水下无人系统学报

Oblique Ice-breaking Load and Motion Characteristics Analysis of Water-exiting Vehicles

YE Yonghao, HE Baiyan, PEI Jinliang, ZHANG Yigan, QU Zehui, LIU Huaping, ZHANG Junhui, QI Runchao

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0002

[Abstract](6) [FullText HTML] (3) [PDF 3892KB](2)

Abstract:
Underwater vehicles possessing water-exit ice-breaking capabilities hold significant application value for polar scientific research and resource exploration. However, existing research primarily focuses on vertical ice-breaking, with a notable lack of investigation into the impact of the oblique angle on ice-breaking performance. Therefore, a numerical model for the oblique water-exit and ice-breaking process of a vehicle is established based on the Arbitrary Lagrangian-Eulerian (ALE) fluid-structure interaction algorithm. The effects of the oblique angle, initial velocity, and ice thickness on the load and motion characteristics of the vehicle are systematically analyzed. The results indicate that during the initial stage of ice-breaking, the impact of the vehicle's conical head induces intense local stress concentration in the ice sheet. This leads to the early initiation of radial cracks at the top surface, followed by failure originating from the center. The center of the resultant force on the vehicle deviates from its axis, causing an exacerbated deflection along the initial oblique direction, and a trend that becomes more pronounced as the initial velocity and ice thickness increases. For the θ=10° case, the vehicle’s attitude is governed by the ice-breaking kinetic energy: under conditions of low velocity and thick ice, the attitude exhibits a “deflection-recovery” pattern; conversely, under high velocity and thin ice conditions, it transitions to a “deflection-steady flight” pattern. The findings of this research provide a valuable theoretical reference for the design and development of polar cross-media vehicles in the future.

High-Fidelity Seafloor 3D Reconstruction Based on Cross-dimensional Gaussian Normal Transition Field

ZHAO Ximan, CHU Xuanhe, CHEN Han, LIU Siyuan

, Available online , doi: 10.11993/j.issn.2096-3920.2025-0167

[Abstract](4) [FullText HTML] (5) [PDF 10699KB](2)

Abstract:
The demand for high-fidelity scene reconstruction of the seafloor is growing in fields such as marine scientific surveying and underwater environmental exploration. As an advanced explicit scene representation method, 3D Gaussian Splatting shows significant application potential in scene reconstruction and novel view synthesis. However, influenced by factors such as blurring effects in underwater medium, the results often exhibit defects like medium artifacts and structural distortion, severely limiting their applicability in complex underwater environments. To address these challenges, we propose a high-fidelity seafloor scene reconstruction based on cross-dimensional Gaussian normal transition field. First, we establish a cross-dimensional and normal transition system for Gaussian primitives, enhancing its capability for detailed geometric modeling of complex structures. Second, we introduce a Gaussian opacity-weighted filtering model to suppress reconstruction artifacts caused by medium blurring effects. Finally, experimental results across multiple underwater scenes demonstrate our method's capability for efficient scene reconstruction and novel view synthesis in underwater environments.

A Physics-Based Method for Drifting Buoy Trajectory Backtracking with Uncertainty Quantification

LI Hui, WANG Shui, XIONG Xinquan, YUE Peng, MO Lihong, WAN Wanghua

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0014

[Abstract](20) [FullText HTML] (11) [PDF 1779KB](8)

Abstract:
High-precision trajectory backtracking technology for drifting buoys is urgently needed for maritime search and rescue (SAR) and pollution source tracing, yet traditional Lagrangian models exhibit significant errors in complex marine environments. This study proposes a physics-driven trajectory backtracking model for marine drifting buoys, which innovatively introduces a dynamic diffusion coefficient based on autocorrelation analysis of wind and current field time series to optimize the subgrid-scale velocity compensation mechanism in random walk models. The model integrates a drift dynamics framework incorporating wind forcing, ocean currents, and Coriolis force, and combines Monte Carlo simulation with kernel density estimation to quantify the spatiotemporal uncertainties in trajectory backtracking. Validated using North Atlantic Ocean Internet of Things buoy data across four typical marine environments—tropical open ocean, current convergence zones, temperate westerlies, and nearshore complex terrain—the proposed model achieves 72-hour trajectory backtracking errors of 3.9-5.8 km. Compared with traditional Lagrangian models, accuracy improvements of 74%, 55%, 59%, and 22% are achieved in the four sea areas respectively, effectively addressing the trajectory backtracking accuracy problem in complex marine environments and providing reliable technical support for maritime emergency rescue and pollution source localization.

A TCN-Attention-Based Pseudo-Velocity Measurement Generation Method for Loosely Coupled SINS/DVL Integrated Navigation

WANG Guoxiang, HAN Xingcheng, GAO Shengwen, WANG Ling

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0047

[Abstract](24) [FullText HTML] (12) [PDF 3674KB](7)

Abstract:
DVL unavailability degrades the accuracy of loosely coupled SINS/DVL integrated navigation for autonomous underwater vehicles. To address this problem, a pseudo-DVL velocity measurement generation method based on a temporal convolutional network with an attention mechanism (TCN-Attention) is proposed. The method uses the angular velocity and specific force measured by the inertial measurement unit (IMU), together with the attitude, position, and velocity obtained from inertial navigation computation, as sequential inputs. During the DVL-available stage, supervised samples are constructed using DVL velocity for offline network training. During the DVL-unavailable stage, the trained model outputs pseudo-velocity measurements, which are incorporated into the extended Kalman filter (EKF) update to suppress inertial error accumulation. Causal dilated convolutions are adopted to extract temporal features, and an attention mechanism is introduced to enhance the representation of key dynamic segments such as turning, acceleration, and deceleration. Simulation results based on 16 trajectory datasets show that, compared with the temporal convolutional network (TCN) and the gated recurrent unit with attention model (GRU-Attention), the proposed method achieves better performance in east- and north-velocity errors as well as absolute trajectory error, and reconstructs trajectories closer to the ground truth, demonstrating its effectiveness and robustness under continuous DVL-outage conditions.

A Review of Energy and Propulsion Technology Development for Autonomous Undersea Vehicles

FENG Shuai, LIU Weijie, YANG Jian, WENG Weiguo

, Available online , doi: 10.11993/j.issn.2096-3920.2025-0169

[Abstract](230) [FullText HTML] (66) [PDF 14330KB](99)

Abstract:
Autonomous undersea vehicles(AUVs) play a pivotal role in ocean engineering, marine scientific exploration, and military operations. Among their core subsystems, the energy and power system is particularly critical, as its performance directly determines the vehicle’s endurance, operational range, and overall efficiency. This study classifies AUVs from multiple perspectives and examines the principal characteristics and applications of their energy and power systems. Particular emphasis is placed on key enabling technologies, including high-energy-density battery systems, underwater charging methods, high-density hydrogen and oxygen storage, and advanced battery management. Finally, the paper outlines prospective directions for energy and power technologies in AUVs, with the aim of providing valuable insights for the future development of their energy systems.

Probability assessment and prediction method for escape area of underwater lost targets

SUN Jihong, ZHENG Yi, YANG Xiangfeng

, Available online , doi: 10.11993/j.issn.2096-3920.2025-0062

[Abstract](27) [FullText HTML] (13) [PDF 1430KB](11)

Abstract:
In the complex environment where underwater high-speed maneuvering vehicles face both real and decoy targets, incorrect target selection may lead to the escape of actual high-value targets. Traditional non-targeted re-search strategies are inefficient, necessitating an in-depth analysis of high-value target countermeasure strategies, comprehensive consideration of their maneuverability and tactical choices, and the formulation of targeted counter-countermeasure and re-search strategies. Based on the analysis of high-value target countermeasure strategies, this paper constructs a target escape area model and proposes a probability assessment method for lost target escape areas, aiming to predict the escape probability of targets within the countermeasure area. This method helps improve the success rate of target re-search, reduce the underwater high-speed maneuvering vehicle's search time, and enhance overall search efficiency.

Modeling and Analysis of Underwater Vehicles Wake-Induced Electromagnetic Fields and Internal Wave Characteristics in a Stratified Ocean

WANG Xiangjin, ZHANG Jiansheng, WANG Xintong, YAN Linbo, LAN Qing

, Available online , doi: 10.11993/j.issn.2096-3920.2025-0162

[Abstract](25) [FullText HTML] (18) [PDF 1390KB](19)

Abstract:
To counter the threat of underwater vehicle stealth and meet the demand for non-acoustic detection, this study investigates the influence mechanism of underwater vehicle wakes in density-stratified ocean environments. Most existing studies are based on the uniform fluid assumption, neglecting the effects of internal waves induced by stratification. This paper establishes a novel mathematical model for the velocity field of an underwater vehicle wake in a stratified fluid, decomposing the wake into a linear superposition of surface wave and internal wave components. Based on electromagnetic induction theory, the expression for the induced electromagnetic field is derived. Through numerical simulations, the spatial distribution, attenuation patterns, and component contributions of the induced magnetic field are analyzed for underwater vehicles at depths ranging from 10 m to 50 m. The results indicate that in a stratified environment, the surface wave-induced magnetic field has a high peak value (0.15 nT in the near-field) but decays rapidly with distance. In contrast, the internal wave-induced magnetic field has a lower peak value (0.006 nT in the near-field) but is more stable and decays slowly, becoming dominant in the far-field. Furthermore, as the submergence depth increases, the contribution of the internal wave component grows significantly (reaching 84.9% in the near-field at a depth of 50 m). This study reveals, from both theoretical and simulation perspectives, that internal waves are the key physical mechanism for far-field detection, providing a new theoretical basis for developing non-acoustic detection technologies for underwater vehicles.

Research on Factors Affecting Leakage Current of Lithium Reserve Battery Packs

GAO Xinlong, JIA Bin, LIN Pei, CHENG Haichao, LI Xuehai

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0083

[Abstract](54) [FullText HTML] (18) [PDF 995KB](32)

Abstract:
The distribution of leakage current of lithium reserve battery packs where the battery cells are in a common electrolyte state was studied, using the equivalent circuit simulation calculation method. The effects of the series cells quantity, electrolyte conductivity, and the structural characteristics of the injection tube on the leakage current were analyzed. A leakage current experimental device for battery modules was established. By comparing the measured results with the simulation results, the validity of the simulation calculation method was confirmed.

A Fast Algorithm for High-Frequency Approximate Scattering Acoustic Field of Complex Multi-Targets Based on the Planar Elements Method

MENG Lining, ZHAO Jingshu, LI Zhenhui, LIU Rui

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0090

[Abstract](69) [FullText HTML] (30) [PDF 5190KB](45)

Abstract:
With the development of unmanned undersea vehicle(UUV) cluster operations, the detection and recognition of complex multi-targets underwater have garnered significant attention. To address this, we established a fast calculation model based on the Planar Elements method to improve both computational accuracy and efficiency. Initially, the method was employed to calculate the target characteristics of a dual-target model. The accuracy of this method was validated by comparing the calculation results with physical field simulations and experimental measurements from an anechoic water tank.To enhance computational efficiency, the OpenMP parallel algorithm was introduced. By optimizing the loop iteration scheduling mechanism according to the varying computational difficulties of complex multi-target scattering acoustic field characteristics under different incident angles and frequencies, high thread load balance was achieved, yielding a 5.3x speedup. This fast algorithm was then applied to investigate more complex multi-target models. By analyzing the angle-frequency maps of target characteristics, the regular variations in the high-frequency scattering acoustic field characteristics of multi-targets with increasing frequency were obtained, revealing that target strength exhibits extrema at certain angles. Meanwhile, high-frequency interference fringes were observed. The correlation between scattering characteristics and geometric positions was analyzed. The research results provide a theoretical reference for underwater target acoustic detection and characteristic studies.

Cetacean call recognition and classification model based on multimodal MAE data augmentation network

LIU Yueyue, NIU Qiuna, SUN Yue, WANG Jingjing, SHI Wei

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0052

[Abstract](87) [FullText HTML] (40) [PDF 5139KB](57)

Abstract:
Passive acoustic monitoring-based call recognition and classification are essential means for marine animal conservation and population surveys. To address the issues of data scarcity and inter-class imbalance in call recognition and classification, data augmentation methods hold significant practical value and research importance. However, marine animal calls contain rich acoustic information, and relying solely on frequency-domain feature extraction lacks the capability to model audio structure and semantics, making it difficult to effectively capture the deep features of calls. To this end, this paper proposes a data augmentation network based on a multimodal masked autoencoder (MAE-MF), which breaks through the limitations of single-modal information. The network employs Mel-spectrograms as the primary modality, integrates temporal features and frame-level statistical metrics to form multimodal inputs, and incorporates semantic labels as conditional guidance for reconstruction. To scientifically validate the effectiveness and practical value of the proposed data augmentation network, a cetacean call recognition and classification model is further constructed based on the MAE-MF network. Experimental results on the Watkins dataset demonstrate superior performance of the proposed method, with improved spectrogram reconstruction quality compared to mainstream algorithms. The proposed method achieves an average recognition accuracy of 97.6% across six cetacean species, representing an improvement of 6.72 percentage points over the baseline MAE method. This scheme effectively alleviates the inter-class imbalance issue and provides reliable technical support for cetacean conservation research.

Anti-Disturbance Control for Underwater Propulsion Motor at Low Speed Based on Hybrid Resolver and High-Frequency Injection Observation

WANG Yu, DUAN Luobao, CUI Jialun, WANG Yuankui

, Available online , doi: 10.11993/j.issn.2096-3920.2025-0144

[Abstract](152) [FullText HTML] (70) [PDF 2247KB](114)

Abstract:
The low-speed control performance constitutes a fundamental prerequisite for unmanned underwater vehicle propulsion systems to execute critical missions such as deep-sea exploration and military reconnaissance effectively. To address the need for enhanced control capabilities during low-speed operations, this paper systematically examines limitations in permanent magnet synchronous motor drive systems employing both position-sensor-based schemes and sensorless schemes. Resolvers introduce position detection errors under harsh environmental conditions, while among dominant sensorless solutions, back-electromotive-force observers contain inherent observation dead zones near zero speed. Although high-frequency signal injection methods improve low-speed observation performance, their estimation accuracy remains susceptible to motor parameter variations. Crucially, the accuracy of all sensorless schemes exhibits critical dependence on current sampling precision, making such approaches vulnerable to severe engineering challenges in complex interference-intensive operating conditions. To resolve these issues, this paper proposes a hybrid observation-based low-speed anti-disturbance control strategy that integrates resolver technology with high-frequency square-wave injection. By applying hardware redundancy and information fusion techniques, the methodology achieves comprehensive integration between the absolute position reference provided by resolvers and dynamic observations generated through high-frequency square-wave injection. This synthesis establishes an advantage-complementary observation architecture that significantly enhances system robustness in difficult scenarios: low-speed operations, variable loading conditions, and signal interference contexts. Simulation results verify the capability of the method to suppress detection error interference arising from position sensors and current sensors concurrently, enabling stable and precise rotor position estimation. The framework therefore delivers a high-reliability control solution for underwater equipment propulsion systems.

Design and simulation of mechanical biomimetic fish tail driven by EAP material

WANG Sijiao, ZHANG Haoyi, CHENG Yanlin, CAO Kaiming

, Available online , doi: 10.11993/j.issn.2096-3920.2025-0164

[Abstract](213) [FullText HTML] (140) [PDF 1812KB](132)

Abstract:
Against the backdrop of advancing marine conservation and exploration, traditional underwater propulsion systems are often hampered by inherent drawbacks such as structural complexity and low motion efficiency. In contrast, flexible materials have emerged as a research focus in underwater actuation due to their superior adaptability, high safety, and remarkable flexibility. Leveraging the favorable core properties of Electroactive Polymer (EAP), namely its high energy density and efficient electromechanical coupling, this study introduces a novel biomimetic caudal fin actuator. This design incorporates a spring element to harness flexural deformation and elastic recovery, effectively simulating the cyclic contraction and relaxation dynamics characteristic of the Body and/or Caudal Fin (BCF) propulsion mode in fish, thereby achieving continuous, compliant changes akin to tail musculature. Based on hydrodynamic theory, the coupled interaction mechanism between fin kinematics and thrust generation is systematically analyzed. An instantaneous mechanical model for fin-ray oscillation is developed and solved by incorporating experimental data. A three-dimensional numerical simulation model is established using Fluent software. The validity of the proposed mechanical model is confirmed through comparative analysis between the computational results from dynamic meshing and the model's predictions. This work provides reliable theoretical support and experimental evidence for the design and development of new biomimetic robotic fish driven by this innovative actuator.

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