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Record W2622385610

Improved Satellite Launcher Navigation Performance by Using the Reference Trajectory Data

2015· article· en· W2622385610 on OpenAlexaff
Y. Beaudoin, André Desbiens, Éric Gagnon, René Landry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInertial Sensor and Navigation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsRobustness (evolution)Global Positioning SystemComputer scienceControl theory (sociology)Standard deviationTrajectorySatelliteSatellite navigationAttitude and heading reference systemGeodesySimulationKalman filterEngineeringMathematicsStatisticsAerospace engineeringArtificial intelligenceGeographyTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Abstract : The navigation is a critical element of a satellite launcher. The objective of this research is toevaluate the additional precision and robustness provided to the navigation solution by using the reference trajectory data. To include this information, the error state model of a GPS/INS configuration is augmented to estimate the difference between the launcher and the reference trajectory attitude data. The assessment of the precision gain is made using the standard deviation of the attitude, velocity and position estimation errors. The robustness is evaluated considering the loss of precision caused by a GPS outage. The velocity estimation is slightly improved, but the attitude estimation greatly benefits from the additional information. Also, the robustness to a GPS outage is greatly improved for all estimated values. The augmented model can withstand errors in the variances of the external perturbations. However, this one could be sensitive to modelling errors.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.233

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 head0.078
GPT teacher head0.269
Teacher spread0.191 · 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

Citations3
Published2015
Admission routes1
Has abstractyes

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