The HAPNet-CD, a new change detection method, is proposed in this paper to solve the problems of noise misalignment, object boundary ambiguity and low change detection rate of small targets in the processes of encoding and decoding with the existing methods. On the one hand, the encoder of HAPNet-CD adopts siamese branches, in which HRNetV2 is used as the backbone network, and the alignment-and-perturbation-aided difference module is embedded to extract the variation features and difference information. As a result, the high-resolution feature representation can always be maintained in the process of feature extraction, so that the obtained features are more accurate in space. On the other hand, the decoder of HAPNet-CD uses the change features and difference information to construct a hybrid decoder and a differential decoder for decoding. By designing a loss function based on label smoothing, the network pays more attention to the variations of object boundaries and small targets, so that the change detection accuracy of object boundaries and small targets can be improved. Tests were carried out on the public data sets DSIFN-CD and LEVIR-CD, and the experimental results are as follows. Compared with the other 9 mainstream methods, the HAPNet-CD has improved the metrics of Precision, Recall, F1, and IoU by 2.55%,4.58%, 3.59%, and 5.9%, respectively, on the DSIFN-CD dataset. On the LEVIR-CD dataset, the Precision metric is improved by 0.54%, while the metrics of Recall, F1, and IoU are all close to the most advanced level.

With the widely use of embedded software，test towards embedded software has become a hot spot in software test area. Traditional interface test methods aim at embedded software depend on artificial data，which is not in support of general utilization. This paper focus on the design and generation methods of interface test data, and come up with a universal modeling tool towards protocol frame format to help testers completing the building process of data frame format. In order to achieve the automatic generation of test data，we designs the rules of data disturbance based on modeling tool. Experiment indicates that the method proposed by this paper to generate the interface test data of embedded software can improve the efficiency and accuracy of test，ascending the coverage of bugs.

Equipment circuits consist of numerous components with complex structures, making it difficult to accurately assess the severity of multi-component composite faults, which impedes effective planning of equipment operation and maintenance schemes. To address this issue, a grading method for equipment circuit fault severity based on residual life prediction is proposed with the residual life as the criterion for fault severity classification. Firstly, to overcome the scarcity of fault data samples in real-service scenarios for certain equipment types, a life prediction approach based on digital-analog fusion is introduced. A fault simulation model is established with Multisim to augment the fault dataset. Given the temporal and nonlinear nature of fault data, a bidirectional long short-term memory network (BiLSTM) is employed to construct a residual life prediction model. Secondly, a fault severity classification model based on residual life grey correlation analysis is developed to quantify the multi-level fault severity under different residual life scenarios and identify equipment fault severity levels. Finally, the efficacy of the proposed method is validated through a case study involving a specific type of equipment.

In response to the challenges faced by border areas, such as harsh natural environments, numerous monitoring blind zones, and limited management personnel, a fiber-optic distributed acoustic sensing (DAS) device that integrates Brillouin optical time-domain reflectometer (BOTDR) and phase-sensitive optical time-domain reflectometer (Φ-OTDR) has been developed to enhance the control capabilities of border management units. This device enables synchronous multi-parameter measurement with a single piece of equipment. Leveraging advanced signal processing algorithms, this system can dynamically perceive changes in environmental acoustic field energy, accurately identify and issue early warnings for intrusion behaviors. A series of experiments have verified the effectiveness and reliability of the system, providing a reference for establishing unmanned and intelligent warning and defense systems in border areas in the future.

The storage, transportation and launch container, serving as the carrying equipment for rocket projectiles, holds significant importance in monitoring its attitude and assessing its safety status during transit. To accurately identify the motion changes of the storage, transportation and launch container during transit, a dual-window-based method for detecting its behavioral attitudes is designed. Three-axis motion data of the container is obtained through attitude sensors; the first window is used for time segmentation and feature extraction of the time-series data, combined with the Temporal Convolutional Network (TCN) to identify the phase in which the container is located; the second window is utilized to assess potential hazardous behaviors of the container; and the results from both windows are integrated to complete the recognition of the container's behavioral attitudes. The experimental results demonstrate that this method can accurately identify hazardous behaviors of the storage, transportation and launch container at different stages during transit, providing a methodological reference for the future development of intelligent storage, transportation and launch containers and possessing certain engineering application value.

The efficient solution of UAV path planning problem is a key to ensure UAV flight efficiency and flight safety. To efficiently solve the problem of UAV 3D path planning, a method based on improved football team training algorithm is proposed. With the actual requirements of UAV flight path considered, the fitness function of UAV 3D path planning model under multiple constraints is constructed, which takes path cost, height constraint and turn constraint into account. Setting a typical 3D path planning problem as the solution object, the effects of three parameters, which are stochastic probability, learning probability and communication probability, are studied on the efficiency of the algorithm considering three evaluation indexes, which are path costs, iteration times and algorithm running time, respectively. Finally, a comparison experiment is conducted with the whale optimization algorithm, and the results show that the improved algorithm has a better solving efficiency.

In the future, the semantic communications will be widely used in cellular wireless networks. This paper focuses on the issue of the on-demand semantic communications in cellular networks in the context of device-to-device (D2D) content recommendation scenarios. A semantic transmission mode is proposed in this paper, which takes the target user's quality of experience (QoE) as the indicator. The mode allows the cluster head's target user to adjust the semantic compression ratio and select the access link based on the requirements of delay and image fidelity, and further designs a resource optimization problem from the perspective of semantic compression ratio and channel allocation. To solve this problem, a ratio compression factor is designed for the semantic encoding and decoding process in image semantic communications, and a small batch model training method is proposed to train sub-semantic models by randomly selecting batches, taking into account the model performance and training complexity. In addition, the game theory approach is introduced to solve the problems of channel allocation and semantic compression factor selection. The problem is modeled as a potential game problem, and utility functions and potential functions are designed, and the existence of Nash equilibrium is proved. Finally, a parameter correction space adaptive algorithm is proposed to achieve Nash equilibrium. The simulation results demonstrate the effectiveness of the proposed method on the overall QoE of the target user.

To address the issues such as the immobility, small killing radius, and significant post-war hazards of traditional landmines, a type of intelligent loitering landmine system deployed by rockets has been proposed. The combat effectiveness analysis model of the loitering landmine was established based on the Monte Carlo algorithm, used to explore the influences of some parameters like the lateral and longitudinal firing dispersion of the rocket launcher, the quantity, the perception capability and flight capability of loitering landmines. The results indicate that compared with traditional landmines, the operational efficiency of the intelligent loitering landmine has been significantly enhanced, and there exists an optimal matching effect between the strike probability and the firing dispersion of the rocket launcher. Additionally, the combat effectiveness is affected by performance parameters such as the mobility of the target, the flight speed and perception range of the loitering landmine. Enlarging the perception radius of the loitering landmine and increasing the flight speed are conducive to improving the blocking and control effect of the intelligent loitering landmine. The findings of this paper can provide technical support for the index demonstration, scheme design, effectiveness evaluation and operational application of the loitering landmine.

The metal airbag has become a research hot issue in the design of dynamic deformation and shock reduction structures of various spacecraft because of its high strength, good air tightness and environmental adaptability, as well as better shape stability, This paper mainly studies the key parameters that lead to fracture or fold instability during the inflation process of airbags, and also analyzes the influences of the location of the air inlet and the thickness of the balloon edge on the swelling effect. With the finite element simulation method, the five groups of commonly used metal material parameters are selected as the basic data to carry out the orthogonal experiments on material density, Young's modulus, Poisson's ratio and yield limit. The simulation results show that the maximum expansion height of the metal airbag is most affected by the material density, and the range is 8.26 mm. The maximum fold depth is most affected by the yield limit, with a range of 5.48 mm. The number of folds is least affected by the yield limit, and the range is only 0.8. The location of the air inlet will affect the uniformity of the balloon expansion, but will provide a larger expansion height in a specific area. Increasing the edge thickness will enhance the strength of the airbag, but reduce the maximum expansion height of the airbag. This conclusion can provide theoretical reference for engineering design of metal airbag.

The hollow-core fiber reinforced polymer (FRP)-concrete-steel (HC-FCS) column is a new type of concrete composite column, which is composed of an outer FRP tube, an inner steel tube and a concrete filling between the two tubes. This study numerically investigated the behavior of HC-FCS column against the close-in blast load. The arbitrary Lagrangian Eulerian (ALE) algorithm was used to establish the numerical model. The accuracy of the numerical model was first validated using the existing test results, the transmission process of blast wave, damage development of concrete, circumferential strain of FRP tube and residual mechanical properties after explosion are analyzed. The results demonstrate that the FRP tube is able to effectively confine the infilled concrete in the blast region during the close-in blast. Both the column's axial load capacity and axial stiffness are significantly decreased after the close-in blast. Changing the FRP thickness, steel tube thickness, hollowness ratio can improve the blast resistant capacity of HC-FCS column, with the effects of increasing FRP tube thickness and steel tube thickness more significant.

The basalt fiber reinforced polymer (BFRP) bar is a new material that can be used in the field of civil engineering instead of steel, and it is urgent to carry out an in-depth study on the failure mechanism of BFRP bar-concrete bond and bond strength. In this paper, the basic theories of elasto-plastic mechanics and concrete fracture mechanics are utilized to describe the bond damage process and failure mechanism of BFRP bar-concrete, and to establish a semi-empirical and semi-theoretical method for calculating the bond strength of BFRP bar-concrete. The method adopts the corresponding calculation method for the damage mode based on the logistic regression model, and comprehensively considers the effects of concrete strength, BFRP bar diameter, concrete protective layer thickness, and loading rate, and finally verifies the reliability and prediction accuracy of the calculation method through the relevant test data. The results show that the bond strength of BFRP bar-concrete is closely related to the damage mode; the tensile strength of concrete is the primary factor affecting the bond strength; the cracking state of concrete depends on the diameter of the BFRP bar; the thickness of the protective layer of concrete and the loading rate directly affects the bond strength of BFRP bar-concrete. The calculation results of this method are in good agreement with the test results, and the prediction error of the proposed method is 0.9%—23.7%,which provides an effective method for predicting the bond strength of BFRP bar-concrete. 

Low earth orbit (LEO) satellites are capable of conducting rapid geolocation of global navigation satellite system (GNSS) interference sources with Doppler measurement data. However, the highly dynamic characteristics of LEO satellites limit the quantity of acquired Doppler observations, consequently restricting the localization accuracy achievable through conventional least squares algorithms. To enhance the accuracy, a weighted least squares localization algorithm based on Doppler measurement Cramér-Rao bound (CRB) is proposed in this paper. This method incorporates a signal-to-noise ratio (SNR) lookup table for Doppler sampling instances to ascertain the Cramér-Rao bound (CRB), thereby standardizing the noise across various Doppler observation moments through weighting. This adjustment ensures that the least squares solution for the interference source location is made close to the optimal estimation. The effectiveness of the proposed algorithm was verified by simulation under different sampling rates, SNRs and sampling durations. The FPGA-based GNSS interference acquisition and localization system was also constructed and tested in real scenarios. The simulation and experiment results show that the proposed algorithm significantly improves the localization accuracy by 17.43%, compared with the least squares algorithm.

Comparison of intuitionistic fuzzy numbers (IFNs) is always the core issue of decision-making theory with intuitionistic fuzzy sets (IFSs). We are aiming to improve the comparison methods of the IFNs in this work, which have been known for lacking differentiating ability or being too complex in the structure. We propose a novel score function of the IFNs from a new perspective and define a new possibility degree formula between two IFNs, which can quantitatively measure the discrimination degree between any two IFNs, to expand the applicability of the proposed score function. Then, we develop a novel multi-attribute decision-making (MADM) method based on the proposed possibility degree formula and further apply it to solve some practical MADM problems under the intuitionistic fuzzy environment. Theoretical analysis and experiment results indicate that: the proposed score function has refined Atanassov's partial order and can construct a more reasonable admissible weak order among all IFNs, and the proposed possibility degree formula employs some nice properties and can effectively expand the usage of the proposed score function of the IFNs. Moreover, the proposed intuitionistic fuzzy MADM method, based on the possibility degree matrix, has a strong self-checking capability in the decision-making process and can ensure the validity of the final decision-making results by guaranteeing the calculation process, and is applicable for large-scale decision-making.

To enhance the enthusiasm of manufacturing units for participating in equipment warranty and improve the effectiveness of equipment warranty, a performance guarantee strategy is adopted for the two-dimensional warranty equipment that employs regular preventive maintenance. Based on the two-dimensional failure rate function of the equipment, the warranty cost model and equipment availability model are established. By constructing a benefit function that includes incentive measures, the warranty costs of the manufacturing units are linked to the minimum availability level required by the troops, and a multi-objective two-dimensional warranty equipment performance guarantee decision model is developed. The effectiveness of the model is verified through the numerical example of a certain type of vehicle equipment with the simulated annealing algorithm. The comparative analysis indicates that the multi-objective performance guarantee strategy can effectively improve the manufacturing units' profits while ensuring equipment availability, making it a win-win warranty strategy for both the manufacturing units and the troops. In addition, the sensitivity analysis provides management recommendations for the manufacturing units to carry out performance guarantee and guidance for implementing proposed performance guarantee strategies.

In order to study the injectable characteristic of coral sand materials from South China Sea islands and reefs, a series of orthogonal experiments on its injectable characteristic were carried out with superfine Portland cement slurry. The influence of factors such as compactness of coral sand, the water-cement ratio of the slurry, grouting pressure and pressure holding time on the stone rate of grouting was 0analyzed. The test results show that the sensitivity order of superfine Portland cement to the effect of coral-sand grouting stone rate is as follows: grouting pressure, water-cement ratio, pressure holding time and compactness. Multiple linear regression analysis method was used to establish the mathematical model between grouting stone rate and influencing factors, and the linear correlation of the model was good.

Vertical cylindrical steel storage tanks, which are usually used as oil storage facilities, are prone to overall deformation or local damage failure in the event of blast or other strong dynamic loads, which will result in significant losses. In order to address this issue, this paper proposes a rapid processing method in which the polyurea spraying is applied to enhance the blast resistance of existing steel tanks, and some blast resistance experiments on sprayed composite tanks have been conducted. The experimental results demonstrate that the polyurea layer can effectively absorb a portion of the energy of the blast products under the action of repeated explosion loads, resulting in a reduction of 12.3% in the transverse width of the concave yield surface of the coated tank and a reduction of 12.5% in the maximum deflection value. A numerical simulation with LS-DYNA was employed to reproduce the experiment. The numerical simulation results were then compared with the experiment in terms of the shape of the concave yield surface and the depth of the tank wall collapse. The result of this comparison demonstrates that the numerical simulation is able to accurately reproduce the experiment, thereby providing evidence of its reliability. The further investigations reveals that the polyurea layer decreases and diffuses the localized strong impact of the repeated blast loads, reduces the local impact compression capacity of the shock wave on the tank wall, and attenuates the stress concentration on the tank wall and weld joints, which can prevent parts of the tank wall from entering the plastic phase and producing local failure. Furthermore, the polyurea layer can reduce the peak kinetic energy of the tank by 27.8% under the action of repeated explosive loads, reduce the overall degree of collapse of the tank, and protect the structural integrity of the tank.

In response to the practical requirement of measuring the absolute spatial orientation of the artillery axis under the condition of an uneven artillery chassis, a dual theodolite spatial angle measurement method based on the solution of the direction cosine matrix is proposed. This method integrates the Beidou dual-antenna orientation and the dual theodolite measurement of three marked points to obtain the absolute spatial orientation of the artillery axis.With the horizontal and vertical angles of these three marked points determined by the theodolites as known inputs, the azimuth and elevation angles of the artillery barrel in the geographical coordinate system are derived through vector correlation and direction cosine matrix calculations, following the principle of double vector attitude determination. The accuracy of spatial angle measurement with dual theodolites is analyzed through the Monte Carlo simulation method, revealing that the azimuth angle measurement precision exceeds 57.6″ and the elevation angle measurement precision surpasses 28.8". An experimental test system, constructed with a high-precision two-axis turntable, demonstrates the azimuth measurement accuracy of 65.5″ and the elevation angle measurement accuracy of 51.1″, accounting for Beidou orientation errors. Both the simulation and experimental results confirm the effectiveness of this method for measuring the spatial orientation of the artillery axis.

Hyperspectral image target detection technology has important application value in many fields. In order to fully exploit the rich spatial and spectral information in hyperspectral images, a hyperspectral image target detection method called Gabor-CEM, which combines Gabor filtering with constrained energy minimization (CEM), is proposed. This method fully combines the advantages of the Gabor filtering and the CEM algorithm. The Gabor filtering is utilized to effectively extract the spatial texture and orientation features from hyperspectral images, providing abundant spatial information for target detection. Meanwhile, the CEM algorithm is leveraged for efficient utilization of target spectral information, enabling target localization and identification. Experiments were conducted using hyperspectral images captured by a field imaging spectrometer, and the results showed that compared with the traditional methods, the Gabor-CEM method can more accurately detect targets, reduce false positives and false negatives, and has significant advantages in target detection tasks, providing a new and effective approach for hyperspectral image target detection.

Existing code similarity detection models primarily focus on constructing encoders, with limited research on loss functions in deep learning. To address the overlooked issue of evaluating embedded binary function vectors, this paper proposes an angular-margin-based binary code contrastive learning framework (AngCLF). By optimizing the objective function of contrastive learning, the model's accuracy and convergence speed are enhanced. Besides, the study analyzes the reasons for the model's effectiveness and introduces multiple metrics for evaluating binary code vector spaces. The experimental results validate the accuracy of the AngCLF. The AngCLF surpasses six models including the jTrans model in accuracy, and has faster convergence speed and obvious advantages in alignment and uniformity metrics.

The evaluation of jamming effectiveness confronts some practical challenges such as information asymmetry, variable communication behaviors, and dynamic channel conditions in complex electromagnetic environments. Meanwhile, under the condition of empowering non-cooperative wireless network targets with artificial intelligence and machine learning theories and technologies, to achieve a precise and robust evaluation of jamming effectiveness remains a major bottleneck constraining the jamming effectiveness. To address the issue mentioned above, an efficient cognitive jamming method is proposed. Based on the deterministic channel modeling technology , this method employs a two-layer genetic algorithm to virtually estimate the performance upper bound of non-cooperative wireless network targets under different jamming decision scenarios. This estimated upper bound serves as the basis for evaluating the jamming effectiveness of different jamming decisions, enabling the selection of optimal or suboptimal jamming strategies. Simulation results and theoretical analyses validate the effectiveness and robustness of the proposed method, providing a reference for enhancing the evaluation of jamming effectiveness and achieving cognitive confrontation in the electromagnetic spectrum domain.

To enhance survival capabilities in modern battlefields, airborne multifunction radars exhibit the characteristics such as complex signal patterns, highly variable parameters, irregular on/off switching, and reduced radiation times, posing certain challenges to radar operating mode recognition based on traditional methods. By referring to sample data generated from typical characteristic parameters of common operating modes of multifunction radars, multiple model parameters are optimized with the water wave center diffusion (WWCD) algorithm, and an adaptive weighting strategy is employed to improve the performance of ensemble learning algorithms for multifunction radar operating mode recognition. Experiments were conducted using genetic algorithms, particle swarm optimization algorithms, differential evolution algorithms, and the WWCD algorithm to optimize single model parameters, and different ensemble learning strategies such as soft voting, hard voting, and adaptive weighting were used for operating mode recognition.The results demonstrate that the proposed algorithm achieves higher accuracy, compared with traditional algorithms. Furthermore, the performance of the algorithm in recognizing radar operating modes under small sample conditions was also tested, verifying the feasibility and high recognition efficiency of this algorithm.

The overload resistance performance of the rotary isolation mechanism is one of the critical factors ensuring the normal operation of trajectory correction fuses. Aiming at the operating environment of trajectory correction fuses for high-speed rotating projectiles, a rotation-isolating mechanism with the functions of "internal cushioning and external isolation"is designed. The elastoplastic coupling deformation of the mechanism is analyzed through a combination of finite element simulation, theoretical analysis, and experimental verification.The simulation results indicate that the internal multi-spherical point-contact cushioning component undergoes a deformation of 1.44 mm at the moment of impact, with a contact radius of approximately 2 mm after impact; the theoretical analysis reveals that a helical spring with a stiffness of 150 N/mm can meet the requirements for outer isolation design; the deformation of the cushioning component in the hydraulic impact test is basically consistent with the simulation results, which verifies the rationality of the structural design. The design of the rotary isolation mechanism will have a significant impact on the engineering application of trajectory correction fuze and the advancement of high-precision guided munitions.

In response to the lack of systematic research on the characteristic of flight stability of rotating stable projectiles with variation of position elevations, with the 155 mm howitzer as an example,the flight stability conditions of rotating stable projectiles were analyzed, and the characteristics of the gyroscopic stability, dynamic stability, and tracking stability with variation of position elevations were simulated and analyzed. The results show that on a certain elevation of the full trajectory, as long as the gyroscope stability of the projectile at the muzzle is met, it will inevitably meet the gyroscope stability on the full trajectory; as the elevation increases, the gyroscope stability factor increases, and thus the gyroscope stability enhances; under high altitude conditions, a decrease in air density is beneficial to maintaining dynamic stability, and with the increase of elevation, dynamic stability is significantly enhanced; the dynamic balance angle increases with the elevation of the position, and the tracking stability deteriorates. However, as long as the tracking stability conditions are met, the overall stability of high-altitude trajectory is stronger than that of low altitude; under high altitude conditions, it is necessary to avoid shooting at high firing angles to prevent the occurrence of excessive power balance angles that may cause fight instability.

Ammunition reserve and scheduling, an important link of ammunition support, has a bearing on whether or not the ammunition support task can be completed in a timely, accurate, and reliable manner. In order to solve the problem of joint optimization of two-level ammunition reserve and scheduling, with the optimization objectives of minimizing the total delay time, the minimum total cost and the maximum actual quantity delivered, considering the uncertainty of scheduling time, a multi-objective joint optimization model of ammunition reserve and scheduling is established, and the multi-objective model is transformed into a single-objective model by the linear weighted sum method, and then solving it using a particle swarm optimization (PSO) algorithm with a penalty function. Finally, the effectiveness of the model and solution algorithm is verified through a numerical example. Compared with a single-objective optimization strategy, the objective function constructed in this paper can effectively reflect the weight coefficients obtained from the expert evaluation method, and can balance all optimization objectives. In conclusion, this study can provide valuable references for the scientific development of ammunition reserve and scheduling.

Based on the fact that the existing calibration methods for imaging systems cannot effectively calibrate and fix the supe wide field-of-view infrared gaze imaging system. this research proposes a new indirect corner detection algorithm as well as an improvement scheme to address the problem of local optimization in the iterative computation of the Scaramuzza calibration model. We use morphological operations to detect the edges of the board calibration board at the pixel level, and then using interpolation techniques to refine the edges so that the edges have sub-pixel level accuracy, obtaining the four board unit corners near the real corner points, and indirectly obtaining the real corner coordinates by averaging the coordinates of the four corners, so that the corner detection correctness reaches 100%, which is much higher than that of general algorithms, and is more in line with the location of the real corner points. The SSRE is collected during each iteration by using specific circular area sampling grid points for the whole area, and then all the collected data are minimized to take the value, which overcomes the local optimum case.It improves the localization accuracy, and greatly reduces the iterative computation volume and the number of iterations. It compensated the existing general calibration algorithms to meet the shortcomings of the ultra large field-of-view infrared gaze imaging system.

As a new concept ultra-high-speed kinetic energy weapon, electromagnetic (EM) railguns possess extensive military application prospects; however, their firing power and development challenges remain unclear. Based on the analysis of the theory of electromagnetic railguns and the progress in armature technology, the development dilemmas of electromagnetic railguns are summarized. It is found that the magnetic saw effect occurring at the throat section of a U-shaped aluminum armature limits the firing power (i.e., muzzle momentum) of simple railguns. Based on this, a high-power EM railgun concept is proposed, which utilizes the principle of independent action of mutually perpendicular magnetic fields and the principle of mechanical contact force superposition and transmission, to synthesize two simple railguns into a complex railgun with dual pulsed power supplies (PPS), dual armatures, four rails, a single projectile, and a near-square bore. The mechanical structure of this railgun is compact and well-designed, with the two electrical circuits operating independently without interference, jointly accelerating the projectile. Its equivalent bore pressure and firing power can both be increased to approximately twice that of a simple railgun of the same caliber. The proposed design can promote the advancement of electromagnetic railgun technology and possesses certain military application value.

As an important anti-penetration device against high-explosive anti-tank (HEAT) projectiles, slat armor, with its unique design principle and structural features, is widely used in battlefields.Taking the traditional slat armor as the research object and focusing on improving the protection performance of armored vehicles, a new type of slat armor design scheme is proposed through innovative design of the unit structure. The finite element software is used to conduct simulation calculations on the anti-penetration behavior of the new slat armor against HEAT projectiles. The results show that the new slat armor design scheme has a greater improvement in realizing high-performance armor protection, compared with the traditional slat armor. It effectively enhances the defense ability against shaped charge ammunition coming from oblique directions with large angles of incidence, greatly increases the interception success rate. When used to protect the front, flanks, rear, engine and the top of the turret of armored vehicles, it can improve the protection performance and achieve all-round protection. This proposed armor design scheme has important military significance for improving the battlefield survivability and exerting the combat effectiveness of weaponry and equipment under the background of the threat of enemy shaped charge ammunition.