In traditional chined waverider design, the adjustment of design profile parameters is complex and the design intuitiveness is insufficient. To address these issues, this paper proposes a chined upper surface design method based on B-spline curves. The design flexibility and convenience are improved by directly adjusting the design profile through control points. The base profile is constructed by means of Bezier curves, the leading edge and lower surface base profile are determined using the osculating cone theory, and the upper surface profile is designed using cubic and quadratic B-spline curves. The reliability of the proposed method is verified by computational fluid dynamics (CFD) methods, and the aerodynamic performance of the chined waverider is analyzed. The results demonstrate that, as the angle of attack gradually increases, the influence of the chined upper surface on aerodynamic characteristics weakens gradually, and the maximum lift-to-drag ratio appears at the angle of attack ranging from 4° to 6°. The proposed method provides a more intuitive profile optimization means for waverider design, which has reference value for engineering design.

The mechanical properties of high-entropy alloys (HEAs) are studied. For this purpose, a simple and precise testing system is established for determining the equation-of-state parameters of HEAs. Based on the principle of wave impedance matching, a test setup is designed using the pressure comparison method to obtain the shock adiabat data of HEA materials. The acquired experimental data is then optimized through adaptive clustering detection. After optimization, the confidence intervals for the slope and intercept of the experimentally determined shock adiabat are narrowed from [1.66293, 2.03332] and [4.01158, 4.38089] to [1.6461, 1.92734] and [4.15248, 4.27542], respectively, and the coefficient of determination (R²) is improved from 0.9687 to 0.9849. The Hugoniot equation-of-state parameters for the HEA are determined as C₂=4.214km/s and λ₂=1.787.The Hugoniot equation of state established in this study is applicable within a pressure range of approximately 5.86-32.77 GPa, and its extrapolation to higher pressure regimes necessitates further experimental validation to guarantee reliability. The results demonstrate that the proposed system achieves high-precision measurement of equation-of-state parameters for high-entropy alloys hrough the combination of data optimization algorithms with experimental design. This work provides critical technical support for the performance assessment and practical application of such materials under dynamic mechanical conditions.

To improve the resistance of B₄C/Al composite targets against explosively-formed projectile (EFP) penetration, the surface morphology of ceramic strike face is modified. Seven types of B₄C/Al composite targets featuring different protrusion-array structures on the strike face are examined. The processes of EFPs penetrating into the composite targets at 1.5, 1.7, and 1.9 km/s are simulated using LS-DYNA. The evolutions of the projectile's mass, velocity and kinetic energy during penetration are analyzed. The results indicate that B₄C/Al composite targets with protruded strike-face structures exhibit superior penetration resistance and deceleration capability compared with B₄C/Al flat-faced targets. Among them, the composite target with a pyramidal protrusion array provides the best deceleration performance for the simulated EFP.The R3 semi-cylindrical target demonstrates the best protective performance under normal impact. The penetration direction significantly affects the penetration resistance of anisotropic protrusion-array targets and the sinusoidal-structured target has the optimal protection performance under oblique impact.

The penetration tests on three sets of geometrically similar projectiles with scaling ratios of 1/1, 1/2 and 1/3 are carried out to investigate the size effect of penetration depth of projectile into concrete media. A calculation method for penetration depth with the projectile diameter coefficient as a variable is proposed, and a conversion coefficient model that takes into account the scaling ratio is established for penetration depth. The dynamic strain rate of material in the projectile-target contact zone during the penetration processare quantitatively analyzed through numerical simulation, and the values of penetration depth conversion coefficients under different scaling ratios are ultimately determined. The results show that the size effect exists in the dimensionless penetration depth between the prototype projectile and the model projectile, which arises from the difference in the average strain rates of target in the tests with different scaling ratios. The strain rate increases with the increase of penetration velocity and the decrease of projectile diameter, and does not conform to the geometric similarity scaling relationship. The established penetration depth conversion coefficient is correlated with the target strain rate and the scaling ratio. This conversion coefficient not only quantifies the influence of the material strain rate on the size effect, but also clarifies the mechanism of the size effect of penetration depth in concrete media from a mechanistic perspective.

To address the issue of small penetration aperture in traditional shaped charge warheads against underwater single-layer targets,a novel W-shaped shaped charge structure design method based on the inner cone angle α and outer cone angle β is proposed.The influence of liner structure on jet formation and damage effectiveness is studied.The ratio μ of the lengths of the inner and outer sides of the liner is defined a-s a characterization parameter affecting the underwater formation and damage performance of the W-shaped liner.The influence of the ratio μ on the formation and initiation points on the formation and penetration of annular jet are analyzed through numerical simulations.The results indicate that,the annular jet converges excessively toward the axis when μ is 0.22,forming an explosively formed projectile (EFP).When 0<μ<1,the outward expansion trend of the annular jet gradually intensifies,the head-to-tail velocity difference decreases,and the jet stability improves with the increase in μ.When μ>1,the slug at the jet tail is reduced,the jet head expands,the head-to-tail velocity difference increases,and the jet stability significantly decreases under the influence of the external water medium with the increase in μ.Additionally,the increase in the number of initiation points induces necking at the head of the annular jet,which has little impact on penetration and aperture formation under the condition of small standoff distance.The large-area damage of annular jet to the target plate can be achieved by optimizing the combination of the inner and outer cone angles of the liner to adjust the value of μ and the number of initiation points.

The influence of grooved structure on the penetration and damage performance of copper-aluminum/polytetrafluoroethylene (Cu-Al/PTFE) energetic composite liner is investigated.A energetic composite liner with large cone angle (140°) is numerically simulated and experimented,and the damage effect of a pre-grooved energetic composite liner on concrete target is examined.A comparison shows good agreement between the experimental and simulated results.The influences of groove structure parameters such as groove width,depth,and wall thickness ratio on the damage effect of jet are further analyzed.The results show that the groovee structure has an effect on the distribution of jet energy between radial expansion and axial penetration.The smaller widths,shallow depths and narrow spacing of grooves are conducive to the radial hole enlargement,whereas the larger widths,greater depths and wider spacing of grooves enhance energy concentration,thereby increasing the penetration depth.Additionally,the number of grooves and the wall thickness ratio significantly influence the stability of jet and the ability of reactive materials to follow up.In particular,a wall thickness ratio of 1∶1 between the copper and reactive material layers yields favourable jet formation and damage performance.

The direction-finding performance of guidance and direction-finding system is limited with a small-aperture array and the array configuration optimization is a key step to improve system performance due to platform resource constraints such as weight,volume,and deployment space.In this paper,the Cramér-Rao bounds (CRBs) for wideband two-dimensional direction-of-arrival (DOA) estimation of both scalar arrays and polarization-sensitive arrays are derived,and a CRB-based performance evaluation and configuration optimization method for small-aperture arrays is proposed.Firstly,the development of wideband DOA estimation and the typical two-dimensional array structures are reviewed,and the wideband signal models based on subband decomposition are established for both scalar arrays and polarization-sensitive arrays.For scalar arrays,a closed-form expression for the CRB of wideband two-dimensional DOA estimation is provided.Subsequently,a general framework and closed-form expression for the CRB of wideband two-dimensional DOA estimation of polarization-sensitive arrays are derived,and a performance evaluation criterion for two-dimensional direction finding with such arrays is established.Finally,A two-dimensional array configuration optimization method based on the derived CRB is proposed by considering the constraints ofguidance system platform on the number of array elements and array aperture.The quantitative optimization of array layout can be achieved by constructing an array configuration optimization set and conducting theoretical performance evaluation.The research results provide theoretical support and technical guidance for the array configuration design and performance evaluation of small-aperture guidance direction-finding systems.

In response to the application requirements of inertial navigation systems for quartz flexible accelerometers with a large range and high dynamic flight accuracy, a new structure for the pendulum assembly of quartz flexible accelerometer is proposed to enhance the range and second-order coefficient of accelerometer. A mathematical model of the designed pendulum assembly is established to derive the scale factor of the designed accelerometer. The design range of accelerometer is theoretically calculated based on the load capacity of servo circuit. The optimization method for the second-order coefficient of the accelerometer is analyzed, and an optimization scheme for the second-order coefficient is provided. Through numerical simulations, it is verified that the deflection and stress of the designed pendulum assembly under full-scale conditions meet the design requirements. Experimental results show that the quartz flexible accelerometer achieves a range of 110g and a second-order coefficient better than 5 μg/g², thereby improving the dynamic application capability of quartz flexible accelerometers in inertial navigation systems.

Aiming at the path planning problem of UAVs in complex scenes,this paper proposes a coupling algorithm that uses the improved A-star algorithm and the improved dynamic window method for path planning,so that the UAV has the ability to avoid static and dynamic obstacles.In terms of global planning,by improving the evaluation function of the A^* algorithm,a path planning algorithm that does not rely on the obstacle expansion map is proposed,so that the UAV can plan a safe path against a priori static obstacles.In terms of local planning,an evaluation function for handling dynamic obstacles is added,so that the UAV has good obstacle avoidance capabilities when facing high-speed dynamic obstacles.Aiming at the problem of too many inflection points on the path resulting in frequent acceleration and deceleration after improving the global planning algorithm,a redundant inflection point deletion strategy was proposed.The simulation results show that compared with the traditional algorithm,the improved algorithm has better obstacle avoidance ability and shorter driving trajectory,which verifies the practicability of the algorithm.

To address the low decision-making efficiency and poor practicality of weapon-target assignment (WTA) in modern air-defense operations,a multi-objective WTA model that comprehensively considers four performance metrics including ammunition consumption,operational cost,total engagement time,and interception benefit is constructed.Practical constraints such as weapon-ammunition compatibility,ammunition inventory,and damage thresholds,etc,are also taken into account to enhance the battlefield applicability of the model.Secondly,a hybrid heuristic algorithm—hybrid ahaotic quantum particle swarm optimization-variable neighborhood search (HCQPSO-VNS) is proposed to solve the proposed WTA model.In the proposed algorithm,a logistic chaotic mapping is employed to improve the quality of the initial population,the quantum particle swarm optimization (QPSO) is utilized for global search; and the variable neighborhood search (VNS) with multiple neighborhood structures is integrated for local optimization to avoid premature convergence.Simulated results demonstrate that the proposed algorithm converges to a high-quality feasible solution within very few iterations.The obtained assignment schemes satisfy the expected lower bounds for damage,weapon-ammunition compatibility,and other constraints,while achieving an effective balance among four performance metrics.Comparative analysis shows that the overall performance of the proposed algorithm outperforms several mainstream algorithms,and can effectively improve the efficiency and scientific rigor of air-defense firepower allocation decisions.Meanwhile,as the problem complexity increases,the proposed algorithm retains high optimization efficiency and acceptable computational load,demonstrating favorable scalability.

This paper investigates the guidance of missiles striking the maneuvering targets in three-dimensional (3D) space in the presence of model uncertainties, unknown target maneuvers and terminal impact angle constraints. An impact angle control guidance law based on nonsingular fixed-time sliding mode control (NFTSMC) and fuzzy logic is proposed. First, a 3D missile-target relative motion model is established, and the terminal impact angle constraint control is reformulated as a line-of-sight (LOS) angle tracking problem. To overcome the singularity commonly encountered in conventional terminal sliding mode control, a nonsingular fixed-time sliding mode surface (NFTSMS) is constructed, and an auxiliary function is introduced to guarantee singularity-free controller design. In addition, a fuzzy logic system (FLS) is incorporated to online approximate the lumped disturbances induced by target maneuvers and model uncertainties. The fixed-time stability of all signals from the closed-loop system is strictly proved based on Lyapunov stability theory. The simulated results show that the proposed guidance law can achieve the accurate interception of maneuvering targets under different initial conditions. Compared with the existing fixed-time sliding mode guidance strategy, it has significant advantages in suppressing the control command chattering and improving the line-of-sight angle tracking accuracy.

In recent years, the development of large-scale low-earth-orbit (LEO) satellite constellations has been progressing at an unprecedented pace, and their potential applications in the military domain have become increasingly prominent. These constellations possess unique technical characteristics that enable them to restructure the traditional kill chain, effectively addressing core challenges such as reconnaissance delays and insufficient cross-domain coordination in precision strikes. This paper provides a comprehensive introduction to the development of large-scale LEO satellite constellations and delves into their application directions in the military field. By examining typical combat scenarios from the perspectives of the kill chain and kill web, this paper analyzes how large-scale LEO satellite constellations can enhance the construction of the kill web and facilitate the closure of the kill chain in the field of precision strike. The findings of this study offer valuable insights and references for the construction of a global and systematic kill web based on a large-scale low-Earth-orbit constellation. Moreover, this research holds significant reference value for the development of China’s anti-access/area denial (A2/AD) strategic system architecture. As related projects in our country continue to advance steadily, the exploration of the potential of large-scale LEO satellite constellations in enhancing military capabilities becomes even more crucial.

The modal parameters of large-scale missile and rocket systems are generally obtained through finite element analysis and ground vibration tests.Due to the inability to simulate the time-varying characteristics of the system under flight conditions,it is usually necessary to conduct finite element modeling or ground vibration tests based on several characteristic conditions,and finally obtain the flight modal frequency through numerical interpolation.The repeated modeling and ground testing process is time-consuming and laborious.This article presents a fast prediction method for time-varying modal parameters of missile and rocket,which is based on the concentrated mass beam model and finite element method.This method introduces time-varying mass matrix,stiffness matrix,and damping matrix to describe the time-varying system,which can quickly provide the time-varying modal frequency parameters of the system.This method has been validated through ground vibration test and flight test,the results show that this method can reliably simulate the time-varying modal parameters of the system,effectively solving the pain points of the tedious simulation of time-varying systems.Moreover,the time-varying dynamic response data obtained based on this method can be used for dynamic inverse problems such as the modal consistency analysis and load identification.

In order to study the spinning projectile stability of coning motion,provide the dynamic equation around the center of mass in quasi-body coordinate system and establish the short period dynamic model.Derive the equations of coning motion represented by Euler angles.Obtain the analytical solution by introducing complex angle of attack.Analyze the stability of coning motion with initial disturbance in two cases:One situation is ignoring the Magnus effect and damping effect,only analyze the coning motion influenced by the gyroscope effect and the aerodynamic static moment.Another situation is the coning motion adding in the Magnus effect and damping effect,analyze the stabilization and provide the conditions for coning stability.Finally,summarize the influence of rotating speed and statically stability acting on the dynamic stability of coning motion based on theoretical analysis and simulation results:For the low-speed rotating missiles,only under the influence of gyroscopic effect and aerodynamic static moment,a statically stable aerodynamic shape is necessary to achieve coning stability.Statically unstable missiles can only achieve dynamic stability by significantly increasing the rotating speed.Considering the Magnus effect and damping effect,the convergent coning motion of the statically stable missiles with low rotating speed is the easiest to achieve.The divergence of coning motion may occur result in the increasing of rotating speed.For the statically unstable missiles,it is necessary to select the moment of inertia reasonably and increase the rotating speed to achieve dynamic stability.

In order to study the effect of heat insulation coating structure on the thermal protection performance of fuzes in different thermal environments,the typical large-caliber grenade fuze of JHX-1 charge was taken as the research object,and the slow burning and fast burning simulation of fuzes with no heat insulation coating structure,single heat insulation coating structure and composite heat insulation coating structure were carried out.The simulation results show that the design of the thermal insulation coating structure can prolong the response time of the fuze under both fast and slow burning conditions,and the delay effect is the most obvious in the fast burning environment,the delay effect is 69.1%.Under the same thermal environment and the same thickness of the overall thermal insulation coating of the fuze,the delay effect of the single-coating thermal insulation structure on the response time is better than that of the composite coating thermal insulation structure,and the thermal protection performance is the best when the shell is coated with flame retardant thermal insulation material,and the delay effect is 51.6% under the fast burning ring.According to the comprehensive analysis,the inner/outer composite thermal insulation coating structure can be considered for the fuze body with limited coating thickness,and the thermal protection effect of the composite coating structure can be improved by increasing the coating thickness of the outer material on the basis of meeting the functional requirements of the fuze.

The super caliber canard-controlled projectiles have a large front diameter,a forward center of gravity,a variable diameter cross section in the middle of the projectile body,and more complex surface gas flow.In order to study its aerodynamic characteristics,the lifting resistance characteristics,pitching moment characteristics and the surface flow field distribution of the projectile were analyzed by numerical calculation.The results show that the lift-drag ratio increases first and then decreases with the increase of attack angle,and the lift-drag ratio reaches the maximum when the attack angle is 8°.The pitch moment provided by different parts of the projectile body is studied in different areas.It is found that the forward pitch moment provided by the projectile tail takes up more than 30% of the total pitch moment when the attack angle α=0°,elevator angle δ_z=5°,and the stability ratio of the δ_z=10° decreases by 46.8% compared with δ_z=5°.Vortices appear at the variable diameter of the projectile body,which interact with the vortices of the rudder surface and the vortices around the surface of the projectile body,making the gas flow on the surface of the projectile body more complicated and increasing the difficulty of control.

Fragments,as the primary damage elements of blast-fragmentation warhead,have their damage lethality which is quantitatively evaluated through precise testing of parameters such as fragment velocity,spatial distribution and mass characteristics.This paper systematically reviews the latest advancements in the parameter testing technologies for the fragment fields of blast-fragmentation warheads,focusing on comparative analysis under two typical conditions of static and dynamic detonations.In the context of static detonation testing,the principles and features of the contact-type technologies such as net targets,the sectional optoelectronic technologies of light curtains and radar and the 3D reconstruction technologies like high-speed stereovision are compared in detail,and their technological improvements and development trends are elaborated.In the context of dynamic detonation testing,the research achievements in testing methods and simulation modeling at home and abroad are reviewed,and the unique challenges such as detonation point control and spatiotemporal synchronizationunder dynamic detonation conditions as well as the corresponding solutions are thoroughly analyzed.Furthermore,this paper also explores the applications and enabling potential of intelligent algorithms represented by machine learning (particularly deep learning) in the aspects fragment target recognition,trajectory tracking,data fusion,and dynamic explosion parameter prediction.Finally,it offers prospects for the future development trends in fragment field parameter testing technologies,and proposes the need to prioritize high-precision dynamic detonation fragment parameter testing technologies,enhance the 3D reconstruction capabilities and strengthen the integration of machine learning in testing methodologies,thereby supporting the optimized design and damage effectiveness evaluation of blast-fragmentation warheads.

To address the issue that traditional UAV obstacle-avoidance algorithms have low efficiency in unknown and complex environments,an improved improved Dynamic Window Approach (DWA) fusion algorithm was proposed.Regarding the lack of a global perspective in the DWA algorithm,a bidirectional search strategy was introduced to enhance the global value of the planned trajectory.Confronted with the difficulty of balancing calculation speed and accuracy in the DWA algorithm,a dynamic time step adjusted according to the environment was designed to weigh the computational efficiency.Aiming at the poor environmental adaptability of the DWA algorithm,a trajectory evaluation function with variable weights was put forward to improve environmental fitness.To boost the inter-UAV obstacle-avoidance ability in the multi-UAV collaborative mode,the improved DWA algorithm was integrated with the with the ORCA (Optimal Reciprocal Collision Avoidance) method.Simulation experiments were conducted to verify the proposed improved fusion algorithm.Compared with the traditional DWA algorithm,the UAV flight trajectory has decreased by 33.10%,the mission completion time has been shortened by 31.32%,and the number of iterations has been reduced by 50.05%.The overall performance has been significantly enhanced,which holds guiding significance for the engineering application of multi-UAV autonomous obstacle-avoidance technology.

The damage expansion of the interface between the coating sleeve and the propellant in the initial operating section of a fully loaded solid rocket motor is analyzed using the LS-DYNA platform.The numerically simulated results show that the pressure difference between the inner and outer surfaces of the coating sleeve is determined only by the minimum flow cross-sectional area between the coating sleeve and the insulation layer without the consideration of fluid-structure interaction，which is inconsistent with the actual physical process.However，when the fluid-structure interaction is taken into account，the pressure difference between the inner and outer of the coating sleeve first increases and then decreases with the increase of the motor operating time.The pressure difference reaches its peak value of 0.604MPa at 0.4s.The additional stresses might exist at the interface between the coating sleeve and the propellant under the effect of this pressure difference，which could lead to the damage and expansion of the interface.During the design of motor，the gap between the coating sleeve and the insulation layer as well as the elastic modulus of coating sleeve should be comprehensively evaluated to ensure the stable interfacial mechanical properties and slower damage propagation，thereby enhancing the structural stability and reliability.

A low-sidelobe array pattern design method utilizing fmincon is proposed based on MATLAB.The array beam optimization problem is transformed into a nonlinear constrained optimization problem with continuous variables by constructing a hybrid penalty cost function with the objective of minimizing the sidelobe level in the target region and utilizing the nonlinear constraints for controlling the gain fluctuation of mainlobe.Numerical results demonstrate that The designed array can achieve a suppression of 15-20dB sidelobe level within specified spatial regions while ensuring that the gain fluctuation of mainlobe is less than 0.3dB.And the optimization process exhibits rapid convergence and excellent stability.The proposed method gives consideration to optimization precision and computational efficiency.It provides a high-performance and high-reliability solution for antenna array designs requiring the mainlobe shaping and sidelobe suppression in specific region,has significant engineering practical value.

For the flight control of quadrotor unmanned aerial vehicles (UAVs) affected by multi-source disturbance,a self-tuning sliding mode flight control algorithm based on multi-source disturbance compensation and hierarchical sliding mode control is proposed.The quadrotor UAV system is divided into a two-degrees-of-freedom dual-input fully-actuated subsystem and a four-degrees-of-freedom dual-input underactuated subsystem,based on which the sliding variable of the fully-actuated subsystem is defined.A sliding variable construction method for hierarchical sliding mode controller is proposed,and the sliding variable of the underactuated subsystem is designed by adopting this method.A generalized Super-Twisting disturbance approximator is designed to observe the multi-source disturbance,and a fuzzy compensator is designed to compensate for the approximation error of the disturbance approximator.A reaching gain self-tuning sliding mode controller is designed by utilizing the combined power reaching law,and the disturbance approximator with fuzzy compensator is used to suppress the influence of the multi-source disturbance.The roles of the core modules in the proposed control algorithm are analyzed,and the proposed control algorithm is compared with the existing control algorithms.The comparison results show that the proposed control algorithm has good multi-source disturbance rejection ability,and can also provide superior dynamic control performance.

Aiming at the problems of insufficient samples， semantic ambiguity and blurred entity boundaries in Chinese named entity recognition for UAV communication， this paper proposes a multifeature fusion Chinese named entity recognition model RCPAC （roberta-wwm-ext-large-CNN-PositionAwareAttention-BiLSTM-CRF）. Firstly， the UAV communication domain dictionary is dynamically integrated into the robertawwmextlarge model to obtain global features fused with domainspecific lexical information. A SqueezeandExcitation Networks （SENet） attention mechanism is introduced into the Convolutional Neural Network （CNN） layer to extraction key feature. Within the bidirectional positionaware attention mechanism， two regiondivided forward and backward attention modules are designed to capture entity boundary features. Then， dynamic weightbased fusion is conducted on the global features with lexical information， multiscale local features extracted by the CNN layer， as well as position information and entity features obtained from the bidirectional positionaware attention mechanism. Next， the Bidirectional Long ShortTerm Memory （BiLSTM） layer is used to model longrange sequence dependencies and filter redundant features. Finally， the Conditional Random Fields （CRF） decoding layer outputs the optimal label sequence. Comparative experiments and ablation experiments verify the effectiveness and superiority of the proposed model. On the selfconstructed smallscale UAV communication dataset， the F1score of the RCPAC model is improved by 1.01%-9.95% compared with other baseline models. In addition， the model achieves F1scores of 92.15% and 95.56% on the CCKS2021 Chinese address element parsing dataset and the MSRA dataset respectively， demonstrating its generalization ability and effectiveness.

To address the challenge that the frequency-agile radars in the stable tracking phase in modern complex electromagnetic environments struggle have difficulty in balancing both coherent integration gain and anti-jamming capability under blanket jamming,this paper proposes a joint control method for frequency and dwell time based on proximal policy optimization (PPO).Firstly,the trade-off relationship between radar coherent integration gain and intercept risk is analyzed.The dynamic combined jamming behavior of jammers is modeled,and a Markov decision process model for radar anti-jamming,incorporating signal-level feature feedback,is constructed.Secondly,the PPO algorithm is introduced.A compound reward function that takes into account both detection performance and survivability is designed,enabling the radar agent to autonomously learn the optimal strategy in unknown dynamical adversarial environments.This strategy can adjust the operating frequency and dwell time in real-time based on environmental feedback to maximize the signal-to-interference-plus-noise ratio.Simulated results demonstrate that,compared to traditional strategies,the proposed strategy can effectively evade the combined blanket jamming.It significantly reduces the probability of being jammed while substantially improving the output SINR,exhibiting strong environmental adaptability and robustness.

The three-axis seeker of loitering missile faces the technical problems of single optical axis pointing mapping multiple frame angle combinations and fast real-time calculation of optimal instructions when tracking the target. Based on the kinematics analysis of the three-axis seeker, an adaptive fast tracking strategy for the three-axis seeker is proposed. The influence of the combination of three-axis bandwidth and three-axis increment on the tracking speed of the seeker is analyzed, and the fitness function evaluation standard with frame adaptability is established. The simulation results show that the proposed strategy can solve the optimal tracking instruction under the framework constraint, solve the problem that the tracking instruction cannot be tracked due to exceeding the mechanical limit, and realize the tracking target of the control optical axis along the optimal path. The average iteration time is 3.54 ms, and the tracking speed is improved by 30.4%.

The shaped charge is widely used in the field of unexploded ordnance destruction disposal due to its high energy utilization rate.For the safe and effective disposal of unexploded ordnance in water,this paper investigates the factors influencing on the underwater initiation capability of jets.Numerical simulation methods are employed to characterize the jet formation process of two charge structures in water.Focusing on the flared liner shaped charge structure,the effects of the charge structure,the length of the combined cavity structure at the head,and the water depth on the initiation capability of the shaped charge jet are analyzed.The results indicate that the flared liner charge structure affects the jet’s initiation capability in the following order of significance:liner height,liner thickness,explosive column height,and liner curvature.The combined cavity structure significantly reduces the energy loss of the jet by 74.8%.The Random Forest (RF) model effectively predicts the nonlinear variation characteristics of the contact velocity between jet and shelled charges in water with the increase in water depth.

In counter-unmanned aerial vehicle （UAV） swarm operations，the attack intent recognition（AIR），as the core preceding link in the decision-making chain，directly determines the effectiveness of counter-UAV resource allocation and countermeasure formulation.In response to the problems of existing intention recognition methods，such as difficult modeling，sensitivity to noise，and poor adaptability to non-attack scenarios，an attack intent recognition method based on long short-term memory （LSTM） and interacting multiple model （IMM） is proposed.The multi-classification problem is transformed into a binary classification task through scenario decoupling，and LSTM is used to extract the temporal motion features.The likelihood value of attack intent is calculated based on the additivity of mutually exclusive event probabilities，and the smooth update and normalization of intent probability are realized combined with the IMM mechanism.Multi-scenario simulations and Monte Carlo experiments show that the proposed method improves the recognition accuracy by more than 10% and shortens the convergence time by more than 2s compared with the traditional UKF-IMM method.It can effectively adapt to complex scenarios such as intent switching and non-attack maneuvers，and has stronger noise robustness，providing accurate intent support for air defense decision-making.

Aiming at the problem of insufficient matching accuracy and even divergence caused by initial errors in inertial navigation and gravity measurement errors in traditional nearest contour iteration (ICCP) algorithm,an improved ICCP algorithm is proposed to improve matching accuracy and reliability.Firstly,two assumptions affecting the matching accuracy of traditional ICCP algorithms were analyzed,and the estimated path was limited to the vicinity of the INS path by introducing a total constraint error; On this basis,rough matching is constructed using MAD and MSD matching rules,and the obtained rough matching path is used to replace the INS measurement path in subsequent accurate matching.Then,the ICCP algorithm is used for fine matching to achieve higher positioning accuracy; Establish a Kalman filter model by taking the difference between the output position of the inertial navigation system and the matching position of the ICCP algorithm as the observation vector of the filter,and correct the errors of the inertial navigation system.The simulation and analysis results show that,considering the initial errors of inertial navigation and gravity measurement errors,the improved ICCP algorithm has a maximum attitude error of less than 0.015 °,heading error of less than 0.4 °,and maximum position error of less than 30m.The navigation accuracy is improved by more than 70% compared to the traditional ICCP algorithm,effectively improving the positioning accuracy of the inertial/gravity gradient integrated navigation system.

To address the difficulty of balancing the operational resources and spatiotemporal constraints in the cooperative interception against high-speed maneuvering targets，this paper proposes a cooperative interception timing optimization method based on an improved SA-ACO algorithm.Firstly，a bilevel programming model for launch scheduling is constructed：the outer layer determines the minimum number of interceptors based on a preset interception probability threshold，while the inner layer cooperatively optimizes the optimal launch time windows for the interceptor missiles.Secondly，to address the difficulty in the continuous-domain optimization of the inner layer，an adaptive simulated annealing-ant colony optimization （SA-ACO） hybrid algorithm is designed as the solver.The shortcomings of traditional algorithms，which are prone to getting stuck in local optima and have slow convergence are overcome by integrating the dynamic hybrid regulation and experience-inspired strategies.Simulations show that the proposed method quickly outputs the optimal combination of minimum interceptor quantity and launch timing while ensuring a high interception probability.It achieves the significant improvements in convergence speed，optimization accuracy and stability，providing an efficient and robust decision-making scheme for multi-missile cooperative scheduling.

Hypersonic missiles,unmanned combat aerial vehicles,and other highly maneuverable targets possess maneuverability comparable to that of interceptors,where the interceptor's maneuverability does not exceed 1.2 times that of the target.The terminal acceleration is easily saturated when applying the traditional guidance laws,leading to a significant degradation in interception accuracy.To address this issue,this paper proposes an optimal guidance law for intercepting maneuvering targets with equilibrium maneuverability.By introducing a relative reference frame,an optimal equilibrium compensation strategy that accounts for target maneuvering with dynamic delays is proposed.This strategy overcomes the under-compensation or over-compensation limitations of conventional guidance laws,which rely on presupposed target maneuver pattern.Based on this strategy,terminal constraints for equilibrium interception are formulated,and a two-stage optimal integrated guidance and control method is derived using kinematics in the relative reference frame.In the first stage,the guidance law is designed based on a minimum-distance performance index to rapidly eliminate pointing errors and converge to the equilibrium interception constraint.In the second stage,a quadratic optimal performance index of acceleration is adopted to deal with the effects of target maneuver and inner-loop delay with minimum required acceleration,thereby achieving terminal equilibrium interception of highly maneuverable targets.Comparative simulation results demonstrate that the proposed guidance law significantly reduces the required interception acceleration and improves terminal guidance accuracy compared to existing optimal guidance methods.

Ground penetrating radar （GPR），as a non-destructive detection technology，is widely used in geological exploration and engineering inspection.The antenna，as a core component，has a direct impact on the detection accuracy and depth of the system.Modern GPR systems impose the stringent requirements on the antennas in terms of miniaturization，ultra-wideband （UWB） and high gain.The traditional antipodal Vivaldi antenna （AVA） often relies on increasing the physical dimensions to extend the low-frequency bandwidth，which limits the portability of the equipment to some extent.Although the existing resistive loading techniques can improve impedance matching，they often come at the cost of significantly reduced gain，leading to insufficient signal-to-noise ratio for detection.To address the aforementioned contradiction，this paper designs a resistively loaded antipodal Vivaldi antenna for GPR.The design introduces structural chamfering at the antenna ends to optimize the current distribution，and incorporates a stepped resistive network to achieve a smooth impedance transition.This approach aims to effectively suppress the end reflections and enhance the radiation efficiency without increasing the antenna aperture.Simulated and measured results show that the antenna achieves a low-frequency cutoff of 1.37GHz，a stable gain over 1.37-26.2GHz band，and a voltage standing wave ratio （VSWR） of less than 2.5 within the frequency band of 1.37-26.2GHz.This study provides key technical support for the realization of high-resolution and lightweight GPR detection systems.

Under the current conditions of air combat confrontation,targets often behave medium and large overloads and strong maneuvers,and it is difficult to predict the trajectory of maneuver.In order to solve the problems of low prediction accuracy and short prediction time of the traditional trajectory prediction methods,a multi-step trajectory prediction method based on Bayesian optimization hyperparameters in bidirectional long short-term memory network (BO-Bi-LSTM)is proposed in this paper.The sliding prediction method is analyzed,and an online rolling prediction mathematical model is established to solve the problem of prediction value construction.The network hyperparameters are optimized automatically by using Bayesian optimization method,and the optimal hyperparameters are obtained after iteration several times.The length of the sliding window is analyzed,and the length of the sliding window with the highest prediction accuracy is obtained among the classical sliding window length.In order to test the prediction performance of this method on the maneuvering trajectory,a classical maneuvering flight trajectory is predicted and simulated in this paper,and compared with three other neural network prediction models,the simulation results prove that the bidirectional long and short time domain memory network multi-step prediction method with Bayesian optimization hyperparameters is higher in prediction accuracy than the other three neural networks.The accuracy of the 3D trajectory error is less than 200m,which can be predicted continuously for about 4.5s.

To further improve the prediction accuracy of solid rocket motor performance a parameter-model coupling-based predictive method for the internal ballistic performance of solid rocket motors is proposed.Firstly,the key factors influencing the prediction deviations are identified by analyzing the discrepancies between the predicted results of the classical zero-dimensional internal ballistic model and the actual motor operations.Secondly,in consideration of the characteristics of these factors,the prediction method is adjusted by using the undetermined parameters and the performance correction models to account for their respective effects.Based on this,a coupled prediction framework integrating both approaches is established.Finally,the internal ballistic performance is predicted and analyzed based on test data by taking the precise performance prediction problems of single-chamber single-thrust and single-chamber dual-thrust solid rocket motors as examples The results indicate that the proposed method significantly enhances the prediction accuracy of macroscopic internal ballistic parameters such as thrust and chamber pressure,while also enabling the precise estimation of mesoscopic parameters including burning surface area,nozzle throat diameter,and propellant burning rate.The prediction deviations for thrust and chamber pressure remain within 1%,and the prediction deviation for mass flow rate remains within 0.1%,thereby supporting comprehensive analysis of the engine's operational process.

The performance of signal acquisition in satellite navigation receivers is significantly influenced by the setting of detection thresholds.The existing methods are difficult to to adapt to the increasingly complex electromagnetic environments in urban areas,where they are prone to generate false alarms under multiple interference conditions,severely affecting acquisition reliability.To address this issue,a constant false alarm rate (CFAR) detection technique is incorporated into the acquisition of BeiDou B1C signals.An algorithm that dynamically adjusts the decision threshold based on the estimated number of interference targets is proposed.This algorithm adaptively determines the decision threshold of signal acquisition according to the real-time estimated number of interference targets in the environment,thereby enhancing the performance of receiver in multi-interference environment.Simulated results demonstrate that the proposed algorithm significantly improves the robustness and acquisition sensitivity of the receiver in complex interference environments,thereby increasing the operational reliability of military equipment in urban warfare.

In response to the threat of aircraft being targeted by air-to-air missiles,a strategy involving the use of decoy for coordinated evasive maneuvers has been proposed. Firstly,a relative motion model between the aircraft,decoy,and incoming missile was established. Five control variables were set up to regulate the movements of the aircraft and the decoy. Based on the principles of coordinated missile evasion,this study divided the decoy’s working process into two stages and established key technical indicators for maneuver decision-making,which led to the development of a variable-weight optimal control computational model for coordinated maneuvers between the aircraft and the decoy to evade missile. Then,under the receding horizon control framework,multi-island genetic algorithm was employed to obtain a closed-loop solution for the optimization model,enabling the real-time provision of quantifiable maneuvering evasion strategies for the aircraft. Finally,the constructed coordinated evasion performance evaluation function was adopted to conduct a quantitative assessment of the optimization results from the aspects of evasion efficiency and safety distance. The results show that,under the selected condition,the aircraft can escape the missile’s field of view within 5.4 seconds and that when the missile hits the decoy,there is sufficient safety distance from the missile. After extensive Monte Carlo simulations,it is found that the optimized control model achieves a missile evasion success rate of 98.1%,significantly enhancing the survivability of our aircraft in combat.

In the process of constructing the ship damage matrix under the conditions of high-dimensional missile terminal parameters，the traditional uniform sampling method has insufficient accuracy due to the limited computing resources.To address this issue，this paper proposes a non-uniform high-precision damage matrix construction method based on the sensitivity analysis of ship damage characteristics.This method first uses the empirical formulas to quickly calculate the probability of damage at discrete explosion points in a ship and obtain the sensitivity distribution of the damage probability space.An then，the sensitive areas within the ship are projected onto the missile terminal parameter space by combining the firing line method and the pixel method to determine the parameter sensitive intervals.On this basis，a probability-weighted non-uniform sampling strategy is adopted to adaptively allocate the sampling resources to the high-sensitive areas while also considering global exploration.Simulation experiments show that，compared with the traditional uniform sampling method，the average prediction deviation mean，median and quartile range of damage matrix constructed by the proposed method are reduced by approximately 50.9%，57.8% and 52.9%，repectively，under the same number of sampling points.The proposed method can effectively improve the accuracy of damage matrix construction under the constraint of limited computing resources.

In order to quickly estimate the peak value of shock wave overpressure caused by the explosion of cased charge in the tunnel,based on the principle of energy conservation and Taylor fracture criterion,the equivalent conversion formula of cased charge and bare charge related to the strength,thickness and density of the case was derived,and the calculation model of shock wave overpressure in the tunnel of cased charge was established. The model and its parameters were verified by the existing tunnel explosion test of cased charge. Two engineering calculation methods for peak overpressure of explosive shock waves with cased charge have been developed. Method Iachieves equivalent conversion between cased charge and equivalent TNT bare charge through equivalent parameters η₁and η₂,and estimates them based on existing empirical formulas for peak overpressure of TNT tunnel explosions; Method IIachieves equivalent conversion between cased charge and free field TNT charge through equivalent parameters η₁,η₂,and η₂,and estimates them using empirical formulas for peak overpressure of free field shock waves; Method I is only applicable to straight tunnels with equal cross-sectional lengths and openings at both ends, Method II can be applied to tunnels with complex shapes,such as cross shaped tunnels. A static explosion test was conducted on a straight tunnel with cased charge and equal cross-sectional length at both ends. The results showed that both methods had good agreement with the experimental results. Method I had relatively higher calculation accuracy.

Infrared small target detection has attracted significant attention due to its strategic value in the key fields such as space-based early warning and maritime rescue.However，the extremely small pixel size，low signal-to-noise ratio，and complex background characteristics make it become a highly challenging visual task.Although the existing deep learning methods significantly outperform the traditional models，the intersection-over-union loss functions commonly used in the existing deep learning methods lack sensitivity to the absolute scale and spatial position variations of predicted targets，resulting in difficulties in achieving pixel-level precise localization and becoming a bottleneck for further performance improvement.To address these issues，this paper proposes an infrared small target detection method based on multi-scale spatial loss and morphological features.Firstly，an absolute-spatial ration （AR） loss function is designed，which enhances the perception of target scaletarget scale by introducing an adaptive dynamic weight based on area differences，and the radial-angular penalty terms in a polar coordinate system are constructed to refine the localization constraints of the center point.Secondly，a lightweight multi-scale prediction head structure is constructed in the U-Net decoder，thereby applying AR loss synchronously to the prediction outputs at different resolution levels to achieve a coarse-to-fine hierarchical supervision.Finally，a dual-stage morphological enhancement strategy for training and testing is constructed，embedding the structural priors via pooling-based differentiable morphological operators during training and correcting the connectivity of the predicted results through opening and closing operations during testing.On the IRSTD1k dataset，the proposed method achieves an intersection-over-union （IoU） of 67.59%，a detection rate （P_d） of 93.02%，and a false alarm rate （F_a） of 9.034×10^-6.Compared to the existing mainstream method DNANet，it improves IoU and Pd by 1.88% and 1.18%，respectively，and reduces the false alarm rate by 48.7%.This achieves a better balance between computational efficiency and detection accuracy.

To address the issue of aeroelastic instability in fuze turbine generators under wide-Mach-number and high-rotational-speed conditions,the deformation characteristics of blades and their impact on the aerodynamic torque are investigated using a sequential fluid-structure coupling method.The decoupling analysis of the loads reveals that the predominant cause of blade deformation is the high-speed centrifugal load,accounting for over 98% of the total deformation,rather than the aerodynamic load.The research demonstrates that this centrifugal-induced deformation leads to the significant geometric distortion of the blades,compromising the original aerodynamic profile.Consequently,the driving torque of turbine generator declines gradiently as the rotational speed increases.The torque is reduced by approximately 26.6% at the maximum rotational speed.The results reveal the underlying mechanism of the flexible blade deformation affecting the performance of fuze turbine generator,providing a theoretical foundation for the robust design of fuze power supplies.

To address the long-term credit assignment and multi-agent coordinative planning challenges in dynamic multi-aircraft mission planning，this paper proposes a novel reinforcement learning framework based on Value Mix Network （VM-Net）.VM-Net consists of three key components，i.e.，agent-level prediction module （VM-P），value mixing module （VM-M） and geometry-aware dense reward function，working in concert under the centralized training and decentralized execution （CTDE） paradigm.The VM-P integrates an improved gated recurrent unit （I-GRU） with a self-attention mechanism，enabling the agents to leverage the historical trajectories for accurate state evaluation and policy learning.The VM-M aggregates individual value functions into a global Q-function to achieve the explicit cooperation among agents under the CTDE framework.The geometry-aware dense reward function based on relative distance and angle effectively mitigates the sparse reward problem in task planning and accelerates policy convergence.Extensive experiments in both symmetric （up to 12v12） and asymmetric （6v24） scenarios demonstrate that VM-Net outperforms SAC，MAPPO and QMIX.It is still able to maintain real-time inference （<20ms per step） and high win rates （>80%） even in complex environments where baselines degrade significantly.The emergence of sophisticated cooperative behaviors during training—such as coordinated flanking and dynamic target allocation—further validates VM-Net’s practical utility and its potential for deployment in real-world adversarial environments.

In application scenarios such as missile tracking and drone navigation, the target tracking trajectory is influenced by various factors, such as changes in lighting, interference from similar targets, and occlusion. This inevitably introduces dynamically accumulated errors, leading to the phenomenon of target drift, making it challenging for conventional Siamese network-based trackers to maintain both accuracy and robustness in long-term tracking scenarios. To overcome this issue, a novel object integrity correction module is proposed, which takes inspiration from human visual habits and the intrinsic features of object integrity. This module is integrated with the SiamRPN algorithm, allowing for dynamic adjustment of the predicted bounding box during the tracking process. By providing real-time correction suggestions, this method effectively reduces the accumulation of errors that typically occurs during tracking, thereby enhancing the model’s ability to resist drift and maintain accuracy over extended periods. The effectiveness of the object integrity correction module is validated through extensive comparative experiments on publicly available datasets such as UAV123 and OTB100. These experiments demonstrate that the proposed module significantly improves the long-term tracking performance of Siamese network-based object tracking algorithms. Moreover, it alleviates the negative impact of various challenging factors, including illumination changes, variations in object pose and scale, as well as occlusion. The results show that the proposed method not only enhances robustness but also enables more reliable tracking in real-world, dynamic environments.