Accurate Star Tracker Simulation with On-Orbit Data Verification
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this study, we develop strategies to simulate high-fidelity star tracker images. Improving simulation fidelity enables better quantitative predictions of sensor performance, particularly during agile attitude maneuvers. These high-fidelity simulations use star tracker calibration parameters, detector sensitivity, and a simple representation of the spacecraft's attitude trajectories to synthesize images useful for detailed study of the star tracker accuracy and availability. The simulations include a variety of non-ideal imaging features such as pixel noise, vignetting, distortion, and nonlinear star tracks. The effectiveness of these high-fidelity simulations is assessed by comparing image features and processed sensor measurements obtained from synthetic images with those extracted from the laboratory, night-sky, and on-orbit sensor telemetry.
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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 | 0.001 |
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 it