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Instantaneous Real-Time Cycle-Slip Correction for Quality Control of GPS Carrier-Phase Measurements

2002· article· en· W2044490862 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNAVIGATION Journal of the Institute of Navigation · 2002
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsGlobal Positioning SystemSmoothingComputer scienceSlip (aerodynamics)KinematicsReal-time computingSimulationControl theory (sociology)Control (management)EngineeringArtificial intelligenceComputer visionTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT: This paper proposes a new cycle-slip correction method that enables instantaneous correction (i.e., using only the current epoch's GPS carrier-phase measurements) at the data quality control stage. The method was originally developed for real-time applications that require consistent high-precision positioning results with the carrier-phase measurements at a 10 Hz data rate. The approach includes (1) two parameters for generating and filtering cycle-slip candidates, and (2) a validation procedure that authenticates correct cycle-slip candidates. Compared with conventional approaches using carrier phases and pseudoranges, the approach does not require a smoothing or filtering process to reduce observation noise. Therefore, it is possible to implement the approach in real-time applications without undue complexity. Simulation tests were conducted to confirm the performance of the approach under worst-case scenarios. Test results for a variety of situations, including static and kinematic modes, short-baseline and long-baseline situations, and low and high data rates, are presented.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.034
GPT teacher head0.287
Teacher spread0.253 · 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