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Record W2127683304 · doi:10.1109/plans.2008.4570038

Coarse alignment for marine SINS using gravity in the inertial frame as a reference

2008· article· en· W2127683304 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInertial frame of referenceInertial navigation systemFrame (networking)Reference frameComputer scienceVibrationMotion (physics)Marine engineeringGeodesyComputer visionControl theory (sociology)Artificial intelligenceEngineeringGeologyAcousticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

Marine strapdown inertial navigation systems (SINS) inevitably experience disturbing motion, even if the carrier ship is moored. The method of ground coarse alignment, which is based on the assumption that SINS is on a stationary carrier with limited vibration, therefore cannot be used to perform the marine SINS coarse alignment. In this paper, a novel method using the gravity in the inertial frame as a reference is investigated for marine SINS alignment. Its algorithmic principle is described in details. The results obtained from both simulation and turntable-test data show that the attitude determined by this novel method can meet the accuracy requirement of coarse alignment and it can be used as input for fine alignment.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.638
Threshold uncertainty score0.239

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 head0.043
GPT teacher head0.267
Teacher spread0.224 · 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

Quick stats

Citations96
Published2008
Admission routes1
Has abstractyes

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