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Enregistrement W6929373501 · doi:10.48336/2w0n-xe71

Blind-time domain motion compensation of and significant-wave height extraction from high-frequency (HF) radar data acquired on a floating platform

2023· article· en· W6929373501 sur OpenAlex

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Notice bibliographique

RevueMemorial University Research Repository (Memorial University) · 2023
Typearticle
Langueen
DomaineComputer Science
ThématiqueMobile and Web Applications
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésRadarAutocorrelationAntenna (radio)Continuous-wave radarDoppler effectTransmitterPulse-Doppler radarRadar engineering detailsDoppler radar

Résumé

récupéré en direct d'OpenAlex

High-frequency surface wave radar (HFSWR) is recognized as one of the essential tools for remote sensing of the ocean surface. It provides wide-area, all-weather, and near-real time surveillance. However, extracting useful information when the radar is mounted on a oating platform can be challenging since the platform motion may considerably affect and contaminate the high-frequency (HF) radar Doppler spectrum. The usual procedure for extracting ocean surface information from a high-frequency surface wave radar transmitting from a oating platform is to first compensate for the motion of the antenna in the acquired motion-contaminated Doppler spectrum and then extract the ocean wave parameters from the motion-compensated result. Two methods for motion compensation of HF radar signals for the case of a floating transmitter and fixed receiver are proposed when the motion parameters (including the amplitude and angular frequency of the motion) are not known a priori. This study assumes that the floating platform follows a single-frequency motion model. In the first method which is a time-domain technique, we estimate motion parameters from the autocorrelation function of the received electric field. The autocorrelation is related to the received radar cross section by application of an inverse temporal Fourier transform. The motion parameters are estimated by comparing the locations of the zeros of the autocorrelation function for the fixed antenna case with those for an antenna on a oating platform. Then, the zeros associated with the platform motion can be found. Alternatively, in the second method which is a frequency-domain approach, we aimed to estimate platform-motion parameters from the received motion-contaminated Doppler spectrum, which is proportional to the observed radar cross-section of the ocean surface from the oating platform. Motion parameters are determined from ii the relation between the locations and amplitudes of the Bragg peaks and motion- induced peaks, and the amplitude and angular frequency of the motion, respectively. While the results from both methods show that the motion parameters are estimated within 10% absolute error, the first method performs the motion compensation in the time domain and does not require frequency-domain data pre-processing, as well as demonstrates generally better results than the second method. The estimated motion parameters are then used to recover the motion-compensated Doppler spectrum from the Doppler spectrum of the antenna on a floating platform, and the results coincide well with the Doppler spectrum of the fixed antenna. In the next stage of the thesis, a new real-time method is proposed to estimate the significant wave height directly from the antenna's received electric field in the time- domain without requiring prior knowledge of the motion parameters or performing motion compensation. Based on the relation between the ocean surface displacement and the received electric field, this method calculates the significant wave height from the windowed variance of the upper envelope of the received electric field. This method is applied for up to second-order backscatter, and the results are compared with the case when only first-order backscatter is considered, and shows a considerable improvement. A preliminary calibration is required, which can be carried out either by the deployment of a wave buoy or by analyzing the data over a time period during which the sea state varies. The results from this simple proposed technique show that it may be used to estimate the signi�cant wave height with a root-mean-square error (RMSE) of less than 12 cm over a wide range of significant wave height values.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,334
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0000,002
Science ouverte0,0020,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,073
Tête enseignante GPT0,277
Écart entre enseignants0,204 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle