A Comparison of the Pseudo-Linear and Extended Kalman Filters for Spacecraft Attitude Estimation
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Bibliographic record
Abstract
Current emphasis on low-budget missions involving small spacecraft leads to a need for an efficient and effective algorithm for attitude and rate estimation. This paper investigates the performance of a Pseudo-Linear Kalman Filter (plkf) with continuous-time dynamics for attitude and rate estimation. The plkf differs from the traditional Extended Kalman Filter (ekf) with its continuous-time dynamics performing estimation using a pseudo-linear state-dependent dynamic model. Both quaternion-based and vector-based measurements have been considered and the dynamic model of the spacecraft accounts for external environmental disturbances. Using computer simulations, the designed filter is shown to overcome large initial errors and yields accurate estimates. The performance indices used for evaluation are based on robustness against plant, measurement and initial estimate errors. While the ekf remains more robust for some cases of angular velocity estimation, the plkf, in general, outperforms the ekf in attitude estimation.
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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