orbit calibration. That was the Median Vertical Plane (MVP) method. The MVP method was based on the symmetry of principal plane, which were the directional reflective properties of the general surface targets. Two geostationary satellites were taken as the endpoint of a segment, targets on the intersecting line of the segment's MVP and the earth surface could be used as a normalization reference target (NRT). Observation on the NRT by two satellites at the moment the sun passing through the MVP brought the same observation zenith, solar zenith, and opposite relative direction angle. At that time, the linear regression coefficients of the satellite output data were the required normalization coefficients. The normalization coefficients between FY-2D, FY-2E and FY-2F were calculated, and the self-test method of the normalized results was designed and realized. The results showed the differences of the responsivity between satellites could up to 10.1%(FY-2E to FY-2F); the differences of the output reflectance calculated by the broadcast calibration look-up table could up to 21.1%(FY-2D to FY-2F); the differences of the output reflectance from FY-2D and FY-2E calculated by the site experiment results reduced to 2.9%(13.6% when using the broadcast table). The normalized relative error was also calculated by the self-test method, which was less than 0.2%.
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