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Instantaneous Cycle-Slip Correction for Real-Time PPP Applications

2010· article· en· W2132796734 on OpenAlex
Simon Banville, Richard B. Langley

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 · 2010
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPrecise Point PositioningClassification of discontinuitiesGlobal Positioning SystemComputer scienceReal-time computingKalman filterTracking (education)GeodesyTelecommunicationsMathematicsGNSS applicationsArtificial intelligenceGeography

Abstract

fetched live from OpenAlex

Real-time precise point positioning (PPP) is limited to only a few applications using a moving receiver because the quality of the solution is vulnerable to interruptions in signal tracking. A loss of lock on all GPS signals simultaneously implies that users may have to wait for several minutes before again obtaining cm-level precision. To avoid such a scenario, this paper proposes a method to instantaneously mitigate the impacts of signal interruptions and the resulting cycle slips. The approach is based on a time-differenced solution that allows for estimating the size of cycle slips in a least-squares adjustment. Once cycle slips are corrected, the PPP filter can be modified accordingly so as to prevent the occurrence of discontinuities in the positioning time series. The usefulness of the approach is demonstrated in selected applications such as geodynamics and car navigation.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.389

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 head0.006
GPT teacher head0.234
Teacher spread0.228 · 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