Underwater Acoustic Simulation Research Articles

UnderwaterImage2IR: Underwater impulse response generation via dual‐path pre‐trained networks and conditional generative adversarial networks

AbstractIn the field of acoustic simulation, methods that are widely applied and have been proven to be highly effective rely on accurately capturing the impulse response (IR) and its convolution relationship. This article introduces a novel approach, named as UnderwaterImage2IR, that generates acoustic IRs from underwater images using dual‐path pre‐trained networks. This technique aims to achieve cross‐modal conversion from underwater visual images to acoustic information with high accuracy at a low cost. Our method utilizes deep learning technology by integrating dual‐path pre‐trained networks and conditional generative adversarial networks conditional generative adversarial networks (CGANs) to generate acoustic IRs that match the observed scenes. One branch of the network focuses on the extraction of spatial features from images, while the other is dedicated to recognizing underwater characteristics. These features are fed into the CGAN network, which is trained to generate acoustic IRs corresponding to the observed scenes, thereby achieving high‐accuracy acoustic simulation in an efficient manner. Experimental results, compared with the ground truth and evaluated by human experts, demonstrate the significant advantages of our method in generating underwater acoustic IRs, further proving its potential application in underwater acoustic simulation.

A novel and computationally efficient subgrid technique for modeling scattering and Doppler effects of rough dynamic sea surfaces using the finite-difference time-domain method

Over the last decade, the improvements in computational performance that multiprocessing, solid-state hard drives, and fast memories have brought to desktop workstations have made modeling and simulation methods that were previously inaccessible into the office workspace. These methods were previously restricted to large servers or computer clusters because of their demanding computation and large memory requirements when applied to underwater acoustic simulation scenarios. One such method is the Finite-difference Time-domain (FDTD) technique. The FDTD method is a discrete numeric model that provides the full pressure wave solution solved directly in the time domain. This makes it an ideal model for investigating scattering and Doppler effects of boundaries with complex geometries and motion. A fully developed sea surface generated using the Pierson–Moskowitz wavenumber spectra meets these criteria. A novel subgrid technique has been developed to improve the accuracy of signals scattered from fully developed sea surfaces. This method remains computationally efficient because the subgrid is applied only along the rough sea surface as it varies over time. The FDTD subgrid method has been applied to simulations that investigate the “frozen” sea surface assumption that is utilized by other traditional models that incorporate boundary motion.

Fractional Low-Order Blind Equalization Algorithm Based On SAPSO Optimization under Impulsive Noise

To address the problem that the traditional constant mode blind equilibrium algorithm (CMA) cannot converge stably in a water channel under α-stable distributed noise, we propose a fractional low-order blind equilibrium algorithm (SAPSO-FLOSCMA) based on simulated annealing particle swarm algorithm optimization. The algorithm introduces a simulated annealing operation in the particle swarm algorithm (PSO) to make the population accept the difference solution with a certain probability of accepting the difference solution to enhance the ability of the PSO algorithm to jump out of the local optimal solution. Then the cost function of the FLOSCMA algorithm is used as the fitness function of the SAPSO algorithm, and the global optimal solution is iteratively searched by using the SAPSO algorithm. The global optimal solution is used as the initial weight vector of the equalizer. The underwater acoustic simulation results show that compared with the CMA and FLOSCMA, the algorithm improves the convergence speed and reduces the inter-code interference.

EFFECTS OF MULTIPATH PROPAGATION CHANNEL IN TIGRIS RIVER

Tigris River is an environment of shallow waters because of its low depth and it has been identified as a multi-path channel. The underwater multi-path propagation leads to reverberation as well as fading, which causes large transmission loss. The present paper conducts 3 underwater acoustic simulation outcomes in the district of Abu Dali - Kazem Al Ali village - Tigris beaches - Baghdad - Iraq. The distance from the sender to the receiver are (100m, 1000 m, and 5000m). With the use Ray model, results have shown that the multi-path propagations dominate in a case where the distance from sender to receiver, has been increased, which resulted in decreasing the grazing angle, thereby, increasing the coefficient of reflection. The consecutive path amplitude values will not be decreased quickly. This is why differences in the time between different paths are minimal. This indicates that the consecutive path-ways will be converged with time, which will result in an inter- symbol interference phenomenon, playing a role in an increase of the received data bit error rate.

WITHDRAWN: A comparative study of impacts multipath propagation channel using empirical models

Tigris river is a shallow water environment due to its low depth and is characterized as a multi-path channel. Underwater multipath propagation causes reverberation and fading, resulting in a large loss of transmission. This research compared two underwater acoustic simulation results in Abu Dali district, Kazem Al Ali village, Tigris beaches, Baghdad, Iraq and Al-Atifiyah district, Iraq. The distance between the sender and the receiver is (100 m and 1000 m). With the use Ray model, the results show that multipath propagation becomes worse in the case of Al-Atifiyah district compared with the case Abu Dali district due to the lower wind speed leads to the surface reflection coefficient (R s ) will increase. Besides, depending on the type of bottom (Bt), the bottom reflection coefficient (R b ) will increase in the case of fine sand compared with the case in very fine sand. Moreover, multipath propagation dominates when the distance between the sender and receiver increased, leading to the grazing angle (φ) decreased, thus increasing the coefficient of reflection. The amplitude of the successive paths will not decrease rapidly. As a result, the difference in time between the various paths is minimal. This means that successive paths will converge over time lead to the phenomenon of inter symbol interference (ISI), which contributes to an increment in the bit error rate of the received data.

Massively parallel structural acoustics for forward and inverse problems

Three-dimensional structural acoustic simulations on highly complex structural models that are immersed in infinite and semi-infinite acoustic domains typically lead to large numbers of degrees of freedom that cannot be solved with commercial software packages. Typical applications include underwater acoustic simulation of submerged structures, and reverberation testing of aerospace structures. Many of these applications of interest involve large acoustic domains and complex 3D structures, thus making a finite element solution an attractive option. In addition, unknown parameters in the models can be mitigated with the solution of inverse problems. In this talk, we will discuss recent research efforts in Sierra-SD in the area of structural acoustics and will also present a partial differential equation (PDE) constrained optimization approach for solving inverse problems in structural acoustics that uses Sierra-SD for solving the forward and adjoint problems. Inverse problems are commonly encountered in structural acoustics, where accelerometer and/or microphone pressures are measured experimentally, and it is desired to characterize the acoustic sources, material parameters, and/or boundary conditions that produced the measurements. With a PDE-constrained optimization approach, the scalability of Sierra-SD can be leveraged for solving inverse problems. We will present results on the application of Sierra-SD on several large-scale structural acoustic applications examples of interest.

Numerical modeling of underwater sound propagation in the presence of triangle obstacles at low frequency

Low frequency sound propagation from industrial activities in underwater is considered immensely important by many scientists. For reducing the destructive effects of low frequency sound at long range, different obstacles can be placed in the direction of sound propagation. However, experimental analysis of this phenomenon is very complex. This is mainly due to the fact that oceans have non-homogeneous environments, while the presence of various sediments, animals, and geological phenomena add to the complexity. Accordingly, numerical models are considered good alternatives for underwater acoustic simulation. In the current study, parabolic equation method is applied for numerically analyzing sound propagation with low frequencies in the presence of triangle obstacles in different situations and arrangements. To accomplish this task, the implicit finite difference approach is adopted to solve the governing parabolic equation and a computer program is developed in Python language. Furthermore, Greene source and Claerbout estimations are applied to simulate wide angle sound propagation. The effects of various physical parameters such as sound speed profiles, source depth, and frequencies are investigated. Results of the analyses performed on the effects of object geometry indicate that triangle obstacle is more effective than the square obstacle for increasing the transmission loss (TL). Investigation of the effects of two sound speeds of Munk (Etter, Underwater acoustic modeling and simulation, Taylor & Francis, New York 2003) and linear profiles on transmission loss shows that Munk (Etter, Underwater acoustic modeling and simulation, Taylor & Francis, New York 2003) profile causes a spatial shift in TL compared to that of linear profile. On the other hand, the conducted study on three arrangements of single, triple and quintuple triangles at different distances, and frequencies indicate that values of TL in the case of triple triangle arrangement are lower than those by the other two triangle arrangements at different frequencies. Therefore, this arrangement is found to be inappropriate for mitigation of sound travel range. The results of parametric studies on the effects of source depth on TL demonstrate that peak of the TL graph for the receiver depth in vicinity of the free surface, in view of the deeper source, is much larger than those of the shallow source depth.

Task Allocation and Path Planning for Collaborative Autonomous Underwater Vehicles Operating through an Underwater Acoustic Network

Dynamic and unstructured multiple cooperative autonomous underwater vehicle (AUV) missions are highly complex operations, and task allocation and path planning are made significantly more challenging under realistic underwater acoustic communication constraints. This paper presents a solution for the task allocation and path planning for multiple AUVs under marginal acoustic communication conditions: a location-aided task allocation framework (LAAF) algorithm for multitarget task assignment and the grid-based multiobjective optimal programming (GMOOP) mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Both the LAAF and GMOOP algorithms are well suited in poor acoustic network condition and dynamic environment. Our research is based on an existing mobile ad hoc network underwater acoustic simulator and blind flooding routing protocol. Simulation results demonstrate that the location-aided auction strategy performs significantly better than the well-accepted auction algorithm developed by Bertsekas in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path-planning technique provides an efficient method for executing multiobjective tasks by cooperative agents with limited communication capabilities. This is in contrast to existing multiobjective action selection methods that are limited to networks where constant, reliable communication is assumed to be available.

Accuracy enhancement of underwater target detection with time-frequency analysis techniques

Underwater target detection is mainly based on acoustic emissions generated by the target of interest (TOI) as it propels itself through the ocean, and operates non-propulsion-related onboard systems. The spectral signature of these acoustic emissions is used for identification and localization of TOI. This paper focuses on underwater target detection using passive sonobuoys. Discrete Fourier transform (DFT) is used in most sonobuoy processing systems to provide spectral analysis of the received signals. Due to the relatively high noise level and the several sources of interference that may exist underwater, the DFT may not determine the spectral signature of TOI with adequate accuracy. The low signal-to-noise ratio (SNR) and the presence of strong interference sources with frequencies close to the TOI frequency jeopardize the detection accuracy, the bearing estimation performance, and target tracking capabilities. The aim of this paper is to: (1) examine the performance of both wavelet packet analysis and high resolution spectral estimation techniques, and (2) provide a comparative study between both methods. Based on underwater acoustic simulation developed in this research, results showed that the proposed methods can achieve robust target detection with low levels of SNR and interferences of nearby signatures that cannot be detected by DFT.