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High Frequency Radar Cross Sections of the Ocean Surface Incorporating Pitch and Roll Motions of a Floating Platform

2018· article· en· W2904387456 on OpenAlexaff
Yue Ma, Eric W. Gill, Weimin Huang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicOcean Waves and Remote Sensing
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsRadarDoppler effectRadar cross-sectionFrequency modulationAcousticsContinuous-wave radarDoppler radarGeologyPulse-Doppler radarRadar imagingSIGNAL (programming language)AmplitudePhysicsComputer scienceOpticsRadio frequencyTelecommunications

Abstract

fetched live from OpenAlex

The first- and second-order high frequency radar cross sections of the ocean surface incorporating pitch and roll motion of a floating platform are derived. Based on these newly derived radar cross sections, simulations are conducted to show the effect of the pitch and roll motion on the radar Doppler spectra. Compared to the conclusions made from the existing work, the radar cross section models proposed in this paper are reasonably validated. Results show that pitch and roll motion bring a frequency modulation to the radar signal. These cause motion-induced peaks to appear symmetrically in the Doppler frequency. The effect of pitch and roll motion on the radar Doppler spectra is seen to be similar to that caused by horizontal motion of the platform. Increasing the amplitudes of the pitch and roll motion is seen to produce a greater modulation effect on the Doppler spectra.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.998

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 head0.012
GPT teacher head0.212
Teacher spread0.199 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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