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Record W4241191772 · doi:10.1109/joe.2017.2701961

High-Frequency Radar Ocean Surface Cross Section Incorporating a Dual-Frequency Platform Motion Model

2017· article· en· W4241191772 on OpenAlexaff
Yue Ma, Weimin Huang, Eric W. Gill

Bibliographic record

VenueIEEE Journal of Oceanic Engineering · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRadarRadar cross-sectionAmplitudeAcousticsPhysicsFrequency modulationAntenna (radio)GeologyDoppler effectOpticsTelecommunicationsComputer scienceRadio frequency

Abstract

fetched live from OpenAlex

The first- and second-order high-frequency radar cross sections of the ocean surface are derived for an antenna on a floating platform. In this analysis, simulations are conducted for a more complicated platform motion than appear in earlier work and comparisons are made to model outputs for a fixed antenna. Results show that motion-induced peaks appear symmetrically in the Doppler frequency and have less energy in the second-order radar cross section than those in the first-order radar cross section. The magnitude and width of the Bragg peaks are seen to decrease and broaden, respectively, as compared to the case for a fixed antenna. The platform motion modulates the radar signals as a frequency modulator, and the modulation indices are related to the amplitudes of the platform motion. With a larger amplitude of platform motion, more energy is transferred from the Bragg peaks to the motion-induced peaks, and more motion-induced peaks need to be considered.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.222
Teacher spread0.205 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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