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Record W2084228889 · doi:10.1109/plans.2010.5507318

Collaborative acquisition of weak GPS signals

2010· article· en· W2084228889 on OpenAlexaff
Ping Luo, Mark G. Petovello

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/N0),from different GPS receivers are investigated. It shows that as the antenna spacing is small (0difference 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2010
Admission routes1
Has abstractyes

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