Amphibious vehicle is a mobile platform capable of operating in both terrestrial and aquatic environments,and has significant application value and development potential in both military and civilian fields.The development history of amphibious vehicles is reviewed,and the characteristics and development trends of different types of amphibious vehicles are compared and analyzed.The key technologies for the navigation of amphibious vehicles on water are expounded from three aspects:modeling and simulation,high-speed amphibious vehicle design,and navigation control.The difficulties and challenges in achieving the unmanned operation of amphibious vehicles on water are discussed based on the research progress of unmanned technology for amphibious vehicles,and the future research direction of amphibious vehicles is prospected.

For the cooperative guidance issue of high-hypersonic re-entry gliding vehicles to simultaneously hit a target at a specified angle in a complex environment,a cooperative guidance law based on meta-learning and reinforcement learning algorithms is proposed.Considering the interference caused by complex combat environment,a Markov decision model for the cooperative guidance issue is established,taking the gliding vehicles’ motion status and proportional guidance factor as the state space and action space.A reward function is designed by comprehensively considering the vehicle-target distance,remaining flight time difference,and overload situation for multiple gliding vehicles attacking a target.Based on meta-learning theory and reinforcement learning algorithm,the proximal policy optimization algorithms are combined with the gated recurrent units to learn the common features of similar cooperative guidance tasks.This approach enhances the accuracy of cooperative guidance strategies in complex interference environments to achieve the constraints on angle of attack and attack time,while also improving the adaptability of cooperative guidance strategy to different combat scenarios.Simulated results indicate that the proposed cooperative guidance law enables multiple aerial vehicles to simultaneously attack a target at a specified attack angle in complex battlefield environment and quickly adapt to new cooperative guidance tasks.The cooperative guidance law maintains good performance even when the cooperative combat scenario changes.

A multi-dimensional enhanced particle swarm optimization algorithm (MDEPSO) is proposed to address the problem of insufficient global search capability and susceptibility to local optima in the 3D trajectory planning process of unmanned aerial vehicles using classical particle swarm optimization algorithms.This algorithm first introduces improvement factors to dynamically adjust inertia weights in various stages of particle optimization,enhancing population adaptability and overcoming local optima; Secondly,relying on dynamic constraint equations to enhance learning factors promotes more efficient information sharing between particles and improves the algorithm’s self-learning ability; Subsequently,the advantages of orderly integration of chaos initialization and elite reverse learning evolution strategies were utilized to re plan the particle swarm evolution process,enhance the balance and diversity of particles in the iterative process,and improve the convergence accuracy of the algorithm.In the experiment,through horizontal comparison of test functions and vertical application in complex 3D task scenarios,the multi-dimensional enhanced particle swarm optimization algorithm showed an improvement in the UAV trajectory planning ability compared to the classical particle swarm algorithm in the new multi-dimensional objective function indicators.It demonstrated good effectiveness and competitiveness among the five comparison algorithms.

During the vertical movement underwater,vehicles are highly susceptible to the marine environment,leading to unstable motion postures. Uncontrolled and unpowered launching has become inadequate in deep water and strong disturbance conditions. PID control,dynamic fluid body interaction,and dynamic nesting/sliding mesh techniques were employed to construct an integrated numerical calculation method that couples fluid dynamics,motion,and control in this paper. The motion process of underwater controlled-propulsion vehicles,analyzing the evolution of tail cavitation and ballistic characteristics under different tail jet pressures(6 MPa,10 MPa,12 MPa)were numerically simulated. The results show that during the merging process of supersonic jets and tail cavitation,the tail gas mass breaks due to interface instability and nozzle swaying,with the break occurring earlier as nozzle pressure increases. Inside the tail spray cavitation,a complex wave system structure exists. At higher nozzle pressures,the jet is under-expanded,resulting in multiple high and low-pressure areas formed by expansion and compression within the gas bubble. Over time,a Mach disk perpendicular to the axis appears near the nozzle exit. Additionally,the larger the nozzle pressure,the greater the disturbance torque caused by the tail spray flow. Increasing the nozzle pressure from 6 MPa to 12 MPa reduces the maximum deviation angle during motion by 18.5%,decreases the overshoot from 32% to 22%,resulting in less attitude fluctuation and better ballistic stability.

The near-space hypersonic gliding vehicle (HGV) poses a significant threat to existing defense systems due to its ultra-high velocity,extreme maneuverability,and superior penetration capabilities.To address the challenges in tracking and predicting HGV trajectories during interception,this paper presents an intelligent trajectory prediction method based on aerodynamic acceleration estimation.The maneuver patterns and aerodynamic variation laws of HGV are systematically analyzed according to the HGV motion model.On this basis,three critical parameters,i.e.,aerodynamic lift acceleration,drag acceleration and bank angle control,are identified as trajectory prediction variables for replacing the unknown terms in the HGV motion model.A dynamics tracking model based on aerodynamic acceleration estimation is developed to use the radar measurement data and the unscented Kalman filter (UKF) for real-time tracking and estimation of these parameters.These estimated parameters are then used as inputs to train a long short-term memory (LSTM) network,which captures the temporal relationships and variation patterns in the prediction parameters.The trained LSTM network is used to iteratively forecasts future aerodynamic accelerations,which are integrated with the numerical solutions of motion equations to extrapolate HGV trajectories.Numerical simulations confirm that the proposed method achieves high prediction accuracy and robust stability in predicting the trajectories of non-cooperative HGVs.

To optimize the fuel economy of the series hybrid tracked vehicle and reduce the offline training time of neural network,an energy management strategy (EMS) based on double-deep Q_learning network (DDQN) algorithm with Munchausen gradient optimization and prioritized experience replay (Munchausen-PER-DDQN) is proposed.The required power is calculated by a vehicle model which involves the engine-generator set,the battery pack and drive motor,and then the peoposed strategy is used to optimally control the throttle opening of engine based on power demand.The Munchausen gradient optimization algorithm adds log-policy to the reward to ease the learning of sub-optimal actions,and the prioritized experience replay algorithm assigns higher selection possibility to certain experience for those who have more influence on the training of the algorithm,Tthe energy management strategy based on Munchausen-PER-DDQN algorithm shows a better performance of fuel economy and training time of neural network.The simulated result shows that,compared with TD3-PER algorithm,the Munchausen-PER-DDQN algorithm achieves 35.3% improvement in neural network training time and 4.6% improvement in the fuel economy.

The launching mechanism of submarine-launched missiles under polar underwater environments is studied. The Arbitrary Lagrangian-Eulerian (ALE) method and the smoothed particle hydrodynamics (SPH) method are used to establish the fluid and infinite whole ice models, respectively, based on finite element software, and a plastic compressive tension material model with equation of state is used to reproduce the sensitivity of mechanical properties of ice to stain rate. Consequently, a fluid-structure interaction model of underwater vehicle ice-breaking is built. Based on the validated key numerical methods, the load and collision force characteristics of underwater vehicle under different ice thicknesses and vehicle speed conditions are investigated by simulation. and the stress distributions of vehicle and ice in the process of ice-breaking are analyzed. The result shows that the load and interaction time imposed on the vehicle increase with the increase in ice thickness, and with the increase in vehicle speed, the loads imposed on the vehicle increase, and the interaction time decreases.

In order to ensure the safety of unmanned underwater vehicle (UUV) when performing the complex tasks such as coastline patrol, collision avoidance of large vessels, and traversing dense islands and reefs, an elliptical modeling obstacle avoidance method based on control barrier function (CBF) is proposed. A control barrier function containing the heading angle constraints is designed on the basis of elliptical modeling obstacles, a quadratic programming (QP) problem with constraints is constructed, and a closed-form obstacle avoidance guidance law is proposed by combining with the guidance law in obstacle-free environment. The simulated results verify the effectiveness of the proposed method, which globally satisfies the safety and stability requirements. The proposed method has practical application value for the safe navigation of unmanned underwater vehicle in complex marine environment.

Aiming at the strong nonlinear problem of the interaction between underwater-launched projectile and ice, the key dimensionless parameters affecting the ice-breaking of projectile are derived by similarity theory. The scaled model test is carried out for the high-speed penetration of projectile through the ice layer. Based on the Gaussian fitting function, an ice load prediction formula is proposed. A fluid-solid coupling model of ice-breaking is established. The ice-breaking phenomenon, the ice load and the motion characteristics of projectile are analyzed by changing the nose shape of projectile, the kinetic energy of projectile and the thickness of ice layer. The results show that the volume of projectile nose cavitation decreases during ice-breaking, the volume of shoulder cavitation gradually increases, and the asymmetry of shoulder cavitation increases with the increase in ice thickness. When the initial speed of projectile is 40m/s, the extreme values of the ice loads on projectiles with hemispherical, spherical conical and pointed conical noses are 35700kN, 33200kN and 18600kN, respectively. The speed loss rate of projectile with pointed conical nose is the lowest, and its ice breaking effect is the best. Under the condition that the ice thickness is 180mm and the ejection pressure is 3MPa and 5MPa, respectively, the speeds of projectile after icebreaking are reduced from 13.1m/s and 17.8m/s to 9.5m/s and 13.4m/s. The greater the ice-breaking speed of projectile is, the lower the speed loss rate is, and the greater the kinetic energy loss is.The extreme value of ice load and the speed loss rate of projectile increase with the increase in ice thickness, and the effect of the initial speed of projectile on the load characteristics and motion characteristics weakens with the decrease in ice thickness.

The influence of the free surface on the shape of supercavitation and the hydrodynamic characteristics of underwater vehicle is investigated. The motion process of a supercavitating vehicle near the free surface is numerically simulated using an adaptive mesh method and the volume of fluid method, and the effects of the free surface on the shape of supercavitation, and the lift, resistance and torque of the vehicle are analyzed. The research findings show that the presence of the free surface causes the tail of supercavitation to shift away from the free surface, resulting in the length of supercavitation being significantly shorter than that in an infinite water domain. The velocity of vehicle has a significant impact on its lift near the free surface. When the velocity of vehicle is less than 50m/s, its lift is negative; when the velocity of vehicle exceeds 60m/s, its lift becomes positive. When the vehicle is fully enveloped by the cavitation, only the cavitator head is wetted. A zero-torque point always appears near the front (x=1D, where D is the diameter of the cavitator) of the vehicle. When the interface of supercavitation tail intersects with the vehicle, it causes a change in the position of the zero-torque point. When the attack angle of the vehicle is positive, the torque is less affected by the water depth. However, when the attack angle is negative, the torque is significantly influenced by the water depth.

A motion parameter estimation method based on acoustic measurement is proposed for identifying the kinetic characteristics of high dynamic underwater vehicle. In the proposed method, the position and velocity data series are obtained by point-by-point solution, and then the data jitters caused by random errors are removed by functional reconstruction and coefficient identification, so a smooth and continuous parameter sequence is obtained. In simulation, the high dynamic underwater vehicle moves from the depth of several tens of meters to surface, and the motion parameter is measured by the seabed four-receiver array. The simulated results show that the estimated parameter sequence has higher accuracy in vertical direction than the point-by-point solved one, and the root mean square errors (RMSE) of position and velocity are reduced by 27.8% and 47.2%, respectively. Calculations based on large samples indicate that the estimated parameter sequence approaches the true value, and the deviations of position and velocity are 0.042m and 0.056m/s, respectively. The water-tank test results show that the estimated parameter sequence generated by the high dynamic physical model is well consistent with the inertial sensor data, and the RMSEs of position and velocity in vertical direction are 0.024m and 0.141m/s, respectively. The proposed method can provide an accurate, smooth and continuous parameter sequence for the high dynamic underwater vehicle in performance testing and has certain engineering application value in sea trials.

In order to effectively identify the visual and auditory channel workloads of operators during the operation of a special vehicle, a machine learning-based workload recognition model is constructed from the electroencephalogram (EEG) signals acquired in a simulated driving environment. A total of 30 participants were recruited for experiment, and the visual and auditory workload states were induced by increasing the scenario complexity and administering an auditory N-back task. The experimental results show that, the power spectral densities in δ, θ, and α bands in the frontal lobe, δ and θ bands in the temporal lobe, θ band in the occipital lobe, and all four frequency bands in the parietal lobe under the auditory workload condition are significantly higher than those under the visual workload condition. Moreover, the brain network has a stronger connectivity at θ and β bands under the auditory workload condition exhibites. Notably, the θ-band power spectral density (PSD) emerges as the most effective feature for the identification of visual and auditory workload channels, enabling the random forest algorithm to achieve a maximum classification accuracy of 95.68%. Shapley additive explanations (SHAP) analysis indicates that the frontal lobe contributes most significantly to the classification outcomes. These findings demonstrate the effectiveness of EEG-based indicators in identifying the visual and auditory channel workloads, providing a theoretical foundation for the development of adaptive interaction systems.

In order to improve the obstacles avoidance ability of intelligent vehicles,an trajectory planning and control method of intelligent vehicles is proposed based on velocity obstacle model.The proposed method is used to establish a velocity obstacle model for intelligent vehicles by combining the velocity obstacle method and obstacle expansion method,The motion uncertainty of dynamic obstacles in the velocity space is transformed into the positional uncertainty,and the safety margin is adaptively adjusted by obstacle size and relative velocity.To balance trajectory tracking accuracy and driving stability,a fuzzy model predictive controller (FMPC) is designed based on the equation of state for vehicle,the fuzzy control principle and the model predictive control principle.A simulation model is established to verify the effectiveness of the proposed method.The simulated results show that the proposed method can be used to avoid the multiple random static and dynamic obstacles,and the reference trajectory can be quickly and smoothly tracked after obstacles avoidance.Based on the analysis of obstacles avoidance stability,it is concluded that the target speed is 100km/h,the maximum lateral speed is 4.01km/h,the maximum yaw rate is 20.8°/s,and the maximum centroid side slip angle is 2.32°,which meet the requirements of driving stability.The proposed method effectively improves the obstacle avoidance ability and driving stability of intelligent vehicles.

Due to the characteristics of hypersonic glide vehicles (HGVs) being unpowered and uncontrollable in axial overload,a significant positional error of HGV often exists at the transition between the gliding phase and the terminal phase,thereby substantially impacting the precision of coordinated strikes during the terminal phase.To address this issue,a formation control method for HGVs is proposed,which considers the capability of adjusting the position in launch direction.Fixed-time consensus controllers are devised for the second-order multi-agent system,serving as the foundation for an underactuated formation control framework.The underactuated control characteristics of HGV formation is analyzed.An adjustment strategy for HGV position in launch direction is formulated,and an analytical relationship between launch-direction position adjustments and additional lateral velocity is established.After enabling the capability for launch-direction adjustment,a three-dimensional artificial potential field is established,and a collision avoidance control strategy for HGV formation is proposed.Theoretical analysis and numerical simulations demonstrate that the proposed method can support the formation and maintenance of a group of HGVs in scenarios such as dispersion,contraction,collective steering,and high and low flying of formation.

At present,the traffic management relying on manpower is characterized by inaccurate statistics and delayed feedback.A vehicle detection algorithm based on the improved YOLOv7-tiny algorithm suitable for deploying on edge terminal devices is proposed to better protect people’s lives and property.A deep powerful residual (DP_Res)convolutional block isconstructed to perform the lightweight improvements on the efficient layer aggregation network-tiny (ELAN-T) module of backbone network.By reducing branches,the lightweight improvement on the ELAN-T module of the feature fusion network is made to reduce the number of parameters and computational load of the network,and the structure of the feature fusion network is reconstructed;The efficient channel attention mechanism and the EIOU bounding box loss function are introduced to improve the accuracy of the algorithm.The experiment is conducted on the preprocessed UA-DETRAC dataset,and the parameters of the improved algorithm are reduced by 15.1% compared to those of the original YOLOv7-tiny,with a reduction in computation of 5.3% and an increase in mAP@0.5 of 5.3 percentage points.The experimental results show that the improved algorithm not only achieves lightweight,but also improves the detection accuracy,making it suitable for deployment on edge terminal devices to complete the task of detecting vehicles on the road.

The high-power diesel generator set for vehicles is the power supply unit of heavy-duty series hybrid electric vehicles.Due to the coupling effect of the torque impact of multi-cylinder diesel engine crankshaft and the electromagnetic torque pulsation of generator,the system torsional vibration phenomenon is prominent,and the dynamic quality is poor.A dynamic model of engine-generator set considering the electromechanical coupling effect is established,and the influence of electromechanical coupling effect on the inherent characteristics of the system is analyzed.The law of variation of torsional vibration characteristics with the parameters,such as electromagnetic stiffness,rotor eccentricity and torsional damper stiffness,is revealed.The dynamic response characteristics of the system under the combined excitation of engine and motor are analyzed,and the order of the main response is clarified.A torsional vibration control overall framework based on dual loop decoupling is proposed to solve the problem of excessive low-frequency torsional vibration response.An independent modal space optimal controller for the start stop process and an adaptive filtering compensating controller for steady-state operating conditions are designed for the suppression of engine main harmonic disturbances,and are verified through simulation.The results show that the proposed torsional vibration active control algorithm can achieve the suppression of main harmonic torsional vibration in the full speed domain of the engine.

The recovery device carried outside the vehicle is susceptible to the interference from flow noise and has an effect on the acoustic stealthiness of underwater vehicle during the acoustic guidance.Regarding the aforementioned problems,this paper numerically simulates the flow noise of underwater vehicle based on Lighthill acoustic analogy theory and large eddy simulation (LES),compares the sound pressure level spectra and directivities of different shaped docking stations,and analyzes the sound pressure levels at different locations in the basin.The results show that the outboard recovery device is the main source of the radiated noise,which is about 50 dB higher than the maximum sound pressure level of the non-attached underwater vehicle,and the high sound pressure level is mainly concentrated between the middle and low frequencoes.For the recovery dock with the same profile areas,the maximum sound pressure level of horn-shaped guide housing is 1.62dB lower than that of the rectangular guide housing.The results can provide theoretical reference for reducing the flow noise during the process of underwater vehicle recovery and improving the recovery efficiency and acoustic stealth of underwater vehicle.

Stable and high-precision localization is a prerequisite for realizing the cooperative autonomous navigation of unmanned ground vehicle (UGV).LiDAR simultaneous localization and mapping (SLAM) often fails to achieve the precise localization in scenarios lacking geometric features,such as corridors,tunnels,and deserts.Therefore,a leapfrog cooperative LiDAR SLAM degradation correction method is proposed for UGVs.This method is used to estimate the normal vector of each feature point in the current frame,and a LiDAR SLAM degradation detection algorithm is devised.When the degradation of environment is detected,the ranging information about two unmanned vehicles is utilized to correct the degradation in LiDAR SLAM.Finally,the locating results are further optimized in the pose graph.Testing on two self-built UGV platforms reveals that the proposed method achieves better mapping performance compared to the current famous LiDAR SLAM methods,demonstrating its significant capability to enhance the locating performance of LiDAR SLAM in degraded scenarios.

The control strategy of traditional tank bidirectional stabilizers is difficult to effectively deal with the coupling,nonlinearity and uncertainty in the new generation of all-electric bidirectional stabilizers,while the model-based nonlinear control can make full use of a priori information from the dynamic model of the system to enhance the control effect.Based on this,an electromechanical coupled dynamics model of an all-electric bidirectional stabilizer taking the actuator dynamics into account is established,and a nonlinear sliding mode control method based on neural network compensation is proposed.The sliding mode surface and the improved sliding mode robust control law based on hyperbolic tangent function are introduced to construct the nonlinear sliding mode control function,which can effectively eliminate the system oscillations and improve the system stability.Meanwhile,the multilayer neural network technique is deeply fused to accurately estimate the uncertainty in the system and make compensation for the feedforward,thereby avoiding high-gain feedback.It is rigorously demonstrated by the stability theory based on Lyapunov functions that the proposed control strategy can achieve the asymptotic stability performance of tank all-electric bidirectional stabilizer with continuous control inputs.A co-simulation environment and a semi-physical experimental platform are built.The superiority of the proposed control strategy is verified through a large number of comparative experiments.

Lubricating oil plays a pivotal role in engines due to carrying a wealth of information about the engine state,and is crucial for characterizing the faults of engine.The engine of an armored vehicle is studied,and a fault diagnosis method for the engine is proposed,which leverages the kernel linear discriminant analysis (KLDA) and an improved dung beetle optimization (DBO) algorithm to optimize a back propagation (BP) neural network.The dimensionality reduction of the acquired lubricating oil data is performed through KLDA,and the dimensionality reduced data is taken as input for the BP neural network.The DBO algorithm is then enhanced by integrating optimal Latin hypercube sampling method,weighting factors and Levy flight strategy in order to further optimize the key parameters of neural network.A fault diagnosis model is established to predict the faults in test data effectively.Experimental results affirm the proposed method’s efficacy in rapidly and accurately predicting the faults,providing a scientific basis for the maintenance and repair of engines in armored vehicles.

Addressing the uncertainty of dynamic model parameters in the terminal guidance phase of hypersonic gliding vehicles and the slow convergence speed of traditional reinforcement learning algorithm,an adaptive guidance algorithm based on reinforcement learning is proposed.The terminal guidance problem for hypersonic gliding vehicles under nominal conditions is converted into an optimal control problem,which is solved using the sequential convex optimization algorithm to generate a dataset of state-control pairs.The dataset is fitted through supervised learning to obtain a corresponding guidance model.The disturbances such as aerodynamic parameter deviation,uncertainty in control response delay coefficient,and state measurement noise are introduced,and the guidance model is further optimized based on the reinforcement learning framework through numerous interactions between the vehicle and the current environment.Numerically simulated results indicate that the proposed guidance method exhibits better robustness and accuracy compared to the supervised learning guidance method.

The high-speed electromechanical transmission(EMT) system for vehicle is characterized by a highly compact structure and high-speed components,leading to significant electromechanical coupling effects and susceptibility to resonance.This paper analyzes the electromechanical coupling inherent vibration characteristics of a series EMT system.An inherent vibration model of the system is derived,its natural frequencies and mode shapes are studied,and six typical vibration modes of the system are summarized based on the characteristics of each mode shape.The influences of high-speed operating conditions and electromechanical coupling effects on the system’s natural frequencies and mode shapes are investigated.The resonance speeds of the system within a wide operating speed range are studied using Campbell diagrams and modal energy method.The results indicate that the electromechanical coupling effects alter the low-frequency vibration characteristics of the system,and the high-speed operating conditions can significantly change the certain natural frequencies of the system.Both factors should be fully considered in dynamics modeling.The research of resonance speed provides a reference for the dynamic regulation and optimization of system.

As the potential applications and strategic value of unmanned ground vehicles(UGVs)in complex operational environments become increasingly prominent,the safety of their autonomous actions is of paramount importance.This paper proposes a system safety analysis method for UGV,which combines the system-theoretic process analysis(STPA)method and the Bow-Tie model.Focusing on the safety of teleoperated UGVs,the STPA method is utilized to identify the unsafe control actions(UCAs)within the UGV system and their associated latent risks.Subsequently,the Bow-Tie model is utilized to analyze the event chain from loss causation scenarios to potential accident consequences,thereby delineating the risk propagation and diffusion pathways.Ultimately,the active and passive safety stratified control measures are determined based on the Bow-Tie analysis,and the system safety management is realized through an autonomous safety controller.

Reforming the current manned tracked vehicles into the unmanned tracked vehicles is one effective way to develop the unmanned tracked vehicle.To this end,a data acquisition system is designed to collect the vehicle state and driver’s operation data.Based on the collected data,the driver’s steering behaviors during the tracked vehicle’s operation are clustered and analyzed based on the Gaussian mixture model(GMM),and a steering control behavior model is established.Based on different steering categories from GMM,a prediction model for the driver’s steering operation is trained by taking the running speed and steering angle deviation of vehicle as model inputs and the turning angle of hydraulic motor swinging arm as the predictive truth value of steering control.The proposed predsiction model is used for the statistical modeling and prediction of driver steering behavior in the in real cross-country environment.Experimental results show that the proposed steering control model can predict the driver’s steering behavior accurately.

Skid-steering wheeled vehicle has a wide range of applications. Understanding the impact of drive system on the vehicle driving and steering performance is the basis for forward design. In response to the design and analysis requirements of hydraulically-driven skid-steering wheeled vehicle, a coupling simulation model of hydraulic drive system and vehicle dynamics system is established based on the principle of the hydraulically-driven skid-steering wheeled vehicle systems. Combined with the specific vehicle parameters, the characteristics of the vehicle driving and steering conditions are simulated and analyzed to obtain the dynamic response characteristics of hydraulic driving system during vehicle driving. The simulated results of the model are verified through the actual vehicle. The results show that time-varying parameters such as road resistance, vehicle speed and driver operation have a great impact on the pressure of hydraulic driving system, which is strongly related to the dynamic steering resistance. The coupled simulation model can be used for the coupled simulation of vehicle motion state and hydraulic driving system state and the coupled analysis of hydraulic driving system characteristics and vehicle dynamics characteristics.

Unmanned surface vehicles (USVs) have high mobility,strong concealment,and extensive operational range,making them highly suitable for performing a wide array of tasks such as reconnaissance,anti-submarine warfare,search and rescue.Environmental perception technology,crucial for the operation of USVs,has attracted considerable attention.This paper conducts a survey on the development status of environmental perception technology for USVs at abroad,and define and analyzed the challenges in USV environmental perception through specific case studies.The current state of research on USV environmental perception technology is analyzed from the perspectives of both unimodal and multimodal perception,considering the sensory equipment utilized by USVs.Finally,the unresolved challenges in USV environmental perception technology are summarized,and its future development is prospected.

Time series matching technology is widely used in vehicle handling consistency evaluation.An evaluation method of vehicle throttle control action consistency based on segmented dynamic time warping (DTW) is proposed for the motion consistency evaluation of a coach vehicle in the process of cooperative driving.On the basis of the inconsistent number of sample data points in the cooperative control test of coach vehicle and the slope constraint of dynamic bending path, the traditional DTW rectangular search area is transformed into a parallelogram search area to reduce the area of the search area by changing the slope of search path, thus greatly reduce the calculation amount.Four groups of typical throttle action curves are selected to carry out 50 rounds of iterative experiments for verification, and the DTW distance matrix between the action curves of real vehicles A and B is calculated by segmented DTW method.A minimum deviation leveling method is used to combine the cluster objects for the actions of vehicles A and B, so as to complete the consistency evaluation of throttle action data.The experimental results show that the average matching accuracy of the improved DTW algorithm in each throttle action can reach 89.2%, which is about 3.2% higher than that of the single DTW algorithm, and the average matching time is about 92.45s, which is about 12.6% lower, thus verifying the feasibility and superiority of the segmented DTW algorithm in the consistency evaluation of throttle action.

Taking the external disturbances caused by the uneven road surfaces of marching tank gun control system (TGCS) and the unbalanced moment of tank gun elevation motion during TGCS operationinto consideration,a two-axis coupled two-degrees-of-freedom (2-DOF) dynamics model of the marching TGCS is established using the second kind of Lagrange method. In terms of the actual force and motion state of TGCS,an electromechanical coupling dynamics model is established for the marching TGCS, which is equipped with permanent magnet synchronous motors (PMSM) in the azimuthal and elevational direction drive system and the gear reduction gearboxes and roller screws in the transmission mechanism. A stable tracking controller for marching tank with finite-time convergence characteristicsis designed to quickly reject the effects of internal and external disturbances of the marching TGCS on the stable tracking of target. This design is based on a nonsingular fast terminal sliding mode (NFTSM) control law and a linear extended state observer (LESO). The stability precision and arrival time of TGCS for marching tank are calculated based on the stable tracking process for targets. The computational results are then compared with those obtained by utilizing traditional control methods under various operating conditions. The findings demonstrate that the proposed tracking controller exhibits rapid response speed,strong robustness against disturbances,and high tracking accuracy,thereby validating the effectiveness of the controller design.

To improve the mobility performance of off-road vehicles, this paper proposes a swing-cylinder hydro-pneumatic suspension system, which utilizes a high-pressure pneumatic principle and a back-pressure adjustable damping valve structure for the real-time adjustment of stiffness and damping characteristics. The vibration responses achieved by different stiffness control methods are comparatively analyzed using a single-wheel suspension model, and the fixed-point equations are derived for frequency-domain damping properties.A graded stiffness adjustment strategy and a frequency-domain hybrid damping control method are proposed. The effectiveness of the proposed method is verified through a single-wheel suspension dynamics model, and a high-mobility tracked vehicle dynamics model is established for the simulation analysis of a full-vehicle. The results show that the driving speed of off-road vehicle with the suspension employing the combined stiffness and damping control is increased by more than 25% compared with that of off-road vehicle with the traditional passive suspension under the actual road conditions of Kangzhuang, Yangbajing and Tuoli. These findings demonstrate the superior vibration suppression capabilities of the proposed control method, supporting the adaptive regulation of stiffness and damping characteristics of suspension system.

With the goal of addressing the challenges of real-time observation and localization of high-value military vehicles on the ground, a real-time algorithm for the detection and localization of military vehicles in aerial photography is proposed. An Armed_vehicle dataset for the detection of multi-type and multi-scale military vehicles in an actual combat environment in aerial photography is established. The detection accuracy reaches 85.82% and the detection efficiency is higher by introducing a large kernel attention (LKA）module into the lightweight neural network model YOLOX-Tiny and using the SIoU edge regression function. A monocular visual localization algorithm based on the visible light images from the unmanned aerial vehicles (UAVs) is proposed. The average target localization error is 3.69 m at a flight altitude of 100 meters. It indicates that the proposed algorithm can accurately obtain the geographical location of ground targets and has good comprehensive performance and application prospects.

The key parts of vehicle occluded due to complex backgrounds and variations in vehicle posture can not be accurately identified in images. A detection method based on partially deformable object graph convolutional network (PDO-GCN) is proposed for detecting the occluded key parts of vehicle. This method is founded on the rigid body structural relationships of vehicles, constructing a spatial association model between key parts on the 2D imaging plane based on PDO-GCN, and utilizes the detected results of visible key parts to estimate the locations of occluded ones. Experimental results demonstrate that the PDO-GCN model can effectively infer the complete vehicle structural information without the need for complex annotations, significantly improves the detection accuracy of occluded parts and fulfils the real-time requirements, thus showcasing considerable potential for practical application.

The formation keeping, reconfiguration and transformation functions of unmanned ground vehicle (UGV) formation systems are studied A hybrid leader-follower strategy is proposed to reduce the dependence on the leading vehicle and ensure the formation integrity. An independent obstacle avoidance function based on vehicle-to-vehicle (V2V) communication for the following vehicles is developed, and a formation node management system is designed manages the attributes of formation members in real time and supports the human-computer interaction. A dynamic extended trajectory planning method with cubic spline curve in three-dimensional space is proposed to generate the following trajectory and realize the obstacle avoidance by acquiring the position information of the front vehicle through V2V communication. The Frenet coordinate system is utilized to decouple the distance keeping and trajectory tracking problems, and the proportional-integral-differential (PID) controller and linear quadratic regulator (LQR) controller are used for longitudinal control and lateral trajectory tracking, respectively. The research results show that the performance of the proposed method can be quickly verifued in the simulation environment built, showing that the method has good performance. And the three functions of the vehicle formation system are verified by real vehicles, and the proposed method is confirmed to have good real-time performance through the stable maintenance of the distance between the vehicles, which is capable of realizing the effective following of the multi-vehicle formation, and shows a high degree of intelligent expansion and adaptability through the transformation of multiple formation shapes as well as the scenarios of members' joinning and departuring from the vehicle formation.

Mines,improvised explosive devices and roadside bombs have become serious threat to vehicle-mounted howitzers(VMH),and the blast wave generated by mine explosion can also cause damage to the cab structure of VMH and endanger the life safety of crew. Because of the significant difference in the response of the shock wave generated by the mines explosion at different positions at the bottom of the cab,numerical simulation of the response process of the cab bottom of VMH under six explosion-shock conditions was carried out. ALE algorithm was used to establish models of soil,air and explosive,and Lagrange algorithm was used to establish the models of cab and chassis of VMH,and the fluid-solid coupling algorithm was used to calculate the propagation process of the explosion-shock wave,as well as the dynamic response of the cab of VMH in this process. The changes of shock-wave pressure,acceleration and velocity at the bottom plate of the passenger's foot position were analyzed,and the maximum shock-wave pressure,acceleration and velocity at the bottom plate of the passenger's foot position were obtained,and the damage to the cab structure under the worst-case operating conditions was analyzed. The simulation results show that the shock wave generated by the mine will make the cab floor produce greater acceleration and speed,and the cab structure will be damaged. In this case,the passengers will be injured. It is necessary to add a protective structure for the cab of VMH. The simulation results can provide reference for the design of cab protective-structure of VMH.

In order to expand the application scope of folding wing UAV and extend the information acquisition ability of underwater platform,an underwater vehicle scheme of carrying UAV for dry launch was proposed by combining the advantages of UUV and UAV. In order to better evaluate the feasibility of launching UAV on the sea,the computational fluid dynamics simulation software StarCCM+ was used to simulate the launching environment of UAV on the sea,and the floating and launching process of UAV was simulated in the simulation environment. The air-bag scheme and the propeller scheme were designed respectively by referencing foreign design experience,and the different sea-conditions,different structural-parameters and attitude parameters were simulated and evaluated,and finally the launching process was simulated under the sea conditions. The results show that the UAV carrier in the state of zero buoyancy underwater can float stably on the water surface under different sea-conditions by the air bag scheme and the propeller propulsion scheme. In terms of UAV launch,the difference between the maximum sinking distance of the air-bag scheme in still water and sea conditions is about 2.5%,and the consistency is better than the error level of the propeller scheme of 30%. The average maximum sinking-distance of the vehicle during the launch of UAV is 0.28 m,which is lower than 0.4 m of the propeller propulsion scheme. In a comprehensive comparison,the air-bag scheme is more stable and reliable.

The trajectory design of air-launched vehicle is limited by many factors such as load,carrier safety,attitude control capability,etc. In order to solve the trajectory optimization problem under complex and multi-constraint conditions,an optimize method considering the crossing distance,maximum load and maximum control capability constraints was proposed. The crossing distance model and load calculation model of the aircraft and launch vehicle were established. By transforming the above model into process constraints and introducing them into the trajectory optimization problem,the pseudo-spectral method was used to solve the trajectory optimization problem,so as to realize the rapid optimization of the ascent trajectory of the air-launched launch vehicle under multiple constraints. On this basis,the typical parameters affecting the rocket crossing distance and maximum load in the trajectory design were sorted out,and the constraints between the parameters were analyzed. The simulation results show that the method can realize the trajectory optimization of the ascent phase of the air-launched vehicle under multiple constraints,and provide a reference for the development of the air-launched vehicle. From the point of view of reducing the maximum flight load of the rocket and improving the overall performance,the air-launched vehicle should be launched at a high altitude. After the launch,the angle of attack should be adjusted to the maximum at the maximum angular rate to ensure that the rocket can quickly pass through the dense atmosphere. At the same time,the crossing distance should be shortened as far as possible to avoid the acceleration of the rocket at low altitude.

To investigate the ventilated cavity flow characteristics of the vehicle water entry with gas jet cavitator,experiments of the vehicle water entry with gas jet cavitator were performed. The formation and development of the open cavity in the process of water entry were analyzed,and the effects of different ventilation rates and water entry angles on the cavity shape and gas jet length were discussed. The results indicate that there are different flow regions(i.e.,disturbance region,transition region,and the cavity develop region)during the formation of the open cavity,and it is related to the position of the vehicle. After the vehicle penetrates the air-water interface,the cavity surface(gas-liquid interface)exhibits the K-H instability significantly due to the viscous shear flow. The cavity collapse phenomenon was observed under the low ventilation coefficient. As the vehicle penetrates the water surface,the cavity diameter and gas jet length decrease gradually. The open cavity depth,cavity diameter and gas jet length increase linearly with the ventilation coefficient. The affect of the water entry angle is limited.

To solve the problem of optimal ascent trajectory design in case of small thrust-weight ratio of launch vehicle’s last stage,and send payloads into orbit with much less velocity loss and propellant consuming,a new trajectory design method based on more accurate line-gravity field was proposed by simplifying yaw program angle and co-states,which transfered the optimal thrust direction in vacuum flight into a two-point boundary value problem containing five constraints,and got the optimal trajectory by integrating motion equations. Furthermore,the initial values of iteration were analyzed according to launch vehicle’s flight features,and an estimation method of initial values of co-states and flight time was deduced,and a means and process of launch vehicle trajectory design in whole ascent flight based on linear-gravity field was put forward. The simulations show that this method generates the same results with the conventional method in situation of normal thrust-weight ratio,and pitch program angle varies nearly linearly. In situation of small thrust-weight ratio,this method generates much less velocity loss,saving 2.9% and 2.1% propellant compared with the conventional method and iterative guidance respectively,and pitch program angle varies non-linearly. This method is of good convergence and optimization effect,and can be well applied in trajectory design of small thrust-weight ratio and launch vehicle’s whole ascent flight. This method can also supply a new means of online trajectory planning,etc.

The design of trajectory in boost phase of the lift vehicle is facing the difficult problem of carrying capacity optimization under the coupling condition of multiple constraints in the complex atmospheric flight environment. It is necessary to design the program angle of the boost phase to maximize speed of entering orbit under the constraints of stages separation height,angle of attack limit,height of the orbit entry point,etc. In order to find an engineering design method to quickly solve this problem,taking the three-stage solid launch vehicle as the research object,the multi-constraint trajectory design method in boost phase of the lift vehicle was put forward. The design variables were formulated by designing the flight trajectory mode of the boost phase,and the constraint conditions of the boost phase were determined. The optimization model aiming at the maximum orbital speed under multi constraints was built. By analyzing the coupling relationship between design variables and constraints,an efficient optimization process was formulated. The optimization initial value was determined by Newton iterative method,and the optimization simulation was carried out by sequential quadratic programming method. The optimal solution satisfies the multi-constraint conditions,and the orbit entry speed increases by 3.1%,which verifies the correctness of the trajectory design method and the effectiveness of the optimization process. The multi-constraint trajectory optimization design method in boost phase of lift vehicle has strong engineering practicability. The modeling method and optimization process can offer reference for other optimization problems.

In order to analyze the influence of power station vibration on a high-precision wheeled weapon launch vehicle,the structural layout of the launch vehicle was analyzed. The chassis suspension structure,the flexible characteristics of tire and mounting bracket,and friction effects of locking mechanism were considered,and the force analysis was carried out. A flex-rigid multi-body dynamics model of this vehicle was established. Vibration load was applied according to the data of power station vibration test,and the verification model was built. Transmission characteristics of power station vibration were simulated,and the aiming precision of launcher under composite impacts of servo adjustment of launcher,the flexibility of bracket and tyres,and power station vibration were analyzed. The simulation results show that vibration of power station was absorbed and attenuated during transmission. The power station and bracket have obvious effect on vibration attenuation. The residual vibration can affect the aiming precision of launcher after the vibration of power station transmitting to the launcher.

In order to accurately reflect the dynamic characteristics,optimize the comprehensive performance and obtain better control tracking effect for tank servo systems,the mathematical model of the nonlinear dynamics of the coupled load between the axles,the mathematical model of the drive end of the azimuth subsystem,and the mathematical model of the drive end of the pitch subsystem,were established. Simulation software Mworks based on Modelica language was used to establish the simulation model base of the tank servo system,and the simulation research was carried out. The results show that the model based on Mworks can accurately simulate and verify the tank servo system,and it can meet the requirement of stable precision of the tank servo system. Based on MWorks,the tank servo system can be intuitively simply modeled,and the relationship between modules directly reflects the relationship between physical quantities. The established comprehensive dynamic model of the tank servo system has good repeatability,which improves the modeling efficiency.