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Record W1962597240 · doi:10.1139/tcsme-2006-0027

NUMERICAL AND EXPERIMENTAL STUDY OF AN ALGORITHM OF ATTITUDE FOR A STRAP-DOWN INERTIAL SYSTEM

2006· article· en· W1962597240 on OpenAlexaffvenue
Teodor Lucian Grigorie, Adrian Hiliuta, Ruxandra Mihaela Botez, Ioan Aron

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsNumerical integrationAlgorithmMATLABNumerical analysisComputer scienceInertial frame of referenceTruncation errorTruncation (statistics)CommutationSoftwareMathematicsApplied mathematicsEngineeringMathematical analysisVoltagePhysics

Abstract

fetched live from OpenAlex

Two numerical algorithms are presented here: the integration of the Poisson equation of attitude and the calculation of the angles from the elements of the matrix of attitude. The method here suggested lies in the use of a fast algorithm of Wilcox type in which the errors of commutation are eliminated by the use of a numerical artifice implemented in a data acquisition card: information on the angular velocity is given on only one channel among the three channels of the chart (the two other channels are put at zero) during a step of calculation. The numerical simulations are performed and validated by use of the Wilcox integration method which implies errors of commutation, with various orders of truncation, and by the integration method with an algorithm with two rates of calculation. By use of a strap-down inertial system and the Matlab software, real time experimental tests are carried out to calculate the best alternatives of the algorithm of integration resulted from the numerical simulations.

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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.993

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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicInertial Sensor and NavigationFrench-language works237,207