中国科技核心期刊
中国指挥与控制学会会刊
军事装备类重点期刊
中国指挥与控制学会会刊
军事装备类重点期刊
中国指挥与控制学会会刊
军事装备类重点期刊
In response to the issue of assessing the decision-making superiority of a System of Systems (SoS), this study focuses on capability packages and kill chains, proposing a system decision-making optionality concept framework and a decision-making optionality measuring model. Corresponding calculation models for the availability of capability packages and the effectiveness of kill chains within the model are also developed. The research findings of this paper are innovative in the measurement of SoS superiority, especially decision-making superiority, and can be used to assess the combat potential of mosaic SoS and combat target analysis.
Thematic information intelligence can provide professional intelligence support for specific field command decisions, strategic analysis, and target analysis. However, due to the lack of intelligent processing and utilization methods, the effectiveness of thematic information intelligence faces problems such as complex intelligence sources, large volume, low credibility, and low utilization rate. In view of this, based on knowledge graph technology, an intelligent service platform for thematic information intelligence was designed. The overall architecture and feature functions of the platform were analyzed. The key technologies were analyzed in detail, including knowledge graph construction, intelligent retrieval, knowledge recommendation, credibility evaluation, and auxiliary generation of thematic intelligence. The work of this paper can provide a reference for the construction of an intelligent utilization platform for thematic information intelligence.
With the advancement of multimodal large model (MLM) technology in capabilities such as information comprehension, logical reasoning, and content generation, its application in the military domain has reached a stage of maturity. This paper proposes a deception countermeasure architecture for command information systems based on MLM technology. First, the necessity of architectural research is clarified by examining the relationship among command information systems, military deception, and MLM technology. Subsequently, the deception countermeasure architecture and specific strategies are detailed at both the holistic and subsystem levels. Analysis demonstrates that the proposed architecture offers significant advantages in real-time performance, scalability, and flexibility. It can effectively disrupt enemy decision-making processes and prevent enemy deception operations, thereby providing engineering insights and theoretical support for the intelligent transformation of command information systems.
Core technologies for online mission planning of hypersonic glide vehicles—rapid maneuverability assessment and autonomous trajectory planning—are ushering in new development opportunities with breakthroughs in artificial intelligence and onboard computing capabilities. By systematically reviewing research progress and trends of four representative methodologies in autonomous trajectory planning and footprint determination (including drag acceleration profile methods, quasi-equilibrium glide condition solutions, rapid optimization techniques, and deep reinforcement learning approaches), this study conducts in-depth comparative analysis. Finally, prospects are provided for key technical directions and challenges in rapid maneuverability evaluation and autonomous trajectory planning, focusing on high-precision intelligent dynamic modeling, collaborative autonomous trajectory generation, and physics-informed neural networks, aligned with the evolutionary trends of glide vehicle technologies and AI advancements.
To address challenges in intelligent mission planning, including subtask decomposition, battlefield event ambiguity, and ethical trade-offs, a system architecture based on human-machine cognitive collaboration is proposed. By deconstructing cognitive processes into five dimensions (situational awareness, assessment, plan generation, evaluation, and action control), a capability complementarity model is established, optimized through dynamic weight allocation. The three-layer architecture comprises: a data support layer integrating operational rules, historical cases, and psychological monitoring for multi-source fusion; an intelligent processing layer utilizing knowledge graphs and hybrid reasoning engines for situational deduction, ethical assessment, and innovative planning; and a human-machine collaboration layer enabling bidirectional cognition via neural enhancement, ethical constraints, and dynamic task negotiation. Some reference for improving the quality and efficiency of human-machine collaboration mission planning system can be concluded from the study.
To address the issues of insufficient global optimality and robustness in traditional mission planning for unmanned aerial vehicles (UAVs) in urban disaster relief scenarios, this paper proposes a multi-heterogeneous UAV static task allocation algorithm based on improved genetic operators. By enhancing genetic operators, designing a functionally coupled chromosome encoding strategy, introducing adaptive crossover and mutation mechanisms, and embedding a path planning module into the task allocation algorithm, the accuracy of the task allocation cost function calculation is improved. This effectively overcomes the drawbacks of traditional methods, such as inaccurate allocation results due to path cost estimation deviations, as well as poor global optimization and robustness.
As humanity gradually enters the era of artificial intelligence, data elements are increasingly becoming the main driving force for productivity development, and optimizing the mode of business data compilation and submission has become even more important. In response to the problems of low efficiency, long time, easy errors, and unclear responsibilities in the existing data collection and reporting system, four data collection and reporting modes are designed. The data collection and reporting flow mechanism and data audit and verification methods are studied. The BPMN business process modeling symbol is used to model the process of the compilation and reporting mode. The Analytic Hierarchy Process is used to comprehensively compare and analyze different submission and reporting modes, and the optimal compilation and reporting mode is obtained as the data compilation room audit and verification compilation and reporting mode, which provides support for optimizing the business data compilation and reporting mechanism in the future.
By constructing a finite element analysis model of the vehicle platform, the impact of firing shock on the performance of a vehicle-mounted weapon system is systematically analyzed. The study found that the elevation angle in tracking measurements is negatively correlated with the platform deformation, while the artillery pointing is positively correlated with the platform deformation. There is a complex nonlinear relationship between the artillery elements and the platform deformation, and the error in the artillery elements is significantly greater than the platform deformation. Based on this, a multidimensional spatial interpolation compensation method is proposed, which effectively reduced the negative impact of firing shock on system accuracy. Simulation verification shows that this method significantly improves system accuracy and has important engineering application value, providing an important reference for related fields.
To address the limitations of conventional radar intelligence support model, particularly their monotonous product categories and inability to meet personalized user requirements, this paper proposes an innovative order-driven radar intelligence support model. Drawing inspiration from the order-response mechanisms of ride-hailing service, the proposed model establishes a bidirectional interaction architecture between intelligence systems and users (i.e., supply-side and demand-side entities). Through dynamic demand-side interactions and agile supply-side responses, the model achieves optimal matching between intelligence production and user requirements. The operational workflow is systematically analyzed, with focused investigation of core technologies including granular demand decomposition and precision-targeted intelligence generation. Theoretical analysis and simulation case studies demonstrate that compared with conventional approaches, the new model expands intelligence product diversity while significantly improving service quality and efficiency. This research provides both theoretical foundations and engineering guidelines for implementing diversified and precision-targeted radar intelligence support systems.
With the increasing demand for remote sensing observation from users in various industries, the current application mode of "passive response to user demand" for space observation resources is becoming more and more limited. Therefore, research on space observation mission derivation technology based on multidimensional data association is carried out. Firstly, the differentiated space resources are modeled to accurately describe the capability attributes of various space resources and space observation mission knowledge. Secondly, for all kinds of explicit or implicit space observation requirements, the method based on large language model is used to understand the requirements and extract the task elements; Then, a multi-semantic inference network is constructed to implement the derived reasoning of aerospace observation tasks. After that, the change rules of the historical task resource supply and demand relationship of typical users are mined to automatically recommend space resources. Finally, the derivation process of space observation mission in emergency disaster relief scenario is taken as an example to verify the method. The example analysis shows that this method can not only ensure the accuracy, but also effectively improve the operation efficiency and use efficiency of the aerospace observation system.
In response to the problem of large computational complexity and false detections in target detection by drones. A target recognition method based on lightweight networks has been proposed. Based on the YOLOv5 object detection algorithm, the algorithm has been optimized using the FasterNet lightweight network architecture, which reduces the number of network parameters and improves the efficiency of the algorithm. In order to accurately capture and emphasize key information in the input sequence, and further enhance the performance of the algorithm, a parameter free attention mechanism SimAM is introduced. The results indicate that this method is an optimized application of object detection technology, which can better balance the relationship between detection speed and accuracy, and achieve better detection results in unmanned aerial vehicle aerial image detection tasks.
The detection and recognition of small targets in complex naval combat scenarios is a critical component of achieving intelligent perception in modern naval operations. This paper provides a systematic review of the development of small-target detection technologies in such environments. This paper examines key technological advances in detection and recognition, including performance under adverse weather conditions, ship-type identification, and multi-sensor and multimodal fusion approaches. Based on battlefield requirements, this paper also explores potential future directions. Under the in-depth empowerment of artificial intelligence technology, the small target detection and recognition technology in complex naval battle scenarios is accelerating its evolution towards automation and expansion towards cluster collaboration. Meanwhile, its level of intelligence has been significantly improved, laying a solid technical foundation for the realization of all-weather and all-dimensional maritime information perception capabilities.
This paper designs a metasurface structure based on the principle of photon spin Hall effect. The high reflectivity in a small angle range is realized by using the high-intensity magnetic dipole resonance, which can effectively improve the energy transmission efficiency of the interface reflection process in optical edge detection. At the same time, the movement of the resonance peak in the wavelength domain under different structural parameters is verified, and the optical edge detection efficiency under various wavelength conditions is improved. This study can be applied to optoelectronics, laser weapons and other optical equipment. Compared with the traditional computer processing image edge detection method, it has the characteristics of high processing efficiency and reliability,low system delay,saving computing resources.
To address the complexity of the Joint Probabilistic Data Association (JPDA) algorithm, which is unsuitable for real-time multi-target tracking in complex electromagnetic environments, this paper proposes a Modified Joint Probabilistic Data Association (MJPDA) algorithm. First, the association matrix is redefined by taking multiple factors into account, and the association probability is calculated. Next, the correlation probability of public measurements in dense clutter is corrected by introducing the Mahalanobis distance for secondary weighting of public measurements, while also considering the influence of both public and non-public measurements. Finally, the corrected association probability is computed. This algorithm avoids the need to split the confirmation matrix, effectively addressing the exponential growth in computational complexity of the JPDA algorithm as clutter density increases. Theoretical analysis and Monte Carlo simulation results demonstrate that the improved algorithm offers good tracking performance with reduced computational load in dense clutter environments, significantly enhancing real-time performance.
Addressing the challenge of quantifying combat capabilities in complex military scenarios, this study proposes a novel capability measurement method based on the potential outcomes framework. This approach first define the object to be evaluated as an intervention variable and selects observable metrics that directly reflect operational effectiveness as outcome variables. Next, a causal graph is constructed, encompassing the intervention, combat capability, and operational effectiveness, thereby explicitly establishing the causal pathways between abstract combat capabilities and measurable effectiveness indicators. Finally, through causal effect inference and statistical significance testing, we transform the problem of measuring combat capability into a function of effectiveness indicators. Case analysis demonstrates that the proposed method, by utilizing effectiveness indicators as a measurement tool, can achieve indirect quantification of combat capabilities, offering a valuable reference for solving the quantification problem of combat capabilities.
How to evaluate the unmanned capability of weapons and equipment has become an urgent problem to be solved. This paper proposes a quantitative evaluation method based on the general mission profile of weapons and equipment. By analyzing the architecture of the general mission profile of weapons and equipment, the evaluation factors within the framework of the mission profile are sorted out, the depth of the unmanned design of each evaluation factor is identified, and the unmanned capability of a single architecture link is calculated. The quantitative value of the unmanned capability of weapons and equipment is calculated, so as to realize the quantitative evaluation of the unmanned capability of weapons and equipment. In addition, the precondition of the quantitative evaluation, the comparison of the unmanned capability of multiple weapons and equipment, and the advantages and disadvantages of the quantitative evaluation method are also given, which is convenient for the application of the method.
The location selection of wartime equipment repair forces in a combined force is a crucial factor affecting the efficiency of equipment repair forces. Reasonable selection of the location of equipment repair forces is essential for completing equipment repair tasks. This paper transforms the battlefield equipment repair location selection problem of a combined force into a specific battlefield network location selection problem, and establishes an optimization model composed of repair quantity, repair distance, coverage range, and maximum load. It also incorporates hard constraints such as coverage rate, anti-destruction deployment, and load balancing. By improving the ant colony algorithm, the node pheromone update, dynamic weight update, and heuristic local search operator are added to achieve the coordinated optimization of multiple objectives. Experimental results show that the proposed improved ant colony algorithm optimization method has better comprehensive performance, with significant improvements in coverage rate, repair distance, and load balancing. It is effective and has practical value for the battlefield equipment repair location selection problem.
In order to solve the problem that blockchain data cannot be tampered with after being uploaded, which will increase the risk of privacy leakage, an asymmetric encryption and secure transmission method of blockchain data under trust is proposed. Through direct trust measurement and asymmetric key mechanism, data processing is optimized and transmission security is enhanced. Authenticate encrypted data in the blockchain organization, distribute key information, determine the number of transmission rounds, and design a secure transmission method. Through the simulation experiment on Ethereum platform, the data encryption and decryption processing ability and node identity authentication ability under different encryption methods are compared and analyzed. The experimental results show that the encryption and decryption rate of asymmetric encryption method considering trust is close to the standard packet rate, and the maximum value of data packet is 461 byte and the minimum value is 399 byte, which is always within the predetermined standard range, showing high processing efficiency and security. The accuracy of authentication is 97.5%, the recall rate is 98.1%, and the F1 score is 0.977. It is proved that this method can effectively improve the security of data transmission and network performance, while maintaining the high efficiency of data processing.
With the development of Industry 4.0 and smart manufacturing, industrial information systems face increasingly complex security threats, especially in data security and risk identification. This paper investigates data security protection and risk identification techniques in industrial systems, analyses data flow characteristics and identifies the security risks of supply chain collaboration and device IoT data, focusing on APT, supply chain contamination and data integrity attacks. A multi-dimensional security protection system based on zero-trust access control, homomorphic encryption, distributed anomaly detection and hybrid risk assessment is proposed for these threats. Experimental results show that the scheme performs significantly in intrusion detection, data encryption and risk assessment, improves the security of industrial control systems, and provides support for future industrial information security protection.
From the perspective of the operational effect of air defense missiles in the Russia-Ukraine conflict, the medium and long range air defense missile weapons were not able to effectively support the role of air and space shield, but were suppressed by hypersonic weapons and anti radiation weapons. Through the research on the air attack threat environment faced by air defense weapons in the Russia-Ukraine conflict, this paper analyzes that the new generation of medium and long range air defense missile weapons and equipment should be improved from four aspects: enhancing the system’s anti strike capability, building the reconfigurable air defense combat capability, strengthening the concealed combat and mobile deployment capability, and the missile cluster interceptor missile design capability. Finally, this paper puts forward the technical approach to the construction of the new generation of medium and long range air defense missile weapons and equipment. Through the prospect of the system effectiveness of the new technical approach, it shows that the new technical approach can effectively support the acquisition of air supremacy under the new form.
As one of the core elements of the naval battlefield, situational awareness plays a vital role in supporting commanders to grasp battlefield information in an all-round way and ensuring the efficient execution of command decisions. Starting from the situation of future wars, this article studies and analyzes the key intelligent projects in the field of situational awareness of the US Navy under the guidance of the new combat concepts of the US Navy, the development strategy of artificial intelligence of the US military, and combat concepts. It also summarizes its key technologies and suggestions for the application of artificial intelligence technology in the field of situational awareness by the navy.
