Sea State Estimation Research Articles

Estimation of Significant Wave Heights from ASCAT Scatterometer Data via Deep Learning Network

Sea state estimation from wide-swath and frequent-revisit scatterometers, which are providing ocean winds in the routine, is an attractive challenge. In this study, state-of-the-art deep learning technology is successfully adopted to develop an algorithm for deriving significant wave height from Advanced Scatterometer (ASCAT) aboard MetOp-A. By collocating three years (2016–2018) of ASCAT measurements and WaveWatch III sea state hindcasts at a global scale, huge amount data points (>8 million) were employed to train the multi-hidden-layer deep learning model, which has been established to map the inputs of thirteen sea state related ASCAT observables into the wave heights. The ASCAT significant wave height estimates were validated against hindcast dataset independent on training, showing good consistency in terms of root mean square error of 0.5 m under moderate sea condition (1.0–5.0 m). Additionally, reasonable agreement is also found between ASCAT derived wave heights and buoy observations from National Data Buoy Center for the proposed algorithm. Results are further discussed with respect to sea state maturity, radar incidence angle along with the limitations of the model. Our work demonstrates the capability of scatterometers for monitoring sea state, thus would advance the use of scatterometers, which were originally designed for winds, in studies of ocean waves.

Sea state estimation based on vessel motion responses: Improved smoothness and robustness using Bézier surface and L1 optimization

Floating structures oscillate in waves, where these wave-induced motions may be critical for various marine operations. An important consideration is thereby given to the sea states at the planning and operating stages for an offshore project. The most important information extracted from a sea state is the directional wave spectrum, indicating wave direction, significant wave height, and wave spectrum peak period. Among several available methods of measuring and estimating the directional wave spectrum, the wave buoy analogy technique based on vessel motion responses is an in situ and almost real-time solution without extra costs of devices. If the forms of the wave spectra are not predefined in the estimation, the method is called a nonparametric approach. Its most remarkable advantage is the flexible form, but the smoothness should be regulated. After the discrete Fourier transform has been applied to the measured vessel motions, smoothing is necessary. However, this process results in disturbed vessel cross-spectra and a lowpass characteristic of the windowing function. This paper presents a nonparametric approach for directional wave spectrum estimation based on vessel motion responses. It introduces novel smoothness constraints using Bézier surface and includes a more robust estimate using L1 optimization. Both techniques are applied to the wave buoy analogy for the first time. Numerical simulations are conducted to verify the proposed algorithm.

Sea state estimation using monitoring data by convolutional neural network (CNN)

In recent years, the size of container ships has become larger, thus requiring a more evident assurance of the hull structural safety. In order to evaluate the structural safety in operation, it is necessary to grasp the encountered sea state. The aim of this study is to estimate the encountered sea state using machine learning from measurement data of ocean-going 14,000TEU container ships. In this paper, as a first step in the study, considerable amounts of virtual sea state data and corresponding ship motion and structural response data are prepared. A convolutional neural network (CNN) is developed using these data to estimate the directional wave spectrum of encountered sea based on the hull responses. The input parameters of the formulated CNN include the spectral values of ship motion and structural response spectrum. The output of the CNN includes the sea state parameters of the Ochi-Hubble spectrum, specifically, significant wave height, modal wave frequency, mean wave direction, kurtosis, and concentration of wave energy directional distribution. It is found from the performance examination that the developed CNN is capable of accurately estimating the sea state parameters, although the level of accuracy decreases when the hull response is low. However, the decrease in accuracy when the hull response is low has a weak influence on the evaluation of the structural response to the estimated sea state.

Experimental Validation of a Nonlinear Wave Encounter Frequency Estimator Onboard a Wave-Propelled USV

Abstract Knowledge of the amplitude and frequency of sea waves is useful to characterize the sea state, and increases the situational awareness as perceived by unmanned marine crafts. The ability to adapt navigation control parameters according to the current sea state is an essential feature for vehicles whose motion is mainly governed by environmental forces. From a control perspective, an estimate of the wave encounter frequency (WEF) can be used to filter out first-order wave-induced motions that cause undesired rudder control action and servo wear and deterioration. In this work we consider a nonlinear second-order observer capable of computing the approximate frequency of a sinusoidal signal with unknown amplitude and phase. This work presents the first experimental validation of the nonlinear estimator, which is tested for the first time on a five meters long wave-propelled unmanned surface vehicle (USV). Moreover, this article shows the estimator’s ability to characterize the dominant frequency of wave spectra across different sea states and discusses two applications of the WEF estimation: sea state estimation and wave-filtered steering control. Theoretical considerations are supported with both simulation and experimental results.

A Study on Bayesian Updating of Time History Sea State Estimation Based on Measured Hull Stresses

A Study on Bayesian Updating of Time History Sea State Estimation Based on Measured Hull Stresses

Estimation of sea state parameters by the wave buoy analogy with comparisons to third generation spectral wave models

This paper presents a study focused on sea state estimation along the route of an in-service container ship. The paper is concerned with the wave buoy analogy in which wave-induced motions of the ship are processed and analysed together with corresponding motion transfer function to give the directional wave spectrum exactly at the point of operation. In this study, a simple and inexpensive instrumentation of the vessel is considered, and wave spectrum estimation is based on measurements from one motion response unit mounted close to the forward perpendicular of the ship. The estimates by the wave buoy analogy are compared with two sets of results from third generation spectral wave models, with one set provided by a commercial supplier and with another set obtained from the Copernicus Climate Change Service Information. Motion measurements from a seven-days voyage across the Pacific Ocean are studied, and it is shown that the wave buoy analogy estimates wave conditions, in terms of sea state parameters, in good agreement with the reports by the sets of ocean wave hindcasts. Along with the comparisons, the paper discusses some of the inherent drawbacks of the wave buoy analogy, notably the fact that a ship acts as a low-pass filter.

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment

Best practices and international standards for determining n-year return period extreme wave (sea states) conditions allow wave energy converter designers and project developers the option to apply simple univariate or more complex bivariate extreme value analysis methods. The present study compares extreme sea state estimates derived from univariate and bivariate methods and investigates the performance of spectral wave models for predicting extreme sea states at buoy locations within several regional wave climates along the US East and West Coasts. Two common third-generation spectral wave models are evaluated, a WAVEWATCH III® model with a grid resolution of 4 arc-minutes (6–7 km), and a Simulating WAves Nearshore model, with a coastal resolution of 200–300 m. Both models are used to generate multi-year hindcasts, from which extreme sea state statistics used for wave conditions characterization can be derived and compared to those based on in-situ observations at National Data Buoy Center stations. Comparison of results using different univariate and bivariate methods from the same data source indicates reasonable agreement on average. Discrepancies are predominantly random. Large discrepancies are common and increase with return period. There is a systematic underbias for extreme significant wave heights derived from model hindcasts compared to those derived from buoy measurements. This underbias is dependent on model spatial resolution. However, simple linear corrections can effectively compensate for this bias. A similar approach is not possible for correcting model-derived environmental contours, but other methods, e.g., machine learning, should be explored.

Ocean wave spectrum estimation using measured vessel motions from an in-service container ship

This article is about the use of measured wave-induced vessel motions for estimation of ocean wave spectra by application of the wave buoy analogy. In the study, data from a larger, in-service container ship is considered. The estimation of wave spectra, equivalently sea state parameters, is based on measurements from, respectively, a gyro and two accelerometers leading to the simultaneous use of the pitching motion together with the horizontal and vertical accelerations in a position close to the forward perpendicular. The study of in-service data leads to contemplations about the vessel's advance speed, as the possible existence of sea current means that speed-over-ground (SOG) and speed-through-water (STW) will be different. The article discusses aspects related to advance speed in the context of the wave buoy analogy, and a smaller sensitivity study is conducted. Preceding to the sensitivity study, a comparison is made between sea state estimates by the wave buoy analogy and estimates obtained from a hindcast study. The article shows an acceptable agreement between the two sets of estimates. Following, the main conclusion from the sensitivity study on advance speed is that errors and uncertainties in the speed log have an effect on the estimates of the wave buoy analogy. In fact, the effect can be severe if reliable STW measurements are not available. In the final part, the article includes a few discussions about (non)stationary conditions in the context of the wave buoy analogy, and, although the effect on results is not necessarily detrimental, care must be shown when the wave buoy analogy is applied during in-service conditions.

Estimation of sea state from Sentinel-1 Synthetic aperture radar imagery for maritime situation awareness

ABSTRACTA new empirical algorithm CWAVE_S1-IW for estimation of significant wave height Hs including swell and wind sea from C-band satellite-borne Synthetic Aperture Radar (SAR) data has been developed for Sentinel-1 (S1) Interferometric Wide Swatrh Mode (IW) imagery. The algorithm was implemented into the Sea Sate Processor (SSP) for fully automatic processing for near real time (NRT) services and allow the estimation of wave fields of thousands of kilometres in the flight direction and 250 km swath from S1 IW scenes consisting of a sequence of individual images.The priority of CWAVE_S1-IW development was an automatic, fast and robust raster processing independent of wave patterns, applicable even when only clutter is visible in the SAR images. The algorithm is based on the spectral analysis of subscenes in wavenumber space. The empirical function allows direct Hs estimation from image spectra without first converting them into wave spectra and uses integrated image spectra parameters as well as estimated local wind information. A texture analysis based on Grey Level Co-occurrence Matrices (GLCM) is also applied. In this way, also the parameters of short waves can be estimated, which are not visible in S1 IW images and are only represented by clutter.The algorithm was tuned worldwide using in-situ collocated measurements of 92 buoys with more than 2500 acquisitions. The validated SSP allows automatic processing of worldwide S1 IW images in VV or HH polarization, including Atlantic storms, cyclones, and huge storms in the Gulf of Alaska with a root-mean-square (RMSE) error of 80 cm for Hs. For the closed seas like the North Sea, Baltic Seas and Black Sea the accuracy is higher with an RMSE = 55 cm. The algorithm is integrated into a demonstration service, used for further validation at the DLR ground station in Neustrelitz. The NRT processing has been tested by supporting a research ship cruise in the Antarctic Sea.

Sea State Estimation Using Quadratic Discriminant Analysis and Partial Least Squares Regression

This paper proposes non-model based sea state estimation methods for a dynamically positioned vessel. Sea state estimation entails finding the wave direction, significant wave height and peak wave period and is done based on sensor data of the vessel response. Sea state estimation is of importance because it assists the on board decision system and provides weather information for the relevant geographical position. In this paper, the methods for sea state estimation are based on machine learning algorithms, rather than the vessel transfer function. The models are trained and tested using simulated time series of response data, and yield promising results.

Sea state estimation using multiple ships simultaneously as sailing wave buoys

The article presents initial ideas towards a network-based approach for sea state estimation used for marine operations and other maritime applications. In principle, all available means, ranging from in situ buoys, fleet of ships to remote sensing by satellite and aircraft, could be considered, emphasising that each means and any combinations among may act simultaneously. This study focuses on just one of the means; the use of ships as sailing wave buoys. The article introduces the wave buoy analogy, i.e. ship-as-a-wave-buoy, and it makes a proposal on how to impose (different) weights to the single ship-specific wave spectrum estimates obtained from multiple ships. Moreover, the work includes a discussion about the importance to associate a measure to reflect the (un)certainty of the wave spectrum estimate. The article presents a numerical case study, where multiple ships act simultaneously as wave spectrum-estimators. The case study relies on numerical motion simulations, as appropriate full-scale data is not yet available. In the analysis, it is shown that the use of simultaneous data from multiple ships leads to more accurate wave spectrum estimations.

A brute-force spectral approach for wave estimation using measured vessel motions

The article introduces a spectral procedure for sea state estimation based on measurements of motion responses of a ship in a short-crested seaway. The procedure relies fundamentally on the wave buoy analogy, but the wave spectrum estimate is obtained in a direct - brute-force - approach, and the procedure is simple in its mathematical formulation. The actual formulation is extending another recent work by including vessel advance speed and short-crested seas. Due to its simplicity, the procedure is computationally efficient, providing wave spectrum estimates in the order of a few seconds, and the estimation procedure will therefore be appealing to applications related to realtime, onboard control and decision support systems for safe and efficient marine operations. The procedure's performance is evaluated by use of numerical simulation of motion measurements, and it is shown that accurate wave spectrum estimates can be obtained for all wave directions in short-crested waves, taking the wave system to be composed by both wind generated sea and swell. Furthermore, the procedure is tested using full-scale motion data obtained from sea trials. Good wave estimations are achieved as compared to corresponding results from a free-floating (classical) wave buoy.

Online wave estimation using vessel motion measurements

In this paper, a computationally efficient online sea state estimation algorithm is proposed for estimation of the onsite sea state. The algorithm finds the wave spectrum estimate from motion measurements in heave, roll and pitch by iteratively solving a set of linear equations. The main vessel parameters and motion transfer functions are required as input. Apart from this the method is signal-based, with no assumptions on the wave spectrum shape, and as a result it is computationally efficient. The algorithm is implemented in a dynamic positioning (DP) control system, and tested through simulations in different sea states, with heading changes. Discrete stability analysis is performed to find iteration gains in the algorithm.

On-board sea state estimation method validation based on measured floater motion

This paper presents a method to estimate the sea state PSD (Power Spectral Density) of the current wave climate, by using the measured floater motion and the body hydrodynamic response. The knowledge of PSD and the sea state synthetic parameters derivable from the PSD, such as the Significant Wave Height and the Energy Period, is fundamental for the navigation and operation in naval field and also for the control strategies of the Wave Energy Converters (WEC). The ISWEC (Inertial Sea Wave Energy Converter) is used as case study for the validation of the sea state estimation method. ISWEC is a floating device using the inertial effects of a gyroscopic system to convert a floater motion into electric energy. Sea state parameters are used in the control of the device to tune gyroscope speed and the generator torque law to achieve maximum power absorption. The heave measurements are used to estimate the PSD of the incoming wave and it is compared with the wave PSD measured by a wave measurement system. The method is studied and validated for three different sea state cases. At this stage the method presents satisfying results, with an accuracy under the 10% of the estimated parameters. Such accuracy is comparable with the short term (1-3h) wave forecast produced by ECMWF.

Sea state estimation using vessel response in dynamic positioning

This paper presents a novel method for estimating the sea state parameters based on the heave, roll and pitch response of a vessel conducting station keeping automatically by a dynamic positioning (DP) system, i.e., without forward speed. The proposed algorithm finds the wave spectrum estimate from the response measurements by iteratively solving a set of linear equations, and it is computationally efficient. The main vessel parameters are required as input. Apart from this the method is signal-based, with no assumptions on the wave spectrum shape. Performance of the proposed algorithm is demonstrated on full-scale experimental DP data of a vessel in three different sea states at head, bow quartering, beam, stern quartering and following sea waves, respectively.

Transformation of a wave energy spectrum from encounter to absolute domain when observing from an advancing ship

The article presents a practical approach to transform a wave energy spectrum from encounter domain to absolute domain. This problem has its specific relevance, when shipboard sea state estimation is conducted by the wave buoy analogy; notably for some particular implementation solving for the sea state directly in the encounter domain. In this context, the encounter domain is that observed from a ship when it advances in a seaway, whereas the absolute domain is that corresponding to making observations from a fixed point in the inertial frame. Spectrum transformation can be uniquely carried out if the ship sails “against” the waves (beam to head sea) but in following sea conditions there exists no unique solution to the problem. Instead, a reasonable approach valid for practical engineering must be applied, and the article outlines one viable solution that can be used to transform a wave spectrum from encounter to absolute domain. Specifically, two pseudo algorithms are presented, and good performance is achieved with both algorithms when they are tested at different operational scenarios.

Numerical study of microwave backscattering from time-evolving JONSWAP-type mixed ocean waves

ABSTRACTThe microwave backscattering from mixed wind-driven wave and swell marine environment is important for estimation of sea state, ship responses analysis, etc. However, most studies mainly focus on the wind wave only. It has been found that the JONSWAP spectrum is suitable for describing not only wind wave but also swell. The Doppler spectrum of dynamic JONSWAP-type nonlinear waves is used as a tool to analyse the microwave backscattering features of mixed ocean waves. The Doppler central frequency and Doppler bandwidth of mixed sea are calculated by the second-order small-slope approximation theory (SSA-II), and the numerical simulation results indicate that the swell impacts Doppler features mainly at small incident angles and the corresponding results are nearly insensitive to polarization, whereas the wind wave relatively dominates the microwave backscattering from mixed sea.

A concise account of techniques available for shipboard sea state estimation

This article gives a review of techniques applied to make sea state estimation on the basis of measured responses on a ship. The general concept of the procedures is similar to that of a classical wave buoy, which exploits a linear assumption between waves and the associated motions. In the frequency domain, this assumption yields the mathematical relation between the measured motion spectra and the directional wave spectrum. The analogy between a buoy and a ship is clear, and the author has worked on this wave buoy analogy for about fifteen years. In the article, available techniques for shipboard sea state estimation are addressed, but with a focus on only the wave buoy analogy. Most of the existing work is based on methods established in the frequency domain but, to counteract disadvantages of the frequency-domain procedures, newer studies are working also on procedures formulated directly in the time domain. Sample results from several studies are included, and the main findings from these are mentioned.

Dependency of the Sentinel-1 azimuth wavelength cut-off on significant wave height and wind speed

ABSTRACTSea wind and sea state estimation by synthetic aperture radar (SAR) measurements is a topic of relevance both on the scientific and user side. The new European Space Agency (ESA) Sentinel-1 constellation is meant to support marine studies and ensure high-quality data. In this paper, we investigate the azimuth cut-off () sea wind speed and significant wave height retrieval approach by taking benefit of two sets of multi-look SAR images with incidence angles varying from 20° to 45°. The images have been co-located with sea surface wind measurements acquired by the scatterometer onboard the Chinese satellite HY-2A (HSCAT) and with the European Centre for Medium Range Weather Forecast (ECMWF) operational model output. This study is meant to analyse both the empirical dependency of SAR on significant wave height () and wind speed (U). Several fitting geophysical model functions (-GMFs) are proposed and discussed. The results show that is strongly correlated with the significant wave height in all sea state conditions, while the correlation with the wind speed is only high for fully developed sea states. The azimuth cut-off based significant wave height retrievals are compared with independent National Data Buoy Centre (NDBC) network observations, showing a root mean square difference of about 0.5 m.

Strategies for active tuning of Wave Energy Converter hydraulic power take-off mechanisms

This paper presents a study of practically implementable active tuning methods for a Wave Energy Converter (WEC) power take-off (PTO). It is distinguished from other simulation studies by the level of detail and realism in the inputs and the PTO model. Wave data recorded at the European Marine Energy Centre is used to derive input data for a detailed component level model of a hydraulic PTO. A methodology is presented for obtaining the optimum PTO damping co-efficient for a given sea state, and an open loop active tuning method is used to adjust the PTO parameters to achieve this optimum damping in service. The investigation shows that tuning of a hydraulic PTO to an estimated wave frequency is a difficult task due to sea state estimation errors and the complex dynamics of a realistic PTO. Preview knowledge of the future waves was shown to provide no meaningful improvement in energy capture for the device under investigation. Significantly, power gains observed in similar work using simplified linear PTO models or simplified sea states are not seen here, demonstrating that over-simplification of the PTO during the simulation phase of WEC development could lead to incorrect design decisions and subsequent additional delay and cost.