Ocean wind and wave parameter estimation from ship-borne x-band marine radar data

Ocean wind and wave parameters are important for the study of oceanography, on- and off-shore activities, and the safety of ship navigation. Conventionally, such parameters have been measured by in-situ sensors such as anemometers and buoys. During the last three decades, sea surface observation usi...

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Main Author: Liu, Xinlong
Format: Thesis
Language:English
Published: Memorial University of Newfoundland 2018
Subjects:
Online Access:https://research.library.mun.ca/13173/
https://research.library.mun.ca/13173/1/thesis.pdf
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spelling ftmemorialuniv:oai:research.library.mun.ca:13173 2023-10-01T03:58:05+02:00 Ocean wind and wave parameter estimation from ship-borne x-band marine radar data Liu, Xinlong 2018-05 application/pdf https://research.library.mun.ca/13173/ https://research.library.mun.ca/13173/1/thesis.pdf en eng Memorial University of Newfoundland https://research.library.mun.ca/13173/1/thesis.pdf Liu, Xinlong <https://research.library.mun.ca/view/creator_az/Liu=3AXinlong=3A=3A.html> (2018) Ocean wind and wave parameter estimation from ship-borne x-band marine radar data. Doctoral (PhD) thesis, Memorial University of Newfoundland. thesis_license Thesis NonPeerReviewed 2018 ftmemorialuniv 2023-09-03T06:49:08Z Ocean wind and wave parameters are important for the study of oceanography, on- and off-shore activities, and the safety of ship navigation. Conventionally, such parameters have been measured by in-situ sensors such as anemometers and buoys. During the last three decades, sea surface observation using X-band marine radar has drawn wide attention since marine radars can image both temporal and spatial variations of the sea surface. In this thesis, novel algorithms for wind and wave parameter retrieval from X-band marine radar data are developed and tested using radar, anemometer, and buoy data collected in a sea trial off the east coast of Canada in the North Atlantic Ocean. Rain affects radar backscatter and leads to less reliable wind parameters measurements. In this thesis, algorithms are developed to enable reliable wind parameters measurements under rain conditions. Firstly, wind directions are extracted from raincontaminated radar data using either a 1D or 2D ensemble empirical mode decomposition (EEMD) technique and are seen to compare favourably with an anemometer reference. Secondly, an algorithm based on EEMD and amplitude modulation (AM) analysis to retrieve wind direction and speed from both rain-free and rain-contaminated X-band marine radar images is developed and is shown to be an improvement over an earlier 1D spectral analysis-based method. For wave parameter measurements, an empirical modulation transfer function (MTF) is required for traditional spectral analysis-based techniques. Moreover, the widely used signal-to-noise ratio (SNR)-based method for significant wave height (HS) estimation may not always work well for a ship-borne X-band radar, and it requires external sensors for calibration. In this thesis, two methods are first presented for HS estimation from X-band marine radar data. One is an EEMD-based method, which enables satisfactory HS measurements obtained from a ship-borne radar. The other is a modified shadowingbased method, which enables HS measurements without the inclusion of ... Thesis North Atlantic Memorial University of Newfoundland: Research Repository Canada
institution Open Polar
collection Memorial University of Newfoundland: Research Repository
op_collection_id ftmemorialuniv
language English
description Ocean wind and wave parameters are important for the study of oceanography, on- and off-shore activities, and the safety of ship navigation. Conventionally, such parameters have been measured by in-situ sensors such as anemometers and buoys. During the last three decades, sea surface observation using X-band marine radar has drawn wide attention since marine radars can image both temporal and spatial variations of the sea surface. In this thesis, novel algorithms for wind and wave parameter retrieval from X-band marine radar data are developed and tested using radar, anemometer, and buoy data collected in a sea trial off the east coast of Canada in the North Atlantic Ocean. Rain affects radar backscatter and leads to less reliable wind parameters measurements. In this thesis, algorithms are developed to enable reliable wind parameters measurements under rain conditions. Firstly, wind directions are extracted from raincontaminated radar data using either a 1D or 2D ensemble empirical mode decomposition (EEMD) technique and are seen to compare favourably with an anemometer reference. Secondly, an algorithm based on EEMD and amplitude modulation (AM) analysis to retrieve wind direction and speed from both rain-free and rain-contaminated X-band marine radar images is developed and is shown to be an improvement over an earlier 1D spectral analysis-based method. For wave parameter measurements, an empirical modulation transfer function (MTF) is required for traditional spectral analysis-based techniques. Moreover, the widely used signal-to-noise ratio (SNR)-based method for significant wave height (HS) estimation may not always work well for a ship-borne X-band radar, and it requires external sensors for calibration. In this thesis, two methods are first presented for HS estimation from X-band marine radar data. One is an EEMD-based method, which enables satisfactory HS measurements obtained from a ship-borne radar. The other is a modified shadowingbased method, which enables HS measurements without the inclusion of ...
format Thesis
author Liu, Xinlong
spellingShingle Liu, Xinlong
Ocean wind and wave parameter estimation from ship-borne x-band marine radar data
author_facet Liu, Xinlong
author_sort Liu, Xinlong
title Ocean wind and wave parameter estimation from ship-borne x-band marine radar data
title_short Ocean wind and wave parameter estimation from ship-borne x-band marine radar data
title_full Ocean wind and wave parameter estimation from ship-borne x-band marine radar data
title_fullStr Ocean wind and wave parameter estimation from ship-borne x-band marine radar data
title_full_unstemmed Ocean wind and wave parameter estimation from ship-borne x-band marine radar data
title_sort ocean wind and wave parameter estimation from ship-borne x-band marine radar data
publisher Memorial University of Newfoundland
publishDate 2018
url https://research.library.mun.ca/13173/
https://research.library.mun.ca/13173/1/thesis.pdf
geographic Canada
geographic_facet Canada
genre North Atlantic
genre_facet North Atlantic
op_relation https://research.library.mun.ca/13173/1/thesis.pdf
Liu, Xinlong <https://research.library.mun.ca/view/creator_az/Liu=3AXinlong=3A=3A.html> (2018) Ocean wind and wave parameter estimation from ship-borne x-band marine radar data. Doctoral (PhD) thesis, Memorial University of Newfoundland.
op_rights thesis_license
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