Shallow Water Channel Research Articles

Study on the effect of marine propeller wake on sediment siltation in a shallow water channel

Study on the effect of marine propeller wake on sediment siltation in a shallow water channel

Space-code division multiple access for broadband acoustic networks

We present an investigation into the design of an acoustic communication network, where multiple users are distributed across space and transmit and receive simultaneously in the same band to and from a common base station. Specifically, we focus on a system that utilizes orthogonal frequency division multiplexing as a modulation method, and allows users to transmit and receive in either synchronous or asynchronous fashion. To distinguish between users on the uplink, the base station employs a combination of code-division and space-division multiple access. The base station iteratively steers a beam to each stable propagation path of the desired user’s channel while placing nulls in the direction of other paths, as well as in the directions of interfering users. Finally, the multiple paths of the desired user are recombined before data detection. The process is repeated for each user. Broadband beamforming is employed to account for the broadband nature of acoustic signals. The beamformer coefficients on each carrier depend on the angles of signal arrivals, which are estimated during the uplink transmission and used to construct both the uplink and the downlink beamformer. On the downlink, the base station utilizes angle information to assemble beamforming weights and point in the direction of stable paths of the users. It superimposes multiuser signals and transmits the sum signal to the users. The signal intended for a given user reaches only that user, requiring just a simple detector. Each user is equipped by a single-element transducer. To demonstrate the design concepts, we conducted simulations using a shallow water channel model and performed experimental over-the-air tests in an indoor environment using an acoustic communications testbed. The results were excellent, thereby encouraging future implementations in practical systems.

Eutrophication hotspots, nitrogen fluxes and climate impacts in estuarine ecosystems: A model study of the Odra estuary system

The Odra estuary in the southern Baltic Sea comprises the Odra (Szczecin) Lagoon, the Pomeranian Bay and a number of other shallow water areas and channels. Known for its abundance of fish, eutrophication in the Odra Lagoon is a pressing issue for science and environmental management representing a global problem: What determines the seasonal variability of nitrogen and nitrogen turnover in shallow water areas, and how does seasonal variability change due to climatic changes such as warming and sea level rise? How do such changes affect nutrient exports to the regional ocean? This study employs a high-resolution unstructured model system to investigate physical-biogeochemical interactions, nitrogen turnover, and conditions leading to nitrogen export to the Baltic Sea within the Odra estuary. The research comprises hindcast and a climatic experiment with modified water level and temperature inputs. The model reproduces the thermohaline dynamics of brackish shallow water areas, phytoplankton blooms and the variability of inorganic nitrogen. The simulations identify the dynamic partitioning of the Odra Lagoon into the highly eutrophic, lake-like Small Lagoon and more frequently flushed, zooplankton-rich Great Lagoon. Although the two years of the hindcast simulation feature very different boundary conditions in terms of river forcing, comparable patterns of seasonal nitrogen export emerge. In a climate change experiment with increased sea levels and global temperatures, the system appears sensitive, but remains stable with regard to nutrient transport and is therefore predictable. The climate change experiment reveals enhanced primary producer biomass concentrations, suggesting heightened eutrophication. While in the shallow waters of Odra Lagoon oxygen concentration remains relatively stable, oxygen depletion intensifies as the lagoon outflows enter the Pomeranian Bay. This phenomenon is linked to increased denitrification within the stratified Odra plume. Deeper, meandering channels, such as Swina, demonstrate resilience to oxygen reduction, influenced by sea level rise and enhanced currents. Based on the temporal-spatial high-resolution coupled, validated simulations, it is possible to develop tailor-made management solutions without having to run expensive and complicated observation campaigns in the shallow waters with complex topography.

High-speed noncoherent underwater acoustic communication using permutation alphabets and sliding hypothesis-tree decoding.

A framework for joint synchronization and decoding is presented, named sliding hypothesis-tree decoding (SHDT), which targets communication applications in adverse underwater acoustic channels. The framework is exemplified by constructing a robust noncoherent link with spectral efficiency 0.149-0.222 bit/s/Hz using Polar coding and super permutation frequency shift keying. The link method is evaluated with randomized time-Doppler shifts through replay simulation of recorded UWA channels, where the five benchmark channels of the public benchmark Watermark and two channels from the Baltic Sea are used; these simulations show that a low frame error rate is achievable in all seven channels. The constructed link method is further evaluated in an adverse acoustic horizontal shallow-water channel using a high-mobility setup; the link method is able to perform synchronization, and a decoder performance similar to the replay simulations is observed. SHDT allows the construction of link methods with a performance limited by the information decoding rather than the time-Doppler synchronization, making it applicable to communication with lower-rate methods in non-line-of-sight scenarios.

A wavefront adaptive sensing beamformer for ocean acoustic waveguides.

This paper addresses robust adaptive beamforming for passive sonar in uncertain, shallow-water environments. Conventional beamforming is still common in passive sonar because adaptive beamformers suffer from signal mismatch in complex multipath environments. Existing approaches to robust adaptive beamforming try to model and account for the uncertainty in the beamformer's hypothesized signal subspace by using additional linear or quadratic constraints. Doing so, however, reduces the adaptivity of the beamformer and is prone to insufficiently suppressing interference. Instead, this paper uses blind source separation methods to adaptively estimate the complex spatial wavefronts of both targets and interference without requiring detailed physical modeling of the channel. By exploiting the different temporal spectra and/or frequency-selective multipath fading of targets and interference, this approach constructs a "signal-free" covariance matrix without imposing directional gain constraints. In doing so, the wavefront adaptive sensing (WAS) beamformer is able to separate targets from strong interference that is within the conventional beam width of the target. Simulation results in a realistic shallow-water channel are presented as well as results using the SWellEx96 S59 data with an injected target to show that the proposed WAS beamformer outperforms conventional and minimum variance adaptive beamformers in a shallow-water scenario.

Enhancing U-net extraction of hydrographic features from IfSAR data in Alaska using shallow water channel depth models

Enhancing U-net extraction of hydrographic features from IfSAR data in Alaska using shallow water channel depth models

Particle paths beneath forced small amplitude periodic waves in a shallow channel with constant vorticity

Particle paths beneath small amplitude periodic forced waves in a shallow water channel are investigated. The problem is formulated in the forced Korteweg-de Vries equation framework which allows to approximate the velocity field in the bulk fluid. We show that the flow can have zero, one or three stagnation points. Besides, differently from the unforced problem, stagnation points can arise for small values of the vorticity as long as the moving disturbance travels sufficiently fast.

Experimental Evaluation of a Real-Time FPGA Platform for Multichannel Coherent Acoustic Communication

This article describes a field-programmable gate array (FPGA) based multihydrophone receiver, and evaluates its real-time performance in various shallow-water channels. The receiver, built around an integer precision multichannel linear equalizer, uses the Least Mean Squares Algorithm for filter tap updates. Combined with a 64-hydrophone line array in the very high-frequency band, the receiver achieves information data rates up to 465 kb/s over 100 m, and rates up to 155 kb/s over 1000 m.

Coupling Dilated Encoder–Decoder Network for Multi-Channel Airborne LiDAR Bathymetry Full-Waveform Denoising

Multi-channel airborne full-waveform LiDAR is widely used for high-precision underwater depth measurement. However, the signal quality of full-waveform data is unstable due to the influence of background light, dark current noise, and the complex transmission process. Therefore, we propose a nonlocal encoder block (NLEB) based on spatial dilated convolution to optimize the feature extraction of adjacent frames. On this basis, a coupled denoising encoder–decoder network is proposed that takes advantage of the echo correlation in deep-water and shallow-water channels. Firstly, full waveforms from different channels are stacked together to form a two-dimensional tensor and input into the proposed network. Then, NLEB is used to extract local and nonlocal features from the 2D tensor. After fusing the features of the two channels, the reconstructed denoised data can be obtained by upsampling with a fully connected layer and deconvolution layer. Based on the measured data set, we constructed a noise–noisier data set, on which several denoising algorithms were compared. The results show that the proposed method improves the stability of denoising by using the inter-channel and multi-frame data correlation.

An investigation of a closed-form solution for non-linear variable-order fractional evolution equations via the fractional Caputo derivative

Determining the non-linear traveling or soliton wave solutions for variable-order fractional evolution equations (VO-FEEs) is very challenging and important tasks in recent research fields. This study aims to discuss the non-linear space–time variable-order fractional shallow water wave equation that represents non-linear dispersive waves in the shallow water channel by using the Khater method in the Caputo fractional derivative (CFD) sense. The transformation equation can be used to get the non-linear integer-order ordinary differential equation (ODE) from the proposed equation. Also, new exact solutions as kink- and periodic-type solutions for non-linear space–time variable-order fractional shallow water wave equations were constructed. This confirms that the non-linear fractional variable-order evolution equations are natural and very attractive in mathematical physics.

Machine-learning-based simultaneous detection and ranging of impulsive baleen whale vocalizations using a single hydrophone.

The low-frequency impulsive gunshot vocalizations of baleen whales exhibit dispersive propagation in shallow-water channels which is well-modeled by normal mode theory. Typically, underwater acoustic source range estimation requires multiple time-synchronized hydrophone arrays which can be difficult and expensive to achieve. However, single-hydrophone modal dispersion has been used to range baleen whale vocalizations and estimate shallow-water geoacoustic properties. Although convenient when compared to sensor arrays, these algorithms require preliminary signal detection and human labor to estimate the modal dispersion. In this paper, we apply a temporal convolutional network (TCN) to spectrograms from single-hydrophone acoustic data for simultaneous gunshot detection and ranging. The TCN learns ranging and detection jointly using gunshots simulated across multiple environments and ranges along with experimental noise. The synthetic data are informed by only the water column depth, sound speed, and density of the experimental environment, while other parameters span empirically observed bounds. The method is experimentally verified on North Pacific right whale gunshot data collected in the Bering Sea. To do so, 50 dispersive gunshots were manually ranged using the state-of-the-art time-warping inversion method. The TCN detected these gunshots among 50 noise-only examples with high precision and estimated ranges which closely matched those of the physics-based approach.

Analysis of the bed forms simulated using the three-dimensional model SSIIM, case of a natural shallow water channel

El objetivo de este trabajo se enfoca en analizar las dimensiones dominantes de las formas de fondo simuladas mediante un modelo hidrodinámico tridimensional acoplado con procesos de transporte de partículas y metodologías numéricas de utilidad para estimar los cambios en la morfología de flujos con superficie libre. En este sentido, se aplicaron técnicas de estadística descriptiva y espectral a las geometrías de fondo simuladas, obteniendo una discretización espacial y temporal de las dimensiones dominantes en el dominio de estudio del río Tercero en su paso por la ciudad de Villa María, Argentina. Las características del tramo seleccionado corresponden a las de un río de aguas poco profundas y con pendiente de fondo acorde con la de un cauce de planicie.

Rotational Solitary Wave Interactions Over an Obstacle

In this work we investigate the propagation of rotational solitary waves over a submerged obstacle in a vertically sheared shallow water channel with constant vorticity. In the weakly nonlinear regime, the problem is formulated in the forced Korteweg-de Vries framework. The initial value problem for this equation is solved numerically using a Fourier pseudospectral method with integrating factor. Solitary waves are taken as initial data, and the interaction wave-current-topography is analysed. We identify three types of regimes according to the intensity of the vorticity. A rotational solitary wave can bounce back and forth over the obstacle remaining trapped for large times, it can pass over the obstacle without reversing its direction or the wave can be blocked, i.e., it bounces back and forth above the obstacle until reaching a steady state. Such behaviour resembles the classical damped spring-mass system.

Array Acoustic Signal Processing in Shallow-Water Channels under Conditions of a Priori Uncertainty: Estimates of the Efficiency Loss

Array Acoustic Signal Processing in Shallow-Water Channels under Conditions of a Priori Uncertainty: Estimates of the Efficiency Loss

Analysis of the Bed Forms Simulated using the Three-dimensional Model SSIIM, Case of a Natural Shallow Water Channel

Analysis of the Bed Forms Simulated using the Three-dimensional Model SSIIM, Case of a Natural Shallow Water Channel

Deep learning-based M-ary spread spectrum communication system in shallow water acoustic channel

A deep learning-based M-ary spread spectrum (SS) underwater acoustic (UWA) communication system is proposed. The long short-term memory (LSTM) model is used as the receiver of the system, enabling the direct demodulation of received signals without de-carrier and de-spreading operations. LSTM architecture-based neural network models are fed with the time-domain waveform of each symbol during the training process to learn the source information carried by each symbol. Simulation results show that the deep learning-based M-ary SS UWA communication system outperforms the conventional system under the low signal-to-noise ratio and complex shallow water acoustic channel. For optimal performance, different LSTM models can be selected according to the simulation conditions. Furthermore, a water tank experiment simulating the complex shallow water channel was conducted and the results show that experimental equipment, different training sample acquisition methods, and LSTM models can affect the performance of the system.

Exploiting Sparsity for Underwater Acoustic Sensor Network Under Time-Varying Channels

As a time-frequency doubly selective channel, severe multipath, Doppler, as well as the large time-delay characteristics of the underwater acoustic (UWA) channel pose significant challenge to the research and design of UWA communication and network systems. To mitigate these negative factors, inherent sparsity contained in the UWA channel has been extensively investigated to improve UWA communication via a sparsity exploitation receiver. While the performance of the UWA sensor network is highly dependent on that of the physical layer, there are few investigations reported on exploiting channel sparsity from the viewpoint of UWA networking. In this article, a UWA sensor network adopting the sparsity exploitation physical layer is evaluated based on the network simulator 3 (NS-3) simulation tool. The simulation time-varying channel is generated by incorporating the Bellhop channel model with the statistical characteristics extracted from experimental shallow water channels. Three types of physical layers, i.e., those do not adopt sparse exploitation, adopting compressed sensing (CS), as well as the dynamic CS (DCS) technique, are employed for evaluation and comparison of network behavior under different media access control (MAC) protocols. The evaluation results verify the effectiveness of sparsity exploitation in improving UWA sensor network performance in the presence of time variations, while giving a quantitative comparison between enhancement achieved by the CS and DCS sparsity exploitation.

Angle dependence in coupling conditions for shallow water equations at channel junctions

In this paper we propose a modeling setting and a numerical Riemann problem solver at the junction of one dimensional shallow-water channel networks. The junction conditions take into account the angles with which the channels intersect and include the possibility of channels with different sections. The solver is illustrated with several numerical tests which underline the importance of the angle dependence to obtain reliable solutions.

Variation of signal-to-noise ratio of vertical array with sound source depth under wind-generated noise background

Wind-generated noise is ubiquitous in ocean environments and highly influences the passive sonar performance. Since it originates from sources near the ocean surface, one of its physical features is that it largely represents only the intermediate- and high-order modes. The array-level signal-to-noise ratio (SNR), which includes the array-sampled sound intensity, background noise power, and array gain, is an essential quantity determining the sonar array performance. What is investigated in this work is how the array-level SNR of the vertical line array (VLA) varies with the source depth in downward-refracting shallow water, contributed by the modal structure of the surface noise. On the assumption that the modes are well sampled, it is theoretically demonstrated that the SNR varying with the source depth can be approximated as a linear combination of the lower-order mode-amplitude intensities varying with the water depth. Particularly, when the surface noise especially dominates and the water channel is highly downward refractive, this variation can be represented nearly only by the 1<sup>st</sup>-order mode-amplitude intensity varying with depth. The structure is meaningful in practice. It suggests the SNR will be inherently larger when the source is submerged than it is near the ocean surface, and will be maximized at a source depth slightly below the 1<sup>st</sup>-order mode peak across different source ranges. The above assertions are demonstrated in a typical downward-refracting shallow-water channel; the effects from the dominant degree of the surface noise, sound speed gradient in water column, and array aperture are investigated numerically. The obtained results are shown below. 1) Under certain circumstances, the variation of SNR with source depth is nearly irrelevant to the source range. 2) When the surface noise is more significant, the largest SNR in a certain source range will be more significantly larger than the SNR for the source near the surface, the corresponding source depth will be closer to that presenting the 1<sup>st</sup>-order mode’s peak, and the variation of SNR with source depth is increasingly irrelevant to the source range. 3) A stronger downward-refracting sound speed also enhances this SNR superiority and irrelevance to the source range, but causes the source depth presenting the largest SNR to be more deviated from the 1<sup>st</sup>-order mode’s peak. 4) Although the structure is unraveled on the assumption that the VLA spans the full water column, it can be seen when the VLA does not but covers the low-order modes' main part; when the array aperture is insufficiently large it will become approximately periodic in the source range, with the source depth presenting the largest SNR fluctuating lightly and nearly periodically around the 1<sup>st</sup>-order mode peak.

A study on unpredictable shallow water channel behavior by various multipath patterns and experimental data analysis

In shallow water applications, multipath signal propagation is a major concern for robust communication. Multipath signal propagation is not explicitly seen in the channel, even though it is a main contributor for signal degradation. This fact motivated us to simulate multipath patterns to understand its influence in short-range communication. In this paper, a three-path signal propagation model is presented, where, besides the line of sight (LOS) signal, other two non-line of sight (NLOS) signals contact any point of channel boundary to reach the receiver. In simulation, the combination of eight possible multipath patterns is converged to estimate the received signal. A source fixed in water-tank periodically transmits low frequency acoustic signals 1 kHz and 1.5 kHz to the channel, and the receiver records them. The experiment was repeated for various input signal strengths. It has been observed that the simulation results coincide with the measured values. The good reception is noticed for signal frequency 1 kHz at 2.5m and 1.5 kHz at 1.2m. This study identifies the optimal signal strength for better signal reception in short range, which drives to the establishment of high-quality communication in shallow water.