水下无人系统学报

A Motion Compensation Method for Circular Synthetic Aperture Sonar Based on Multi-Sensor

HUANG Tianfeng, YE Tianming, DU Xuanmin, YANG Tianlin

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0063

[Abstract](0) [FullText HTML] (0) [PDF 4557KB](0)

Abstract:
Circular synthetic aperture sonar(CSAS) is a high-resolution underwater imaging technique whose imaging performance is highly sensitive to the accuracy of platform position and attitude. However, in practical survey operations, unmanned platforms are often affected by environmental disturbances such as ocean currents and waves, causing deviations from the ideal trajectory and resulting in position and attitude errors, which significantly degrade imaging quality. Existing CSAS motion compensation methods mainly rely on underwater acoustic positioning systems to obtain the platform position. However, such methods usually require the deployment of additional acoustic transponders or base stations, resulting in complex system deployment and a strong dependence on external equipment. To address this issue, a CSAS platform motion compensation method based on multi-sensor fusion of the global positioning system(GPS) and the inertial navigation system(INS) is proposed in this paper. By integrating the position information obtained from GPS with the attitude data provided by the INS, the spatial pose of the sonar platform can be jointly estimated, and the spatial position of the sonar array can be corrected accordingly, thereby reducing the influence of platform motion errors on the imaging results. Simulation studies are conducted to analyze the effects of platform motion errors on imaging performance, and lake experiments are further carried out to validate the effectiveness of the proposed method. The experimental results demonstrate that the proposed approach can effectively compensate for motion errors caused by platform movement and significantly improve the imaging quality of CSAS. The proposed method does not rely on external underwater acoustic positioning systems and instead utilizes only the onboard navigation sensors of the platform to achieve effective motion compensation. This provides a simple and practical solution for high-resolution CSAS imaging in complex environments.

A Small-Sized Low-Cost and High-Resolution Two-Dimensional Side-Scan Sonar Imaging Method Using Sparse Transmit-Receive Arrays

ZHAO Wanchun, LIU Xionghou, YANG Yixin

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0060

[Abstract](2) [FullText HTML] (3) [PDF 3107KB](1)

Abstract:
To overcome the problems of excessively large array aperture and high element cost when improving angular resolution in existing two-dimensional side-scan sonar imaging methods, this paper proposes a small-size, low-cost, high-resolution two-dimensional side-scan sonar imaging method. The proposed method uses a uniformly spaced linear array with large inter-element spacing as a sparse transmitting array and multiple uniformly spaced linear arrays with full sampling as subarrays to form a sparse receiving array. By utilizing the product theorem, a horizontally fully-sampled large-aperture virtual array is formed. The number of elements in this virtual array equals the product of the number of transmitting elements, the number of receiving subarrays, and the number of elements per subarray, while the aperture is the sum of the transmitting array aperture and the receiving array aperture. Thus, a large-aperture equivalent array is achieved with smaller size and fewer elements. Based on the designed array configuration, the proposed method adopts the same waveform and normal-direction single-beam side-scan imaging mode as traditional two-dimensional side-scan sonar imaging methods. Numerical simulations demonstrate that compared with the traditional method (240 transmitting elements / 240 receiving elements, center frequency of 450 kHz), the proposed method reduces the array size from 0.40 m to 0.33 m, decreases the total number of elements from 480 to 40, narrows the horizontal -3 dB beamwidth from 0.41° to 0.25°, and improves the angular resolution by approximately 40%. The proposed method achieves higher imaging resolution with smaller array size and fewer elements.

1D ViT-ResNet Method for Magnetic Source Localization of Small Ferromagnetic Targets on Shallow Seabeds

HUI Ran, LIANG Xiaofeng, GAO Haoran, YAN Shu

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0057

[Abstract](8) [FullText HTML] (4) [PDF 3579KB](5)

Abstract:
To address the challenges of magnetic signal acquisition in complex underwater environments, this study designed and constructed a modular towed-platform system equipped with a fluxgate magnetometer array. This system efficiently collects magnetic environmental noise and magnetic anomaly signals from four typical small ferromagnetic targets under dynamic conditions, successfully establishing a corresponding real-world measurement dataset . To compensate for the limitations of measured data and enhance data diversity, a simulation dataset was developed using COMSOL Multiphysics software, based on the characteristics of the real-world dataset. This dataset includes the magnetic source signature curves for the four target types, providing robust data support for model training. Ultimately, to enable real-time magnetic source detection and precise localization, this research proposes an innovative collaborative magnetic source localization method. This method integrates a 1D-ViT detection model with a 1D-ResNet localization model (hereinafter referred to as the 1D ViT-ResNet magnetic source localization method). Validated against real-world target signals, the algorithm achieved an average localization estimation error of approximately 7.0%. Compared to single-model approaches, this dual-model strategy significantly reduced the false detection rate, with an average reduction of 11.0 percentage points observed in real-world target signals, thereby substantially enhancing detection accuracy and system robustness .

A Review of Research on the Acoustic Scattering Characteristics of Small Underwater Targets

LIU Yan, LI Jie, GE Lili, FAN Jun, WANG Bin

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0073

[Abstract](46) [FullText HTML] (28) [PDF 4798KB](12)

Abstract:
Research on the acoustic scattering characteristics of small underwater targets provides a fundamental physical basis for active sonar target detection, identification, and security applications, and has significant application value in shallow-water security, mine countermeasures, and underwater engineering detection. This paper reviews the progress in theoretical modeling, experimental measurements, and engineering applications for three representative classes of small underwater targets: divers and their propulsion devices, unmanned underwater vehicles, and mines. First, the scope of the review is defined by combining the normalized size parameter with the functional attributes of the targets, and the fundamental features of different scattering regions are outlined. Then, representative studies on the modeling, experiments, and applications of these three types of targets are systematically summarized. Research indicates that diver targets exhibit significant multi-component coupling and time-varying modulation characteristics, with exhaled bubbles, the lungs, and diving equipment serving as the main contributors to acoustic scattering. The scattering of unmanned underwater vehicles is greatly affected by hull structures, the flooding state of internal compartments, and multiple scattering from appendages. Echoes from targets such as buried mines are jointly governed by target elasticity, interface propagation, and coupling with sediment layers. Current research still faces several challenges, including insufficient understanding of target scattering–propagation coupling mechanisms in complex marine environments, the difficulty of balancing accuracy and efficiency in broadband scattering prediction, inadequate integration of scattering mechanisms with data-driven recognition, and limited experimental validation under complex field conditions. This review is expected to provide a reference for understanding the acoustic scattering mechanisms of small underwater targets and for improving their sonar detection and recognition.

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](34) [FullText HTML] (19) [PDF 5139KB](12)

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.

Analysis on Acoustic Scattering Characteristics of Icosahedral Sphere Composite

DONG Yanhua, ZHOU Fulin, FAN Jun, WANG Bin, WANG Wenhuan, XIONG Jianbing

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0078

[Abstract](37) [FullText HTML] (21) [PDF 5057KB](14)

Abstract:
To address the limitations of conventional underwater acoustic standard targets in terms of deployment difficulty and insufficient acoustic adaptability, a lightweight underwater icosahedral buoy-rod composite quasi-spherical scatterer structure is proposed. The structure forms an approximate spherical scattering interface using curved buoyant units and a rod–sphere framework, and a permeable design enables buoyancy self-balance and stable underwater positioning without additional ballast, which improves deployment feasibility while preserving spherical scattering characteristics. A frequency-segmented numerical model for acoustic scattering is established. The variations in scattering strength with acoustic frequency and incident direction are numerically analyzed, and the formation mechanism of path-difference interference is clarified. Experimental measurements are further carried out to validate the proposed modeling method and the corresponding conclusions, providing theoretical support and experimental evidence for the design and optimization of acoustic scattering standard targets. The results show that the average target strength of the proposed quasi-spherical scatterer is approximately 3.87 dB higher than that of a rigid sphere with the same radius. Meanwhile, the structure exhibits coherent interference characteristics caused by multiple scattering components. Therefore, it can serve as an underwater acoustic calibration target and provide a useful reference for experimental calibration, acoustic scattering analysis, and testing of underwater unmanned systems.

A Correction Method for Imaging Buried Targets in Layered Media Based on the Range-Doppler Algorithm

JIANG Haosong, LI mei

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0043

[Abstract](40) [FullText HTML] (22) [PDF 1155KB](12)

Abstract:
Synthetic aperture imaging algorithms are generally based on the assumption of a homogeneous medium. When detecting buried targets on the seafloor, refraction occurs as acoustic waves pass through the medium interface, leading to image defocusing and positioning errors. To address this issue, this paper proposes a parameter correction algorithm suitable for layered medium imaging. First, a seawater-sediment layer refraction propagation model is constructed, and based on Snell's law, an expression for the two-way propagation delay is derived, along with a joint estimation method for sediment layer sound speed and burial depth. Second, this layered model is embedded into the range-Doppler (R-D) algorithm, and the analytical expressions for Doppler frequency modulation and range migration correction are rederived and corrected. Finally, numerical simulations compare the imaging results before and after algorithm correction at different burial depths. The results indicate that the corrected algorithm can effectively rectify range positioning deviations caused by refraction and improve azimuth focusing performance, thereby validating the effectiveness of the proposed correction algorithm.

Review of Optical-based Detection Technology for Underwater Small Targets

CHEN Qingyan, WU Guojun, WU Yafeng, MIAO Yuhong

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0049

[Abstract](52) [FullText HTML] (32)

Abstract:
Accurate detection and recognition of underwater small targets (e.g., micro underwater vehicles, underwater detection device etc.) constitute a critical component in the fields of marine resource exploitation, underwater security early warning, and underwater engineering inspection. Constrained by the combined effects of water body attenuation, optical scattering, acoustic multipath effect, and complex background noise, traditional detection technologies exhibit notable limitations in terms of effective detection range, spatial resolution, and real-time responsiveness. With the advancement of marine development toward refinement and intelligence, coupled with the increasingly prominent strategic value of underwater unmanned equipment countermeasures, optical detection technology for underwater small targets has emerged as a research hotspot in the domain of marine information technology. This paper systematically sorts out the research background and strategic significance of optical detection technology for underwater small targets, and presents a comprehensive review focusing on two major technical approaches: image-based and LiDAR-based methods. For the image-based technical system, the study centers on two core modules—image enhancement and target detection—and conducts an in-depth analysis of the principle mechanism, improvement strategies, and performance characteristics of various technologies. For the LiDAR-based technical system, aiming at detection modes including area-scan imaging, point-scan imaging, and line-scan imaging, the paper systematically elaborates on their technical features and typical application scenarios. Furthermore, this paper analyzes the bottleneck problems faced by existing technologies, and prospects future research directions in combination with the development trend of marine technology, so as to provide theoretical support and practical reference for the engineering implementation of optical detection technology for underwater small targets.

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](62) [FullText HTML] (30) [PDF 14542KB](21)

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.

Two-Dimensional Deconvolved Conventional Beamforming Based on Non-Stationary Signal Demodulation

FAN Xiaomeng, LIU Zhen, LI Mei, YE Tianming

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0064

[Abstract](44) [FullText HTML] (27) [PDF 1368KB](21)

Abstract:
Underwater weak target detection is a core topic in underwater acoustics signal processing, yet it still faces numerous challenges such as complex environments, numerous interfering targets, weak echoes, and poor image quality. Frogmen are typical weak underwater intrusion targets. To address the difficulty in their detection, this paper proposes a two-dimensional deconvolved conventional beamforming based on non-stationary signal demodulation. This method utilizes two-dimensional deconvolved conventional beamforming method to obtain high-resolution target azimuth-range images. By combining peak detection on these high-resolution images, the time-domain waveform of suspected target echoes is precisely located. Subsequently, the time-domain waveforms of suspected echoes are demodulated and the spectral kurtosis index is calculated. Leveraging the difference in spectral kurtosis between genuine target echoes and clutter, weights are assigned to the two-dimensional deconvolved conventional beamforming images to achieve enhancement of weak target echoes and suppression of clutter, ultimately yielding high –resolution target images. Experimental results demonstrate that the proposed method effectively suppresses clutter and improves target detection and tracking capability(The stable tracking range is improved by 60 meters).

Single-Beam Sonar Small Target Recognition Algorithm Based on Underwater Unmanned Platform

XU Linpeng, MA Jingwen, QU Guorui, DU Weidong, ZHOU Tian, YU Xiaoyang

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0061

[Abstract](62) [FullText HTML] (20) [PDF 998KB](26)

Abstract:
Aiming at the difficulty of small target recognition caused by the limited payload capacity of underwater unmanned platforms and the scarcity of sonar data samples, this paper proposes a single-beam sonar signal target recognition algorithm adapted to the few-shot condition of underwater unmanned platforms. Based on the single-beam echo signal of active sonar targets, the algorithm realizes high-accuracy target recognition under the few-shot condition by extracting multi-dimensional time-frequency features of the signal, optimizing feature selection via correlation analysis and PCA dimensionality reduction, and integrating the random forest classifier. Test results on water tank experimental data show that, compared with various methods combining multi-beam sonar images with deep learning, the proposed algorithm achieves performance indicators of 99.42% precision, 99.39% recall, 99.39% F1-score, and 99.39% accuracy with a smaller training set. The proposed method has the advantages of low computational cost, fast running speed and strong interpretability, making it more suitable for deployment on underwater unmanned platforms with limited computing and storage resources. It provides an efficient and feasible scheme for small target recognition by underwater unmanned platforms under resource-constrained conditions.

Experimental Study on Low-Frequency Characteristics of Typical Physical Fields for Small Underwater Vehicles

ZHOU Guangyuan, WEN Wudi, ZHANG Guanghua, TU Yifan

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0056

[Abstract](46) [FullText HTML] (20) [PDF 1678KB](22)

Abstract:
Current research on underwater multi-physical field detection mostly focuses on large-scale targets such as ships and submarines, while little attention has been paid to joint multi-physical field detection for small underwater vehicles. To investigate the low-frequency characteristics and inter-field correlation of multi-physical fields within 100 Hz and below for small underwater vehicles, field tests were carried out in a shallow-water sheltered harbor. Signals of acoustic, electric, magnetic, pressure, seismic wave, and alternating magnetic fields were synchronously acquired. After data preprocessing and power frequency interference suppression, the time-domain passage characteristics and frequency-domain line spectrum features of each physical field were analyzed, and the coupling characteristics of multi-physical fields were discussed. The results show that the electric field and magnetic field exhibit strong correlation and common-source characteristics, and the alternating magnetic field contains richer target feature information. The frequency-domain characteristics of the acoustic field and seismic wave field are highly consistent, and the seismic wave field is significantly superior to the water pressure field in resisting marine environmental interference. This study analyzes the typical low-frequency multi-physical field characteristics and coupling laws of small underwater vehicles, which can provide experimental support for joint multi-physical field detection and recognition of underwater small targets.

Dynamic Evaluation Method for Underwater Small Target Detection Effectiveness

YU Zhimin, CHEN Xiangguang, WANG Renzhong

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0026

[Abstract](51) [FullText HTML] (20) [PDF 1830KB](22)

Abstract:
The evaluation of underwater small target detection effectiveness is a core challenge for ensuring maritime security and resource exploitation. Traditional static evaluation methods rely on fixed environmental parameters and single metrics, making it difficult to capture the dynamic adaptability of algorithms in complex and time-varying marine environments. To address this bottleneck, this paper proposes a novel dynamic effectiveness evaluation method based on multi-indicator fusion using Python. An environment-coupled dynamic detection probability model is established, extending classical detection theory to time-varying marine environments. The weighted geometric mean is introduced into the modeling of the Comprehensive Effectiveness Index (CEI). An underwater detection dynamic evaluation system (UDDES) is designed and developed, supporting dynamic environment simulation, parallel testing of multiple algorithms, and multi-dimensional effectiveness visualization analysis. Simulation experimental results demonstrate that the detection probability of AI-Det is improved by approximately 99.8% compared with conventional beamforming (CBF). In dynamic environment stress tests involving sudden sea state deterioration and SNR drops, the mean CEI of AI-enhanced algorithms is increased by 36.5% over CBF, along with a 44.8% improvement in robustness coefficient and a 55.3% reduction in tracking stability error. This study shows that the proposed framework and system effectively overcome the inability of traditional static evaluation to quantify dynamic performance evolution, providing systematic theoretical methods and engineering tools for closed-loop testing, optimal selection, and effectiveness prediction of underwater detection algorithms.

MFLM-FPN and GAFF-driven Underwater Target Detection Algorithms and Class Balancing Strategies

ZHAO Yan, LI Jinxin, JIA Rujian

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0007

[Abstract](37) [FullText HTML] (17) [PDF 4264KB](21)

Abstract:
To address the problem of scarce feature information for underwater targets, this paper proposes a feature pyramid mapping mechanism combined with global attention. This mechanism maps each proposal box to different feature layers, resulting in four feature layers of consistent size and complementary information after region-of-interest pooling. Global attention is then used to achieve feature fusion, fully utilizing the feature information from each layer and effectively alleviating the problem of feature scarcity for underwater targets. To address the class imbalance problem in underwater datasets, a copy-paste class balancing strategy is designed to enhance the neural network's attention to scarce categories such as sea cucumbers, starfish, and scallops. To address the issue of insufficient penalty in the loss function leading to decreased detection accuracy, the normalized distance between the predicted and target boxes is introduced as a penalty term in the smoothed L1 loss function, significantly improving the localization accuracy of underwater multi-scale targets. Experimental results show that on the National Underwater Robotics Competition dataset, the proposed method achieves a recognition accuracy of 81.93%, a 5.71% improvement over the baseline model Faster R-CNN, effectively reducing false negatives and false positives in complex underwater environments.

Dual-Station Tracking Algorithm for Small Underwater Targets Based on AIMM-UKF with Probability Lower Bound Constraint

GAO Xuwen, YU Ge, LI Qing, YU Xiaoyang

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0058

[Abstract](48) [FullText HTML] (23) [PDF 1083KB](25)

Abstract:
The complex underwater environment (boundary scattering, multipath effects, and strong noise) makes it difficult to achieve real-time, precise tracking of the maneuvering trajectories of small underwater targets (e.g., unmanned underwater vehicles and frogmen). Targeting the dual-station active sonar cooperative tracking system, this paper proposes an Adaptive Interacting Multiple Model-Unscented Kalman Filter (AIMM-UKF) algorithm incorporating probability lower bound constraints. In traditional AIMM algorithms, when a target remains in a long-term steady state, the prior probability of transitioning to a maneuvering model decays toward zero, leading to switching hysteresis and increased tracking errors during sudden maneuvers. To mitigate this issue, this study innovatively introduces a probability lower bound constraint and a decision-window secondary correction mechanism based on traditional likelihood ratio modification. During long-endurance steady-state periods, the decision-window mechanism guarantees high steady-state precision; at the instant of sudden maneuvers, the probability lower bound mechanism cooperates with likelihood ratio scaling to achieve rapid and accurate model switching. Monte Carlo simulations demonstrate that the proposed algorithm effectively overcomes the degradation problem caused by excessive probability absorption. It reduces the peak error during the initial maneuvering stage, achieves the lowest global position and velocity errors, and attains an optimal balance between transient switching and steady-state accuracy. This provides robust technical support for the continuous tracking and security early warning of small underwater targets.

Underwater Low-speed Small Target Recognition: A Comprehensive Overview and Prospects

LIU Xionghou, LAI Kai, YANG Yixin

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0042

[Abstract](63) [FullText HTML] (59) [PDF 1598KB](38)

Abstract:
Underwater low-speed small targets, represented by frogmen and unmanned underwater vehicles, have become major threats to nearshore military and economic facilities due to their strong concealment, high maneuverability, and significant destructive potential. Their recognition has emerged as a hot topic and a challenging issue in the field of underwater security. This paper focuses on three key aspects of acoustic recognition for underwater low-speed small targets: acoustic signal characteristic analysis, feature extraction, and feature classification. It systematically reviews the current research status, core challenges, and development trends in this field. First, the acoustic signal characteristics of underwater low-speed small targets are analyzed from the perspectives of active echo signals and passive radiated noise. Subsequently, mainstream feature extraction methods are summarized based on active and passive features. Then, two major classification approaches—statistical learning and deep learning—are introduced and compared. Following this, the main challenges faced in this field and corresponding countermeasures are discussed. Finally, in light of technological development trends, future research directions are prospected, aiming to provide references for the advancement of underwater low-speed small target recognition technologies.

, Available online , doi: 10.1234/t

[Abstract](63)

Abstract:

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](108) [FullText HTML] (53) [PDF 2247KB](69)

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.

Method of Vision-Task-Friendly Underwater Image Enhancement

CHENG Miao, WEI Yanhui, SUN Wenbin, HOU Tongtong

, Available online , doi: 10.11993/j.issn.2096-3920.2026-0023

[Abstract](103) [FullText HTML] (54)

Abstract:
Underwater images suffer from severe color and structural distortions, which degrade the performance of various underwater vision tasks. Existing underwater image enhancement methods focus on improving visual appearance while ignoring the necessity of optimizing the downstream vision tasks. To address this issue, this paper proposes a Visual Task-Friendly underwater image enhancement Network(VTF-Net). Specifically, we first design a novel Spatial-Frequency Fusion enhancement module(SFF), which can significantly improve the model’s perception of texture details and image fidelity. Second, to achieve efficient information transmission between the encoder and decoder, we introduce a Multi-Scale Cross-Attention module(MSCA) and a Bottleneck Attention module(BNA), which enhance the perception of global gradients while ensuring efficient feature extraction, thereby effectively alleviating color cast and blurring. Finally, in line with the concept of visual task-friendliness, we propose a detection loss function that guides the optimization direction of the model by incorporating underwater object detection results. Experimental results demonstrate that the proposed method achieves superior performance in both qualitative and quantitative evaluations, and obtains the best result in the application experiment of underwater object detection.

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](141) [FullText HTML] (101) [PDF 1812KB](83)

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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