MétaCan
Menu
Back to cohort
Record W2888079633 · doi:10.2514/1.a34117

GPS Relative Navigation for the CanX-4 and CanX-5 Formation-Flying Nanosatellites

2018· article· en· W2888079633 on OpenAlexafffund
Erin Kahr, Niels Roth, Oliver Montenbruck, Ben Risi, Robert Zee

Bibliographic record

VenueJournal of Spacecraft and Rockets · 2018
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsUniversity of TorontoUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space AgencyZonta International FoundationEngineers CanadaAlberta InnovatesAlberta Innovates - Technology FuturesOntario Centres of Excellence
KeywordsSpacecraftGlobal Positioning SystemOrbit determinationAerospace engineeringOrbit (dynamics)Computer scienceDifferential GPSGeodesyDifferential (mechanical device)AerospaceRange (aeronautics)Remote sensingEngineeringGeologyTelecommunications

Abstract

fetched live from OpenAlex

In November 2014 the CanX-4 and CanX-5 spacecraft became the first nanosatellites to demonstrate autonomous formation control with error less than 1 m. This feat was accomplished both in along-track formations at 1000 and 500 m range and projected circular orbit formations at 100 and 50 m. This control performance was enabled through carrier-phase differential GPS navigation techniques, providing online relative state estimates typically accurate to better than 10 cm. It was an important milestone on the road to regular and fully operational formation-flying missions. This paper provides an overview of the relative positioning algorithm design, presents an independent assessment of the receiver performance, and assesses the absolute and relative navigation results. The mission’s on-orbit results are compared with an independently determined orbit solution computed using the GPS High Precision Orbit Determination Software Tools at the German Aerospace Centre.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Spacecraft and RocketsSame topicSpacecraft Dynamics and ControlFrench-language works237,207