IEEE Journal of Oceanic Engineering最新文献

{"title":"Recognizing the State of Motion by Ship-Radiated Noise Using Time-Frequency Swin-Transformer","authors":"Fan Wu;Haiyang Yao;Haiyan Wang","doi":"10.1109/JOE.2024.3369663","DOIUrl":"10.1109/JOE.2024.3369663","url":null,"abstract":"Ship-radiated noise recognition is an essential but complex task in the construction of marine information systems and marine scientific research. Ambient noise, unstable frequency shifts, and irregular multipath interference make it complicated to recognize ship-radiated noise accurately. Existing recognition methods exhibit constrained proficiency in the identification of the motion states of ships, thus leading to disappointing application performance. To effectively recognize the ship movement with less computation, this work proposes the time-frequency Swin-Transformer (TFST) network. A hierarchical self-attention module is presented to extract multilayer time-frequency features so that the TFST network could learn moving targets' features in TF representations of the noise radiated by moving targets. A scale-difference simplified architecture is designed to reduce network complexity. Experiments reveal that the TFST network outperforms the state-of-the-art convolutional neural networks (CNNs) and Transformers on two underwater acoustic data sets. Moreover, the TFST network achieves at least 1.3 times improvement compared to five state-of-the-art methods on both average accuracy (OA) and kappa coefficient in three motion status recognition experiments.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"667-678"},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Occlusion Modeling for Coherent Echo Data Simulation: A Comparison Between Ray-Tracing and Convex-Hull Occlusion Methods","authors":"Benjamin Thomas;Ciaran Sanford;Alan J. Hunter","doi":"10.1109/JOE.2024.3369861","DOIUrl":"10.1109/JOE.2024.3369861","url":null,"abstract":"The ability to simulate realistic coherent data sets for synthetic aperture imaging systems is crucial for the design, development, and evaluation of sensors and their signal processing pipelines, machine learning algorithms, and autonomy systems. In the case of synthetic aperture sonar (SAS), collecting experimental data is expensive, and it is rarely possible to obtain ground truth of the sensor's path, the speed of sound in the medium, and the geometry of the imaged scene. Simulating sonar echo data allows signal processing algorithms to be tested with known ground truth, enabling rapid and inexpensive development and evaluation of signal processing algorithms. The de facto standard for simulating conventional high-frequency (i.e., \u0000<inline-formula><tex-math>$&gt; {text{100}}$</tex-math></inline-formula>\u0000 kHz) SAS echo data from an arbitrary sensor, path, and scene is to use a point- or facet-based diffraction model. A crucial part of this process is acoustic occlusion modeling. This article describes a SAS simulation pipeline and compares implementations of two occlusion methods: 1) a ray-tracing method and 2) a newer approximate method based on finding the convex hull of a transformed point cloud. The full capability of the simulation pipeline is demonstrated using an example scene based on a high-resolution 3-D model of the SS Thistlegorm shipwreck, which was obtained using photogrammetry. The 3-D model spans a volume of \u0000<inline-formula><tex-math>$text{220}times text{130}times text{25},text{ m}$</tex-math></inline-formula>\u0000 and is comprised of over 30 million facets that are decomposed into a cloud of almost 1 billion points. The convex-hull occlusion model was found to result in simulated SAS imagery that is qualitatively indistinguishable from the ray-tracing approach and quantitatively very similar, demonstrating that the use of this alternative method has potential to improve speed while retaining high fidelity of simulation. The convex-hull approach was found to be up to four times faster in a fair speed comparison with serial and parallel central processing unit (CPU) implementations for both the methods, with the largest performance increase for wide-beam systems. The fastest occlusion modeling algorithm was found to be graphics processing unit (GPU)-accelerated ray tracing over the majority of scene scales tested, which was found to be up to two times faster than the parallel CPU convex-hull implementation. Although GPU implementations of convex-hull algorithms are not currently readily available, the future development of GPU-accelerated convex-hull finding could make the new approach much more viable. However, in the meantime, ray tracing is still preferable, since it has higher accuracy and can leverage the existing implementations for high-performance computing architectures for better performance.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"944-962"},"PeriodicalIF":3.8,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiscale Correlation Network and Geodesic Distance for Remote Passive Ship Detection in Marine Environment","authors":"Hongwei Zhang;Haiyan Wang;Yongsheng Yan;Xiaohong Shen;Qinzheng Zhang","doi":"10.1109/JOE.2024.3383924","DOIUrl":"10.1109/JOE.2024.3383924","url":null,"abstract":"The remote passive detection of vessels in the oceans is a significant activity for improving port security and the security of coastal and offshore operations. There still needs to be an efficient approach to achieve weak ship signal detection with nonparametric and noninformation priors. This study proposes a new multiscale correlation network construction method to effectively distinguish the ship from the ambient noise, which should be promising. Meanwhile, to effectively characterize the constructed network, we render definite the topological network matrix positive definite, then introduce the matrix into the Riemann space to measure the distance between the topology matrix of the noise and the signal by using the geodesic distance. Those methods are demonstrated by simulation and applied to actual recorded data. Compared with the existing network construction and characterization methods, the results show that multiscale correlation network and geodesic distance (GD) methods can distinguish nonlinear time series from noise more effectively.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"992-1008"},"PeriodicalIF":3.8,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141198307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Motion Mechanism of a Novel Underwater Exploration Robot for Stratum Drilling","authors":"Peihao Zhang;Jiawang Chen;Haisheng Xia;Zhijun Li;Xingshuang Lin;Peng Zhou","doi":"10.1109/JOE.2024.3383883","DOIUrl":"10.1109/JOE.2024.3383883","url":null,"abstract":"As the exploitation of natural gas hydrates intensifies, there is a growing imperative to enhance the monitoring of extraction and storage areas. However, existing monitoring methods, such as seismic detection and seabed drilling technology, exhibit inherent limitations. These shortcomings primarily stem from challenges associated with conducting prolonged, in situ monitoring and the constrained scope of exploration. Addressing these shortcomings necessitates the development of innovative exploration methods or devices. This article introduces Stratloong, a novel underwater exploration robot designed specifically for drilling in seabed stratum. Comprising a drill bit, front and rear support units, and a propulsion unit, Stratloong emulates the peristaltic motion of an earthworm to achieve efficient drilling. In this research, kinematic and dynamic models of the robot are formulated, and a task-based control method based on inverse kinematic control is presented. In addition, a generic motion control framework is proposed to realize the drilling motion. Straight drilling tests are conducted in prepared seabed clay under different static settlement times to assess Stratloong's performance. Data collected include rotational speed, displacement, and axial force during motion. The robot maintained over 90% motion efficiency in the prepared seabed clay. Furthermore, outdoor tests confirmed the robot's ability to drill into soil without external thrust. The robot advanced 2230 mm with 89% motion efficiency. The comprehensive evaluation of Stratloong's drilling capabilities, conducted through a series of laboratory and field tests, yields valuable data and experiences for its potential application in seabed strata exploration.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"763-774"},"PeriodicalIF":3.8,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Dual-Comb Underwater Ranging via an Improved VMD Algorithm","authors":"Haonan Shi;Haihan Zhao;Zhiwei Zhu;Chao Wang;Haofeng Hu;Jingsheng Zhai;Xiaobo Li","doi":"10.1109/JOE.2024.3384563","DOIUrl":"10.1109/JOE.2024.3384563","url":null,"abstract":"Advanced sensors and signal processing algorithms are significant for the use of remotely-operated vehicles and autonomous underwater vehicles. The distance/length measurement is the basis of many sensing functions, including positioning, tracking, surface reconstruction, and pose determination. Optical-based ranging sensors have been proven as a promising tool and obtain up to micrometer-level accuracy when combined with dual-comb interference. Applying this approach to underwater scenarios is feasible, but one must handle the issue that the ranging signal is significantly affected by environmental disturbances and system noises. However, it has been rarely reported that processing algorithms are tailored to the dual-comb signal to improve the quality of measuring signals. This article presents an enhanced underwater dual-comb ranging (DCR) solution via an improved variational mode decomposition (VMD). Specifically, we design a fitness function considering desired dual-comb interferogram characteristics. Accordingly, we optimize vital parameters and decompose the interested ranging signal to ensure final interferogram quality. Experiments verify that our method is superior to others and can improve the signal-to-noise ratio and restore the Gaussian-like shape of interferograms simultaneously. To the best of the authors knowledge, it is the first time DCR is boosted via VMD, and answers the question about interferogram shaping. The proposed solution may find important applications in ranging and imaging tasks underwater, as well as extend their working range and robustness against non-ideal environments.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"841-855"},"PeriodicalIF":3.8,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Power Spectrum Estimation Under Strong Interferences Using Beam-Space Fast Nonnegative Sparse Bayesian Learning","authors":"Jichen Chu;Lei Cheng;Wen Xu","doi":"10.1109/JOE.2024.3365799","DOIUrl":"10.1109/JOE.2024.3365799","url":null,"abstract":"In acoustic array signal processing, spatial power spectrum estimation and the associated direction-of-arrival (DOA) estimation are often inflicted by strong interferences, which lead to significant performance degradation and even mask the weak targets. Although tremendous efforts have been put into related research, simultaneously realizing robust interference suppression and DOA estimation against various model mismatches is still challenging. To address this challenge, this article proposes a systematic scheme that cohesively integrates a robust beamforming step and a beam-space sparse learning step, to effectively recover the spatial power spectrum in the presence of strong interference. Considering the sparsity and nonnegativity of the spatial power spectrum, we propose a nonnegative fast sparse Bayesian learning algorithm to reconstruct the spatial power spectrum of target sources from the beam-space data. In addition to the outstanding interference suppression capabilities, our method exhibits better denoising performance (i.e., lower noise level) and DOA estimation accuracy, even under challenging scenarios, such as snapshot deficiency and low signal-to-noise ratios. Simulated and real-life experimental data results verify the robustness and superior performance of the proposed scheme over other competitors.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"692-712"},"PeriodicalIF":3.8,"publicationDate":"2024-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140297672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Side-Scan Sonar Underwater Target Detection: Combining the Diffusion Model With an Improved YOLOv7 Model","authors":"Xin Wen;Feihu Zhang;Chensheng Cheng;Xujia Hou;Guang Pan","doi":"10.1109/JOE.2024.3379481","DOIUrl":"10.1109/JOE.2024.3379481","url":null,"abstract":"Side-scan sonar (SSS) plays a crucial role in underwater exploration. Autonomous analysis of SSS images is vital for detecting unknown targets in underwater environments. However, due to the complexity of the underwater environment, few highlighted areas of the target, blurred feature details, and the difficulty of collecting data from SSS, achieving high-precision autonomous target recognition in SSS images is challenging. This article solves this problem by improving the You Only Look Once v7 (YOLOv7) model to achieve high-precision object detection in SSS images. First, we enhance and enlarge real and experimental images using the denoising–diffusion model to establish a self-made SSS image data set, as there are data pictures of the detection target in the SSS images obtained from real experiments. Since the SSS image has large areas without targets, this article introduces a vision transformer (ViT) for dynamic attention and global modeling, which improves the model's weight in the target region. Second, the convolutional block attention module is adopted to further improve the feature expression ability and reduce floating-point operations. Finally, this article uses Scylla-Intersection over Union as the loss function to increase the accuracy of the model's inference. Experiments on the SSS image data set demonstrate that the improved YOLOv7 model outperforms other technologies, with an average accuracy (mAP0.5) and (mAP0.5:0.95) of 78.00% and 48.11%, respectively. These results are 3.47% and 2.9% higher than the YOLOv7 model. The improved YOLOv7 algorithm proposed in this article has great potential for object detection and recognition of SSS images.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"976-991"},"PeriodicalIF":3.8,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141146908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Chinese Remainder Theorem–Based Synthetic Aperture Sonar Motion Estimation","authors":"Cheng Chi;Shiping Chen;Rongxing Zhong;Pengfei Zhang;Peng Wang;Yu Li;Jiyuan Liu;Haining Huang","doi":"10.1109/JOE.2023.3328084","DOIUrl":"10.1109/JOE.2023.3328084","url":null,"abstract":"Motion estimation is required to obtain high imaging quality in synthetic aperture sonars (SASs). Displaced phase center antenna (DPCA) micronavigation is an important technique of motion estimation in SASs. A key step in DPCA micronavigation is accurately determining the time delay between echoes received by the approximate “phase center” array between adjacent pings. Unfortunately, the accuracy of the existing method for estimating this time delay is often deteriorated by the ambiguity of the time delay estimates in the presence of noise or interference. This article proposes an accurate method of estimating the time delay based on the Robust Chinese Remainder Theorem (RCRT). The experimental results show that the proposed method decreases the ambiguous rate of time delay estimates by one order of magnitude, compared to the conventional approach, which means the estimation accuracy is improved significantly. The SAS imaging results demonstrate that the RCRT-based motion estimation helps to obtain higher-quality images.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"933-943"},"PeriodicalIF":3.8,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental and Numerical Investigation on the Performance of a Moored Pitching Wave Energy Conversion System","authors":"Bruno Paduano;Fabio Carapellese;Edoardo Pasta;Mauro Bonfanti;Sergej Antonello Sirigu;Dario Basile;Domenica Pizzirusso;Nicoláas Faedo;Giuliana Mattiazzo","doi":"10.1109/JOE.2024.3353372","DOIUrl":"10.1109/JOE.2024.3353372","url":null,"abstract":"This study delves into the question of whether the mooring system influences the dynamics of the device by conducting a comprehensive analysis of the inertial sea wave energy converter (ISWEC). Recognizing that wave energy converters exhibit complex behaviors that often push numerical models beyond their range of validity, this study highlights the importance of developing a representative model that accurately captures the intricate dynamics involved. To address this challenge, an experimental investigation of the ISWEC is conducted, aiming to establish a benchmark model that serves as a reference for validating and refining numerical models. Following the experimental investigation, this study proceeds with a numerical investigation to further explore the influence of the mooring system on the pitching device. The response of the device is analyzed both with and without the mooring system, allowing for a direct comparison of its effects on device dynamics and the associated harvested energy. By conducting numerical simulations under various operating conditions, this study provides an insight into the definition of representative mathematical modeling, analyzing and motivating the strong influence of the mooring system on the performances of a moored pitching wave energy conversion system.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"802-820"},"PeriodicalIF":3.8,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10473602","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local Polynomial Interpolation Method Optimization in the Process of Digital Terrain Model Creation Based on Data Collected From a Multibeam Echosounder","authors":"Wojciech Maleika","doi":"10.1109/JOE.2024.3353271","DOIUrl":"10.1109/JOE.2024.3353271","url":null,"abstract":"This article describes a local polynomial interpolation (LPI) optimization used to create digital terrain models (DTM) of the seabed based on data collected via a multibeam echosounder (MBES) during a sea survey. In the studies presented in this article, the optimal parameters of this interpolation are sought in terms of the accuracy of the created models and the calculation time. The parameters to be optimized are: the size of the area from which we select the points for interpolation (radius size), the number of points involved in the local interpolation (no), and the polynomial degree used in the interpolation (poly degree). Based on the obtained results, it was shown that the optimal values of these parameters can be selected for this type of input data, and their value depends mainly on grid resolution and the density of measurement points collected during the sea survey. Based on research using various test surfaces, it has been shown that the use of properly selected interpolation parameters enables the creation of models with slightly higher accuracy. During the research, attention was also paid to the speed of calculations, which is an important aspect of the process of creating bathymetric models. It was assumed that the new method should not significantly increase the calculation time. Finally, the author proposed using a new point selection technique (named the growing radius) during LPI, which made it possible to further increase the accuracy of the created models and the speed of calculations. The results obtained are compared with other commonly used interpolation methods using the same test data, showing the good and the bad features of the optimized LPI method. The final results of the research and the conclusions presented in this article indicate that the use of the optimized LPI together with the new technique of selecting points (the growing radius) can be a better alternative to other interpolation methods used in the process of creating bathymetric models based on data from MBES.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"920-932"},"PeriodicalIF":3.8,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140170342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}