Multiple repeat cycles for a satellite mission in a Sun-synchronous orbit
Bibliographic record
Abstract
Although satellites launched into Sun-synchronous orbits do not necessarily have repeat ground-track characteristics, in space missions where the users demand re-imaging or re-observing the same scene periodically, utilizing a repeat ground-track can satisfy the user requirement. For instance, Radarsat-1 was designed in a Sun-synchronous orbit with a 343/24 repeat cycle that implies after 343 revolutions and 24 nodal days, the satellite shall, within an error due to perturbations, return to the same spot over the Earth. Satellite missions in Sun-synchronous, repeat ground-track orbits require periodic inclination and altitude adjustments to maintain their desired Sun-synchronous and repeat orbit parameters (semi-major axis, inclination, days-to-repeat, revolutions-to-repeat, and Local Time of Ascending Node (LTAN)) due to the perturbing effects of drag, the non-spherical shape of the Earth, and the gravitational attraction of the Sun and Moon. For certain values of the LTAN, the coupled perturbations of the Earth's oblateness and the solar attraction can be exploited to minimize the out-of-plane manoeuvres by changing the repeat cycle of the satellite. This paper proposes an orbit control strategy that periodically decreases the semi-major axis of the satellite to a new set of Sun-synchronous repeat ground-track parameters to reduce the overall ΔV required to maintain the orbital elements during the mission and de-orbit the spacecraft at the end of its life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".