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Record W2047648546 · doi:10.5539/apr.v1n2p83

Ionospheric Correction and Ambiguity Resolution in DGPS with Single Frequency

2009· article· en· W2047648546 on OpenAlexvenueno aff
Norsuzila Ya’acob, Mardina Abdullah, Mahamod Ismail, Kamaruzaman Jusoff

Bibliographic record

VenueApplied Physics Research · 2009
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal Positioning SystemAmbiguity resolutionPseudorangeIonosphereComputer scienceGeodesyRemote sensingReal Time KinematicGPS signalsAmbiguityAssisted GPSTelecommunicationsPhysicsGeologyGNSS applicationsGeophysics

Abstract

fetched live from OpenAlex

The free electron distributed in the atmospheric region known as the ionosphere produces a frequency dependent effecton the Global Positioning System (GPS) signals, a delay in the pseudorange and advance in the carrier phase. Theionospheric influence is one of the main problems in the real-time ambiguity resolution for the carrier phase GPS datain radio navigation. Real Time Kinematics (RTK) and Malaysian Active Station (MASS) data from JUPEM (JabatanUkur dan Pemetaan Malaysia) were used in this analysis. In this study, the effects of initial phase ambiguity at GPS andmodeling of ionosphere on base components were researched. To overcome this problem, a correction ionosphericmodel was used. This correction model could be implemented in single frequency measurements with similar accuracy,which can be obtained from dual frequency.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.035
GPT teacher head0.273
Teacher spread0.238 · 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 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

Citations1
Published2009
Admission routes1
Has abstractyes

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