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A New Method for Carrier-Phase-Based Precise Point Positioning

2002· article· en· W2134020105 on OpenAlexafffund
Yang Gao, Xiaobing Shen

Bibliographic record

VenueNAVIGATION Journal of the Institute of Navigation · 2002
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsUniversity of Calgary
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceConvergence (economics)Point (geometry)Integer (computer science)Phase (matter)Precise Point PositioningAmbiguityStability (learning theory)Filter (signal processing)AlgorithmReal-time computingTelecommunicationsComputer visionGlobal Positioning SystemMathematicsMachine learning

Abstract

fetched live from OpenAlex

ABSTRACT: This paper describes a carrier-phase–based precise point positioning (PPP) method based a new observation model. Unlike the traditional PPP processing method, the new method allows for exploitation of the integer characteristics of carrier-phase ambiguities. The new method also opens the door for the development of new algorithms for ambiguity resolution to support real-time PPP applications in the future. Numerical results indicate that the new method is superior to the traditional PPP processing method in terms of positional accuracy, convergence speed, and filter stability.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations178
Published2002
Admission routes2
Has abstractyes

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