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Record W2549004003 · doi:10.1002/navi.144

An Analysis of SBAS Signal Reception in Space

2016· article· en· W2549004003 on OpenAlex
Erin Kahr, Oliver Montenbruck, Kyle O’Keefe

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNAVIGATION Journal of the Institute of Navigation · 2016
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsUniversity of Calgary
FundersUniversity of TorontoUniversity of Calgary
KeywordsCubeSatGeostationary orbitGNSS augmentationGeodesyGlobal Positioning SystemEphemerisRangingRemote sensingComputer scienceTelecommunicationsGNSS applicationsGeographySatelliteEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

WAAS, EGNOS, GAGAN, and MSAS data have been collected from the CanX-2 CubeSat. The suitability of SBAS for navigation in geostationary orbits (GEO), where SBAS satellites may be permanently in view, was assessed. The analysis revealed that all tracked SBAS transmit enough power to be tracked over Earth's limb. GAGAN has the narrowest gain pattern, WAAS has a similar pattern to EGNOS but a 2–4 dB higher transmit power, and MSAS has the lowest signal power but more even global coverage, with stronger power transmitted towards the edge of the Earth. SBAS ranging typically agrees with GPS single-point positions to within +/−10 m for WAAS and +/−20 m for MSAS and GAGAN. It was determined that the SBAS ranging capability is useable in GEO and other high orbits, provided that fast correction data are applied to the broadcast ephemeris, and the lower accuracies are accounted for. Copyright © 2016 Institute of 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)0.001
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 score0.245
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.273
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