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Record W2027171914 · doi:10.1155/2013/549080

A Low-Cost Photodiode Sun Sensor for CubeSat and Planetary Microrover

2013· article· en· W2027171914 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Aerospace Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsYork University
Fundersnot available
KeywordsCubeSatPhotodiodeSatelliteComputer scienceSimple (philosophy)Heading (navigation)Remote sensingElectronic engineeringAerospace engineeringEngineeringOpticsPhysicsGeography

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.192
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it