Multiresolution analysis of the ocean surface image: a case study based on X-radar data
Multiresolution analysis of the ocean surface image: a case study based on X-radar data
The problem of analysing the ocean waves behaviour represents a widely discussed topic, which finds many applications in several technical fields. In this paper a numerical elaboration of X-radar data is presented; in particular, the dual tree complex wavelet (DT-CoWT) transform has been applied to radar image samples to perform a spectral analysis of the waves and eventually separate the noise (which in radar applications corresponds to small amplitude waves and ripples) from the harmonics which actually carry a significant contribution of energy in a fluid-structure interaction context. This aspect has a strong importance in the particular field of quiescent period prediction (QPP), which consists of predicting the ship motions due to the waves. More specifically, if the waves are measured from a long distance, it is possible to predict their propagation along a specific direction, evaluate their interaction with the ship and subsequently calculate the corresponding ship motions. The actual definition of ‘quiescent period’ indicates the period of time during which the ship motion is within a certain range in order to carry out a number of possible operations (landing and recovery of air vehicles, rescue etc.) safely. The assessment of a threshold which actually corresponds to a quiescent period depends on several factors, mainly the ship size and the specific application. Therefore, it is evident how a proper harmonic identification of the wave signal is crucial for the wave propagation modelling and eventually its calculation. The advantages of oriented wavelets analysis within the complex dual tree transform over the traditional critically sampled wavelet (Discrete Wavelet Transform, DWT) will be shown, with particular regard to the identification of the wave direction for each decomposition sub-band.
SEA STATE, radar
207-215
Caiazzo, Giuseppe
37f9766e-73e5-4c47-8f08-3140ed38e9e8
Taunton, Dominic
10bfbe83-c4c2-49c6-94c0-2de8098c648c
Wilson, Philip A.
8307fa11-5d5e-47f6-9961-9d43767afa00
24 October 2017
Caiazzo, Giuseppe
37f9766e-73e5-4c47-8f08-3140ed38e9e8
Taunton, Dominic
10bfbe83-c4c2-49c6-94c0-2de8098c648c
Wilson, Philip A.
8307fa11-5d5e-47f6-9961-9d43767afa00
Caiazzo, Giuseppe, Taunton, Dominic and Wilson, Philip A.
(2017)
Multiresolution analysis of the ocean surface image: a case study based on X-radar data.
High Speed Marine Vehicles 2017, Università degli Studi di Napoli Federico II, Naples, Italy.
25 - 27 Oct 2017.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The problem of analysing the ocean waves behaviour represents a widely discussed topic, which finds many applications in several technical fields. In this paper a numerical elaboration of X-radar data is presented; in particular, the dual tree complex wavelet (DT-CoWT) transform has been applied to radar image samples to perform a spectral analysis of the waves and eventually separate the noise (which in radar applications corresponds to small amplitude waves and ripples) from the harmonics which actually carry a significant contribution of energy in a fluid-structure interaction context. This aspect has a strong importance in the particular field of quiescent period prediction (QPP), which consists of predicting the ship motions due to the waves. More specifically, if the waves are measured from a long distance, it is possible to predict their propagation along a specific direction, evaluate their interaction with the ship and subsequently calculate the corresponding ship motions. The actual definition of ‘quiescent period’ indicates the period of time during which the ship motion is within a certain range in order to carry out a number of possible operations (landing and recovery of air vehicles, rescue etc.) safely. The assessment of a threshold which actually corresponds to a quiescent period depends on several factors, mainly the ship size and the specific application. Therefore, it is evident how a proper harmonic identification of the wave signal is crucial for the wave propagation modelling and eventually its calculation. The advantages of oriented wavelets analysis within the complex dual tree transform over the traditional critically sampled wavelet (Discrete Wavelet Transform, DWT) will be shown, with particular regard to the identification of the wave direction for each decomposition sub-band.
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More information
Accepted/In Press date: 24 June 2017
e-pub ahead of print date: 24 October 2017
Published date: 24 October 2017
Venue - Dates:
High Speed Marine Vehicles 2017, Università degli Studi di Napoli Federico II, Naples, Italy, 2017-10-25 - 2017-10-27
Keywords:
SEA STATE, radar
Identifiers
Local EPrints ID: 418621
URI: http://eprints.soton.ac.uk/id/eprint/418621
PURE UUID: e4c8bda6-87d3-44f1-bed1-a8098099bd6b
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Date deposited: 12 Mar 2018 17:31
Last modified: 06 Jun 2024 01:37
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Author:
Giuseppe Caiazzo
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