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Record W2961110679 · doi:10.3390/rs11131607

Experimental Investigation of Ocean Wave Measurement Using Short-Range K-Band Radar: Dock-Based and Boat-Based Wind Wave Measurements

2019· article· en· W2961110679 on OpenAlexafffund
Jian Cui, Ralf Bachmayer, Brad de Young, Weimin Huang

Bibliographic record

VenueRemote Sensing · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsMemorial University of Newfoundland
FundersAtlantic Canada Opportunities Agency
KeywordsWave radarWind waveRadarBuoyWave heightDoppler effectRemote sensingGeologyContinuous-wave radarOpticsPhysicsRadar imagingEngineeringTelecommunications

Abstract

fetched live from OpenAlex

In this paper, an ocean wave measurement technique and a newly developed short-range K-band radar are tested. In previous work, the technique and its feasibility were studied based on numerical simulations and wave tank experiments, while its performance at sea was still unknown. Surface current, Stokes drift, and wave breaking can greatly complicate interpreting radar backscatters. The feasibility of the technique needed to be further investigated with sea experiments. Experiments were carried out at a stationary site and from a moving platform. The short-range K-band radar transmitted continuous wave and received backscatters at low-grazing angles. The Bragg-scattering from the radar’s effective footprint dominated the backscatters. The Doppler shift frequency of the Bragg-scattering was attributed to the phase velocity of Bragg waves and modulated by the surface motions induced by current, Stokes drift, platform, and gravity waves. These sources of the Doppler shift frequency were analyzed, and the components induced by wind waves were successfully retrieved and converted into wave spectra that were consistent with the measurements of wave rider buoy. The experimental investigation further validated the feasibility of using short-range K-band radar to measure ocean waves.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.075
GPT teacher head0.233
Teacher spread0.157 · 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 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

Citations9
Published2019
Admission routes2
Has abstractyes

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