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Record W2133272479 · doi:10.1109/taes.2012.6324671

Integration of a Triaxial Magnetometer into a Helicopter UAV GPS-Aided INS

2012· article· en· W2133272479 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIEEE Transactions on Aerospace and Electronic Systems · 2012
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsUniversity of Alberta
FundersElse Kröner-Fresenius-Stiftung
KeywordsObservabilityHeading (navigation)Global Positioning SystemExtended Kalman filterInertial navigation systemKalman filterMagnetometerCompassInertial measurement unitComputer scienceGPS/INSControl theory (sociology)EngineeringInertial frame of referenceAerospace engineeringAssisted GPSComputer visionArtificial intelligenceGeographyPhysicsMathematics

Abstract

fetched live from OpenAlex

The University of Alberta's Applied Nonlinear Controls Lab (ANCL) helicopter unmanned aerial vehicle's (UAV's) existing GPS-aided inertial navigation system (INS) does not provide observability of heading angle during hover. This motivates the integration of a triaxial magnetometer aiding sensor into the extended Kalman filter (EKF)-based navigation algorithm. A novel magnetometer calibration procedure is implemented and compared with conventional approaches. Experimental results in ground and flight testing confirm that the observability issue is resolved and demonstrate improvements in attitude estimation.

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 score0.197
Threshold uncertainty score0.596

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 head0.010
GPT teacher head0.223
Teacher spread0.213 · 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