IEEE Journal of Oceanic Engineering最新文献_第3页

Image Compression Using Novel View Synthesis Priors 使用新的视图合成先验的图像压缩

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-03-05 DOI: 10.1109/JOE.2026.3674685

Luyuan Peng;Mandar Chitre;Hari Vishnu;Yuen Min Too;Bharath Kalyan;Rajat Mishra;Soo Pieng Tan

{"title":"Image Compression Using Novel View Synthesis Priors","authors":"Luyuan Peng;Mandar Chitre;Hari Vishnu;Yuen Min Too;Bharath Kalyan;Rajat Mishra;Soo Pieng Tan","doi":"10.1109/JOE.2026.3674685","DOIUrl":"https://doi.org/10.1109/JOE.2026.3674685","url":null,"abstract":"Real-time visual feedback is essential for tetherless control of remotely operated vehicles, particularly during inspection and manipulation tasks. Though acoustic communication is the preferred choice for medium-range communication underwater, its limited bandwidth renders it impractical to transmit images or videos in realtime. To address this, we propose a model-based image compression technique that leverages prior mission information. Our approach employs trained machine-learning based novel view synthesis models to store and render views of scenes that serve as priors, and minimizes the differences between camera images and model-rendered images to improve compressibility. We evaluate our method using data sets collected in an artificial ocean basin and demonstrate significant improvements in compression ratio and image quality compared to existing methods. Moreover, our approach exhibits robustness to the introduction of novel objects within the basin scene and maintains performance under real-world degradations, such as backscatter, as demonstrated on an online coral reef data set. These results highlight the promise of our proposed technique for enabling real-time, high-quality visual feedback over bandwidth-constrained underwater acoustic links.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"1689-1704"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148452055","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}

引用次数: 0

Physics-Aware Modal Intensity Modeling for Dynamically Stable Ocean Front Prediction 动态稳定海锋预测的物理感知模态强度建模

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-06-26 DOI: 10.1109/JOE.2026.3698731

Yishuo Wang;Muping Zhou;Feng Zhou;Zhijun Hu;Yi Wang;Qicheng Meng;Hailong Guo

{"title":"Physics-Aware Modal Intensity Modeling for Dynamically Stable Ocean Front Prediction","authors":"Yishuo Wang;Muping Zhou;Feng Zhou;Zhijun Hu;Yi Wang;Qicheng Meng;Hailong Guo","doi":"10.1109/JOE.2026.3698731","DOIUrl":"https://doi.org/10.1109/JOE.2026.3698731","url":null,"abstract":"Ocean fronts play a critical role in marine dynamics, biogeochemical processes, and operational ocean engineering. While most previous studies focus on predicting oceanographic scalar variables, such as sea surface temperature or chlorophyll, physically consistent and dynamically stable ocean front prediction remains relatively underexplored. In this study, we propose a physics-aware modal intensity modeling framework for ocean front prediction, which integrates convolutional spatial encoding, Transformer-based temporal modeling, and selectively applied physics-informed constraints. Unlike conventional approaches that treat fronts as binary structures or pixel-wise regression targets, the proposed method models the temporal evolution of modal intensities. Spatial structures are preserved by modulating the feature map of the last input frame with learned modal intensities, enabling improved structural persistence and dynamical stability. To further enhance training robustness, an adaptive loss balancing strategy is introduced to coordinate classification, regression, and physics-informed objectives. In addition, uncertainty quantification based on Monte Carlo Dropout and a computational efficiency analysis are incorporated to assess the reliability and practicality of the framework. Experiments conducted on the South China Sea, the Kuroshio Extension, and the Gulf Stream region demonstrate that the proposed method achieves superior structural coherence, improved physical consistency, and strong generalization capability compared with representative baselines. The proposed method follows a structure-preserving and intensity-evolving paradigm, decoupling spatial representation from temporal dynamics under physics-aware constraints.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"2159-2176"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148452094","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}

引用次数: 0

Estimation of the Maximum Plane Positioning Error of Deep Submersibles Based on Underwater Virtual Reference Points 基于水下虚拟参考点的深潜器最大平面定位误差估计

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-06-08 DOI: 10.1109/JOE.2026.3693857

Wenlong Gao;Yongfu Sun;Yibin Li;Muzi Zhang;Yue Zhang;Yixu Liu;Yinghao Zhuang;Yan Song

{"title":"Estimation of the Maximum Plane Positioning Error of Deep Submersibles Based on Underwater Virtual Reference Points","authors":"Wenlong Gao;Yongfu Sun;Yibin Li;Muzi Zhang;Yue Zhang;Yixu Liu;Yinghao Zhuang;Yan Song","doi":"10.1109/JOE.2026.3693857","DOIUrl":"https://doi.org/10.1109/JOE.2026.3693857","url":null,"abstract":"Integrated navigation is widely used for the navigation and positioning of submersibles. However, in deep-sea environments, the inability to obtain Global Navigation Satellite System signals and the lack of precise underwater reference points on the seabed make it challenging to quickly and cost-effectively estimate the maximum plane positioning error (MPPE) of the ultra short baseline (USBL)-assisted integrated navigation system at a 95<inline-formula><tex-math>$%$</tex-math></inline-formula> confidence level. This article proposes a method for estimating the MPPE of integrated navigation coordinates based on underwater virtual reference points. This method introduces underwater virtual reference points and derives analytical expressions for error bounds using vector representation and the Cauchy–Schwarz inequality, then calculates the MPPE for integrated navigation coordinates at a 95<inline-formula><tex-math>$%$</tex-math></inline-formula> confidence level by sorting the upper and lower bounds of horizontal error in ascending order. Experimental results indicate that for submersibles operating at an average slant range of 4201 m, the MPPE for strapdown inertial navigation system/USBL integrated navigation coordinates is 11.74 m, representing 0.76<inline-formula><tex-math>$%$</tex-math></inline-formula> of the submersible's range. The use of long baseline positioning values as ground truth validates the accuracy of these estimation results. The proposed method for estimating the MPPE of integrated navigation coordinates requires only speed, heading, attitude, and USBL positioning data, thereby eliminating the need for specialized positioning error estimation experiments. This offers a more convenient, rapid, and cost-effective solution. Estimating the MPPE provides significant reference for determining the submersible's positioning errors during marine environmental data collection and establishing the coordinate range of important underwater targets.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"2545-2554"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148452084","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}

引用次数: 0

A Bernoulli Particle Filter for Target Tracking in a Radar Detection-Occluded Environment 一种用于雷达探测遮挡环境下目标跟踪的伯努利粒子滤波器

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-03-05 DOI: 10.1109/JOE.2026.3674016

Shuai Sun;Guchong Li;Hongguang Lyu

{"title":"A Bernoulli Particle Filter for Target Tracking in a Radar Detection-Occluded Environment","authors":"Shuai Sun;Guchong Li;Hongguang Lyu","doi":"10.1109/JOE.2026.3674016","DOIUrl":"https://doi.org/10.1109/JOE.2026.3674016","url":null,"abstract":"In maritime environments, target detection using radar signals often suffers from occlusion by islands or other vessels, particularly in where the radar platform is a small autonomous surface vehicle (ASV) with a civil marine radar with a low-height viewing angle. Low antenna height on a ASV platform can significantly reduce the spatial coverage of the radar beam as a result of signal occlusion. Once a high value target is occluded, continuous tracking of it may be interrupted because of the lack of radar measurements. In the literature, target occlusion is often ignored or only partly addressed for a specific target tracking scenario. This article proposes to use Bernoulli random finite sets to model the appearance and disappearance of a target in a radar detection occluded environment, and a particle-based implementation to produce an algorithm with environmental occlusion awareness. More specifically, we first segment the environment using uniform grid cells and then check the line-of-sight condition between each particle and the radar platform for occlusion. This method is tested using both simulated and real radar data. The results demonstrate that our proposed solution outperforms existing trackers that ignore target occlusion.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"2109-2121"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451838","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}

引用次数: 0

Application of a Delay Multiply and Sum Reconstruction Algorithm to a Synthetic Aperture Imaging Sonar 延时乘和重构算法在合成孔径成像声纳中的应用

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-07-02 DOI: 10.1109/JOE.2026.3697320

Thomas E. Blanford;Daniel C. Brown;Shawn F. Johnson

引用次数: 0

Ensemble of Vision Transformers for Sea State Classification 海况分类视觉变压器集成

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-03-06 DOI: 10.1109/JOE.2026.3674388

Marina Ivasic-Kos;Domagoj Palinic;Miran Pobar

{"title":"Ensemble of Vision Transformers for Sea State Classification","authors":"Marina Ivasic-Kos;Domagoj Palinic;Miran Pobar","doi":"10.1109/JOE.2026.3674388","DOIUrl":"https://doi.org/10.1109/JOE.2026.3674388","url":null,"abstract":"This study presents an innovative method for real-time sea state classification that utilizes an ensemble-based computer vision framework. Multiple pretrained submodels, each individually fine-tuned on specialized data sets, are integrated to recognize eight classes on the Beaufort scale. A comprehensive multimodal data set was assembled, combining visual information with wind speed data from anemometers and further optimized through preprocessing steps. Standalone models based on cutting-edge architectures, such as the data efficient vision transformer and EfficientNet deep convolutional network, were adapted specifically for sea state recognition. Initial results yielded F1 scores of 66% and 65%, respectively, for these models. To boost overall accuracy, a weighted majority voting and precision-driven ensemble strategy was adopted. The unimodal ensemble achieved 73% F1 score, while the multimodal ensemble, leveraging both image and wind data, reached an F1 score of 97%. For a reduced six-class scenario, where noncritical classes were grouped, the unimodal ensemble reached an impressive F1 score of 94%. These outcomes illustrate the potential of this ensemble approach to significantly advance maritime safety and operational efficiency in sea state monitoring.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"2122-2136"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11510753","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451852","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}

引用次数: 0

Active Platform Stabilization of Floating Offshore Wind Turbines Under Harsh Marine Environments 恶劣海洋环境下浮式海上风力发电机主动平台稳定研究

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-06-18 DOI: 10.1109/JOE.2026.3695322

Shuzhen Li;Keum-Shik Hong;Xian Li

{"title":"Active Platform Stabilization of Floating Offshore Wind Turbines Under Harsh Marine Environments","authors":"Shuzhen Li;Keum-Shik Hong;Xian Li","doi":"10.1109/JOE.2026.3695322","DOIUrl":"https://doi.org/10.1109/JOE.2026.3695322","url":null,"abstract":"This article investigates posture control strategies for floating offshore wind turbines operating in harsh marine environments. A novel thruster-assisted triangular platform is modeled using a four-degree-of-freedom representation that captures heave, roll, pitch, and tower deflection dynamics. To facilitate controller synthesis, a reduced three-degree-of-freedom model is derived and employed to design a sliding-mode controller that integrates equivalent control with a supertwisting algorithm. The proposed scheme enhances robustness and stability under significant wind and wave disturbances. Numerical simulations conducted under calm, moderate, and severe sea states demonstrate that the proposed sliding-mode controller substantially outperforms a conventional proportional–integral controller, yielding marked reductions in platform oscillations and improved transient behavior. The enhanced vibration attenuation and faster stabilization indicate that the proposed integrated approach can effectively improve energy capture efficiency and extend the operational lifespan of floating offshore wind turbines, supporting its suitability for deep-sea deployment.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"2077-2090"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451826","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}

引用次数: 0

Feedback Stabilization and Trajectory Tracking of a Drifting Vortex Near a Robotic Fish Using Shape Control 基于形状控制的机器鱼附近漂移涡反馈稳定与轨迹跟踪

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-06-24 DOI: 10.1109/JOE.2026.3690341

Rose Gebhardt;Derek Paley

{"title":"Feedback Stabilization and Trajectory Tracking of a Drifting Vortex Near a Robotic Fish Using Shape Control","authors":"Rose Gebhardt;Derek Paley","doi":"10.1109/JOE.2026.3690341","DOIUrl":"https://doi.org/10.1109/JOE.2026.3690341","url":null,"abstract":"This article presents a feedback control design that adjusts the trajectory of a drifting vortex in a freestream near a deformable Joukowski foil using camber shape control. We derive the dynamics of a point vortex in flow around a Joukowski foil using a potential flow model and provide numerical analysis of the number, stability, and controllability of open-loop equilibrium points of the vortex-foil system. We show that the position of a point vortex can effectively be regulated using a full-state feedback camber control law based on a linear–quadratic regulator design while maintaining the validity of the dynamics model. We then provide a vortex trajectory tracking method that adjusts sinusoidal camber changes using full-state feedback applied to the phase offset of the sinusoid, implemented through an optimization loop and backstepping. We present an illustrative example of effective trajectory tracking achieved through closed-loop control, along with a visualization of the region of convergence for several different system parameters and initial conditions. The results demonstrate the ability to track a desired feasible trajectory with minimal persistent error across a wide range of system configurations.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"1734-1746"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451827","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}

引用次数: 0

Energy-Optimal Trajectory Planning for Autonomous Underwater Vehicles Using Pontryagin’s Maximum Principle 基于Pontryagin最大值原理的自主水下航行器能量最优轨迹规划

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-06-09 DOI: 10.1109/JOE.2026.3692006

Raymond Young;F. Hunter Akins;Sophia T. Merrifield

{"title":"Energy-Optimal Trajectory Planning for Autonomous Underwater Vehicles Using Pontryagin’s Maximum Principle","authors":"Raymond Young;F. Hunter Akins;Sophia T. Merrifield","doi":"10.1109/JOE.2026.3692006","DOIUrl":"https://doi.org/10.1109/JOE.2026.3692006","url":null,"abstract":"Pontryagin’s Maximum Principle, a classical tool from optimal control theory, is used to compute energy-optimal trajectories for an autonomous underwater vehicle (AUV) navigating in deterministic, complex flows. This approach reformulates the optimal control problem as a two-point boundary value problem (TPBVP) for ordinary differential equations (ODEs) and offers computational benefits compared to alternative solutions which require the solution of partial differential equations (PDEs). This study introduces a numerical framework using pure shooting to solve the associated TPBVP and demonstrates its efficacy for trajectory optimization through analytic flows and current fields from high-resolution ocean simulations. The method is tested on two case studies: first, a multiday transit through the Southern California Bight, where ocean currents are dominated by mesoscale eddies and tidal variability, and energy-optimal planning predicts over 20% of savings relative to a straight-line transit, and second, a multihour transit off the coast of Ram Head, St. John, U.S. Virgin Islands, where the flow is dominated by energetic tidal vortices and energy consumption varies by up to 50% within a 6 h launch window. In both cases, the tradeoff between time and energy is analyzed for a wide range of AUVs that are parameterized by their nominal speed through water, between 0.25 and 2.0 m/s.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"1747-1766"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11556408","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451828","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}

引用次数: 0

Dual-Critic Proximal Policy Optimization for Trajectory Tracking of Autonomous Underwater Vehicle Under Time-Varying Dynamics 时变动态下自主水下航行器轨迹跟踪的双临界近端策略优化

IF 5.6 2区工程技术

IEEE Journal of Oceanic Engineering Pub Date : 2026-07-01 Epub Date: 2026-06-18 DOI: 10.1109/JOE.2026.3692007

Ye Yuan;Chaoyang Chen;Dan Yang;Weidong Zhang;Yaonan Wang

{"title":"Dual-Critic Proximal Policy Optimization for Trajectory Tracking of Autonomous Underwater Vehicle Under Time-Varying Dynamics","authors":"Ye Yuan;Chaoyang Chen;Dan Yang;Weidong Zhang;Yaonan Wang","doi":"10.1109/JOE.2026.3692007","DOIUrl":"https://doi.org/10.1109/JOE.2026.3692007","url":null,"abstract":"The autonomous underwater vehicle (AUV) serves as an ideal platform for replacing human operators in high-risk underwater operations, where high-precision trajectory tracking control is crucial for ensuring mission effectiveness. However, the time-varying dynamics caused by the complexity of the underwater environment present significant challenges to achieving high-precision trajectory tracking for AUVs. To address this challenge, a model-assisted deep reinforcement learning-based trajectory tracking method for an AUV with time-varying dynamics is presented in this article. Specifically, a novel state space is proposed, which replaces the absolute position of the agent with the relative position. This representation provides a more comprehensive description of the relationship between the AUV and the reference trajectory. The policy trained based on this state space can be easily transferred and applied to a different type of reference trajectory. Furthermore, by decomposing the reward function into three components, the sparse reward issue is effectively mitigated. The smoothness term within the reward function effectively suppresses abrupt changes in control commands, ensuring that the AUV maintains smooth navigation even under time-varying dynamics. Finally, an improved proximal policy optimization algorithm is proposed. The algorithm includes two critics that separately evaluate the value functions of actions under time-varying and static dynamics, and adaptively adjust their weights based on the intensity of the time-varying dynamics, effectively enhancing the policy’s disturbance rejection capability and robustness. Experimental results demonstrate that the proposed method maintains high-precision trajectory tracking across various time-varying dynamics, significantly outperforming other algorithms and validating its effectiveness.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"51 3","pages":"1899-1912"},"PeriodicalIF":5.6,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451880","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}

引用次数: 0