Showing papers in "IEEE Journal of Oceanic Engineering in 2016"

Human-Visual-System-Inspired Underwater Image Quality Measures

Abstract: Underwater images suffer from blurring effects, low contrast, and grayed out colors due to the absorption and scattering effects under the water. Many image enhancement algorithms for improving the visual quality of underwater images have been developed. Unfortunately, no well-accepted objective measure exists that can evaluate the quality of underwater images similar to human perception. Predominant underwater image processing algorithms use either a subjective evaluation, which is time consuming and biased, or a generic image quality measure, which fails to consider the properties of underwater images. To address this problem, a new nonreference underwater image quality measure (UIQM) is presented in this paper. The UIQM comprises three underwater image attribute measures: the underwater image colorfulness measure (UICM), the underwater image sharpness measure (UISM), and the underwater image contrast measure (UIConM). Each attribute is selected for evaluating one aspect of the underwater image degradation, and each presented attribute measure is inspired by the properties of human visual systems (HVSs). The experimental results demonstrate that the measures effectively evaluate the underwater image quality in accordance with the human perceptions. These measures are also used on the AirAsia 8501 wreckage images to show their importance in practical applications.

An Overview of Underwater Time-Reversal Communication

Abstract: Time reversal (TR) exploits spatial diversity to achieve spatial and temporal focusing in complex environments. Over the last decade, the TR concept has been applied successfully to phase-coherent acoustic communications in time-varying multipath ocean environments, as an alternative to conventional adaptive multichannel equalization. Temporal focusing (pulse compression) mitigates the intersymbol interference (ISI) and subsequent single-channel equalization removes the residual ISI, thus providing nearly optimal performance in theory. The spatial focusing capability facilitates multiuser or multiple-input–multiple-output (MIMO) communications without explicit use of time, frequency, or code division multiplexing, while an adaptive TR approach can reduce further the crosstalk among users or multiple transmitters. TR communications can be extended easily to time-varying channels using a block-based approach with channel updates. This paper provides an overview of TR communications in both shallow and deep water and recent advances including bidirectional equalization, multiuser communications with mobile users, and communication with a glider serving as a mobile gateway.

Optimal Sensor Placement for Acoustic Underwater Target Positioning With Range-Only Measurements

Abstract: This paper addresses the problem of optimal acoustic sensor placement for underwater target localization in 3-D using range measurements only. By adopting an estimation theoretical framework, the optimal geometric sensor formation that will yield the best achievable performance in terms of target positioning accuracy is computed by maximizing the determinant of an appropriately defined Fisher information matrix (FIM). For mathematical tractability, it is assumed that the measurements of the ranges between the target and a set of acoustic sensors are corrupted with white Gaussian noise. For the sake of completeness, an explicit analytical result for a generic $n$ -sensor network is first obtained for the case when there is no uncertainty in the prior knowledge about the target position. The result is then extended to the practical case where the target is known to lie inside a region of uncertainty. The optimal sensor configuration thus obtained lends itself to an interesting and useful geometrical interpretation. In addition, the “spreading” of the configuration is shown to depend on the number of range measurements, target depth, and the probability distribution function that characterizes the prior knowledge about the target position. Results are also obtained for the problem of optimal sensor placement with constraints, namely, by considering that the sensors can be either located at the sea surface or distributed between the surface and the seabed. The connection between 2-D and 3-D scenarios is clarified. Simulation examples illustrate the key results derived.

Bayesian Iterative Channel Estimation and Turbo Equalization for Multiple-Input–Multiple-Output Underwater Acoustic Communications

Abstract: This article investigates a robust receiver scheme for a single carrier, multiple-input–multiple-output (MIMO) underwater acoustic (UWA) communications, which uses the sparse Bayesian learning algorithm for iterative channel estimation embedded in Turbo equalization (TEQ). We derive a block-wise sparse Bayesian learning framework modeling the spatial correlation of the MIMO UWA channels, where a more robust expectation–maximization algorithm is proposed for updating the joint estimates of channel impulse response, residual noise, and channel covariance matrix. By exploiting the spatially correlated sparsity of MIMO UWA channels and the second-order a priori channel statistics from the training sequence, the proposed Bayesian channel estimator enjoys not only relatively low complexity but also more stable control of the hyperparameters that determine the channel sparsity and recovery accuracy. Moreover, this article proposes a low complexity space-time soft decision feedback equalizer (ST-SDFE) with successive soft interference cancellation. Evaluated by the undersea 2008 Surface Processes and Acoustic Communications Experiment, the improved sparse Bayesian learning channel estimation algorithm outperforms the conventional Bayesian algorithms in terms of the robustness and complexity, while enjoying better estimation accuracy than the orthogonal matching pursuit and the improved proportionate normalized least mean squares algorithms. We have also verified that the proposed ST-SDFE TEQ significantly outperforms the low-complexity minimum mean square error TEQ in terms of the bit error rate and error propagation.

First Comparison of Sentinel-1 and TerraSAR-X Data in the Framework of Maritime Targets Detection: South Italy Case

Abstract: The Sentinel-1A is the first of two satellites that composes the Sentinel-1 radar mission. Both satellites operate a C-band synthetic aperture radar (SAR) system to give continuity to the European SAR program. SAR is a flexible sensor able to fulfil users/applications requirements in terms of resolution and coverage thanks to different operational modes and polarizations. With the in-orbit availability of very-high-resolution X-band SAR sensors, the Sentinel-1 satellites have been designed to achieve wide coverage at medium to high resolution. The interferometric wide swath (IWS) mode implemented with the terrain observation with progressive scan (TOPS) technique is the standard acquisition mode over European waters and land masses. IWS in dual-polarization (VV/VH) combination offers 250-km swath at $\hbox{5 m} \times \hbox{20 m}$ (range $\times$ azimuth) spatial resolution. These specifications are in line with the needs of the European Maritime and Security Agency (EMSA) for oil spill and ship detection applications included in the CleanSeaNet program. The main goals of this paper are: assessment of medium-to-high-resolution C-band Sentinel-1 data with very-high-resolution X-band TerraSAR-X data for maritime targets detection; synergetic use of multiplatforms satellite SAR data for target features extraction; evaluation of polarimetric target detectors for the available co-polarization and cross-polarization Sentinel-1A IWS VV/VH products. The objectives are achieved by means of real, almost coincident C-band and X-band SAR data acquired by Sentinel-1A and TerraSAR-X satellites over Gulf of Naples and Catania (South Italy). Furthermore, the obtained results are supported by recorded ground truth vessel reports via terrestrial automatic identification system (AIS) stations located in the area.

A Self-Contained Subsea Platform for Acoustic Monitoring of the Environment Around Marine Renewable Energy Devices–Field Deployments at Wave and Tidal Energy Sites in Orkney, Scotland

Abstract: The drive towards sustainable energy has seen rapid development of marine renewable energy devices (MREDs). The NERC/Defra collaboration FLOw, Water column and Benthic ECology 4-D (FLOWBEC-4D) is investigating the environmental and ecological effects of installing and operating wave and tidal energy devices. The FLOWBEC sonar platform combines several instruments to record information at a range of physical and multitrophic levels for durations of two weeks to capture an entire spring-neap tidal cycle. An upward-facing multifrequency Simrad EK60 echosounder is synchronized with an upward-facing Imagenex Delta T multibeam sonar. An acoustic Doppler velocimeter (ADV) provides local current measurements and a fluorometer measures chlorophyll (as a proxy for phytoplankton) and turbidity. The platform is self-contained, facilitating rapid deployment and recovery in high-energy sites and flexibility in gathering baseline data. Five 2-week deployments were completed in 2012 and 2013 at wave and tidal energy sites, both in the presence and absence of renewable energy structures at the European Marine Energy Centre (EMEC), Orkney, U.K. Algorithms for target tracking have been designed and compared with concurrent, shore-based seabird observations used to ground truth the acoustic data. The depth preference and interactions of birds, fish schools and marine mammals with MREDs can be tracked to assess whether individual animals face collision risks with tidal stream turbines, and how animals generally interact with MREDs. These results can be used to guide marine spatial planning, device design, licensing and operation, as different device types are tested, as individual devices are scaled up to arrays, and as new sites are considered.

Joint Probabilistic Data Association Tracker for Extended Target Tracking Applied to X-Band Marine Radar Data

Abstract: X-band marine radar systems are flexible and low-cost tools for monitoring multiple targets in a surveillance area. Although they may suffer from several sources of interference, e.g., sea clutter, they can provide high-resolution measurements in both space and time. Such features offer the opportunity to get accurate information not only about the target kinematics, i.e., positions and velocities, as other conventional radars, but also about the targets’ extents. This research area is named extended target tracking (ETT). In this paper, we propose a signal processing chain composed by a detector and a joint probabilistic data association (JPDA) tracker to handle the problem of multiple ETT and to jointly estimate both the targets’ kinematics and their sizes, i.e., length and width. The performance assessment is conducted on real data acquired by an X-band marine radar located in the Gulf of La Spezia, Italy. The experimental results demonstrate the ability of the processing chain to reach high performance with a limited computational burden.

Doppler-Resilient Orthogonal Signal-Division Multiplexing for Underwater Acoustic Communication

Abstract: Underwater acoustic (UWA) channels are characterized by a severe spread in time and frequency, and are usually labeled as “doubly spread channels.” In this paper, we propose Doppler-resilient orthogonal signal-division multiplexing (D–OSDM), to provide a highly reliable communication environment in doubly spread channels for UWA communication. D–OSDM multiplexes several data vectors in addition to a pilot vector, and preserves orthogonality among them even after propagation through doubly spread channels, under the assumption that the channel can be modeled by a basis expansion model (BEM). We describe the signal processing steps at the transmitter and the receiver for D–OSDM, and evaluate its performance by both simulations and experiments. To generate a doubly spread channel, a test tank with a wave generator is employed. The obtained results suggest that D–OSDM can provide low-power and high-quality UWA communications in channels with large delay and Doppler spreads; for example, D–OSDM succeeds to achieve a block error rate (BLER) of 10 $^{-3}$ while BEM-based orthogonal frequency-division multiplexing (OFDM) has a BLER floor of 10 $^{-2}$ in the experiments. Equivalently, D–OSDM can reduce the signal power required for communications to achieve the same BER significantly. Overall, it was found that D–OSDM can become a powerful communication tool for underwater operations.

Obstacle Avoidance Approaches for Autonomous Underwater Vehicle: Simulation and Experimental Results

Abstract: Autonomous underwater vehicles (AUVs) operate in unknown underwater environments and must be able to avoid submerged obstacles such as cliffs, wrecks, and seabed changes. This paper proposes a methodology for obstacle avoidance by AUVs that are equipped with forward-looking sonars (FLSs). The data collected from two FLSs placed in horizontal and vertical orientation are processed in real time to provide obstacle detection information in the $xz$ - and $xy$ -planes, respectively. Due to the necessity of maintaining constant height when employing sidescan sonar (SSS) and lower energy consumption, horizontal avoidance maneuvers are preferred over vertical ones. For the horizontal obstacle avoidance, a two-layer obstacle avoidance algorithm (OAA) contains two different processes, an OAA based on Bandler and Kohout (BK) product of fuzzy relation used as a preplanning method and a reactive approach based on potential field and edge detection methods. The preplanning technique has a clear advantage on a line segment of the path, and the reactive method is more efficient on a curved segment. In case a horizontal approach cannot find a path to safely avoid the obstacle, the reactive vertical approach is activated. A seabed gradient detection technique that allows prediction of seabed and altitude changes up to 40 m ahead of the AUV is presented. Simulation and experimental results clearly demonstrate that the proposed methodology enables AUVs to navigate safely through obstacles and provide crucial information about the seafloor terrain changes.

Mission and Motion Planning for Autonomous Underwater Vehicles Operating in Spatially and Temporally Complex Environments

Abstract: This paper seeks to enhance the autonomy of underwater vehicles. The proposed approach takes as input a mission specified via a regular language and automatically plans a collision-free, dynamically feasible, and low-cost trajectory which enables the vehicle to accomplish the mission. Regular languages provide a convenient mathematical model that frees users from the burden of unnatural low-level commands and instead allows them to describe missions at a high level in terms of desired objectives. To account for the constraints imposed by the mission, vehicle dynamics, collision avoidance, and the complex spatial and temporal variability of the ocean environment, the approach tightly couples mission planning with sampling-based motion planning. A key aspect is a discrete abstraction obtained by combining the finite automaton representing the regular language with a navigation roadmap constructed by probabilistic sampling. The approach searches the discrete abstraction to compute low-cost and collision-free navigation routes that are compatible with the mission. Sampling-based motion planning is then used to expand a tree of dynamically feasible trajectories along the navigation routes. The approach is validated both in simulation and field experiments. Results demonstrate the efficiency and the scalability of the approach and show significant improvements over related work.

Motion-Compensated Acoustic Localization for Underwater Vehicles

Abstract: This paper develops and applies a Bayesian inference algorithm for long-baseline (LBL) acoustic localization of a maneuvering undersea vehicle which compensates for vehicle motion during the interrogation–reception time interval between the vehicle and transponders of the LBL system using only acoustic timing measurements. The method is based on including travel-time corrections as additional unknown parameters in the inference, constrained with prior estimates determined by interpolating the vehicle location at interrogation instants from the results of an initial localization based on a static-vehicle model. Monte Carlo simulation studies show that the motion-compensated localization method performs much better than the static-model localization method or a localization based on applying fixed travel-time corrections. Results from field trials carried out in a large lake are also presented, with averaged acoustic localization errors for a surface vehicle (judged relative to high-precision GPS locations) reduced from $19 \pm 14$ cm for the static-model localization to $3.4 \pm 1.4$ cm for the motion-compensated localization, which is comparable to the GPS uncertainties.

Online System Identification of an Autonomous Underwater Vehicle Via In-Field Experiments

Abstract: The dynamic characteristic of an autonomous underwater vehicle (AUV) is affected when it is reconfigured with different payloads. It is desirable to have an updated model, such that the control and guidance law can be redesigned to obtain better performance. Hence, we develop a method to enable online identification of AUV dynamics via in-field experiments, where the AUV is commanded to execute a compact set of maneuvers under doublet excitation. The identification process has two stages. In the training stage, state variable filter and recursive least square (SVF-RLS) estimator is used to estimate the unknown parameters. In the validation stage, the prediction capability of the model is checked using a fresh data set. The parameters converged within 12 s in the experiments using five different thrusts. Validation results show that the identified models are able to explain 78% to 92% of the output variation. Next, we compare the SVF-RLS estimator with the conventional offline identification method. The comparison shows that the SVF-RLS estimator is better in terms of prediction accuracy, computational cost and training time. The usefulness of the identified models is highlighted in two applications. We use it to estimate the turning radius of the AUV at different speeds, and to design a gain-scheduled controller.

Neural-Network-Based Data Assimilation to Improve Numerical Ocean Wave Forecast

Abstract: This paper demonstrates the skill level of a wavelet neural network in improving numerical ocean wave predictions of significant wave height ( ${{H}_{s}}$ ) and peak wave period ( ${{T}_{p}}$ ) having practical applications in operational centers. The study uses data of ${{H}_{s}}$ and ${{T}_{p}}$ for a coastal region off Puducherry located in the east coast of India, and obtained from a high-resolution wave model resulting from nesting of the SWAN model with the WW3 model. A wave rider buoy located off Puducherry provided data for a period of 25 months during the period from June 2007 until July 2009 used in this study. The time series of error between numerical and corresponding measured values was first constructed, and using a wavelet neural network, the errors were predicted for future time steps. The predicted errors when incorporated into the model values provided the updated prediction of ${{H}_{s}}$ and ${{T}_{p}}$ . The study signifies that numerical estimations could be significantly improved using this procedure. The results provide quite satisfactory predictions with a lead time varying from 3 to 24 h. The study points out that adequate training of the neural network is an essential prerequisite to obtain good performance and skill levels. A comparison between the suggested prediction method with the standalone neural network model trained with measured data off Puducherry showed that the former approach is preferred over the latter in obtaining a sustained prediction performance.

A Brain–Computer Interface (BCI) for the Detection of Mine-Like Objects in Sidescan Sonar Imagery

Abstract: Detection of mine-like objects (MLOs) in sidescan sonar imagery is a problem that affects our military in terms of safety and cost. The current process involves large amounts of time for subject matter experts to analyze sonar images searching for MLOs. The automation of the detection process has been heavily researched over the years and some of these computer vision approaches have improved dramatically, providing substantial processing speed benefits. However, the human visual system has an unmatched ability to recognize objects of interest. This paper posits a brain–computer interface (BCI) approach, that combines the complementary benefits of computer vision and human vision. The first stage of the BCI, a Haar-like feature classifier, is cascaded in to the second stage, rapid serial visual presentation (RSVP) of images chips. The RSVP paradigm maximizes throughput while allowing an electroencephalography (EEG) interest classifier to determine the human subjects' recognition of objects. In an additional proposed BCI system we add a third stage that uses a trained support vector machine (SVM) based on the Haar-like features of stage one and the EEG interest scores of stage two. We characterize and show performance improvements for subsets of these BCI systems over the computer vision and human vision capabilities alone.

Development of Underwater Short-Range Sensor Using Electromagnetic Wave Attenuation

Abstract: In this paper, we discuss a novel underwater short-range sensor using electromagnetic (EM) wave attenuation. We use the revised Friis–Shelkunoff formula to calculate the EM wave attenuation underwater as a function of distance. This requires knowledge of the antenna gain underwater, which is very different from the gain in air, and also the attenuation constant which depends on the water conductivity. We calibrated the gain and attenuation in a ranging experiment and also in a 2-D localization experiment. Both methods agreed, confirming that in situ calibration of a 2-D localization experiment is feasible. The localization results show good accuracy, validating the sensor model and showing that multipath effects can be made negligible in such an experiment.

Design and Performance Analysis of Double Stator Axial Flux PM Generator for Rim Driven Marine Current Turbines

Abstract: This paper presents the design and performance analysis of double stator axial flux permanent magnet generators for rim-driven marine current turbines (MCT). In submarine applications, drive train reliability is a key feature for reducing maintenance requirements. Rim-driven, direct-drive, multistator generators can therefore be an interesting solution to improve reliability. In this context, the work presented here focuses on the design of a double-stator, axial flux, permanent magnet (PM) generator as a rim-driven, direct-drive, multistator generator. The models, specifications and an optimization procedure that facilitate the preliminary design of these kinds of generators for rim-driven marine turbines are presented. Validation with finite element computations and a performance analysis for a particular design of rim driven generators are conducted. The results obtained highlight some designs issues associated with PM generators for rim driven marine turbines. To assess the effectiveness of the double stator axial flux PM generator, a comparison with a surface mounted radial flux PM generator design for rim marine turbines is carried out. The comparison shows that the double stator axial flux generator has a better cooling characteristic and a reduced active parts cost and mass than the radial flux PM generator.

Robust Steering Autopilot Design for Marine Surface Vessels

Abstract: In this paper, a novel design based on an extended state observer (ESO) technique for yaw control of marine surface vessels is proposed. A marine vessel by virtue of its operation at sea is inherently under the influence of uncertainties and disturbances. Uncertainties arise because of parametric variation in hydrodynamic coefficients due to trim, loading, ballast, speed, and changes in underwater depth, where external disturbances due to winds and waves are present. The uncertainties and disturbances pose a great challenge in designing an effective autopilot for such vehicles. In this work, a robust design for steering autopilot is proposed wherein the effect of uncertainties and disturbances is estimated using ESO and the estimate is used to augment an input–output linearization (IOL)-based controller designed for nominal system to achieve robustness. The notable feature of the design is that while achieving robustness, it neither requires accurate plant model nor any information about the uncertainties and disturbances. The effectiveness of the ESO in estimation of the total disturbance and states and in meeting the specified performance in the presence of significant uncertainties, disturbances, and measurement noise is illustrated by simulation. Further, to demonstrate its efficacy, performance comparison of the proposed controller with some well-known existing designs in literature is carried out and the results are presented.

Experimental Confirmation of Nonlinear-Model- Predictive Control Applied Offline to a Permanent Magnet Linear Generator for Ocean-Wave Energy Conversion

Abstract: To further maximize power absorption in both regular and irregular ocean wave environments, nonlinear-model-predictive control (NMPC) was applied to a model-scale point absorber developed at the University of California Berkeley, Berkeley, CA, USA. The NMPC strategy requires a power-takeoff (PTO) unit that could be turned on and off, as the generator would be inactive for up to 60% of the wave period. To confirm the effectiveness of this NMPC strategy, an in-house-designed permanent magnet linear generator (PMLG) was chosen as the PTO. The time-varying performance of the PMLG was first characterized by dry-bench tests, using mechanical relays to control the electromagnetic conversion process. The on/off sequencing of the PMLG was tested under regular and irregular wave excitation to validate NMPC simulations using control inputs obtained from running the choice optimizer offline. Experimental results indicate that successful implementation was achieved and absorbed power using NMPC was up to 50% greater than the passive system, which utilized no controller. Previous investigations into MPC applied to wave energy converters have lacked the experimental results to confirm the reported gains in power absorption. However, after considering the PMLG mechanical-to-electrical conversion efficiency, the electrical power output was not consistently maximized. To improve output power, a mathematical relation between the efficiency and damping magnitude of the PMLG was inserted in the system model to maximize the electrical power output through continued use of NMPC which helps separate this work from previous investigators. Of significance, results from latter simulations provided a damping time series that was active over a larger portion of the wave period requiring the actuation of the applied electrical load, rather than on/off control.

Power Takeoff Optimization for Maximizing Energy Conversion of Wave-Activated Bodies

Abstract: This paper presents a fundamental investigation on optimizing the power takeoff (PTO) for maximizing wave energy conversion of the wave-activated bodies (WABs) wave energy converters. In this research, two relative heave motions are taken for capture power, and a linear PTO is considered in the primary analysis. For such a linear dynamic system, the frequency-domain analysis can be carried out, and an analytical formula can be derived for the optimized frequency-dependent PTO damping coefficient, which can be used to determine an optimized PTO damping for maximizing wave energy conversion in regular waves. However, when an optimized PTO is required for maximizing energy conversion from ocean waves, the PTO damping optimization may be very different and much less certain, because it may be based on one of many characteristic periods of the given sea state and the dependency may change from different sea states. For this reason, the optimized PTO damping coefficient for a given sea state must be studied carefully. Another important aspect of the research is to examine whether an optimized nonlinear PTO can take more energy out from waves than that of an optimized linear PTO. For this purpose, the maximized capture powers by the optimized linear and nonlinear PTOs are compared using the time-domain analysis. It has been shown from the examples that the maximized capture power by a nonlinear PTO system may exceed that by the linear PTO, but only marginally (less than 1%). Hence, it can be generally concluded that the maximized power using a linear PTO system can be a very good indicator for the device in extracting the maximal energy from waves regardless of the linear or nonlinear PTO in actual use. This conclusion may help simplify the analysis of the wave energy converters in terms of the energy production as well as the device optimization for improving energy conversion capacity.

Spatially Multiplexed CDMA Multiuser Underwater Acoustic Communications

Abstract: Direct-sequence (DS) code-division-multiple-access (CDMA) signaling allows multiple users to communicate simultaneously over the same bandwidth at the expense of a reduced rate. Due to severe cochannel interference (CoI) in multipath rich underwater channels, no more than 4 users have been demonstrated. Multiple-input-multiple-output (MIMO) communication also allows multiple users. Using parallel/sequential interference cancellation schemes, experimental results show similar limitations on the number of users. To extend the number of users beyond four (as required for certain applications), it is proposed to combine CDMA with MIMO, utilizing the spatial-temporal processing gain of passive-phase conjugation, and the approximate-orthogonality of the spreading codes to remove the (increased) CoI. The receiver algorithm uses simple matched filters without explicit channel-equalization and CoI cancellation. The algorithm performance is studied as a function of input-SNR, using simulated data based on experimentally measured channel impulse responses. M-sequences with 127, 255 and 511 chips are used. One finds that 255/511 chips are generally required to support 8 users, and 127/255 chips are needed to support 6 users for the channel studied. Multiuser communications are demonstrated with at-sea data for 8 users, with spreading codes of 511 chips, yielding zero bit errors. The data rate is ${\sim} 8$ bits/s/user, given 4 kHz bandwidth.

System Identification of Vessel Steering With Unstructured Uncertainties by Persistent Excitation Maneuvers

Abstract: System identification of vessel steering associated with unstructured uncertainties is considered in this paper. The initial model of vessel steering is derived by a modified second-order Nomoto model (i.e., nonlinear vessel steering with stochastic state-parameter conditions). However, that model introduces various difficulties in system identification, due to the presence of a large number of states and parameters and system nonlinearities. Therefore, partial feedback linearization is proposed to simplify the proposed model, where the system-model unstructured uncertainties can also be separated. Furthermore, partial feedback linearization reduces the number of states and parameters and the system nonlinearities, given the resulting reduced-order state model. Then, the system identification approach is carried out, for both models (i.e., full state model and reduced-order state model), resorting to an extended Kalman filter (EKF). As illustrated in the results, the reduced-order model was able to successfully identify the required states and parameters when compared to the full state model in vessel steering under persistent excitation maneuvers. Therefore, the proposed approach can be used in a wide range of system identification applications.

Ocean Surface Current Measurement Using Shipborne HF Radar: Model and Analysis

Abstract: The extension of onshore high-frequency surface wave radar (HFSWR) to shipborne HFSWR has the advantage of extended monitoring area and high application flexibility. However, additional modulation on the echo signal introduced by the forward movement and six-degree-of-freedom (6-DOF) ship motion may increase the surface current measurement error. Considering the radar array position on the ship, six-DOF ship motion, forward movement velocity, first-order Bragg scatter, and background noise, this paper models the backscattered Doppler spectrum of shipborne HFSWR. Based on this model, the performance of surface radial current measurement is analyzed, with the adoption of the MUltiple SIgnal Classification (MUSIC) to estimate the azimuth of the sea patches. Simulation results show that, rotation, sway and forward movement of the ship all have significant impacts on the surface radial current measure error. Nevertheless, if the ship sails at relative low speed and keeps its sailing direction (with small yaw amplitude), shipborne HFSWR may provide a better result than onshore HFSWR.

Development of Wireless and Passive Corrosion Sensors for Material Degradation Monitoring in Coastal Zones and Immersed Environment

Abstract: Wireless and fully energetically passive corrosion sensors inspired from the chipless Radio-Frequency IDentification (RFID) technology are presented for the monitoring of degradation of infrastructures located in coastal zones and underwater environments. The device consists of a reader and a remote passive sensor. This study presents two radio-frequency (RF) corrosion-sensitive resonators that can be integrated in such a device. The first is sensitive to a loss of metal due to its degradation, and the second is sensitive to the corrosion potential of metals, with respect to a reference electrode. The RF characterization of these two resonators demonstrates unambiguously the sensitivity of the method to corrosion of metal, passivation of steel as well as degradation of organic coatings. Then, their integration in a demonstrator including antennas is considered. The main parameters that influence the RF wave propagation and thus the reading distance are discussed. Following the presented results, the proposed method is considered as a reliable and versatile tool which should be able to be deployed in immersed, tidal, and splash zones, for example, for offshore facilities monitoring.

Fast Broadband Beamforming Using Nonuniform Fast Fourier Transform for Underwater Real-Time 3-D Acoustical Imaging

Abstract: A broadband 2-D array is necessary for the application of underwater real-time 3-D high-resolution acoustical imaging. However, the number of sensors and beams is so large that the computational load is overly high for generating a 3-D image in real time, when using the conventional broadband beamforming methods. Therefore, a fast broadband beamforming method is needed. In this paper, a fast broadband frequency-domain beamforming method based on nonuniform fast Fourier transform is proposed for underwater real-time 3-D acoustical imaging. The computational load of the proposed method is one or two orders of magnitude lower than that by the conventional frequency-domain direct method. Compared with the conventional time-domain delay-and-sum method, the computational load required by the proposed method will be lowered by approximately three orders of magnitude. Moreover, unlike the chirp zeta transform (CZT) beamforming method which is only suitable for equispaced 2-D arrays or sparse arrays thinned from equispaced 2-D arrays, the proposed method can be applied to arbitrary 2-D arrays. Even for the arrays available for the CZT method, the computational load needed by using the proposed method is still lower than that needed by using the CZT method in most cases.

COMPILE—A Generic Benchmark Case for Predictions of Marine Pile-Driving Noise

Abstract: The prediction of underwater noise emissions from impact pile driving during near-shore and offshore construction activities and its potential effect on the marine environment has been a major field of research for several years. A number of different modeling approaches have been suggested recently to predict the radiated sound pressure at different distances and depths from a driven pile. As there are no closed-form analytical solutions for this complex class of problems and for a lack of publicly available measurement data, the need for a benchmark case arises to compare the different approaches. Such a benchmark case was set up by the Institute of Modelling and Computation, Hamburg University of Technology (Hamburg, Germany) and the Organisation for Applied Scientific Research (TNO, The Hague, The Netherlands). Research groups from all over the world, who are involved in modeling sound emissions from offshore pile driving, were invited to contribute to the first so-called COMPILE (a portmanteau combining computation, comparison, and pile) workshop in Hamburg in June 2014. In this paper, the benchmark case is presented, alongside an overview of the seven models and the associated results contributed by the research groups from six different countries. The modeling results from the workshop are discussed, exhibiting a remarkable consistency in the provided levels out to several tens of kilometers. Additionally, possible future benchmark case extensions are proposed.

Preliminary Design of a Trench Cutter System for Deep-Sea Mining Applications Under Hyperbaric Conditions

Abstract: Seafloor massive sulfides (SMSs) are formed as precipitation products from hot hydrothermal fluids as a result of mixing with cold seawater and are mostly found at depths between 1500 and 3600 m. These deposits are formed in tectonically active zones of oceans (midocean ridges and “back-arc” spreading systems) and are the result of the global heat transfer from the mantle in the oceanic crust. As these fluids mix with the cold surrounding seawater, metal sulfides in the water are precipitated on or in the nearby seabed. The appearance of the solid mineral occurs as cylindrical chimney structures: the so-called black and white smoker (caused mainly by the presence of iron, copper, zinc, and sulphur). Larger sulfide occurrences are mostly originated in several generations of hydrothermal cycles, and they form deposits that can range from several thousands to about million tons. SMS contains pyrite (iron), galena (lead), sphalerite (zinc), and chalcopyrite (copper). Deep-sea mining is concentrating now to exploit such deposits. So far, the only known commercial project is the one developed by Nautilus Minerals, which is based on a horizontal system. This paper describes a preliminary design of a novel cutting tool developed for a vertical mining approach. The vertical mining method is preferred when rough terrain is expected and the device is easy to relocate. Using an atmospheric and hyperbaric cutting model, the cutting energy for two selected SMS deposits has been estimated and validated with real onshore excavation sites performed with a cutting tool normally used for diaphragm wall installation (i.e., the trench cutter technology). Preliminary results suggest that the estimated cutting energy ${\bf E}_{\bf SP}$ is 2.9 times higher with respect to the measured one in atmospheric conditions. This could be because the model considers the worst case scenario, i.e., higher energy due to the maximum cutting forces assumed. This factor has been used to design a cutting tool which is able to work up 2000-m water depth to mine SMS deposits.

A Concept for Docking a UUV With a Slowly Moving Submarine Under Waves

Abstract: Docking an unmanned underwater vehicle (UUV) with a submerged submarine in littoral waters in high sea states requires more dexterity than either the submarine or streamlined UUV possess. The proposed solution uses an automated active dock to correct for transverse relative motion between the vehicles. Acoustic, electromagnetic, and optical sensors provide position sensing redundancy in unpredictable conditions. The concept is being evaluated by building and testing individual components to characterize their performance, errors, and limitations, and then simulating the system to establish its viability at low cost.

Repeat-Pass Synthetic Aperture Sonar Micronavigation Using Redundant Phase Center Arrays

Abstract: In this paper, a new algorithm is introduced for high-precision underwater navigation using the coherent echo signals collected during repeat-pass synthetic aperture sonar (SAS) surveys. The algorithm is a generalization of redundant phase center (RPC) micronavigation, expanded to RPCs formed between overlapping pings in repeated passes. For each set of overlapping ping pairs (two intrapass and three interpass), five different RPC arrays can be formed to provide estimates of the vehicle’s surge, sway, and yaw. These estimates are used to find a weighted least squares solution for the trajectories of the repeated passes. The algorithm can estimate the relative trajectories to subwavelength precision (on order of millimeters to hundreds of micrometers at typical SAS operating frequencies of hundreds of kilohertz) in a common coordinate frame. This will lead to improved focusing and coregistration for repeat-pass SAS interferometry and is an important step toward repeat-pass bathymetric mapping. The repeat-pass RPC micronavigation algorithm is demonstrated using data collected by the 300-kHz SAS of the NATO Center for Maritime Research and Experimentation (CMRE) Minehunting Unmanned underwater vehicle for Shallow water Covert Littoral Expeditions (MUSCLE).

Image-Based Automated Change Detection for Synthetic Aperture Sonar by Multistage Coregistration and Canonical Correlation Analysis

Abstract: In this paper, an automated change detection technique is presented that compares new and historical seafloor images created with sidescan synthetic aperture sonar (SAS) for changes occurring over time. The method consists of a four-stage process: a coarse navigational alignment that relates and approximates pixel locations of reference and repeat–pass data sets; fine-scale coregistration using the scale-invariant feature transform (SIFT) algorithm to match features between overlapping data sets; local coregistration that improves phase coherence; and finally, change detection utilizing a canonical correlation analysis (CCA) algorithm to detect changes. The method was tested using data collected with a high-frequency SAS in a sandy shallow-water environment. Successful results of this multistage change detection method are presented here, and the robustness of the techniques that exploit phase and amplitude levels of the backscattered signals is discussed. It is shown that the coherent nature of the SAS data can be exploited and utilized in this environment over time scales ranging from hours through several days. Robustness of the coregistration methods and analysis of scene coherence over time is characterized by analysis of repeat pass as well as synthetically modified data sets.

On the Capability of Hybrid-Polarity Features to Observe Metallic Targets at Sea

Abstract: In this paper, target at sea detection is addressed using hybrid-polarity (HP) synthetic aperture radar (SAR) architecture. Wave polarimetry concepts are used to define HP features that are used to observe targets at sea. The sensitivity of HP features to both targets and the surrounding environment is analyzed through a novel objective norm, namely the Relative Sensitivity for Polarimetric Features (RSPolF) index. Detection performance is evaluated by the novel Dependency of Sea state and Target (DoST) surface characteristics metric, and by the well-known Figure of Merit (FoM). Experiments undertaken on HP measurements emulated from Radarsat-2 and ALOS-PALSAR full-polarimetric actual SAR data demonstrate the effectiveness of the proposed HP approach and the different sensitivity of HP features to targets and background sea characteristics. Following those results, a ranking of the HP features performance is proposed which mainly highlights that HP features complement each other in the detection process. Finally, a constant false alarm rate (CFAR) approach is proposed to exploit two HP features for target detection in an unsupervised way.