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Accuracy: Adaptive Calibration of Cubesat Radiometer Constellations
- Source :
- IGARSS
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Recent technological developments have enabled usage of constellations of radiometer carrying CubeSats in scientific remote sensing missions. CubeSats, forming such constellations, on the other hand, bring unique challenges in terms of calibration of their instruments as they are easily impacted by ambient conditions. To address this problem, a constellation level calibration framework called “Adaptive Calibration of CUbesat RAdiometer Constellations (ACCURACy)” is introduced in this paper. The framework utilizes machine-learning algorithms such as principal component analysis and density based clustering to separate constellation members into time-adaptive groups of similar-state radiometers based on their telemetry data. Within each group, all radiometers will contribute to a calibration data pool with their absolute calibration measurements. Such shared data pools, which include measurements of different calibration targets at different times, will facilitate frequent N>2-point absolute calibration; thus, reduce and quantify calibration errors and uncertainties.
- Subjects :
- Radiometer
010504 meteorology & atmospheric sciences
Calibration (statistics)
Computer science
0211 other engineering and technologies
02 engineering and technology
01 natural sciences
Telemetry
Calibration
CubeSat
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Constellation
Remote sensing
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium
- Accession number :
- edsair.doi...........0748b3f8d437e239d39119cfbef9bbf9