Description: Underwater pulse position modulation (PPM) transmission uses acoustic pulses since they allow communication, remote control of underwater vehicles, and positioning estimation; the last one when more than one detector is present by using only one technology, that is, the same transmission module. On the other hand, PPM pulses are difficult to detect since they carry information on signal delays, assuring that reliable information delivery both in shallow- and deep-sea channels may be considered a timely challenge due to strong multipath and other interference sources/causes giving rise to signal fluctuation and high noise level. This paper proposes a transceiver architecture characterized by a signal analyzer and an adaptive detection based on the channel features. The signal analysis is based on the Wigner–Ville transform (WVT) that converts a 1-D signal into an image. Edge detection procedures performed on the obtained image so as to discover the interference features and understand the main characteristics of multipath with their adverse effects on detection of pulse position information have been taken into account. Based on this, maximal ratio combining (MRC) and equal gain combining (EGC) for RAKE reception and truncated channel equalization have been considered. Numerical results showing the ability of the proposed transceiver to detect pulses in the presence of multipath and interference generated by external acoustic sources have been carried out also by taking into account the estimation error effects and by comparing the actual performance with ideal cases. Finally, field tests corroborate the reliability of the proposed approach.

Description: Real-time 3-D acoustical imaging technique is a key advance to broaden the scope and enhance the feasibility of underwater missions. In this paper, a real-time 3-D underwater acoustical imaging system to handle the actual tasks under a narrowband excitation is presented. The system consists of three parts: a transmitter, a receiving hydrophone array, and a signal processor. In this system, a distributed and parallel subarray (DPS) beamforming algorithm is proposed to process the acquired signals from a scene placed in the far field. The DPS beamforming algorithm is an approximate method for the sonar signal processing with an advantageous computational efficiency. The direct method (DM) and fast Fourier transform (FFT) beamforming are compared with DPS beamforming for the memory and computational requirements. Based on this algorithm, a prototype was developed, which has been extensively employed in the lake and sea trials. The trials demonstrate that the system can achieve the 3-D imaging of the scene and meet the real-time requirement of the underwater operations.

Description: This paper addresses the modeling and experimental identification of six different six degree-of-freedom (6-DOF) coupled nonlinear second-order plant models. We report a comparative experimental evaluation of six different candidate plant models whose unknown plant parameters are estimated from data obtained in free-motion vehicle trials. The parameter estimation methodologies of ordinary least squares (OLS), total least squares (TLS), and underdetermined TLS were employed to identify experimentally the unknown plant model parameters. We evaluate the performance of each of the six different 6-DOF coupled nonlinear finite-dimensional plant models of an underwater vehicle estimated by OLS and the plant model identified by TLS by comparing the mean absolute error between the experimentally observed vehicle velocities and the velocities obtained by a numerical simulation of the identified plant models. We also report a cross validation which evaluates the performance of a plant model to accurately reproduce observed plant velocities for experimental trials differing from the trials from which the plant model parameters were estimated. We conclude that: 1) plant models identified by TLS generally perform better (i.e., more accurately reproduce observed experimental behavior) than models identified by OLS; and 2) plant models including fully parametrized coupled quadratic drag terms perform best overall in cross validation. This study has the following contributions: it is the first reported experimental 6-DOF fully coupled plant model identification and cross validation of a low-speed, fully actuated, and neutrally buoyant underwater vehicles; it is the first experimental 6-DOF plant model identification for this same class of underwater vehicles during free-flight experiments; and it is the first reported use of TLS to perform 6-DOF plant model identification of an underwater vehicle.

Description: This paper presents a robust cascaded control strategy to underwater robot thrust. The dynamics of surge motion, of propeller axial flow, of propeller shaft, and of electrically driven circuit in the motor constitute a cascaded system with respect to propeller thrust. Instead of the usual parameter perturbation, generalized modeling errors are considered in the plant, which may be parametric errors, ignored high-order modes, or some unmodeled dynamics in the underwater thrust system. External disturbances are also taken into account, which may be the random noises from mechanical or electrical equipment, or the environmental forces possibly induced by nonuniform currents, ocean internal wave, or cable tension. Combined with state feedback control, an online neural network (NN) compensator is introduced to identify the modeling errors, while L2-gain design is used to suppress the externally continuous or instantaneous disturbances. The Lyapunov's second method is applied to instruct the controller design, which guarantees the uniformly ultimately bounded (UUB) stability of the error system. By analyzing the tracking errors, it is recommended how to properly select the controller parameters. Good tracking performance and reasonable control inputs are illustrated by numerical simulations.

Description: Experimental testing of an unmanned amphibious tracked vehicle on dry sand, in the surfzone and in water, has been performed to explore its maneuvering and performance characteristics for the planned future development of an automatic control system. The 2.69-m-long, 295-kg concept vehicle utilizes a small waterplane area twin hull (SWATH) configuration with integrated crawler tracks and twin propellers for propulsion. Maximum traversable incline tests on dry sand reveal that the vehicle has a drawbar pull (DP) of about 1000 N (about one third of its weight) and can operate on slopes of 15 $^{circ}$ briefly and 10 $^{circ}$ for extended periods of time. Maneuvering tests were performed on flat, dry sand, as well as into and out of a surfzone at a beach site with inclines ranging from about 3 $^{circ}$ to 6 $^{circ}$ . In each of the tests, the track forces, speed over ground, and both linear and rotational accelerations were measured. Also recorded were environmental conditions, such as wind speed, significant waveheight/period, and ground slope. The tests reveal that the vehicle has a maximum straight-line flat ground speed of about 2 m/s, a minimum flat ground turning radius of 2.4 m, an in-water minimum turning radius of 1.9 m, and a maximum straight-line waterborne speed of 1.2 m/s. It is also shown that system identification applied to the data recorded from the flat ground and waterborne maneuvering tests can be used to find a linear, parametric state–space model for the vehicle that adequately reproduces its motion. Land-to-sea transition tests in two different seas of one-third significant waveheights of 8 and 28 cm (both measured at a distance of 6 m from the mean waterline on - he beach) show that the vehicle exhibits substantial track slip as it traverses into the surfzone and its weight becomes increasingly supported by the displacement of its hulls. The tractive force model developed by Wong (Theory of Ground Vehicles, New York, NY, USA: Wiley, 2001) is modified to account for the reduction in track-supported vehicle weight as the vehicle becomes waterborne. It is shown that this adapted model captures the main physical features of the measured track forces. The waveheights and periods recorded during surfzone transition tests are used to examine the seakeeping properties of the vehicle. It is found that the vehicle's natural frequency of roll is near the dominant wave frequencies measured. A Froude–Krylov strip theory simulation shows that the wave forces acting on the vehicle in 28-cm waves may be slightly larger than the force measured on each track when the DUKW-Ling is crossing the transition zone between the beach and surfzone and should not be ignored in modeling and simulation studies.

Description: Dead-reckoning (DR) navigation is used when Global Positioning System (GPS) reception is not available or its accuracy is not sufficient. At sea, DR requires the use of inertial sensors, usually a gyrocompass and an accelerometer, to estimate the orientation and distance traveled by the tracked object with respect to a reference coordinate system. In this paper, we consider the problem of DR navigation for vessels located close to or on the sea surface, where motion is caused by ocean waves. In such cases, the vessel pitch angle is fast time varying and its estimation by direct measurements of orientation is prone to drifts and noises of the gyroscope. Regarding this problem, we propose a method to compensate for the vessel pitch angle using a single acceleration sensor. Using a constraint expectation–maximization (EM) algorithm, our method classifies acceleration measurements into states of similar pitch angles. Subsequently, for each class, we project acceleration measurements into the reference coordinate system along the vessel heading direction, and obtain distance estimations by integrating the projected measurements. Results in both simulated and actual sea environments demonstrate that, by using only acceleration measurements, our method achieves accurate results.

Description: In this paper, the authors study the problem of robust adaptive path-following control for underactuated ships with model uncertainties and nonzero-mean time-varying disturbance. A concise adaptive neural network (NN)-based control scheme is proposed using backstepping, feedforward approximations, dynamic surface control, and minimal learning parameter techniques. In addition, to tackle the strong couplings among state variables (including the underactuated state variable) and underactuated characteristics, much effort is put into guaranteeing semiglobal uniform ultimate boundedness of the ship motion control system. The outstanding advantage of this scheme is that the control law has a concise form and is easy to implement in practice due to a smaller computational burden, with only two online parameters being tuned to tackle the uncertainties. The simulation results demonstrate the effectiveness of the proposed algorithm, especially including the experiment in the simulated marine environment.

Description: Plankton image classification is an important, yet challenging, problem in marine biology. This challenge can be attributed to: 1) large within-class variations; 2) large between-class similarity; and 3) large noise. To mitigate these problems, we propose a novel subspace classification framework, called pairwise nonparametric discriminant analysis for binary plankton image recognition. In this framework, first we decompose the multiclass recognition into a combination of pairwise binary classes, then train an appropriate classifier for each class pair using the nonparametric discriminant analysis technique (a newly developed subspace analysis technique) to effectively remove unwanted information (such as the within-class variations and the noise) and extract discriminant information (such as the boundary structural information), and, finally, combine all the pairwise classifiers using an efficient fusion rule for real-time classification. Extensive experiments are conducted on a large data set to show the improvement obtained by our new approach over the state-of-the-art ones.

Description: Correct identification and tracking of stable raypaths are critical for shallow-water acoustic tomography. Separating raypaths using high-resolution methods has been presented to improve resolution ability based on the prior knowledge of the number of raypaths. It is clear that the precise knowledge of the number of raypaths largely determines the separation performance. Therefore, a noise-whitening exponential fitting test (NWEFT) using short-length samples is proposed in this paper to automatically detect the number of raypaths in a shallow-water waveguide. Two information-theoretic criteria are considered as comparative methods in terms of the capability of correct detection. Their performances are tested with simulation data and real data obtained from a small-scale experiment. The experimental results show that the NWEFT can provide satisfactory detection compared to the two classic information-theoretic criteria—the Akaike information criterion (AIC) and the minimum description length (MDL). MDL is asymptotically consistent while AIC overestimates even if analyzed asymptotically. Compared to these criteria, the proposed method is more suitable for short-length data.