MétaCan
Menu
Back to cohort

Dual-Frequency GPS Precise Point Positioning with WADGPS Corrections

2007· article· en· W2162889446 on OpenAlexafffund
Hyunho Rho, Richard B. Langley

Bibliographic record

VenueNAVIGATION Journal of the Institute of Navigation · 2007
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsUniversity of New Brunswick
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsGlobal Positioning SystemComputer sciencePrecise Point PositioningSmoothingSatelliteDifferential GPSPseudorangeDual (grammatical number)Noise (video)Point (geometry)GPS disciplined oscillatorProcess (computing)Real-time computingGPS signalsAssisted GPSTelecommunicationsGNSS applicationsComputer visionMathematicsEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

ABSTRACT: The goal of the research described in this paper is the design of a GPS dual-frequency data processing technique capable of producing high-accuracy positioning results with wide area differential GPS (WADGPS) corrections. The main issues in using WADGPS corrections for dual-frequency GPS point positioning are the satellite clock referencing issue and how to handle the increased noise level by use of the ionosphere-free dual-frequency combination. To address these concerns, a sequential forward carrier-phase smoothing technique which utilizes the fully combined uncertainty for both systematic and random errors in the smoothing process has been designed. To account for the satellite clock referencing issue, the effects of the satellite instrumental biases have been precisely investigated and the observation equations for the different observables assuming the source of corrections is WADGPS have been developed. Results determined via developed software indicate that positioning accuracy at the few decimeter-level is attainable at a 95% confidence level.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.008
GPT teacher head0.228
Teacher spread0.219 · 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
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

Citations9
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueNAVIGATION Journal of the Institute of NavigationSame topicGNSS positioning and interferenceFrench-language works237,207