水下无人系统学报

2025, 33(3): 1-1.

[Abstract](5) [FullText HTML] (6) [PDF 3394KB](4)

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Research Status and Development Trends of Deep-sea Unmanned Equipment Control System

WANG Biao, LUO Ruilong, WANG Fang, CUI Weicheng

2025, 33(3): 390-399. doi: 10.11993/j.issn.2096-3920.2025-0074

[Abstract](302) [FullText HTML] (21) [PDF 854KB](43)

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Deep-sea unmanned equipment, as a strategic reflection of a nation’s marine scientific and technological strength, has been widely integrated into core fields such as resource exploration, marine scientific research, military security, and economic development. The control system, serving as the neural center for complex underwater operations, directly determines the mission execution efficiency of the equipment. This paper systematically combed the control theory system of deep-sea unmanned equipment, including technical paths such as traditional proportional-integral-derivative (PID) control, model-based control, data-driven intelligent control, and multi-agent control. It deeply analyzed the technical characteristics and engineering applicability of centralized, hierarchical, distributed, and hybrid control architectures. By comparing and analyzing the research status of key technologies such as navigation and positioning, communication transmission, and energy supply, the paper revealed common challenges in the industry, including model uncertainty, robust control performance, and multi-equipment collaboration mechanisms. The study shows that future control systems will develop towards deep empowerment of artificial intelligence, clustered collaborative operations, integration of new communication and energy technologies, and interdisciplinary innovation, providing theoretical and technical support for the intelligent transformation of deep-sea equipment.

Three-Dimensional Path Planning of AUVs in Dynamic Obstacle Environments

CHEN Chaoyang, TANG Yute, HUANG Yi, LIU Zhiqun

2025, 33(3): 400-409. doi: 10.11993/j.issn.2096-3920.2025-0008

[Abstract](61) [FullText HTML] (20) [PDF 5132KB](22)

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Traditional algorithms suffer from heavy computational burden and insufficient accuracy in the high-dimensional space and dynamic obstacle environment faced by autonomous underwater vehicles(AUVs). To overcome the challenges posed by dynamic obstacles to AUV path planning in complex three-dimensional environments, this study proposed a three-dimensional path planning method for AUVs based on an enhanced double deep Q-network(DDQN). By optimizing the network architecture and designing an efficient reward function, the AUV path planning efficiency and accuracy were significantly improved. Moreover, dynamic obstacle trajectories were modeled, and the Singer model, combined with the Kalman filter algorithm, was used to precisely predict obstacle states, thereby enhancing the dynamic obstacle avoidance capabilities of AUVs. Additionally, Basis spline functions were utilized to smooth the paths, thereby improving the path continuity and stability of AUVs. Simulation and experimental results demonstrate that the proposed approach effectively avoids collisions in complex dynamic environments and achieves real-time planning of safe and efficient paths. Compared to traditional methods, the DDQN algorithm shows significant advantages in terms of path length, obstacle avoidance success rate, and computational efficiency, effectively addressing the challenges associated with three-dimensional path planning of AUVs in dynamic obstacle environments.

Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms

MA Yuhong, PANG Wen, ZHU Daqi

2025, 33(3): 410-419. doi: 10.11993/j.issn.2096-3920.2025-0054

[Abstract](69) [FullText HTML] (14) [PDF 2441KB](15)

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To address the challenges of low path planning efficiency for autonomous undersea vehicle(AUV) in multi-target environments, as well as the limitations of the traditional whale optimization algorithm(WOA) in terms of susceptibility to local optima and inadequate adaptability to three-dimensional obstacle avoidance requirements, this study proposed a collaborative planning strategy that integrated a fluid perturbation algorithm with an improved WOA. A hybrid population initialization method was developed by combining chaotic mapping to generate high-coverage initial solutions and a greedy algorithm to construct locally optimal sequences, effectively addressing the issue of poor solution quality caused by random initialization in traditional WOA. For the discrete characteristics of the traveling salesman problem(TSP), a discrete position update strategy based on random insertion and local inversion was proposed, significantly enhancing the algorithm’s capability to escape from local optima. An elite retention mechanism was introduced to ensure the global convergence of the algorithm through an iterative optimization framework that replaced the worst individuals with the optimal ones. During the path generation phase, a three-dimensional fluid disturbance field model was established, where obstacle perturbation matrices adjusted the original flow field direction to achieve continuous obstacle avoidance in complex obstacle environments. Simulation results demonstrate that the proposed algorithm reduces the average path length by 15.4% and 7.5% compared to traditional genetic algorithm and particle swarm optimization, respectively, while improving computational efficiency by 45.5% and 16.8%.

Fixed Depth Control Strategy for Remotely Operated Vehicle Based on Improved Model Predictive Control Algorithm

YANG Shuo, WANG Honghui, LIU Xinyu, FANG Xin, LI Guanghao, LIU Guijie

2025, 33(3): 420-432. doi: 10.11993/j.issn.2096-3920.2024-0172

[Abstract](26) [FullText HTML] (7) [PDF 2643KB](14)

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To address the issue of poor depth control stability in remotely operated vehicles(ROVs) with cables due to external disturbances in complex marine environments, a composite control strategy based on an improved model predictive control(MPC) was proposed. This strategy aims to achieve high-precision fixed depth control while significantly enhancing the robustness and disturbance rejection capability of ROVs under sudden external disturbances. First, a nonlinear marine predator algorithm(NMPA) was introduced to optimize key control parameters of MPC, ensuring fast and precise depth tracking of ROVs in complex marine environments. Secondly, by considering the impact of large external disturbances on the performance of the traditional MPC algorithm, the strategy incorporated a nonlinear disturbance observer(NDO) to compensate for external disturbances in real time, improving the ROV’s control performance and robustness. Simulation results demonstrate that the proposed strategy reduces the steady-state time of the ROV by approximately 30% compared to traditional MPC and decreases the overshoot by about 10%. Under disturbance conditions, the maximum overshoot is reduced by about 27.7%. The proposed strategy significantly enhances the ROV’s fixed depth control performance, exhibiting higher tracking accuracy and better disturbance rejection capability.

ARV Nonlinear Disturbance Estimation Based on Extended State Observer

LIU Xiaohan, ZHAO Chenhao, NIE Haomiao, XIANG Feng, LI Chenguang, ZHAO Min

2025, 33(3): 433-440. doi: 10.11993/j.issn.2096-3920.2025-0035

[Abstract](29) [FullText HTML] (6) [PDF 2364KB](9)

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Autonomous/remotely-operated vehicles(ARVs) are susceptible to complex flow field disturbances during underwater path tracking missions, where traditional linear observers exhibit suboptimal performance in addressing flow field-induced nonlinear disturbances. This paper proposed a dynamic high-gain extended observer method to resolve the nonlinear disturbance estimation challenge for the “Siyuan” ARV. Firstly, a nonlinear kinematic and dynamic model of the ARV was established, with external disturbance data acquired through sea trial path tracking experiments. Secondly, a dynamic gain compensation mechanism was introduced to address nonlinear system observation, effectively overcoming limitations in conventional methods such as the difficulty in determining Lipschitz function coefficient and empirical dependence in parameter tuning. The convergence of dynamic gains was rigorously ensured through the incorporation of performance constraint parameters. To validate the proposed method, comparative simulation experiments were conducted against traditional Luenberger observers. Results demonstrate that the developed observer achieves superior convergence speed and steady-state accuracy in estimating disturbance forces, disturbance moments, surge velocity, heave velocity, and yaw angular velocity. This advancement significantly enhances state tracking capability under complex disturbances.

Trajectory Tracking Control Method for AUV Planar MotionBased on Three-Level Hierarchical Speed Regulation

SUN Haonan, WANG Lei

2025, 33(3): 441-449. doi: 10.11993/j.issn.2096-3920.2025-0029

[Abstract](29) [FullText HTML] (21) [PDF 1196KB](13)

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Autonomous undersea vehicle(AUV) often encounter the problem of track overshoot when moving underwater. To address this issue, this paper proposed a cooperative control strategy that integrated the adaptive line-of-sight guidance algorithm and the three-level hierarchical speed control architecture. In this study, the distance parameter at the end of the track was introduced into the control decision, and the dynamic allocation of the speed was achieved through a three-level hierarchical control strategy. The simulation results verify the effectiveness of the dynamic speed regulation mechanism based on the three-level hierarchical control strategy. By calculating the distance deviation between the AUV and the end of the expected track section in real time, the controller can actively implement the hierarchical deceleration strategy before the large curvature turning requirement is triggered, thereby effectively suppressing the trajectory offset phenomenon caused by momentum accumulation. Compared with the heading-speed double closed-loop algorithm, under the same trajectory, the overshoot of the method in this paper is reduced by 34.15%, enabling the AUV to still accurately travel along the predetermined trajectory when turning and significantly reducing the trajectory deviation.

Numerical Simulation of Variable-Speed Propulsion Characteristics of Bionic Undulating Fins

XU Chuanxin, LIU Guijie, MA Penglei, LI Guanghao, YAO Bing, ZENG Jiajun

2025, 33(3): 450-458. doi: 10.11993/j.issn.2096-3920.2025-0001

[Abstract](65) [FullText HTML] (23) [PDF 2663KB](16)

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The hydrodynamic performance of bionic undulating fin robots is crucial for their precise control. This paper investigated the hydrodynamic response mechanism of the undulating fin during acceleration and deceleration through numerical simulation, revealing the relationship between the propulsive force and control frequency at variable-speed stages. The results show that at the acceleration stage, when the frequency increases from low to high, the vortices remaining at the low-frequency stage merge with newly generated vortices at the high-frequency stage, resulting in a propulsive force higher than steady value, which can be controlled by appropriately increasing the frequency; at the deceleration stage, when the frequency drop is small, the lagging vortices come off too late, producing a long period of irregular higher propulsive force, and the frequency gradient can be appropriately reduced to minimize this effect. This effect is significantly reduced when the frequency drop is too large. This research can provide theoretical support for the precise control of bionic undulating fin robots during speed changes, contributing to the improvement of control system stability.

Adaptive Multi-Objective Optimization-Based Coverage Path Planning Method for UUVs

ZHAO Shaojing, FU Songchen, BAI Letian, GUO Yutong, LI Ta

2025, 33(3): 459-472. doi: 10.11993/j.issn.2096-3920.2025-0031

[Abstract](61) [FullText HTML] (22) [PDF 1187KB](21)

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Coverage path planning for unmanned undersea vehicles(UUVs) in unknown aquatic environments is a critical task. However, due to environmental uncertainties, motion constraints, and energy limitations, traditional path planning methods struggle to adapt to complex scenarios. This paper proposed an adaptive multi-objective optimization-based coverage path planning method for UUVs, integrating proximal policy optimization(PPO) with a dynamic weight adjustment mechanism. By analyzing the correlation between reward objectives and employing linear regression estimation, the proposed approach adaptively adjusted the weights of different optimization objectives, enabling UUVs to autonomously plan efficient coverage paths in environments with unknown obstacles and ocean currents. To validate the effectiveness of the proposed method, a UUV motion and sonar detection model based on a two-dimensional simulation environment was constructed. Among them, the UUV motion model was simplified to a planar motion model on the basis of the six-degree-of-freedom rigid-body motion. Comparative experiments were conducted under various obstacle distributions and random ocean currents. Experimental results demonstrate that compared with traditional methods, the proposed approach improves coverage while optimizing mission completion rate, trajectory length, energy consumption, and information latency. Specifically, it increases coverage by 4.03%, enhances mission completion rate by 10%, improves utility by 10.96%, reduces mission completion time by 14.13%, shortens trajectory length by 26.85%, lowers energy consumption by 10.3%, and decreases information latency by 19.34%. These results indicate that the proposed method significantly enhances the adaptability and robustness of UUVs in complex environments, providing a novel optimization strategy for autonomous underwater exploration tasks.

A Real-time Motion Planning Algorithm for AUV based on IDVD Method

LIU Guoshun, GUO Wei, LAN Yanjun, FU Yifan

2025, 33(3): 473-483. doi: 10.11993/j.issn.2096-3920.2025-0033

[Abstract](43) [FullText HTML] (6) [PDF 1753KB](13)

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To enhance the intelligence of autonomous undersea vehicles(AUVs), this paper proposed a real-time motion planning algorithm based on the inverse dynamic virtual domain(IDVD) method, ensuring safe navigation in unknown environments with obstacles. In view of the limited computational resources of AUVs, a hierarchical framework was adopted to guarantee high computational efficiency for real-time planning. First, a safe global path was generated using a path planning algorithm, followed by path optimization within the sensing range of the forward-looking sonar to produce safe and feasible trajectories. Specially, for the kinematic constraints of underactuated AUVs, the hybrid A* algorithm was employed for searching safe paths based on global path search. Subsequently, a nonlinear optimization problem was formulated to enhance path smoothness and safety. The IDVD method was then applied to derive feasible velocity and acceleration trajectories of AUVs, which served as reference inputs to guide the AUVs’ navigation. Simulations and experiments on the “Stingray-II” AUV were conducted. The results validate that the proposed method is capable of efficient online trajectory planning for AUVs in unknown complex environments.

A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems

LEI Zhenkun, CHEN Mingzhi, ZHU Daqi

2025, 33(3): 484-494. doi: 10.11993/j.issn.2096-3920.2025-0032

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Investigating the applications and challenges of multi-robot pursuit-evasion problems in underwater environments holds significant importance for enhancing the autonomous decision-making and collaborative capabilities of underwater robot systems. By searching the Web of Science Core Collection database, over 2 200 relevant literatures published between 2004 and 2024 were screened, and a comprehensive analysis was conducted on the definition of pursuit-evasion problems, research status, intelligent pursuit-evasion methods, and their applications in underwater environments. The principles, advantages, disadvantages, and applicability of four intelligent pursuit-evasion methods, including reinforcement learning, model predictive control, Apollonius circle, and artificial potential field, were analyzed in depth. The study reveals that reinforcement learning optimizes strategies through training to adapt to complex environments but suffers from a long training cycle; model predictive control formulates strategies based on future state predictions, boasting high accuracy but facing real-time challenges; the Apollonius circle optimizes paths using geometric relationships; and the artificial potential field method guides robots with virtual force fields. In underwater environments, robot pursuit-evasion games confront multiple challenges, such as ocean current disturbances and limited communication. This paper summarizes the application potential and existing issues of current methods in underwater environments and proposes future research directions, including the development of more efficient and adaptive intelligent pursuit-evasion algorithms, so as to address the technical requirements of complex underwater environments and provide theoretical references for designing pursuit-evasion strategies for underwater multi-robot systems.

Ore-Collecting Characteristic Analysis of Deep-Sea Polymetallic Nodule Collection Device Based on Variable Cross-Section Flow Channel

WEI Jiakang, ZHANG Xiuzhan, LIU Xixi, LIU Jiancheng, LI Lei, CHEN Fengluo, ZHANG Tiedong, LI Hao

2025, 33(3): 495-503. doi: 10.11993/j.issn.2096-3920.2025-0044

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With the rapid advancement of deep-sea mineral resource exploitation, there is an escalating demand for enhanced technological capabilities in equipment. The design flaws of the flow channel structure caused by the complex fluid-solid coupling effect of the polymetallic nodule hydraulic collection device have significantly reduced the nodule capture efficiency, seriously restricting the commercialization process of deep-sea mining. In this paper, for the widely used dual-row jet and wall-attached jet devices, based on the shear stress transfer k-ω turbulence model and the numerical analysis method of the discrete element method(DEM), the flow field distribution, particle movement law, and the compatibility of the collection head with the variable cross-section flow channel of the two hydraulic ore collection methods were explored. The findings reveal that both collection methods exhibit increasing transport rates with elevated jet velocities, and the collection efficiency demonstrates limited sensitivity to jet velocity variations within certain ranges. Flow channel configuration emerges as the dominant factor affecting collection efficiency. The dual-row jet configuration achieves only 80% collection efficiency due to vortex-induced flow field heterogeneity, particularly at the flow channel inlet region where efficient nodule collection is impeded. In contrast, the wall-attached jet configuration demonstrates superior nodule collection efficiency of 95%, attributable to its uniform flow field distribution. Comparative analysis under identical structural dimensions and hydraulic parameters confirms the wall-attached jet’s advantages in both ore collection capacity and flow channel compatibility. This study proposes that commercial applications of dual-row jets should prioritize vortex mitigation strategies in flow channel design. The presented findings provide references for optimizing structural configurations of efficient deep-sea polymetallic nodule collection devices.

Stability Constraints of ROV-Coordinated Hole Drilling on Shipwrecks

GUO Dongjun, WANG Xuyang

2025, 33(3): 504-510, 526. doi: 10.11993/j.issn.2096-3920.2025-0037

[Abstract](40) [FullText HTML] (10) [PDF 3049KB](11)

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Remotely operated vehicle(ROV)-coordinated hole drilling on shipwrecks is a key technical component for achieving underwater drilling and oil extraction integration. Currently, research on this control scenario in the engineering field is limited, and effective methods for stabilizing the pose of ROV-coordinated hole drilling on shipwrecks are lacking. This paper addressed the pose stability requirements during the ROV-coordinated hole drilling process on a shipwreck. By drawing parallels with the stability principles of ground-based equipment, a stability criterion for ROV-coordinated hole drilling on shipwrecks was established. Based on this criterion, a thrust correction algorithm was proposed. By modifying the thrust of each thruster, the force state of the collaborative system met the stability criterion, thereby achieving the stability constraints for the collaborative system’s pose. Simulation results show that the proposed stability constraint method can effectively maintain the pose stability of the collaborative system during the operation. In terms of stability, compared with the pre-correction state, the collaborative system transitions from an unstable constraint state to a stable constraint state, fully verifying the effectiveness and feasibility of the stability constraint method proposed in this study.

Research on Near-Field High-frequency Echo Strength Characteristics of Small Undersea Vehicle

CAO Hao, ZHANG Xinze, ZHANG Jun, FAN Shuhong

2025, 33(3): 511-517. doi: 10.11993/j.issn.2096-3920.2024-0146

[Abstract](36) [FullText HTML] (7) [PDF 1386KB](13)

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In response to the need for detecting and identifying small undersea vehicles, modeling and simulation research have been conducted on the high-frequency echo strength characteristics of small undersea vehicles in the near field. This article used the plate element method to calculate and analyze the near-field echo strength of a cylindrical undersea vehicle and presented the spatial distribution characteristics of the echo strength. On this basis, a pool test was conducted to compare the consistency and variation characteristics of the measured results and simulation results. The results show that the simulation results and pool test results are consistent in spatial distribution trends, with strong echo strength at the head end face and transverse azimuth of the small undersea vehicle, and the high-frequency echo strength characteristics of the small undersea vehicle in the near field exhibits a butterfly-like distribution.

A Data-Driven Front Tracking Algorithm for Autonomous Undersea Vehicles

LU Jieyang, WEN Yongpeng, GUO Qian, ZHU Xinke, JIAO Junsheng

2025, 33(3): 518-526. doi: 10.11993/j.issn.2096-3920.2024-0151

[Abstract](35) [FullText HTML] (16) [PDF 5587KB](10)

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To meet the requirement for adaptive observation of autonomous undersea vehicles(AUVs), a data-driven ocean front tracking algorithm was designed. This algorithm constructed a hybrid temperature field prediction model based on Gaussian process regression(GPR) and particle swarm optimization(PSO). Pre-collected data was utilized as prior information to train the model. The PSO algorithm was employed to iteratively optimize the hyperparameters within the kernel function, which were then substituted back into the GPR model to obtain predictions of the adjacent temperature field. By calculating the temperature gradient values between the AUV’s current position and the predicted region, the algorithm selected corresponding temperature gradient tracking strategies based on the AUV’s different positions within the front. This allowed the AUV to maintain motion along the gradient direction or track along isotherms, enabling rapid tracking of the ocean front by the AUV. To validate the effectiveness of the algorithm, simulation tests were conducted using real ocean front data. The results indicate that compared to other methods, this algorithm exhibits superior accuracy and speed in tracking ocean fronts, thereby satisfying the demand for efficient autonomous observation by AUV.

Fuzzy Method-Based Sliding Mode Control for AUVs

LI Rongchang, BAI Huajun, ZHANG Jingxi, ZHANG Yi

2025, 33(3): 527-534. doi: 10.11993/j.issn.2096-3920.2024-0149

[Abstract](144) [FullText HTML] (53) [PDF 1441KB](24)

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Underactuated autonomous undersea vehicles(AUVs) exhibit characteristics of high nonlinearity, strong controlled variable coupling, and parameter uncertainties in their models. Meanwhile, they are also affected by unmeasurable disturbances in the marine environment, which makes it difficult to design the controller for AUVs. In addition, most existing results adopt simplified linear models of AUVs or only consider single-dimensional models. Since the strong coupling of controlled variables, the designed controllers are only suitable for simplified models and cannot be extended to the original nonlinear AUV systems. To solve the above problems, this paper proposed an adaptive sliding mode controller based on the T-S fuzzy method for underactuated AUV systems. The controller has high versatility and strong robustness and is suitable for complex AUV systems. Firstly, the T-S fuzzy modeling method was used to linearize the nonlinear AUV system with parameter uncertainties, and a global linearized model was obtained. Meanwhile, the parameters of the system that are difficult to obtain their precise values were transformed into uncertainties, and their reconstruction expressions were obtained. Moreover, it was decomposed to improve the degree of freedom of solving the controller parameters. Secondly, by considering the presence of internal actuator faults and external environmental disturbances, an adaptive sliding mode controller was designed, which could estimate unknown parameters and adaptively update the control law to stabilize the system. Finally, the stability and state reachability of the closed-loop system were ensured through the Lyapunov stability theory. Simulations verified the effectiveness of the designed controller.

Study on Effect of Tandem Charges with Different Charge Mass Ratios on Underwater Explosion Power

ZHANG Wei, GUO Rui, CUI Hao

2025, 33(3): 535-544. doi: 10.11993/j.issn.2096-3920.2024-0142

[Abstract](22) [FullText HTML] (12) [PDF 2711KB](11)

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In order to explore the influence of different charge mass ratios of tandem charges on the underwater explosion power, theoretical analysis of the impulse of the underwater explosion shock wave induced by tandem charges was carried out according to the empirical formula of the underwater shock wave, and the underwater explosion power of tandem charges with different charge mass ratios was numerically simulated. Under the same charge mass, the underwater explosion output impulse laws and the damage effects on the target structure of the tandem charge with different charge mass ratios and single charge were compared. At the same time, a scaled-down water tank test on the damage to the target structure caused by the tandem charge was carried out. The results show that when the total charge is 400 g TNT, the underwater explosion output impulse of the tandem charge structure and its effect on the target panel are obviously better than that of a single charge, and the explosion power of the tandem charge increases with the increase in the charge ratio η. When η is 1:1, the impulse gain and the deflection of the target panel are the largest, and the impulse gain is increased by 27.43%; the deflection of the target panel is increased by 23.58%. The scaled-down experiment results of small charges show good agreement with the theoretical analysis and numerical simulation results.

A Deep Learning-Based Solver for Underwater Explosion Shock Response Spectrum

WANG Shuang, LÜ Feng, MA Feng, CHEN Si, ZHU Wei, HAN Feng, HUANG Qinyi

2025, 33(3): 545-551. doi: 10.11993/j.issn.2096-3920.2024-0144

[Abstract](112) [FullText HTML] (104) [PDF 1406KB](21)

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Due to the short duration and complexity of ship shock responses, the shock response spectrum(SRS) is commonly used as a tool for analyzing these responses. To address the conflict between calculation speed and accuracy inherent in traditional SRS solving methods, this paper proposed a deep learning-based fast solver for the SRS. An adaptive threshold selection mechanism tailored to the characteristics of the SRS was designed to improve the solver’s calculation accuracy. A comparison between the SRS obtained by the proposed solver and the results calculated using traditional methods demonstrated a high degree of consistency, validating the effectiveness of the solver. Additionally, L2 regularization was introduced in the solution process, effectively preventing overfitting and further enhancing the robustness of the solver.

Influence of Beam Angle of Array Sound Source on Sound Propagation in Typical Shallow Sea Environments

LU Yanyang, CHEN Qinglang, LI Xun, WANG Zhaohong

2025, 33(3): 552-558. doi: 10.11993/j.issn.2096-3920.2024-0150

[Abstract](25) [FullText HTML] (10) [PDF 1942KB](10)

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With the development of active sonar technology, the beam output capability of active sonar has become the focus of engineering research. It is necessary to study the influence of the sound beam angle on sound propagation for a typical vertical linear array sound source. Based on the theory of normal modes in acoustics, this paper derived the expression of the sound signal for an array sound source and discovered that the sound signal was mainly affected by the following two factors: the beam output of the array sound source at each modal mode and the modal amplitude sampling at the receiving depth. Simulation results show two phenomena: a clear differential distribution structure of the sound signal in the receiving depth and a deviation of the optimal beam angle from 0° as the sound source depth increases. The paper explains the mechanism of the two phenomena based on the derived sound field formula and gives design suggestions for the optimal beam angle under different sonar transmitting and receiving position relationships in typical shallow sea environments, providing a reference for the active sonar sound beam design research and providing ideas for the rational deployment of the transmitting and receiving positions.

Intelligent Perception Algorithms for Sonar Images: A Review

JIAO Wenpei, LI Jie, ZHANG Chunyan, XIE Guangming, XIAO Wendong, ZHANG Jianlei

2025, 33(3): 559-572. doi: 10.11993/j.issn.2096-3920.2024-0127

[Abstract](106) [FullText HTML] (36) [PDF 756KB](33)

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Intelligent perception algorithms for sonar images are vital in ocean exploration and underwater rescue. In recent years, deep learning has achieved remarkable advancements in intelligent perception tasks related to sonar images. This paper provided a comprehensive review of the field, focusing on sonar image datasets and data augmentation techniques, classical sonar image processing algorithms, and deep learning-based sonar image processing methods. By summarizing open-source datasets and commonly used data augmentation techniques, the paper provided data support for future research efforts. Additionally, this paper systematically analyzed the application and evolution of both classical and deep learning-based algorithms across various tasks, offering researchers an overview of the current state of the field. Finally, based on the research progress, the paper predicted future research directions. It was pointed out that the interpretation ability of sonar images could be further improved by obtaining larger-scale sonar image data, designing more robust algorithms, and developing task settings that are more suitable for real-world underwater environments.

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2025, Volume 33, Issue 3

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Current Issue 2025, Volume 33, Issue 3

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Current Issue
2025, Volume 33, Issue 3