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Record W1636013699 · doi:10.1109/plans.1994.303354

GPS signal availability in an urban area-receiver performance analysis

2002· article· en· W1636013699 on OpenAlexaff
T. Melgard, Gérard Lachapelle, H. Gehue

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIndoor and Outdoor Localization Technologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGlobal Positioning SystemSIGNAL (programming language)Multipath propagationGPS signalsComputer scienceChannel (broadcasting)Code (set theory)Real-time computingRemote sensingAssisted GPSElectronic engineeringTelecommunicationsGeographyEngineering

Abstract

fetched live from OpenAlex

GPS signal availability and DGPS positioning accuracy for two-dimensional navigation in two types of urban area, namely a downtown type with buildings up to 50 stories, and a residential area with two-story housing and tree-lined streets, is investigated using three multi-channel C/A code receiver types, including a fast-reacquisition narrow correlator spacing receiver. Signal availability, defined as the percentage of time during which HDOP/spl les/5, is shown to be strongly dependent on the receiver signal tracking performance. Signal availability variations between receivers exceed 25% in some cases. The DGPS positions obtained with various receivers are intercompared and analysed as a function of satellite geometry and of the multipath environment. The narrow correlator spacing receiver is shown to produce superior positioning results, in terms of repeatability, as compared to the standard wide correlator spacing receivers used. Performance statistics based on repeated test runs are presented for the various scenarios described above.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.194
Teacher spread0.177 · 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 designSimulation or modeling
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

Citations23
Published2002
Admission routes1
Has abstractyes

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