Showing papers in "IEEE Journal of Oceanic Engineering in 2015"

Underwater Optical Imaging: The Past, the Present, and the Prospects

Abstract: This paper discusses the current state of underwater optical imaging in the context of physics, technology, biology, and history. The paper encompasses not only the history of human's ability to see underwater, but also the adaptations that various organisms living in oceans or lakes have developed. The continued development of underwater imaging systems at military, commercial, and consumer levels portends well for both increased visibility and accessibility by these various segments. However, the fundamental limits imposed by the environment, as currently understood, set the ultimate constraints. Physics, biology, computer modeling, processing, and the development of technology that ranges from simple cameras and lights to more advanced gated and modulated illumination are described. The future prospects for continuing advancements are also discussed.

Finite-Time Output Feedback Tracking Control for Autonomous Underwater Vehicles

Abstract: In this paper, the finite-time output feedback trajectory tracking control problem for autonomous underwater vehicles (AUVs) is investigated. The vehicle model is constructed in six degrees of freedom and the vehicle attitude is represented by quaternions to avoid representation singularities. The control design consists of three steps. First, by using the finite-time control technique, two global finite-time stabilizing controllers based on state feedback are proposed for the vehicle translational and rotational tracking error subsystems, respectively. Second, considering the estimation problem of the vehicle translational velocities, a global finite-time convergent observer is employed to reconstruct the information of the vehicle translational velocities. Finally, based on the proposed state feedback controllers and the finite-time convergent observer, a finite-time output feedback trajectory tracking control scheme for AUVs is derived. Global finite-time stability of the closed-loop system is rigorously proved by using Lyapunov theory. Compared with the conventional backstepping control scheme via output feedback, the proposed finite-time output feedback control scheme offers not only a faster convergence rate but also a higher tracking accuracy for trajectory tracking control of AUVs. Simulations demonstrate the effectiveness of the proposed control scheme.

Adaptive Modulation and Coding for Underwater Acoustic OFDM

Abstract: Underwater acoustic channels are fast varying spatially and temporally according to environmental conditions. Adaptive modulation and coding (AMC) is appealing for underwater acoustic communications to improve the system efficiency by matching transmission parameters to channel variations. In this paper, we construct an AMC system with a finite number of transmission modes in the context of underwater orthogonal frequency-division multiplexing (OFDM). We propose the effective signal-to-noise ratio (SNR) computed after channel estimation and channel decoding as a new performance metric for mode switching, which is shown to predict the system performance more consistently than the input SNR and the pilot SNR. Real-time AMC tests have been conducted in a recent sea experiment to maximize the transmission rate with a given transmission power.

Experimental Evaluations on Ship Autonomous Navigation and Collision Avoidance by Intelligent Guidance

Abstract: Experimental evaluations on autonomous navigation and collision avoidance of ship maneuvers by intelligent guidance are presented in this paper. These ship maneuvers are conducted on an experimental setup that consists of a navigation and control platform and a vessel model, in which the mathematical formulation presented is actually implemented. The mathematical formulation of the experimental setup is presented under three main sections: vessel traffic monitoring and information system, collision avoidance system, and vessel control system. The physical system of the experimental setup is presented under two main sections: vessel model and navigation and control platform. The vessel model consists of a scaled ship that has been used in this study. The navigation and control platform has been used to control the vessel model and that has been further divided under two sections: hardware structure and software architecture. Therefore, the physical system has been used to conduct ship maneuvers in autonomous navigation and collision avoidance experiments. Finally, several collision avoidance situations with two vessels are considered in this study. The vessel model is considered as the vessel (i.e., own vessel) that makes collision avoidance decisions/actions and the second vessel (i.e., target vessel) that does not take any collision avoidance actions is simulated. Finally, successful experimental results on several collision avoidance situations with two vessels are also presented in this study.

Dynamic Modeling of a Robotic Fish Propelled by a Compliant Tail

Abstract: In this paper, a dynamic model for a robotic fish propelled by a tail with a flexible fin is presented. The robotic fish is composed of two links connected by an actuated joint; the frontal link is rigid and acts as the robotic fish body, while the rear link serves as the tail. The latter comprises a rigid element connected to a flexible caudal fin, whose underwater vibration is responsible for propulsion. The dynamics of the frontal link are described using Kirchhoff's equations of motion for rigid bodies in quiescent fluids. The tail vibration is modeled using Euler–Bernoulli beam theory and the effect of the encompassing fluid is described using the Morison equation. The thrust production is assessed from static thrust data in terms of the fin-tip displacement; other salient model parameters are estimated through a nonlinear least squares technique. The model is validated against experimental data on circular and S-shaped trajectories. The model can be used for simulation, prediction, design optimization, and control, as it allows for the description of the robot's motion as a function of the unique input of the system, that is, the servomotor angle. Within the latter application, a heading control algorithm, in which the controller is tuned on the basis of the dynamic model, is presented.

Differentially Coherent Multichannel Detection of Acoustic OFDM Signals

Abstract: In this paper, we propose a class of methods for compensating for the Doppler distortions of the underwater acoustic channel for differentially coherent detection of orthogonal frequency-division multiplexing (OFDM) signals. These methods are based on multiple fast Fourier transform (FFT) demodulation, and are implemented as partial (P), shaped (S), fractional (F), and Taylor (T) series expansion FFT demodulation. They replace the conventional FFT demodulation with a few FFTs and a combiner. The input to each FFT is a specific transformation of the input signal, and the combiner performs weighted summation of the FFT outputs. The four methods differ in the choice of the pre-FFT transformation (P, S, F, T), while the rest of the receiver remains identical across these methods. We design an adaptive algorithm of stochastic gradient type to learn the combiner weights for differentially coherent detection. The algorithm is cast into the multichannel framework to take advantage of spatial diversity. The receiver is also equipped with an improved synchronization technique for estimating the dominant Doppler shift and resampling the signal before demodulation. An additional technique of carrier sliding is introduced to aid in the post-FFT combining process when residual Doppler shift is nonnegligible. Synthetic data, as well as experimental data from a recent mobile acoustic communication experiment (few kilometers in shallow water, 10.5–15.5-kHz band) are used to demonstrate the performance of the proposed methods, showing significant improvement over conventional detection techniques with or without intercarrier interference equalization (5–7 dB on average over multiple hours), as well as improved bandwidth efficiency [ability to support up to 2048 quadrature phase-shift keying (QPSK) modulated carriers].

Fuzzy Docking Guidance Using Augmented Navigation System on an AUV

Abstract: A fundamental successful docking operation requires the autonomous underwater vehicle (AUV) to be able to guide, navigate, and control itself into the docking station in a strategic manner and even possibly execute different maneuvers at different mission phases, depending on docking scenario, requirements, and homing sensor type. A docking station, due to environmental or mission requirements, is possibly oriented at a specific direction instead of allowing omnidirectional homing, and necessitates vehicle docking in only this direction. Depending on the operating environment, either wave or current presence or both can result in a dominating disturbance to the vehicle docking operation. In this work, an inverted ultrashort baseline (USBL) system is used as the main homing sensor to complement the existing navigation suite on the DSO-developed AUV. A docking guidance system was designed and implemented using the Sugeno fuzzy inference system (FIS). A desired heading vector field and the fuzzy rules were developed to perform the fuzzy docking maneuver. An error-state Kalman filter (KF) was designed, formulated, and implemented successfully on the AUV and has proven to perform excellent relative positioning estimation in sea trials. A software architecture was designed for the docking algorithms, and implemented onto a single board computer in the AUV. A sensor fusion approach to the software programming was adopted to ensure that navigation data from all navigation sensors are properly acquired and synchronized. A docking station was designed and eventually deployed at sea for docking trials. Successful AUV docking attempts at sea trials were demonstrated, thus showing the effectiveness of the implemented docking algorithms.

Sea Oil Slick Observation Using Hybrid-Polarity SAR Architecture

Abstract: In this study, hybrid-polarity (HP) architecture is exploited to observe sea oil slicks. HP features are interpreted in terms of sea surface scattering with or without oil slicks, under low-to-moderate wind conditions. They are shown to exhibit a different sensitivity with respect to slick-free, weak-damping slick-covered, and oil-covered sea surfaces. This sensitivity is verified against HP measurements obtained transforming actual L- and C-band quad-polarimetric synthetic aperture radar (SAR) data where both oil slicks and weak-damping look-alikes are present. Experiments demonstrate: 1) the remarkable performance of HP features to both observe oil slicks and distinguishing them from weak-damping look-alikes; 2) the marginal effect played by the sensor's noise floor on HP features performance; 3) the pronounced sensitivity of the HP features to the damping properties of the surfactants; and 4) the comparable performance that characterizes polarimetric entropy derived by HP and conventional polarimetric measurements.

Power Control of a Nonpitchable PMSG-Based Marine Current Turbine at Overrated Current Speed With Flux-Weakening Strategy

Abstract: This paper deals with power control strategies for a fixed-pitch direct-drive marine current turbine (MCT) when the marine current speed exceeds the rated value corresponding to the MCT nominal power. At overrated marine current speed, the MCT control strategy is supposed to be changed from maximum power point tracking (MPPT) stage to constant power stage. In this paper, flux-weakening strategy is investigated to realize appropriate power control strategies at high marine current speeds. During flux-weakening operations, the generator can be controlled to produce nominal or overnominal power for a specific speed range (constant power range). These two power control modes are compared, and the constant power range is calculated. The relationship between the expected constant power range and generator parameter requirements [stator inductance, permanent magnet (PM) flux, and nominal power coefficient] is analyzed. A Torque-based control with a robust feedback flux-weakening strategy is then carried out in the simulation. The proposed control strategies are tested in both high tidal speed and swell wave cases; the results validate the analysis and show the feasibility of the proposed control method.

Filterbank Multicarrier Communications for Underwater Acoustic Channels

Abstract: This work is motivated by the needs in the doubly dispersive underwater acoustic (UWA) communication channels. We propose and develop the use of filterbank multicarrier (FBMC) technique for communications in the channels of interest. A novel cost function for optimization of the filterbank prototype filter, to achieve a robust performance in doubly dispersive channels, is proposed. A design algorithm that optimizes the proposed cost function is then developed. The developed FBMC technique is compared with the celebrated orthogonal frequency-division multiplexing (OFDM). Our study shows that in doubly dispersive channels, in terms of signal-to-interference-plus-noise ratio (SINR), FBMC outperforms OFDM by several decibels. The theoretical results are validated and confirmed to be applicable to UWA communications, by examining real data from an at-sea experiment (ACOMM10), off the coast of New Jersey in July 2010.

Accumulated CA–CFAR Process in 2-D for Online Object Detection From Sidescan Sonar Data

Abstract: This paper describes a novel approach to object detection from sidescan sonar (SSS) acoustical images. The current techniques of acoustical images processing consume a great deal of time and computational resources with many parameters to tune in order to obtain good quality images. This is due to the handling of the large data volume generated by these kinds of devices. The technique proposed in this work does not make any a priori assumption about the nature of the SSS image to be processed. However, it is able to make a segmentation of the image into two types of regions: acoustical highlight and seafloor reverberation areas, and based on this, it makes detection. The developed algorithm to achieve this consists of a migration and adaptation of a technique widely used in radar technology for detecting moving objects. This radar technique is known as the cell average–constant false alarm rate (CA–CFAR). This paper presents a drastic improvement of such approach by making an extension into 2-D analysis of the SSS image, in a way similar to integral image used in CA–CFAR detection for pulse Doppler radar. In this form, optimization of the computational effort is achieved. This new technique was called the accumulated cell average–constant false alarm rate in 2-D (ACA–CFAR 2-D). It was applied to pipeline detection and tracking with a very interesting degree of success. In addition, this technique provides similar results to image segmentation with respect to other frequently used approaches, but with much less computational resources and parameters to set. Its simplicity is a strong support of its robustness and accuracy. This feature makes it particularly attractive for using it in real-time applications, such as underwater robotics perception systems. This proposal was tested experimentally with acoustical data from SSS and the results detecting pipelines, and other shapes like sunken vessels or airplanes, are presented in this paper. Likewise, an experimental comparison with the results obtained with inverse undecimated discrete wavelet transform (UDWT) and active contours techniques is also presented.

Fast Target Detection in Synthetic Aperture Sonar Imagery: A New Algorithm and Large-Scale Performance Analysis

Abstract: In this paper, a new unsupervised algorithm for the detection of underwater targets in synthetic aperture sonar (SAS) imagery is proposed. The method capitalizes on the high-quality SAS imagery whose high resolution permits many pixels on target. One particularly novel component of the method also detects sand ripples and estimates their orientation. The overall algorithm is made fast by employing a cascaded architecture and by exploiting integral-image representations. As a result, the approach makes near-real-time detection of proud targets in sonar data onboard an autonomous underwater vehicle (AUV) feasible. No training data are required because the proposed method is adaptively tailored to the environmental characteristics of the sensed data that are collected in situ. To validate and assess the performance of the proposed detection algorithm, a large-scale study of SAS images containing various mine-like targets is undertaken. The data were collected with the MUSCLE AUV during six large sea experiments, conducted between 2008 and 2012, in different geographical locations with diverse environmental conditions. The analysis examines detection performance as a function of target type, aspect, range, image quality, seabed environment, and geographical site. To our knowledge, this study—based on nearly 30 000 SAS images collectively covering approximately 160 km $^{2}$ of seabed, and involving over 1100 target detection opportunities—represents the most extensive such systematic, quantitative assessment of target detection performance with SAS data to date. The analysis reveals the variables that have the largest impact on target detection performance, namely, image quality and environmental conditions on the seafloor. Ways to exploit the results for adaptive AUV surveys using through-the-sensor data are also suggested.

OFDM-Modulated Dynamic Coded Cooperation in Underwater Acoustic Channels

Abstract: Dynamic coded cooperation (DCC) allows relay diversity without altering the transmission procedure from the source to the destination. In this paper, we propose a practical orthogonal frequency-division multiplexing (OFDM)-modulated DCC scheme for underwater relay networks, where OFDM modulation accommodates multipath fading channels with large delay spread. Two cooperation strategies are studied, where the relay transmits either identical or different OFDM blocks as the source during the cooperation phase. The block-level synchronization between the OFDM blocks from the source and the relay is achieved by a delay control mechanism at the relay, by knowing the distances among the source, relay, and destination. Two OFDM–DCC design examples are presented, one based on nonbinary rate-compatible low-density parity-check (LDPC) codes applied across multiple OFDM blocks, and the other using layered interblock erasure correction and intrablock error-correction coding. In addition to simulation studies, one particular design has been implemented on practical OFDM modems, and tested in a swimming pool and in a recent sea experiment. The proposed OFDM–DCC scheme is particularly appealing to underwater acoustic (UWA) networks where a relay node with abundant resources (e.g., a surface buoy) can enhance communications among underwater nodes without changing their transmission procedure.

Toward an Autonomous Sailing Boat

Abstract: Among autonomous surface vehicles, sailing robotics could be a promising technology for long-term missions and semipersistent presence in the oceans. Autonomy of such vehicles in terms of energy will be achieved by renewable solar and wind power sources. Autonomy in terms of sailing decision will be achieved by innovative perception and navigation modules. The main contribution of this paper is to propose a complete hardware and software architecture for an autonomous sailing robot. The hardware architecture includes a comprehensive set of sensors and actuators as well as a solar panel and a wind turbine. For obstacle detection, a segmentation is performed on data coming from an omnidirectional camera coupled with an inertial measurement unit and a sonar. For navigation and control of the vehicle, a potential-based reactive path-planning approach is proposed. The specific sailboat kinematic constraints are turned into virtual obstacles to compute a feasible and optimal heading in terms of cost of gybe and tack maneuver as well as safety relative to obstacle danger. Finally, field test experiments are presented to validate the various components of the system.

OFDM Transmission Without Guard Interval in Fast-Varying Underwater Acoustic Channels

Abstract: In this paper, we consider orthogonal frequency-division multiplexing (OFDM) transmission in fast-varying underwater acoustic channels. We demonstrate on experimental data that reliable communications can be achieved without any guard interval (such as cyclic prefix or zero padding) and with a superimposed pilot. Such OFDM transmission possesses a high spectral efficiency, but incurs severe intersymbol and intercarrier interference, and interference from the superimposed pilot. We propose a receiver that can efficiently deal with the interference and has a relatively low complexity as most of its operations are based on fast Fourier transform and local spline interpolation. The receiver is verified in an experiment with a transducer towed by a surface vessel moving at a high speed; a complicated trajectory of the transducer resulted in a severe Doppler distortion of the signal received on a single hydrophone. The performance of the proposed receiver is investigated for different parameter settings and compared with an ideal receiver with perfect channel knowledge, operating in interference-free scenarios, and mimicking the signal-to-noise ratio (SNR) of the experiment. The proposed receiver has provided error-free detection of encoded data at data rates of 0.5 b/s/Hz at a distance of 40 km and 0.33 b/s/Hz at a distance of 80 km, approaching the performance of the ideal receiver with a less than 3-dB loss in SNR.

The HydroNet ASV, a Small-Sized Autonomous Catamaran for Real-Time Monitoring of Water Quality: From Design to Missions at Sea

Abstract: In this paper, we describe the design, the development, and the sea trials of a novel small-sized autonomous surface vehicle (ASV) designed for monitoring the coastal water quality. The vehicle is characterized by the capability of measuring hydrocarbon and heavy metal concentrations directly onboard by means of custom-made miniaturized sensors. This capability, novel for an ASV, is combined with a winch-based sampling system specifically designed for small-sized vehicles. The sampling system can collect water samples up to 50 m in depth and measure the physical/water quality parameters of the water column. With these two features, the HydroNet ASV provides an autonomous, practical, real-time monitoring system, conceived to complement the current water monitoring practices in which samples are collected by a dedicated boat and analyzed in specialized laboratories at a later stage. The design process had the aim of realizing a vehicle capable of hosting the sampling system and the custom-made sensors that represent a unique payload in the world of small-sized ASVs. A twofold objective was pursued: realizing an ASV suited for monitoring missions in realistic scenarios (e.g., attention was paid to avoid water sample contamination), at the same time limiting the size for the ease of transportability and deployment. Severe constraints rose from these considerations and were addressed during the realization of the robot such as reduced length/weight (that limit the available space for the sensor payload) and low draft and protected propellers to allow the ASV to navigate in shallow waters with likely floating obstacles such as plastic bags. We report the design process aiming at a tradeoff between ease of transportability (small vehicle), available payload, and navigation performance in terms of achievable speed, endurance, and resistance to environmental disturbances (favored by larger ASV dimensions). We present sea trials of the realized vehicle validating the design choices. In particular, a long-range mission is discussed in which the robot executed a monitoring survey covering autonomously 12.5 km in front of Livorno, Italy, coast.

Space–Frequency Block Coding for Underwater Acoustic Communications

Abstract: In this paper, Alamouti space–frequency block coding, applied over the carriers of an orthogonal frequency-division multiplexing (OFDM) system, is considered for obtaining transmit diversity in an underwater acoustic channel. This technique relies on the assumptions that there is sufficient spatial diversity between the channels of the two transmitters, and that each channel changes slowly over the carriers, thus satisfying the basic Alamouti coherence requirement and allowing simple data detection. We propose an adaptive channel estimation method based on Doppler prediction and time smoothing, whose decision-directed operation allows for reduction in the pilot overhead. System performance is demonstrated using real data transmitted in the 10–15-kHz acoustic band from a vehicle moving at 0.5–2 m/s and received over a shallow-water channel, using quadrature phase-shift keying (QPSK) and a varying number of carriers ranging from 64 to 1024. Results demonstrate an average mean squared error gain of about 2 dB as compared to the single-transmitter case and an order of magnitude decrease in the bit error rate when the number of carriers is chosen optimally.

A Two-Stage Approach for the Estimation of Doubly Spread Acoustic Channels

Abstract: In this paper, the estimation of doubly spread acoustic channels is investigated. By parameterizing the amplitude variation and delay variation of each path with polynomial approximation, this paper derives a mathematical model for the discrete-time channel input–output relationship tailored to single-carrier block transmissions. Based on the mathematical model, the channel estimation problem is transformed into estimation of the low-dimensional parameter sets (amplitude, delay, Doppler scale) that characterize the channel. A two-stage sparse channel estimation technique is then developed, which estimates the delay and Doppler scale sequentially. Compared to the one-stage joint estimation, the two-stage estimation approach greatly reduces the number of candidates on the delay-Doppler scale grid searched by the orthogonal matching pursuit (OMP) algorithm, that is, the dictionary size is reduced dramatically. As a result, the computational complexity is much lower. Further, the two-stage approach demonstrated higher levels of accuracy in computer simulations and led to better detection performance when applied to experimental data.

Robust Equalization of Mobile Underwater Acoustic Channels

Abstract: Several underwater acoustic channels exhibit impulsive ambient noise. As a consequence, communication receivers implemented on the basis of the Gaussian noise assumption may yield poor performance even at moderate signal-to-noise ratios (SNRs). This paper presents a new channel-estimate-based decision feedback equalizer (CEB–DFE) that deals with high platform mobility, exploits any sparse multipath structure, and maintains robustness under impulsive noise. The key component of this DFE is a linear-complexity sparse channel estimator, which has the ability to detect and reject impulses based on two noise models: contaminated Gaussian and symmetric alpha stable $({\rm S}\alpha{\rm S})$ . By processing phase-shift keying (PSK) signals from three mobile shallow-water acoustic links, the gain of the proposed receiver over existing equalizers is demonstrated.

Underwater Acoustic Network Simulation With Lookup Tables From Physical-Layer Replay

Abstract: An underwater acoustic network simulation methodology is presented that is based on lookup tables (LUTs) with physical-layer error ratios. These LUTs are prepared with a validated replay channel simulator, which is here driven by channel measurements from the Kauai Acomms MURI 2011 (KAM11) experiment. Three physical-layer candidates are considered: a coherent single-carrier scheme, a coherent multicarrier scheme, and an incoherent scheme. The three modulation schemes are operated at a fixed message size and at four different data rates. Low rates are more robust to noise, interference, and channel dispersion, but also more prone to collisions in a network with busy traffic, because the packets are longer. Error statistics for colliding packets have been measured and are incorporated in the network simulator as collision LUTs. Example simulations are presented for a reduced flooding protocol with or without retransmissions. The results demonstrate how retransmissions pose a tradeoff between performance at high and low traffic load. The best network performance is obtained if the highest data rate is selected that yields a reasonably well-connected network. Collision avoidance is more important than the extended connectivity offered by low-rate signaling. On the other hand, at a given bit rate, a physical-layer scheme with extended connectivity but relatively weak links is shown to outperform a scheme with stronger links over fewer connections.

Control Performance Assessment and Design of Optimal Control to Harvest Ocean Energy

Abstract: Different approaches exist to design the optimal control strategy to harvest ocean energy with a point absorber. However, the control paradigm changes if the efficiency of the power takeoff (PTO) is taken into account. The motivation of this paper is twofold. The first objective is to develop a framework that includes the PTO efficiency to determine the optimal control strategy. The second objective is to assess the performance of any control strategy given the PTO efficiency. The performance assessment is based on the upper bound of the deliverable electrical energy of the optimal control strategy. As an example, different PTO efficiencies were considered for a given point absorber model, and extensive simulation results show the annual electrical energy delivered to the grid by the optimal control strategy. The performance of a nonoptimal control strategy is assessed with respect to the optimal control strategy.

Design of a Fuel-Cell-Powered Catamaran-Type Unmanned Surface Vehicle

Abstract: The goal of this study is to verify the applicability of fuel cells for powering surface vessels by developing a small catamaran-type unmanned surface vehicle (USV) powered by a hydrogen fuel cell. This study encompasses the entire process of designing a fuel-cell-powered USV, as well as sea trial tests with a 1.487-m full-scale prototype. To improve the performance and system efficiency of the USV, a simulation-based hull form design and integrated control systems were implemented during the design process. First, the optimum hull form of the catamaran, with the optimum separation, was determined based on hydrodynamic optimization using parametric models to achieve good fuel economy. Second, an automatic control system integrated with the global positioning and inertial navigation systems was implemented in the designed catamaran so that it had the ability to perform waypoint, departure, station keeping, and turning circle maneuvers. Next, the gain parameters of the fuzzy proportional–integral–derivative (PID) controller were adjusted to assure reliable tracking control. Automatically controlled trial tests were then conducted to validate the performance of the autonomous surface vehicle with respect to the fuel cell power requirements and its dynamic motion. Based on the results of the trial tests and the transient response of the fuel cell, a hybrid power control algorithm for the fuel cell and the batteries was implemented for more efficient power utilization. This catamaran-type unmanned surface vehicle powered with a fuel cell can be utilized for ocean environment monitoring and multifunctional missions.

Modeling, Control, and Experimental Validation of a High-Speed Supercavitating Vehicle

Abstract: Underwater vehicles that travel inside a bubble or supercavity offer possibilities for high-speed and energy-efficient transportation of cargo and personnel. Validation and testing of mathematical models and control systems for these vehicles is a challenge due to the cost and complexity of experimental facilities and testing procedures. A cost-efficient and low-complexity approach to the experimental validation of mathematical models and control systems for a supercavitating test vehicle is presented in this paper. The proposed method enables the testing of control algorithms subject to steady and unsteady flows in a high-speed water tunnel. The method combines a real-time simulation of the vehicle dynamics, force measurements from an experimental scale vehicle, and flight control computer to reproduce the vehicle motion subject to realistic flow conditions and hardware constraints as actuator saturation and time delay. The model of the vehicle dynamics, used for the validation infrastructure and control design, is derived using experimental data. A controller designed to track pitch angle reference commands was tested on the experimental platform. The test cases validated the operation of the vehicle and controller subject to steady and unsteady flows.

Mapping of Translating, Rotating Icebergs With an Autonomous Underwater Vehicle

Abstract: This paper presents a method for mapping translating, rotating icebergs with an autonomous underwater vehicle (AUV). To map an iceberg, the AUV first circumnavigates it, collecting multibeam sonar ranges and iceberg-relative Doppler sonar velocities from the submerged iceberg surface. The primary challenge is then to estimate the trajectory of the mapping vehicle in a noninertial reference frame attached to the moving iceberg. The collected multibeam ranges may then be projected from this trajectory to form a map of the iceberg's submerged surface. The approach of the method involves identifying the iceberg-frame locations of all the Doppler sonar measurements made during circumnavigation, allowing the AUV's iceberg-relative trajectory to be computed from those locations. The measurement locations are estimated simultaneously with the trajectory of the iceberg to be most consistent with the inertial-space positions, inertial-space velocities, distances between points on the iceberg surface as measured by the Doppler sonar, and alignment of multibeam ranges measured at the beginning and end of the circumnavigation. The measurements depend nonlinearly on the modeled positions and iceberg trajectory, and the paper presents a solution formulation that deals efficiently with the nonlinearity. By incorporating iceberg-relative vehicle velocity into the estimation, the method achieves two significant advances beyond prior work by the authors. First, and most significantly, the method adds ice-relative vehicle velocity measurements (e.g., using a Doppler velocity logger). This makes the method robust to common vehicle inertial navigation errors. Second, inclusion of iceberg-relative vehicle velocity data allows for the identification of a more general model of iceberg trajectory, making the method robust to changes in iceberg translation and rotation rates. Currently, no iceberg circumnavigation data sets are available that include iceberg-relative velocity from Doppler sonar. However, this paper includes results from simulated free-drifting icebergs, and experimental results from an AUV seafloor mapping dive. The simulation data provide a moving iceberg testbed with known ground truth for the mapping results. The seafloor data provide a qualitative verification that the method works with real vehicle data.

Robust Object Classification in Underwater Sidescan Sonar Images by Using Reliability-Aware Fusion of Shadow Features

Abstract: Detecting and classifying objects in sidescan sonar images is an important underwater application with relevance to naval transportation and defense. Properties of the imaging modality, in this case, often introduce large intraclass variabilities reducing the discriminative power of any classification algorithm and limiting the possibilities of improving classification accuracy by advances in pattern recognition only. In this work, we investigate the role of an ancillary feature set computed on object shadows and propose a scheme for exploiting this useful, but variedly reliable information for object classification. A mean-shift-clustering-based segmentation technique is used for isolating highlight and shadow segments from the images. We show the results of reliability-aware fusion of features computed on highlight and shadows on three different data sets of sidescan sonar images, to illustrate under what conditions such information might be useful.

On the Achievable Rate of a Class of Acoustic Channels and Practical Power Allocation Strategies for OFDM Systems

Abstract: In this paper, we consider a class of single-input–multiple-output (SIMO) underwater acoustic communication channels, where each propagation path can be characterized by a complex-valued Gaussian block-fading model. The capacity of such channels is computed and analyzed using three power allocation strategies: waterfilling, uniform, and on–off uniform power allocation across the signal bandwidth. Our analysis considers the effects of imperfect channel estimation, delayed feedback, and pilot overhead, which are found to contribute to about 1 (b/s)/Hz loss from 4 (b/s)/Hz at 20-dB signal-to-noise ratio (SNR) for the experimental channel. We find that given the long feedback delays associated with acoustic channels, all-on uniform power allocation, which does not require feedback and is simple to implement, emerges as a justified practical solution that outperforms the other strategies. Furthermore, when considering acoustic-specific propagation effects, such as frequency-dependent attenuation and colored noise, considerable gain can be achieved by selecting the frequency band according to the attenuation pattern and the available transmit power, e.g., at least 6-dB gain for a 10-km link when compared to transmission over a preselected frequency band of 10–15 kHz.

Semisynthetic Versus Real-World Sonar Training Data for the Classification of Mine-Like Objects

Abstract: The detection of mine-like objects (MLOs) in sidescan sonar (SSS) imagery continues to be a challenging task. In practice, subject matter experts tediously analyze images searching for MLOs. In the literature, there are many attempts at automated target recognition (ATR) to detect the MLOs. This paper focuses on the classifiers that use computer vision and machine learning approaches. These techniques require large amounts of data, which is often prohibitive. For this reason, the use of synthetic and semisynthetic data sets for training and testing is commonplace. This paper shows how a simple semisynthetic data creation scheme can be used to pretest these data-hungry training algorithms to determine what features are of value. The paper provides real-world testing and training data sets in addition to the semisynthetic training and testing data sets. The paper considers the Haar-like and local binary pattern (LBP) features with boosting, showing improvements in performance with real classifiers over semisynthetic classifiers and improvements in performance as semisynthetic data set size increases.

Estimating Geoacoustic Properties of Surficial Sediments in the North Mien-Hua Canyon Region With a Chirp Sonar Profiler

Abstract: Acoustic reflection coefficients and attenuation rolloff rates of the seabed near North Mien-Hua Canyon, northeast of Taiwan, were measured from chirp sonar echoes during the Quantifying, Predicting, and Exploiting (QPE) Uncertainty Initiative Experiment in 2009. Using these measurements and the Biot theory with a fluid approximation, the depth-averaged sound speed, density, and medium attenuation of the surficial sediment layer were estimated. The sediment types in the chirp sonar survey area vary from fine sand to coarse silt. To capture this spatial variability, the 1-D geoacoustic parameter estimates along the chirp sonar track were interpolated onto a 2-D grid using an objective mapping technique. The 2-D maps of surficial sediment properties, along with interpolation errors, can be further applied to underwater sound propagation models in the experimental area.

Adaptive Error-Correction Coding Scheme for Underwater Acoustic Communication Networks

Abstract: Underwater acoustic communication networks (UWANs) have recently attracted much attention in the research community. Two properties that set UWANs apart from most radio-frequency wireless communication networks are the long propagation delay and the possible sparsity of the network topology. This in turn offers opportunities to optimize throughput through time and spatial reuse. In this paper, we propose a new adaptive coding method to realize the former. We consider time-slotted scheduling protocols, which are a popular solution for contention-free and interference-free access in small-scale UWANs, and exploit the surplus guard time that occurs for individual links for improving transmission reliability. In particular, using link distances as side information, transmitters utilize the available portion of the time slot to adapt their code rate and increase reliability. Since increased reliability trades off with energy consumption per transmission, we optimize the code rate for best tradeoff, considering both single and multiple packet transmission using the incremental redundancy hybrid automatic repeat request (IR–HARQ) protocol. For practical implementation of this adaptive coding scheme, we consider punctured and rateless codes. Simulation results demonstrate the gains achieved by our coding scheme over fixed-rate error-correction codes in terms of both throughput and consumption of transmitted energy per successfully delivered packet. We also report results from a sea trial conducted at the Haifa harbor, which corroborate the simulations.

Reliable Point-to-Point Underwater Acoustic Data Transfer: To Juggle or Not to Juggle?

Abstract: Reliable data transfer speeds using underwater acoustic communication systems are limited by long propagation delays, small link data rates, and high bit error rates. We consider the practical problem of transferring a data file or data stream reliably from one half-duplex underwater node to another. In a typical automatic repeat request (ARQ) approach, a node transmits one or more packets and waits for the corresponding acknowledgments (ACKs). With long propagation delay, the long waiting time for ACKs results in low average throughput. The long propagation delay, however, presents an opportunity for two nodes to simultaneously transmit data and ACKs toward each other in a juggling-like approach, potentially reducing the average waiting time for ACKs. The approach needs to satisfy certain timing constraints, and its performance is largely dependent on the network settings and chosen parameters. Through analytical and numerical studies, we provide key insights into appropriate choice of ARQ strategies and protocol parameters under different internodal propagation delays. We show that the juggling-like ARQ (J–ARQ) provides good data streaming throughput but performs poorly for small file transfers. We propose a novel rate-less code-based J–ARQ protocol that overcomes this limitation and offers high data transfer speeds for small files in long propagation delay environments.