Sea Test Data Research Articles

Research on Multi-target Tracking Algorithm Based on Track Segment Association

In the process of multi-target tracking, the complex underwater acoustic channel, target model mismatch, target strong maneuvering and other factors are easy to cause track interruption and rerun, which have a bad influence on the situation assessment and tactical decision of the Unmanned sonar system. Aiming at the problem of track interruption, this paper integrates the track adhesion algorithm into the active multi-target tracking algorithm. Simulation results show that the track adhesion algorithm can effectively improve the correct track association rate and track lifetime. By comparing the effect of the new and old methods with the sea test data, the track adhesion can effectively solve the problem of track interruption in the case of target track maneuvering and improve the track life.

Estimating the direction of arrival of spatially spread sources using block-sparse Bayesian learning with an extended dictionary.

Estimating the direction of arrival (DOA) of spatially spread sources is a significant challenge in array signal processing. This work introduces an effective method within the sparse Bayesian framework to tackle this issue. A spatially spread source is modeled using a multi-dimensional Slepian signal subspace that expands the dictionary and results in a block-sparse structured solution. By taking advantage of block-sparse Bayesian learning, parameter estimation becomes feasible. A complex Gaussian posterior is derived under a multi-snapshot block-sparse framework with a complex Gaussian prior and varying noise conditions. The hyperparameters are estimated using the expectation-maximization algorithm. Through numerical tests and sea test data evaluations, the proposed method shows superior energy focusing for spatially spread signals. Under limited snapshots and challenging signal-to-noise ratios, the current method can still offer precise DOA determination for spatially spread sources.

Joint CFO, Gridless Channel Estimation and Data Detection for Underwater Acoustic OFDM Systems

In this article, we propose an iterative receiver based on gridless variational Bayesian line spectra estimation (VALSE), named JCCD-VALSE, that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</i> ointly estimates the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</i> arrier frequency offset (CFO), the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</i> hannel with high resolution and carries out <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> ata decoding. Based on a modularized point of view and motivated by the high resolution and low-complexity gridless VALSE algorithm, three modules named the VALSE module, the CFO estimation (CFO est.) module, and the decoder module are built. Soft information is exchanged between the modules to progressively improve the channel estimation and data decoding accuracy. Since the delays of multipath of the channel are treated as continuous parameters instead of on a grid, the leakage effect is avoided. Beside, the proposed approach is a more complete Bayesian approach as all the nuisance parameters, such as the noise variance, the parameters of the prior distribution of the channel, and the number of paths are automatically estimated. Numerical simulations and sea test data are utilized to demonstrate that the proposed approach performs better than the existing grid-based joint channel and data decoding approaches. Furthermore, it is also verified that joint processing, including CFO estimation, provides performance gain.

A tracking method of equivalent constraint boundary for offshore monopile wind turbines from measured accelerations

For offshore wind turbines, the foundation constraint boundary is important for safe operation yet difficult to determine due to the invalidity of the fixed point assumption and influences from soil variability, liquidation, scour, etc. In this paper, a tracking method of equivalent constraint boundary is proposed on the basis of a limited numbers of measured responses, which are entirely different from the results by fixed constraints. The most theoretical achievement of the proposed method is that the time series of so-called first-order displacements can be accurately retrieved from the measured accelerations, leading to the significant difference from the first-order mode shape of conventional modal identification methods. The obvious advantage of the proposed method is that the change in the equivalent constraint boundary can be easily tracked just from the assembled accelerometers, which means that the difficulty and uncertainty of considering soil and water can be avoided. To verify the performance of the proposed method, two numerical examples and a beam experiment are conducted, and measured sea test data from a monopile wind turbine is processed. In detail, the first example is a cantilever beam with a theoretical fixed constraint position, and the results show that the fixed boundary position of the cantilever beam can be accurately estimated with a maximum relative error of 5.3% when six sensors and a fifth-order polynomial are used. The second example is a physical experiment of a cantilever beam and the change of constraint is considered by removing segments one by one. The experimental results show that the predicted constraint position is consistent with the cut length, with a maximum error of 0.009 m at 1.9 m. Furthermore, a 4 MW offshore monopile wind turbine evaluated by commercial software Ansys considering pile–soil interaction is analyzed, and the changes of the predicted equivalent constraint position are in good agreement with the preset values. Finally, the proposed method is applied to the field test data of a 6 MW monopile wind turbine, and a stable estimation of the equivalent constraint position can be obtained. The good accuracy of the proposed method demonstrates its capability in monitoring structural health for offshore wind turbines.

Horizontal Correlation of Long-Range Bottom Reverberation in Shallow Sloping Seabed

The performance of active sonar detection systems is seriously affected by the reverberation at the bottom of the waveguide in shallow water. In order to improve the performance of active sonar detection, it is necessary to understand the horizontal correlation of shallow-water bottom reverberation in active towed-array processing technology. However, the current research on the spatial correlation of reverberation is mainly based on vertical correlation, little work has been done on the horizontal correlation characteristics of long-distance seabed reverberation, and there is no support from sea test data. In this paper, the coupled mode reverberation model is applied to the horizontal correlation, and is studied according to the receiving position, time, and frequency. The simulation results show that, for the long-range bottom reverberation, the lateral correlation is greater than the longitudinal correlation in the horizontal space. By introducing the adiabatic mode solution, the mathematical model of horizontal correlation in the range-dependent waveguide with depth is derived. The numerical results show that the influence of the seabed dip angle on the horizontal correlation should be considered and that the horizontal correlation is affected obviously by the propagation effects of the sloped sea floor. Finally, the experimental data processing and analysis are given and verify the correctness of the algorithm.

Hardware-in-the-loop simulation of wave energy converters based on dielectric elastomer generators

Dielectric elastomer generators (DEGs) are soft electrostatic generators based on low-cost electroactive polymer materials. These devices have attracted the attention of the marine energy community as a promising solution to implement economically viable wave energy converters (WECs). This paper introduces a hardware-in-the-loop (HIL) simulation framework for a class of WECs that combines the concept of the oscillating water columns (OWCs) with the DEGs. The proposed HIL system replicates in a laboratory environment the realistic operating conditions of an OWC/DEG plant, while drastically reducing the experimental burden compared to wave tank or sea tests. The HIL simulator is driven by a closed-loop real-time hydrodynamic model that is based on a novel coupling criterion which allows rendering a realistic dynamic response for a diversity of scenarios, including large scale DEG plants, whose dimensions and topologies are largely different from those available in the HIL setup. A case study is also introduced, which simulates the application of DEGs on an OWC plant installed in a mild real sea laboratory test-site. Comparisons with available real sea-test data demonstrated the ability of the HIL setup to effectively replicate a realistic operating scenario. The insights gathered on the promising performance of the analysed OWC/DEG systems pave the way to pursue further sea trials in the future.

Interference reduction of high-energy noise for modal parameter identification of offshore wind turbines based on iterative signal extraction

An iterative noise extraction and elimination method is proposed, to solve the difficulty of modal parameter identification caused by contaminated high-energy components in measured signals. The approach is based on the idea that if only the high-energy noise is extracted and eliminated accurately, modal parameter identification can be improved significantly by using the remaining (filtered) signal. A theoretical development is that a general form of noises is considered, i.e., they can be purely harmonic or damped, which implies noises from machine vibration or other unknown sources can be taken into account. The advantage of this approach is that only one significant, relatively noisy component is extracted at each iteration, i.e., only the most reliable component is extracted each time, so more accurate high-energy noise elimination is expected. To demonstrate the accuracy of the proposed method, a numerical signal with one high-energy noisy component is used. Numerical results show that the approach can extract and eliminate high-energy noise at 2.1 Hz accurately by setting a small model order. A special case is the noisy component as a harmonic, which means the traditional Fourier transform can be applied. However, one can conclude that the proposed method outperforms the Fourier transform due to its limitation of fixed frequency resolution. To further investigate the effectiveness of the approach, an experiment on a steel offshore platform is conducted, and experimental results indicate that when measured raw data is used, only the first mode can be identified; if filtered data is used by employing the proposed method, the first two modes can be identified with improved damping ratio estimation. Finally, sea-test data from an offshore wind turbine in operating conditions are used, results show that the first mode with a frequency of 0.3592 Hz and a damping ratio of 0.0151 are successfully identified, while no reasonable parameters can be obtained by employing the stochastic subspace identification method, even when the used model order reaches 300.

Influence Analysis on the Floating Underwater Monitoring System Applicable for Very-Low-Frequency Acoustic Measurement

Ocean vector acoustic measurement is feasible affected by the hydrodynamic interference caused by the flow fluctuations and structural vibrations, especially in the very-low-frequency monitoring. Hence, a novel horizontal floating platform including a horizontal floating cable, vertical mooring cable and floating main body is proposed and described in this paper. It has the advantages of good maneuverability along with the current and multi-stage vibration isolation. The main application of this platform is to measure the ocean ambient noise coming from the wave fluctuation and the deterministic acoustic signals such as aquatic organisms, underwater targets and sailing vehicles. The influence of the current fluctuation on the attitude angle and flow induced vibration of cables and main body are analyzed with some previous sea test data. Moreover, the comparison between the vertical type platform used before and the horizontal type platform is also discussed. It is concluded that there is obvious relevance between the attitude angle and ocean current variation. Meanwhile, the abnormal influence on the main body is caused by the vibration transmission from the fluctuation of cables. There will be the influence on the accuracy of the acoustic measurement above 100 Hz, and the inherent vibration characteristic of the main body is the primary reason.

Selective Dynamic Coded Cooperative Communications for Multi-Hop Underwater Acoustic Sensor Networks

Due to the limitation of acoustic velocity in underwater environments, propagation delay is a horrible problem in multi-hop underwater acoustic sensor networks (UW-ASNs). In this paper, we proposed an improved scheme of dynamic coded cooperation called selective dynamic coded cooperation (S-DCC) for the multi-hop UW-ASNs, aiming at reducing the end-to-end delay and improving the transmission efficiency. In S-DCC scheme, the cooperative node actively transmits blocks with limited redundancy; yet the receiver only selectively receives those cooperative blocks depending on its own decoding conditions. The S-DCC scheme can utilize the retransmission mechanism adequately to eliminate the waiting time and drastically shorten the overall transmission time, the gain of which increases linearly with the number of hops. Concerning the transmission delay and energy consumption, we evaluated the performances with the different maximum number of retransmissions and different data burst sizes for the proposed S-DCC scheme and other compared schemes. The simulation results showed that the proposed S-DCC scheme could achieve decent outage performance and reduce the end-to-end delay effectively without extra energy consumption compared with other existing schemes, especially for the cases with low transmission signal to noise ratio. Sea test data were also adopted to further verify the conclusions.

Weak-mode identification and time-series reconstruction from high-level noisy measured data of offshore structures

The identification of true weak modes buried in high-level, noisy, measured data from offshore structures is a practical but challenging problem because weak modes are typically eliminated as noise and rarely, yield a discrete time series. This study proposes a weak-mode identification and time-series reconstruction method for offshore structures when high-level noise is present. A theoretical development proposed in this study extends the traditional modal analysis to reconstructing the discrete time series of weak modes, thereby removing its previous limitations to only frequencies, damping ratios and mode shapes. Additionally, a second development proposed in this study makes the reconstructed time series not simply a combination of harmonic components from a Fourier transform but rather complex exponentials; the damping of the test structure is thus estimated with a better accuracy. A third theoretical development avoids variations in the results from different original signals by handling multiple signals simultaneously. The proposed approach primarily includes three steps: (1) estimate the poles and corresponding residues of high-level, noisy, measured data by converting high-order difference equations to first-order difference equations; (2) isolate the poles of weak modes by assigning multiple rough-pole windows, and subsequently extract the corresponding residues based on the row number of the isolated pole vector; and (3) identify and reconstruct the time series of the weak modes of interest in the form of complex exponentials. The most primary advantage of the proposed process in engineering applications is that the pole windows can be easily obtained and assigned from the relationship between the frequencies and their poles. Three numerical examples are studied: the first presents the detailed numerical operation of the proposed method, the second extends the proposed method from managing one signal to managing multiple signals, and the third demonstrates the advantage of the approach compared with traditional methods. The numerical results indicate that the original signals can be decomposed into multiple complex exponentials with representative poles and corresponding residues, and that the new signals representing weak modes could be reconstructed by assigning a range of frequencies in terms of their relations with the poles. To study the performance of the proposed method when applied to offshore structures such as offshore platforms and marine risers, the experimental data from the high mode VIV experiments sponsored by the Norwegian Deepwater Programme (NDP) are used firstly. The results show that two dominant frequencies corresponding to the in-line and cross-flow directions can be identified simultaneously even one mode is very weak compared with the other, and the time series of the weak mode could be reconstructed with a rough frequency window. Then sea-test data of two offshore platforms are used: one was collected from the JZ20-2MUQ offshore platform when it was excited by ice, and the other was collected from the WZ11-4D platform when it was excited by waves. The results further demonstrated that a large model order is required to estimate all poles and residues of the original noisy signals, and that the row number corresponding to a weak mode of the isolated pole matrix could be easily determined via finite element analysis or engineering experiences. Therefore, the proposed approach provides not only modal parameters, such as frequencies and damping ratios of true weak modes buried in high-level noise, but also the discrete time series of the weak mode.

실해역 시험 데이터를 이용한 파일럿 채광로봇 엄빌리컬 케이블의 축진동 해석

실해역 시험 데이터를 이용한 파일럿 채광로봇 엄빌리컬 케이블의 축진동 해석

A wave structure based method for recognition of marine acoustic target signals

The loudness and timbre of propeller are remarkable features of ship-radiated noise. The information of loudness and timbre is indicated in the wave structure of time series, and the feature of wave structure can be applied to classify various marine acoustic targets. In this paper, the feature extracting method of time series wave structure is studied. A nine-dimensional feature vector is constructed through statistical characteristics, containing zero-crossing wavelength, peek-to-peek amplitude, zero-crossing-wavelength difference and wave train areas. The feature vectors are inputted into SVM classifier to identify marine acoustic targets. The kernel function is set radial basis function (RBF).The penalty factor and kernel width of RBF are selected by the method of grid search. Finally, the recognition rate of test data reaches over 89.5%, with the help of cross validation. The sea-test data show the validity of target recognition ability of the method above.

Frequency variation and sensor contribution assessment: Application to an offshore platform in the South China Sea

In this paper, a time–frequency and multiple-sensor assessment method is presented and then applied to an offshore platform in the South China Sea with the goal of providing a more suitable time duration of measured signals and evaluating each sensor׳s contribution to mode shapes of interest. By processing all measured signals simultaneously, a series of linear parameters are used to fit the measured signals. A moving window in overlapping steps along the time record of a non-stationary signal is used for time–frequency analysis while a series of amplitude matrices are obtained for all sliced segments. These segments are then used to evaluate each sensor׳s contribution to some mode(s) of interest. Compared with the short-time Fourier transform (STFT) or S-transform method, the frequencies used in this time–frequency analysis are shared by the sensors involved so that the variations in the results due to the characteristics of different sensors are avoided. In addition, the approach requires only a short-duration segment to obtain high-frequency resolution, which will improve the computing efficiency of modal analysis using measured seat est data. The proposed method could also be used to estimate damping ratios and each sensor׳s contribution to modes of interest based on the analysis of the series of amplitude matrices; this could be used to guide the installation of sensors in field tests of offshore structures. To demonstrate the proposed method with a time–frequency analysis, a numerical example of a synthesized signal with five segments, each with its owns different frequency componentsincluding a relatively weaker component, is constructed; numerical results from the analysis of this example signal indicate that the approach could yield a sharper image with a good computing efficiency. The second example simulates three signals that represent multiple measurements; this example is used to study each sensor׳s contribution to different modes based on an amplitude matrix. Finally, measurements from a four-leg jacket-type offshore platform located in the Beibu Gulf in China are used to study the proposed method. It can be concluded that sea-test measurements of offshore platforms show frequency-varying characteristics, and the proposed method could provide a more suitable time duration of signals for modal analysis. The assembled 24 sensors are shown to have different contributions to frequencies at 1.0375Hz, and the amplitude of each sensor will not be a constant when different segments of a measurement are used for analysis. However, each sensor׳s contribution to the assigned modes can be assessed based on average values. For example, the contribution of sensor 3 is estimated to be 12.5362 per cent, sensor 15׳s contribution is estimated to be 7.1803 per cent. Each sensor׳s importance to the mode of interest could then be evaluated.

The classification of underwater acoustic target signals based on wave structure and support vector machine

The sound of propeller is a remarkable feature of ship-radiated noise, the loudness and timbre of which are usually applied to identify types of ships. Since the information of loudness and timbre is indicated in the wave structure of time series, the feature of wave structure can be extracted to classify types of various underwater acoustic targets. In this paper, the method of feature vector extraction of underwater acoustic signals based on wave structure is studied. The nine-dimension features are constructed via signal statistical characteristics of zero-crossing wavelength, peek-to-peek amplitude, zero-crossing wavelength difference, and wave train areas. And then, the support vector machine (SVM) is applied as a classifier for two kinds of underwater acoustic target signals. The kernel function is set radial basis function (RBF). By properly setting the penalty factor and parameter of RBF, the recognition rate reaches over 89.5%, respectively. The sea-test data shows the validity of target recognition ability of the method above.

Lower-order modal parameters identification for offshore jacket platform using reconstructed responses to a sea test

Usually only a few of lower-order modes of interest extracted from stochastic response under the excitation of environmental forces, such as waves, winds or ice, could be obtained from sea tests of offshore jacket platforms; and what is more serious, this lower-order modal information is often buried in noises, which will be a challenge for identifying the modal parameters of interest. In this article, we propose an improved modal parameter identification method by reconstructing a new response consisting of only lower-order frequencies, and apply this method to a real offshore jacket platform located in the north of Liaodong Bay, China. One theoretical contribution is that the fainter modes could be isolated as one expected by defining reasonable pass band width and centering frequency. The elimination of noisy modes is realized by reconstructing the Eigensystem Realization Algorithm (ERA) block data matrix using the reconstructed responses. The other contribution is that the difficulty in judging whether an identified mode is due to noise or a genuine one has been resolved properly. A numerical offshore jacket platform is chosen to illustrate the procedure and demonstrate the performance of the proposed scheme. Numerical results indicate that: (1) lower-order frequencies can be isolated successfully using FFT filtering, and unexpected peaks in auto spectral density can be removed effectively using our smoothing procedure; (2) modal parameters of interest such as frequencies and damping ratios both can be identified properly by reconstructing Hankel matrix with a small dimension of ERA. Using sea test data measured from accelerometers mounted at the joints of the test platform, we find that our approach outperforms traditional ERA because no noisy modes are introduced. Though traditional ERA could identify two of the first three modal frequencies and damping ratios using the same segment of measured sea data, the dimension of Hankel matrix reaches 1000 times 1000, with a large amount of noisy modes. The achievement may contribute to two research areas: (1) signal processing when fainter frequencies are expected to be isolated, and (2) modal parameters identification when amount of noisy modes exist using traditional methods, such as ERA. Specifically, accuracy and efficiency of modal parameters identification (interested) of offshore jacket platforms can be improved.

Modal parameter estimation for jacket-type platforms using noisy free-vibration data: Sea test study

Accurate estimate of the modal parameters of an offshore structure is crucial to many practical engineering issues, such as finite element (FE) model updating/validation, damage detection, etc. Using noisy acceleration signals collected from a step-relaxation test of a jacket-type offshore platform, we estimate its modal frequencies and damping ratios by an extended Prony's method, which includes a noise removal procedure to yield filtered signals before implementing the classical Prony's method on the filtered signals. To validate the applicability of the proposed approach, numerical simulations were firstly performed. Investigating corrupted relaxation response signals simulated from a FE model of the test platform, we conclude that the proposed approach is very accurate on estimating the modal parameters. A significant improvement can be achieved when the filtered, rather than the originally measured, signals are used. Using sea test data measured from accelerometers mounted at three different locations of the test platform, we find that the modal parameters estimated from the filtered signals of the three locations separately are in excellent agreement.

Underwater Terrain Matching Positioning Method Based on MLE for AUV

Aiming at the precise positioning of autonomous underwater vehicle(AUV) during submerged operation for long periods of time,an underwater terrain matching positioning method based on maximal likelihood estimation(MLE) is proposed.In this method,multibeam echo sounder(MBES) is taken as the underwater terrain measuring means,and maximum likelihood algorithm is used for correlation analysis of terrain character.For the influence from false peaks of likelihood function at flat bottom area,the Fisher criterion is introduced to restrict it.The false peaks are eliminated effectively and the discrimination of flat bottom area is enhanced.The simulation results based on one electronic chart data and sea test data from a multibeam echo sounder show that the proposed method is effective and feasible.

Analysis of non‐Rayleigh reverberation model with ocean experiment data in coastal area

PurposeThe purpose of this paper is to improve active sonar detection performance in shallow water. A stochastic‐like model multivariate elliptically contoured (MEC) distributions is defined to model reverberation, which helps to reveal structure information of target signatures.Design/methodology/approachActive sonar systems have been developed with wider transmission bandwidths and larger aperture receiving array, which improve the signal‐to‐noise ratio and reverberation power ratio after matched filtering and beamforming. But, it has changed the statistical distribution of the reverberation‐induced envelope from the traditionally assumed Rayleigh distribution. The MEC is a kind of generalized non‐Gaussian distribution model. The authors theoretically derive the compound Gaussian, Rayleigh‐mixture, Weibull, K distributions are all special cases of MEC. It is known that Weibull and K distributions have obvious heavy‐tail than Rayleigh distribution. MEC is a suitable model to characterize non‐Rayleigh heavy‐tailed distribution of reverberation.FindingsThe analysis of test data shows reverberation envelopes obviously deviate Rayleigh distribution. In a broad non‐Gaussian framework, reverberation is modelled as MEC distribution, which is suitable to characterize non‐Rayleigh reverberation. The received data in trials validate the effectiveness of MEC model. The real data envelops follows K distribution, which is a special case of MEC. So, the MEC can be applied to develop novel signal‐processing algorithms that mitigate or account for the effects of the heavy‐tailed reverberation distributions on the target detection.Research limitations/implicationsThe limited sea test data are the main limitation to prove model validation in further.Practical implicationsA very useful model for representing reverberation in shallow‐water.Originality/valueThe MECs in fact represent an attractive set data model for adaptive array, and it provides a theoretic framework to design an optimal or sub‐optimal detector.

A stochastic model for scattering from the near-surface oceanic bubble layera)

A stochastic scattering model is derived in which the backscatter from the near-surface oceanic bubble layer is written directly in terms of an integral over the wave-number spectrum (‘‘power’’ spectrum) of the sound-speed fluctuations in the layer. A factored form is given for the integral that allows the backscatter cross section per unit area to be expressed as the product of a ‘‘geometric factor’’ and an effective horizontal wave-number spectrum. Because a power spectrum formulation is statistical, there are no assumptions about the geometry of the bubble layer (e.g., hemispherical or cylindrical plumes are not assumed). By dividing measured data for backscatter versus frequency by the geometric factor, scattering data from 12 different deep-ocean reverberation measurements were inverted, and the wave-number spectrum of the sound speed in the bubble layer was directly inferred. For all 12 measurements, the inferred wave-number spectrum is an inverse power law of the form P(K)=AK−β, where A is a strength parameter, K is the horizontal wave number for a Fourier component of the sound-speed distribution, and the mean value of the spectral roll-off exponent β is 3.86±0.45. The consistency in the inferred wave-number spectrum strongly suggests that on scales of less than half an acoustic wavelength (5 to 10 m), the sound-speed structure in the bubble layer is governed by turbulence in the inertial subrange (Kolmogorov subrange) which has a universal value of β=11/3=3.67 for fully developed isotropic turbulence. Using Von Karman’s interpolation formula for Kolmogorov turbulence, together with oceanographically constrained input parameters, theoretical backscatter cross sections were computed and compared with the empirical fits of Ogden and Erskine to Critical Sea Test data. It is shown that with no adjustable parameters, the stochastic scattering model gives a good account of the observed backscatter, as a function of both frequency and grazing angle.

Sailing Performance of Ocean Cruising Yacht by Full-Scale Sea Test

“What is the best tacking procedure ?” has been long-pending problem for yachtsmen. In order to solve this problem, a numerical simulation of tacking motion was conducted, and the results were compared with data from the full-scale sea tests.The equations of motion were described in the horizontal body axes coordinate system, and the sailing parameters and the trajectory of the boat were calculated using the Runge-Kutta method. The full-scale sea tests were performed using a 10.6 m-LOA sailing cruiser, whose steady sailing performance and dynamic performance in waves were examined in the previous report.The trajectory of the boat was measured using differential GPS receivers. First, powering run turning test and zigzag maneuver test were conducted to confirm the adequateness of the equations of motion and the hydrodynamic derivatives of the hull. Then, the tacking test was performed under various wind conditions and steering processes. By the full-scale sea tests, the mechanism of tacking motion was revealed, and the results of the numerical simulation coincided well with the sea test data.