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Record W7097975088

31st Annual Precise Time and Time Interval (PTTI) MEeting ENHANCING GPS TIMING ENGINES USING WAAS SIGNALS

2016· article· en· W7097975088 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Frequency and Time Standards
Canadian institutionsnot available
Fundersnot available
KeywordsGlobal Positioning SystemEphemerisAssisted GPSTime to first fixSatelliteInterval (graph theory)Precision Lightweight GPS Receiver
DOInot available

Abstract

fetched live from OpenAlex

Accurate timing sources are becoming a very important issue in the development of networked telecommunication systems. Since the early 1990’s, GPS has been exploited for this purpose. The common GPS time transfer technique is mostly used to minimize the timing error caused by satellite clock and ephemeris errors, and Selective Availability. This technique provides a typical timing accuracy of SO nanoseconds (I sigma). Currently, a new WAAS (Wide Area Augmentation System) is being developed under the authority of the FAA (Federal Aviation Adminisfration). This system is a SatelliteSased Augmentation System (SBAS) which will be used to enhance signal continuity, availability, and integrity to GPS receivers. WAAS is scheduled to be officially commissioned in the summer of 2000. This paper describes the features and performance of a GPS/WAAS Timing Engine developed by Marconi Canada. The paper will discuss the features of the WAAS system and how it can be used to dramatically decrease the timing errors of a GPS engine. Results obtained using a GPS simulator and live signals will be analyzed. Comparative results between a GPS only and a GPS/WAAS Timing Engine will be presented. Finally, additional features of the GPS/WAAS Timing Engine, such as TRAIM (Time Remote Autonomous Integrity Monitoring), will be discussed.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.369
Threshold uncertainty score0.997

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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 teacher head, not a consensus.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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