ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations
As a result of progress in space technology, more scientific missions are benefiting from using CubeSats equipped with radiometers. CubeSat constellations are especially effective in overcoming obstacles in cost, weight, and power. However, these benefits have certain significant downsides, includin...
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MDPI AG
2025-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/3/486 |
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| author | John Bradburn Mustafa Aksoy Lennox Apudo Varvara Vukolov Henry Ashley Dylan VanAllen |
| author_facet | John Bradburn Mustafa Aksoy Lennox Apudo Varvara Vukolov Henry Ashley Dylan VanAllen |
| author_sort | John Bradburn |
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| description | As a result of progress in space technology, more scientific missions are benefiting from using CubeSats equipped with radiometers. CubeSat constellations are especially effective in overcoming obstacles in cost, weight, and power. However, these benefits have certain significant downsides, including the difficulty in calibration due to the increased sensitivity of instruments to ambient conditions. Such limitations prevent conventional calibration methods from being reliably applied to CubeSat radiometers. A novel, constellation-level calibration framework called “Adaptive Calibration of CubeSat Radiometer Constellations (ACCURACy)” is being developed to address this issue. ACCURACy, in its current version, uses telemetry data obtained from thermistors in each CubeSat to cluster constellation members into time-adaptive groups of radiometers in similar states. Each radiometer is assigned membership to a cluster and this status is updated as in-orbit measurements shift in the clustering model. This paper introduces the ACCURACy framework, discusses its theoretical background, and presents a MATLAB prototype with performance and uncertainty analyses using synthetic radiometer data in comparison with traditional radiometer calibration methods. |
| format | Article |
| id | doaj-art-540446b5bf854a46bab49d84fbbf648e |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-540446b5bf854a46bab49d84fbbf648e2025-08-20T02:48:07ZengMDPI AGRemote Sensing2072-42922025-01-0117348610.3390/rs17030486ACCURACy: A Novel Calibration Framework for CubeSat Radiometer ConstellationsJohn Bradburn0Mustafa Aksoy1Lennox Apudo2Varvara Vukolov3Henry Ashley4Dylan VanAllen5Department of Electrical and Computer Engineering, University at Albany—State University of New York, Albany, NY 12222, USADepartment of Electrical and Computer Engineering, University at Albany—State University of New York, Albany, NY 12222, USADepartment of Electrical and Computer Engineering, University at Albany—State University of New York, Albany, NY 12222, USADepartment of Electrical and Computer Engineering, University at Albany—State University of New York, Albany, NY 12222, USADepartment of Electrical and Computer Engineering, University at Albany—State University of New York, Albany, NY 12222, USADepartment of Electrical and Computer Engineering, University at Albany—State University of New York, Albany, NY 12222, USAAs a result of progress in space technology, more scientific missions are benefiting from using CubeSats equipped with radiometers. CubeSat constellations are especially effective in overcoming obstacles in cost, weight, and power. However, these benefits have certain significant downsides, including the difficulty in calibration due to the increased sensitivity of instruments to ambient conditions. Such limitations prevent conventional calibration methods from being reliably applied to CubeSat radiometers. A novel, constellation-level calibration framework called “Adaptive Calibration of CubeSat Radiometer Constellations (ACCURACy)” is being developed to address this issue. ACCURACy, in its current version, uses telemetry data obtained from thermistors in each CubeSat to cluster constellation members into time-adaptive groups of radiometers in similar states. Each radiometer is assigned membership to a cluster and this status is updated as in-orbit measurements shift in the clustering model. This paper introduces the ACCURACy framework, discusses its theoretical background, and presents a MATLAB prototype with performance and uncertainty analyses using synthetic radiometer data in comparison with traditional radiometer calibration methods.https://www.mdpi.com/2072-4292/17/3/486radiometercalibrationmachine learningcubesatsmallsatconstellation |
| spellingShingle | John Bradburn Mustafa Aksoy Lennox Apudo Varvara Vukolov Henry Ashley Dylan VanAllen ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations Remote Sensing radiometer calibration machine learning cubesat smallsat constellation |
| title | ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations |
| title_full | ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations |
| title_fullStr | ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations |
| title_full_unstemmed | ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations |
| title_short | ACCURACy: A Novel Calibration Framework for CubeSat Radiometer Constellations |
| title_sort | accuracy a novel calibration framework for cubesat radiometer constellations |
| topic | radiometer calibration machine learning cubesat smallsat constellation |
| url | https://www.mdpi.com/2072-4292/17/3/486 |
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