A Low-Cost Photodiode Sun Sensor for CubeSat and Planetary Microrover
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents the development of low-cost methodologies to determine the attitude of a small, CubeSat-class satellite and a microrover relative to the sun's direction. The use of commercial hardware and simple embedded designs has become an effective path for university programs to put experimental payloads in space for minimal cost, and the development of sensors for attitude and heading determination is often a critical part. The development of two compact and efficient but simple coarse sun sensor methodologies is presented in this research. A direct measurement of the solar angle uses a photodiode array sensor and slit mask. Another estimation of the solar angle uses current measurements from orthogonal arrays of solar cells. The two methodologies are tested and compared on ground hardware. Testing results show that coarse sun sensing is efficient even with minimal processing and complexity of design for satellite attitude determination systems and rover navigation systems.
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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