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Record W2088484007 · doi:10.1109/icassp.2010.5495961

A new approach for mitigating carrier phase multipath errors in multi-gnss real-time kinematic (RTK) receivers

2010· article· en· W2088484007 on OpenAlexaff
M. Sahmoudi, Ammar B. Kouki, René Landry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGNSS positioning and interference
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMultipath propagationGNSS applicationsMultipath mitigationComputer scienceAmbiguity resolutionReal-time computingConstraint (computer-aided design)Electronic engineeringAlgorithmGlobal Positioning SystemTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

In this paper, we introduce a new approach for RTK positioning using triple-frequency combinations of GNSS measurements in presence of carrier phase multipath. The proposed method is based on a modification of the LAMBDA method, where the a-priori information on multipath errors is exploited as a constraint in the optimization and ambiguities search process to mitigate the effect of multipath. Triple-frequency combinations of measurements is used to formulate a new carrier phase multipath index, then incorporate it as additional constraint in the LAMBDA method cost function for multi-frequency ambiguity resolution. Simulations and real experiments shows the effectiveness of the developed scheme.

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 categoriesnone
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 score0.929
Threshold uncertainty score0.696

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 head0.024
GPT teacher head0.278
Teacher spread0.254 · 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.

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

Citations5
Published2010
Admission routes1
Has abstractyes

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