UAV combat style is widely used in modern battlefield due to its unique characteristics of “fast/precise/cheap”, and has achieved extraordinary combat effects. This paper analyzes the shortcomings of the current UAV combat style by summarizing the combat characteristics of UAV in modern battlefield and combining with the world’s advanced anti-UAV technology. To fill in the technology gap of UAV combat style and satisfy the demands of the future war and the anti-UAV technologies, the paper tries to find out the future development direction of military combat UAV by modern and foreseeable future technologies. This paper has certain reference value for the development of military combat UAV and its combat style.

With the continuous improvement of the performance of unmanned aerial vehicles and the extensive use of tactical methods, the cooperative operation of unmanned aerial vehicles (UAV) swarm has brought new challenges to the current air defense system. By combing and analyzing the application cases of UAV swarm warfare in recent years, this paper summarizes the characteristics of current UAV swarm warfare application, and explains the necessity and urgency of developing anti UAV swarm warfare command and control system. In addition, this paper analyzes the current situation of the command and control system of anti UAV swarm warfare in the world's military powers, and on this basis, puts forward some enlightenment suggestions for the development of the future anti UAV swarm warfare command and control system.

Capability requirement analysis is the key stage of operational concept development. Based on the formal description of the operational concept capability requirement analysis, a method of operational concept capability requirement analysis based on DRL(deep reinforcement learning) is designed from the perspective of qualitative and quantitative combination. In this method, small sample data sets with high reliability can be obtained through simulation experiments. Based on the experience data, the surrogate model of operation concept is constructed, and the model is optimized and trained by using multi-objective optimization algorithm with the high credibility simulation data set as the input. Finally, the agent model obtained from the training and the DRL framework are interactively optimized to achieve the reverse exploration of the operational concept capability requirements. The experiment results show that the method is feasible.

The command control (C2) is the most important part of the war for all dynasties. In information age, the future battlefield poses new challenges for C2. By analyzing the characteristics of network enabled command and control in the information age, this paper studies the C2 function and approach space, defines five C2 archetype, discriminates in detail the objectives and requirements of each archetype, analyzes its maturity level and maturity migration model, and finally discusses the challenges to C2 in the future battlefield. It is important to help the combatant analyze the problems existing in current C2, to improve the C2 ability of the current and future, to improve the control of the commanders, and to improve the manage ability of complex, dynamic and uncertain combat missions.

In recent years, based on high-end competition among powers, the US has taken a series of measures to strengthen its cyberspace warfare capabilities and maintain its leading position in cyberspace. Using literature research, case studies, system research, interdisciplinary research, combing analysis at home and abroad, a think-tank, academic circles about cyberspace warfare status quo and development of the related research literature in US, on the public to support the cyberspace warfare practice case, to distinguish the strategic instruction, combat forces, weapons technology, drill four major developments content, both across, such as politics, science and technology. The latest developments of US cyberspace warfare are systematically summarized based on the influence factors of disciplines and cross-fields. After that, the paper summarizes the new developments and makes innovative thinking in terms of strengthening top-level planning and design, strengthening professional personnel training, strengthening cyberspace weapons resarching, and strengthening offensive and defensive exercises in cyberspace, providing inspiration and reference for the PLA’s cyberspace warfare capability building.

An ontology-based knowledge graph construction method for military terminology is proposed, which is used to obtain semantic information in military terminologycorpus and construct military terminology knowledge graph. Then the ontology of military terminology is built firstly based on the analysis of military terminologycorpus. In this method, the rule based method and the pre-trained model based method are used to extract the relation of military terminology and the knowledge of military terminology is stored in the graph database at last. This method can construct high quality knowledge graph of military terminology for intelligent applications such as semantic search, intelligent question and answer.

The cooperative region search of UAV swarm can obtain ground information of the mission region and reduce the uncertainty of environmental information effectively. The traditional collaborative region search methods based on the balanced allocation of divided region and the heuristic algorithms depend on the pre-designed rules and heavy computation, and have no ability to generate new rules of the cooperative search. These algorithms belong to the algorithms that can not evolve new rules. Due to the complexity of the mission environment, the algorithms must contain fast,intelligent and robust characteristics, the cooperative searching algorithms of UAV swarm based on emerging theory with strong information fusion ability, self-learning ability have been widely concerned. Evolutionary and reinforcement learning algorithms are the important parts of the emerging theory and both of them can generate some new cooperative searching rules according to the different environment and task. The paper would systematically analyze and summarize the current research status and progress of cooperative search methods. Finally, the shortcomings of the existing research and the further development are put forward.

Aimming at the multitudinous battlefield situation information and the difficulty in recognizing the changing trends, based on large models, a situation awareness agent and an intelligent situation awareness inductive method are proposed. Starting from cognitive concepts and combining the abstractness and embodiment characteristics of agents, three key components in the construction of agents have been clarified: learning environment, memory mode, and knowledge generation mechanism. The architecture of the battlefield situation awareness agent is designed, including memory component, planning component, execution component, evaluation component, and key points for agent training. In the long-term memory component, based on the modeling characteristics of complex battlefield states, the paper discusses the application of large language models, multimodal large models and large sequence models.

In the process of the battle between the enemy and us on the battlefield, accurately predicting the deployment of the enemy forces will be beneficial to our combat. Based on the situation data of wargame, this paper proposes a method for predicting the unknown operator position of the enemy by training Graph Neural Networks. Firstly, after preprocessing the data, the transformation from situation to graph structure data is realized, and the graph structure data set of wargame situation is constructed for training Graph Neural Networks. Secondly, according to the characteristics of wargame situation and its data, GraphVAE model is modified to complete the graph structure data of wargame situation. Finally, a method for calculating the position of the enemy operator based on the completed graph structure data is designed. The effectiveness and feasibility of the proposed method are verified by experiments.

Information technology has encountered a bottleneck in the generation of combat effectiveness, which forces people to seek solutions through intelligent technology. At present, artificial intelligence has also successfully used artificial intelligence technology. They have also made some breakthroughs at the tactical level in the military field. However, at the campaign level, it has the greatest need to assist combat planning and decision-making, and also has encountered the most difficulties. From the current point of view, to realize the intelligent planning at the campaign level, we must not be blindly optimistic. We must scientifically demonstrate the development thinking and path, and gradually achieve the goal in stages, steps and fields by learning from successful cases, returning to the essence of artificial intelligence and relying on mature technology.

This paper analyzes the capability characteristics of the unmanned combat platform, envisages the cooperative application scenario of the unmanned combat system in the sea battlefield, designs the command and control system composition and command and control structure of the unmanned combat system, analyzes the main key technologies in the command and control of the unmanned combat system, and hopes to promote the cooperative operation application of the unmanned combat platform in the sea battlefield.

Intelligent battlefield situation assessment is the basis and key of realizing intelligent battle command. With the rapid development of machine learning and its wide application in military field, as well as the improvement of battlefield data acquisition ability, data-driven battlefield situation assessment based on machine learning has become a research hotspot. The author summarizes the concept of battlefield situation assessment and the research status of battlefield situation assessment based on machine learning, analyzes the existing problems of battlefield situation assessment based on machine learning, and looks forward to its solutions and research methods.

For the lack of command and control modeling principles and mechanisms in the current end-to-end campaign tactical level simulation for unmanned air combat, this paper systematically combs and studies the recent research in unmanned air campaign tactical simulation. Combined with the relevant research, this paper explored the principles and methods of different C2 modeling at different simulation levels and established a C2 simulation system suitable for the characteristics of CISE in unmanned air combat. Further, theoretical and practical guidance is provided for innovative demonstration and evaluation methods of CISE through the effectiveness evaluation support of unmanned air combat tasks.

The modern warfare has turned into a confrontation between the systems and the evaluation of operational system is an important method to strengthen the construction of the systems. This paper discusses the connotation and the challenges of operational system evaluation, analyzes the application and limitation of the traditional methods. Then new methods such as complex network, war-gaming and deep learning are studied and analyzed. Finally, thoughts and suggestions on the research are proposed.

This paper systematically compares the development history of the large-and medium-unmanned vehicle, sorts out the main R&D and test units, and analyzes the main features of their R&D, brings us different enlightenments from system design, capacity building and trial by the development of the U.S. military unmanned boat, which can provide reference for the future development of China's surface unmanned equipment.

Unmanned swarm operations have become the normal mode of modern warfare. How to realize the coordinated control of manned nodes and unmanned swarms is the key to give full play to the combat effectiveness of unmanned systems. This paper sorts out the development route of foreign unmanned swarms, describes the possible cooperative operations between unmanned swarms at sea and manned warships, analyzes the use of intelligent unmanned swarm operations in future wars and the demand for continuous improvement of ability and discusses requirements of swarm coordinated command and control for the compatibility with the manned warship combat system, the openness of the architecture, and the swarm intelligence. Finally, it proposes a manned-unmanned cooperation control structure for unmanned swarm at sea, gives a functional service deployment idea that can adapt to distributed and centralized control, and helps to promote the rapid formation of the collaborative capability of manned and unmanned swarms at sea.

Military regulations are of great significance to modern military operations. However, consulting the texts is inefficient and error-prone. A military legal question answering system is constructed by integrating retrieval and knowledge graph technologies. The optimized TF-IDF model is used to establish a data structure for the hierarchical retrieval of laws and regulations to improve the efficiency. Knowledge graph technologies are used to generate a large amount of knowledge for the clauses of laws and regulations, ensuring the ability of question understanding. According to the characteristics of military laws and regulations, the algorithms of question processing and clause retrieval are designed, and the complete answer is composed of a short answer, clause content and an answer source. Analysis and testing show that the underlying data constructed is highly hierarchical and semantically rich. The prototype system can accurately answer questions from multiple perspectives, and it combines the advantages of retrieval and knowledge graph technologies. The system can provide decision aid for the commander to deal with legal problems, and the technologies are also applicable to regulations in other fields.

The Manned-Unmanned Teaming technology can fully leverage the low cost and expendable advantages of unmanned platforms to expand the operational space of manned platforms, thereby enhancing their situational awareness, penetration capability, and survivability. This paper provides a research overview on the development of MUM-T in the United States, Britain, France, Australia, South Korea, and other countries. It provides several application examples of MUM-T in foreign militaries on marine, land, and air space. It also analyzes some technical challenges and key technologies of MUM-T in wireless communication and networking, remote measurement and control, autonomous decision-making, and human-machine interaction. Finally, the future development trend of MUM-T is prospected, which can serve as a reference for the study of collaborative combat styles and related technological research in future joint operational systems.

In this paper, the coverage model of Starlink constellation is established by means of the Satellite Simulation Kit (STK), and the coverage capability of Starlink constellation to Washington, Beijing, Taiwan and Kiev, which are located in north latitude 70 degree to south latitude 70 degree, is simulated and analyzed in detail. The simulation results show that the Starlink constellation can reach 100% coverage between the north latitude about 53 degree to south latitude about 53 degree, and the 1.5v Starlink satellites begin to cover the bipolar areas up to the present. Obviously, the Starlink constellation is developing steadily towards global coverage. According to simulation results, the Starlink constellation can achieve 24-hour full coverage in high latitudes such as Washington, Beijing and Kiev, and the coverage satellites number is large. But the Starlink constellation can’t achieve 24-hour full coverage in Taiwan and other low latitude regions. In conclusion, the Starlink constellation coverage capacity of all regions in the world is improving steadily and in high speed.

The paper introduces the origin and concept of the digital twin technology, and the difference between digital twin and parallel system/simulation system. Combined with the application of digital twin in the weapon equipment system, it designs the technical framework, application framework, and puts forward the key technology of weapon equipment digital twin design in equipment perception, model building, system integration, evaluate forecasts, interaction control five areas, and the theory and practice evolution suggestion of the digital twin.

In recent years, underwater systems have gradually evolved toward unmanned, intelligent and swarmed directions. The perception and cooperation techniques, as the key techniques of the unmanned system swarm, have enormous potential in maritime application scenarios. In this paper, we first review the background and related work on the research of underwater unmanned systems at home and abroad and further illustrate the significance and practicability of developing underwater unmanned system swarm for our country. Next, we summarize and analyze the underwater perception and underwater collaborative techniques, and elaborate the developments in details for underwater acoustic and optical perception, under cooperative communication, cooperative control and cooperative navigation and positioning. Finally, we address the challenges on perception and cooperation for underwater unmanned system swarm, and provide the potential development trends. The research can be used as a technical guide for underwater combat missions.

Starting with the concept, principle and classification of AI technology, this article focuses on the analysis of three main scenarios and eight key directions of AI military applications. It comprehensively uses the maturity evaluation method of technology patent analysis and the Gartner technology maturity curve to evaluate the maturity of eight key directions of AI military applications.

With the evolution of war forms and development of weapon equipment systems, the new intelligent equipment selection and decision-making methods are more and more important for equipment construction top-level planning and combat decision making. Based on the systematic analysis of the background and development status of equipment combination selection, this paper explains the conceptual connotation and technical framework of equipment combination selection, discusses the main methods of equipment combination selection from four aspects: problem construction, candidate equipment space construction, value construction and optimization selection, and analyzes the existing problems and development trend, and provides reference for the research and application of equipment combination selection.

Facing the asymmetrical conditions in both overall national strength as well as military strength in a certain regional conflict, the weak side takes UAVs of observation and attacking integrated capabilities as its break through, thus achieving effects that exceed expectation in repeatedly low-intensity regional conflict operation, and makes innovation to intelligence guerrilla warfare tactics at the same time. This paper first clarifies and summarizes basic information about UAV operational applications of both sides in the conflict, then analyses the characteristics of UAV operation, further on, it makes suggestions on enhancing UAV data chain construction, the importance of collaborative use of manned/unmanned aerial vehicles, innovation on warfare strategy and tactics, as well as the design of anti-UAV strategy, in hopes of providing some preset reference for our army in response to the concept of unmanned combat in the intelligence warfare era.

In recent years, the breakthrough of machine learning based on deep reinforcement learning provides a new development direction for intelligent game confrontation. In order to solve the problems of slow convergence speed and great difference in training effect of heterogeneous multi-agent reinforcement learning algorithm in intelligent confrontation, this paper proposes a priori knowledge-driven multi-agent reinforcement learning game antagonism algorithm PK-MADDPG, and constructs a MADDPG model under the framework of double Critic. The model uses the experience first replay technique to optimize the prior knowledge extraction, thus achieving remarkable results in the training of game confrontation. In the national competition of MaCA heterogeneous multi-agent game confrontation, the paper compares the game confrontation results of PK-MADDPG algorithm with classical rule algorithm, and verifies the effectiveness of the algorithm proposed in this paper.

This paper summarizes the origin, development and interrelation of system science systems, such as system engineering, system engineering and digital engineering. Based on the analysis of the development of underwater attack and defense systems at home and abroad, and in view of the main problems faced by underwater attack and defense systems in the development process, such as complex system operation mechanism and weak technical foundation, this paper expounds the necessity of applying the relevant theories of system science system to the construction and development of underwater attack and defense systems. From the perspective of system engineering, system engineering and digital engineering, the paper puts forward relevant development suggestions of underwater attack and defense system, which has certain military significance and theoretical value for the subsequent research of underwater attack and defense system.

Modern war presents the explosive growth of battlefield information and new combat style. With the continuous emergence of new technologies such as artificial intelligence and edge computing, a new generation of command information system is coming. Based on the international fourth generation command information system, this paper imagines the overall architecture of the fifth generation command information system, expounds the technical characteristics of its knowledge center, intelligent enabling, cloud edge integration, independent evolution and resilience adaptation, analyzes its key technologies, continuously improves the battlefield information advantage, and transforms to the battlefield cognitive advantage, decision-making advantage and action advantage.

With the development of intelligent technology, the future air combat will present the widespread participation of intelligent weapons, and the research on the design of intelligent air combat concepts has become a hot topic in the military field. The DoDAF is the framework of the defense system of the United States, which mainly used the model of DoDAF to design the architecture framework of the intelligent air combat concept, and provides the reference and basis for the following research on the concept of intelligent warfare in the air, which has some military practical significance.

The command decision and action control of UAV command and control system are indispensable in the process of UAV sea combat. This paper analyzes in detail the characteristics of the application of UAV and buzzer in naval anti-ship operations, air defense operations, amphibious landing operations, etc. Combined with the development of UAV and buzzer battle command and control system in the United States in recent years, it puts forward some enlightenment and suggestions for the development of future naval UAV and buzzer battle command and control system.

Strategic evaluation is the key link of military strategic system and capacity building. Selecting and evaluating the system construction scheme can optimize strategic decision-making and improve strategic management level to a certain extent. This paper constructs an intelligent selection analysis framework of "prospect cost" system construction scheme based on MATE, and uses NSGA-Ⅱ intelligent optimization algorithm to find the Pareto front of alternative scheme in multi-dimensional tradeoff space, which improves the problem of large data volume. Taking a joint operation system as an example, the effectiveness of the proposed method is verified, providing theoretical support for the optimization and evaluation of system construction scheme.

UAV swarm operations are developing rapidly towards intelligence and actual combat, which will pose a huge threat on the future battlefield. Therefore, research on anti-UAV swarm operations is imperative. This paper analyzes the development history, research progress, and actual combat application of UAV swarms and sorts out the research status of foreign anti-UAV swarm operations from three aspects: detection and tracking, hard damage, and soft kill methods. Hard damage include conventional weapons, directed energy weapons, and armed combat drone, and soft kills include electronic jamming and deception control. Finally, the future development trend of anti-drone swarm warfare is proposed, including seamless and comprehensive detection and early warning, efficient intelligent decision-making and deployment, the coordination of new conventional weapons, the combination of soft and hard damage, multi-dimensional intelligent system operations, and standard formulation are urgently needed.

With the development of science and technology, the Mosaics theory has been put forward and applied in practice gradually. This paper analyzes the basic characteristics of Mosaics, such as the plurality of subjects, the fusion of forms, the bewilderment of actions and the controllability of risks, it also researches the operation mechanism of Mosaics about the distributed decomposition of complex systems, networked integration of decomposition elements, intelligent aggregation of integrated systems and highly elastic self-healing of polymeric systems. This paper puts forward the Mosaic winning mechanism of distributed system winning, network system winning, intelligent system winning and high elastic system winning. This paper lays an important foundation for the in-depth study of the mechanism of winning the mosaic war and winning the initiative in the future war.

There are various ways for various services to carry out accusation information interoperability. The establishment of a standardized accusation information interoperability framework can provide a way to solve the problem of diversified and complicated implementation of accusation information interoperability between systems. This paper analyzes and compares three types of design methods, centering on the Battle Management Language(BML), combined with the structural concepts of Service-Oriented Architecture(SOA) and Unified Architecture Framework(UAF). Finally, a directly connected structural framework was chosen to build, and a public service supporting structural framework including six levels of system, technology, resources, service, function and organization, and multiple elements such as ontology model, semantic mapping and model generation is constructed, providing theoretical support for the research on standardization of accusative information interoperability.

The breakthrough and progress of intelligent gaming technology with deep reinforcement learning as the core in the field of games provide a method reference for the research of agents in sea-air wargames. The architecture design of the agent is the primary core key problem that needs to be solved, and a good architecture can reduce the complexity and difficulty of training and accelerate the convergence of policies. A stochastic game model of sea-air cross-domain cooperative decision-making has been proposed, and its corresponding equilibrium solution concepts have been analyzed. Based on the analysis of typical agent frameworks, aiming at the decision-making gaming process of sea-air wargames, and then an agent bi-level architecture based on multi-Agent hierarchical reinforcement learning is proposed, which can effectively solve the problems of collaboration and dimensional disaster. The key technologies are analyzed from four aspects: force coordination, agent network design, adversary modeling and training mechanism. Hoping to provide architectural guidance for the subsequent design and implementation of sea-air wargaming agents.

Operation task planning is mainly used to support pre-war planning and in-war control of operational plans. The fast pace, high intensity and complexity of modern warfare make it difficult for commanders and staff organizations to undertake heavy tasks. There is an urgent need to use intelligent technology to improve the level of decision-making automation and autonomy. This paper summarizes the concept and existing methods of operation task planning, analyzes the limitations of military application and the difficulties caused by the complexity of war, expounds the necessity of intelligent methods to assist operation task planning in threat judgment, temporal and spatial reasoning, strategy generation and evaluation, strategy learning and growth. Furthermore, the framework design and theoretical basis of operation task intelligent planning is proposed, which can be used for reference to realize intelligent operation task planning in the future.

As a high-value target, aircraft carrier formations will inevitably become the focus of drone swarm attacks, and the importance and necessity of Counter-UAV swarm operations are constantly highlighted. The article expounds the characteristics of the threat of UAV swarms faced by aircraft carrier formations, and analyzes the current Counter-UAV swarm combat capability of aircraft carrier formations based on the actual weapons and equipment and tactical tactics, and then proposes future aircraft carrier formations. The capability requirements provide a theoretical basis for the formulation of the aircraft carrier formation Counter-UAV swarm combat plan and the development of future aircraft carrier formation air defense weapons.

According to the autonomous characteristics of the unmanned combat system in the context of military application, the level division of the autonomy of the unmanned combat system is proposed and its conceptual model is established. The paper analyzes the autonomy of unmanned combat systems, establishes relevant hierarchical models and assessment methods. A task-oriented optimal assignment model for autonomy level of unmanned combat system is proposed. First of all, the operational task planning model of unmanned combat system is established, and takes minimality of the consumption of task resources and the total time of task completion as the goals. In addition, the autonomous level modulation model of the unmanned combat system is established. The decision rules are formulated to maximize the task completion rate of the unmanned combat system in the execution of combat activities while minimizing the resource consumption and the risk of executing tasks. Finally, a landing battle case is designed to verify the correctness and effectiveness of the hierarchical optimization distribution model proposed in this paper.

With the rapid development of multi-agent collaboration, unmanned swarm systems, network centric warfare and other technologies, future operations will face supersaturated and intelligent UAV swarm cooperative attacks. By analyzing the characteristics of unmanned aerial vehicle swarm and the development of unmanned aerial vehicle swarm technology abroad, this paper studies the combat style of unmanned aerial vehicle swarm at sea. It also puts forward some enlightenment for the development of unmanned aerial vehicle swarm at sea in the future.

In view of the requirements of air defense equipment system construction and equipment development, take the air attack/anti air attack operation in the Russia-Ukraine military conflict in February 2022 as an example to analyze the key factors that affect the countermeasure effect, such as the attacker’s electronic jamming effect, the cruise missile penetration height, and the defender’s air defense and anti-missile weapon performance. Three exploratory experimental schemes are designed by using exploratory analysis combined with simulation. The influence of the above factors on the hit quantity of tactical ballistic missiles, cruise missiles and other munitions of the attacking side is quantitatively analyzed through simulation, and the development suggestions of the defense’s air defense and anti-missile equipment system, such as networked operations, integrated air defense and anti-missile are put forward, providing reference for the development, system construction and application of air defense and missile defense equipment.

The offensive and defensive confrontation between the submarine and the surface ship formation is the key content of submarine combat research. How to ensure that the submarine survives and breaks through the joint blockade of the ship formation and anti-submarine helicopters is a test of the submarine command decision. To this end, in view of the asymmetry of the submarine-ship-helicopter confrontation scenario, the submarine agent is constructed from two aspects of deep reinforcement learning and rule inference, and two Proximal Policy Optimization (PPO) algorithm improvement mechanisms are proposed. It carries out mutual game confrontation and distributed training, and finally realizes the intelligent decision-making of submarines in the confrontation process. Related technical routes and algorithms have been implemented and verified on the wargaming platform. The improved algorithm has greatly improved the convergence speed and stability. The research on submarine intelligent command decision-making provides technical reference.