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Record W2084228889 · doi:10.1109/plans.2010.5507318

Collaborative acquisition of weak GPS signals

2010· article· en· W2084228889 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

VenueIEEE/ION Position, Location and Navigation Symposium · 2010
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGlobal Positioning SystemGPS signalsFalse alarmCarrier-to-noise ratioCode (set theory)Doppler effectComputer scienceSIGNAL (programming language)Noise (video)Assisted GPSSignal-to-noise ratio (imaging)Electronic engineeringTelecommunicationsPhysicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Signal commonality among local GPS receivers is studied in this paper. More specifically, the GPS signal parameters, carrier Doppler, code phase and carrier to noise power density (C/N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> ),from different GPS receivers are investigated. It shows that as the antenna spacing is small (<;30 meters) the code phase and carrier Doppler are quite in-common. The code phase falls into the same code bin, while the carrier Doppler difference is mainly due to the clock drifts from different receivers. It also shows that theC/N <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> difference is within a certain range (more than 90% is less than 8dB). The impacts of imperfection of these parameters on GPS signal acquisition are then studied in terms of probability of detection and probability of false alarm. Based on the field measurements and the theoretical analysis, the potential advantage of collaborative GPS signal acquisition is present.

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 score0.044
Threshold uncertainty score0.788

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 head0.004
GPT teacher head0.227
Teacher spread0.222 · 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