Bibliographic record
Abstract
This paper investigates the attitude estimation ca pabilities of a debris-removing nanosatellite called deorbite CubeSat. The spacecraft is designed based on the utilizatioi of commercially-available components with long space heritage which are embedded in an eight-unit form factor. The attitud. estimation machinery employed in this work is a discrete time, quaternion-based, extended Kalman filter, which utilize measurements provided by a three-axis rate sensor, five su sensors, and a three-axis magnetometer. To obtain a linear state space model, gravity gradient and magnetic disturbance torque are included in the plant model, and the model is linearizec with respect to the process noise and the states, namely the inertial angular velocities and the quaternions. measurement noises are modelled based on zero-mean Gaussian distributions and are quantified based on the performance of the state-of-the art, commercial-of-the-shelf devices. A Monte Carlo simulatioi is created to analyze the performance of the estimator agains various initial angular velocities and quaternions, both in the sunlit and in the eclipsed portions of the orbit. In light o the results, the accuracy of the deorbiter CubeSat's attitud knowledge is discussed.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".