Comparison of Relative Mean Orbital Element Estimation Methods for Spacecraft Formation Flying
Why this work is in the frame
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Bibliographic record
Abstract
Accurate relative state estimation is a necessity for precision spacecraft formation ying. Inaccurate estimation can lead to excessive fuel use and possible spacecraft collision. Control of mean di erential elements has been identi ed as a promising formation-keeping strategy when considering secular perturbative forces such as J2 and atmospheric drag. This work compares the performance of several di erent techniques for estimating mean di erential orbital elements of a controlled spacecraft in formation ight with a passive target. Inter-satellite range measurements, line of sight measurements, and single di erence pseudorange and carrier phase measurements from the Global Positioning System constellation are considered. An extended Kalman lter and a Gauss-Newton batch estimator are formulated for the di erent measurements and their performances evaluated when subjected to measurement noise. These estimators are compared on the basis of their nal estimation accuracy, and noise levels for inter-satellite range and LOS measurements to achieve precise formation ight are presented.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it