Paper
9 February 2001 Modeling the brightness of the Moon over 350 - 2500 nm for spacecraft calibration
James M. Anderson, Hugh H. Kieffer, Kris J. Becker
Author Affiliations +
Abstract
A program to characterize the brightness of the Moon for use with spacecraft calibration is continuing its operation. Observations are made over the wavelength range 350—2500 nm in 32 passbands, almost half of which approximate existing spacecraft bands. Observations of bright stars provide instrument calibration, measure atmospheric extinction, and provide an absolute calibration pathway. The processed data from this project currently contain over 40 000 Lunar images. Photometric models of the total Lunar irradiance are generated from image irradiance sums. Independent radiance models for '- 250000 pixel locations in the calibrated image projection are also calculated, allowing accurate treatment of spacecraft viewing geometries. Within the phase angle range 5_900,the uncertainty in the relative irradiance models is less than 1.5%. At a constant phase angle, the irradiance uncertainty due to libration is significantly lower. These uncertainties are small enough to establish the Moon as a good calibrator for tracking relative instrument stability. The uncertainty in the absolute radiance scale is currently 6—10%, but relative and absolute model uncertainties are expected to decrease with further analysis and as more observations are added to the dataset during the next few years.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James M. Anderson, Hugh H. Kieffer, and Kris J. Becker "Modeling the brightness of the Moon over 350 - 2500 nm for spacecraft calibration", Proc. SPIE 4169, Sensors, Systems, and Next-Generation Satellites IV, (9 February 2001); https://doi.org/10.1117/12.417129
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CITATIONS
Cited by 11 scholarly publications.
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KEYWORDS
Calibration

Reflectivity

Space operations

Short wave infrared radiation

Stars

Atmospheric particles

Data modeling

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