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
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.
Aiming at the cooperative pursuit and confrontation task of multiple UAVs in the unknown escape UAV environment, a multi-UAVs cooperative pursuit and confrontation strategy based on P3C-MADDPG algorithm is proposed. First, in order to solve the problem of slow training speed and over estimation of Q value of Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm, In MADDPG algorithm, Prioritized Experience Replay (PER) based on tree structure storage and a parallel Critic network model with 3 threads are prioritized respectively, and the P3C-MADDPG algorithm is proposed. Then, based on the kinematics model of UAV, training elements such as state space, reward function combining sparse reward and guided reward, pursuit action space with different accelerations are designed. Finally, based on the above training elements, the P3C-MADDPG algorithm is used to generate the cooperative pursuit and confrontation strategy of multiple UAVs in the unknown escape UAV environment. Simulation experiments show that the P3C-MADDPG algorithm increases the training speed by 11.7% on average, and decreases the Q value by 6.06% on average. The generated multi-UAV cooperative pursuit and confrontation strategy can effectively avoid obstacles, and more intelligently realize the pursuit of unmanned aerial vehicles with unknown strategies.
Helicopter is the superior combat force of low altitude and ultra-low altitude. With the increasingly complex battlefield environment and the continuous upgrading of battlefield threats, the combat capability of helicopter is required to be higher. This paper briefly describes the helicopter construction and application of Russian air forces during the conflict between Russia and Ukraine, summarizes the helicopter battle loss, analyzes the causes of helicopter battle loss, and puts forward measures and suggestions to promote the helicopter equipment construction and development based on the research of the helicopter ability defects, which has a certain reference value for helicopters to adapt to the future battlefield environment and combat effectiveness improvement.
With the continuous deepening of the reform of the military organization system, the military equipment presents the characteristics of technical complexity and variety, and the issue of equipment supply and support is increasingly. It is of great significance to study how to meet the requirements of equipment use and maximize the efficiency of support. On the basis of summarizing the current research situation of equipment supply and support at home and abroad, this paper proposes practical problems which need to be solved urgently in the army. Using numerical integration methods, a quantity decision-making model is established from four aspects: satisfied quantity, shortage quantity, redundant quantity, and error quantity. The optimal equipment supply and support quantity is obtained through programming and solving with Matlab. Finally, an example is used to verify the accuracy and practicality of the model.
Aiming at the problems of low efficiency of minor repair and maintenance of military equipment in the synthetic force, strong randomness of maintenance human resource allocation, and unbalanced and unreasonable resource utilization, taking the armored equipment as the research object, this paper analyzes the task and demand of the operation process of relying on maintenance workshops to carry out equipment minor repairs in peacetime. The optimization goals are to minimize the total maintenance period and maximize the balance of maintenance personnel allocation, taking the professional and quantity requirements of maintenance personnel in the maintenance process as constraints, a mathematical model of the equipment minor repair operation process is constructed. And then aiming at the sequence relationship of maintenance procedures, a maintenance network process update algorithm with tabu table and a genetic algorithm considering equipment parallel maintenance operations are proposed to optimize the maintenance human resource allocation strategy for equipment minor maintenance operations. The example shows that the algorithm is reasonable and feasible.
In order to solve the problem of how to quickly and accurately obtain the location information of self-organizing networks or target objects in the narrow and closed battlefield environment, such as the enemy command center, cabins, and underground buildings, this paper proposes a positioning algorithm based on the communication module provided by individual intelligent terminal equipment, we use the support of hardware devices such as visible light sensors, and study the communication signal fingerprint of swarm intelligence perception, combined with image matching algorithm. This algorithm mainly communicates with fingerprint data to achieve preliminary positioning, combines a weighted average algorithm of fused images and attitude sensors, and uses swarm intelligence perception to supplement and update positioning data. By adjusting the image matching strategy, while maintaining accuracy, compared to a single image matching positioning algorithm, it reduces computational power requirements and improves real-time performance in battlefield environments with complex communication conditions. Compared with the standard WKNN (Weighted K-Nearest Neighbors) algorithm, it improves the stability of localization in complex environments, and the average localization error is less than 1.72 m, reducing the error by about 50%.
In this paper, the key technologies of multi-radar network and cooperative detection are studied in order to meet the urgent needs of radar network operations in the future strong countermeasure environment. Firstly, the operational capability requirements of radar network are introduced. Secondly, based on the traditional tree hierarchical structure of radar network, the new distributed network architecture is given. Finally, the key technologies of radar network information distribution and sharing, intelligence fusion processing, autonomous cooperative detection and system feedback control are studied. This paper will promote the updating of the concept and the development of the domain technology of the multi-radar network, and will promote the iterative upgrading of radar equipment and intelligence systems.
In order to improve the tracking performance of cognitive radar, this paper proposes a waveform selection algorithm for cognitive radar tracking assisted by amplitude information. Firstly, the framework of waveform parameter selection for cognitive radar tracking is discussed. Secondly, the performance of amplitude-assisted tracking probability data association is analyzed, and the method of waveform parameter selection is proposed. Finally, combined with the Interactive Multiple Model Unscented Kalman Filter (IMMUKF), an amplitude information assisted waveform selection algorithm for cognitive radar tracking is proposed. Simulation results show that the proposed algorithm can effectively improve the target tracking performance and reduce the probability of target tracking loss.
The accurate prediction of driving intention and driving tracks of surrounding vehicles is the basis to ensure the safe driving of Intelligent Connected Vehicles in complex road scenes. This paper proposes a driving intention and behavior prediction model of intelligent connected vehicles based on BLSTM-DCG-ATT by combining Bi-directional Long Short-Term Memory, Deep Convolutional Generic Adversary and Attention Mechanism. The data with dual characteristics are obtained through the forward and reverse Bi-directional LSTM link and attention mechanism, and then the characteristic data are convolved through the Deep Convolutional Generic Adversary to iteratively generate the lane change intention and driving data of the intelligent connected vehicle and surrounding vehicles in the future. The simulation results show that the model can accurately predict the lane change intention and driving track of the intelligent connected vehicle and its surrounding vehicles under the condition of complex road network and dense traffic flow, and the prediction accuracy reaches 94%.
It is always difficult to analyze the law of ship movement, especially the behavior of ship. In this paper, a frequent pattern mining method based on a large number of historical track clustering of ships is proposed to estimate the future behavior of ships, and the software implementation is presented. In this paper, a comprehensive similarity measurement method of track is proposed and the meaning of frequent pattern mining based on track clustering is introduced. Secondly, the adaptive transformation of the classical density clustering algorithm is carried out and the implementation method of the clustering algorithm based on comprehensive similarity is given. Then, the most similar cluster of virtual trunk track calculation is extracted, and the estimation results of current ship behavior are obtained by statistics. Finally, the software design and test results based on C/S architecture are given. Experimental results show that this method can describe the behavior of track association, and the behavior estimation results obtained by the software can assist the research and judgment.
As one of the main ammunitions for attacking air targets, the fragmentation and shock wave power of grenades are important parts of evaluating damage ability. In order to study the comprehensive power of grenade, grenade simulation ammunition is designed refers to Italy’s Oto Melera 127 mm ammunition. On the basis of experiment, numerical simulation and empirical formula, the fragmentation velocity, fragmentation spatial distribution and shock wave overpressure are analyzed. The experimental results show that,the scattering direction angle of the grenade simulation ammunition is 93.67°, the scattering angle is 65.42°, and the initial velocity of the fragments is 1 451 m/s. The simulation and calculation results show that, for the scattering angle, the deviation between theoretical and experimental values is relatively small, for fragmentation velocity, the error between theoretical calculation and experimental value is less than 20%, for shock wave overpressure, the error of theoretical value, simulation value and experimental value is less than 15%.
By analyzing the performance and main penetration technology of typical subsonic anti-ship missile of formidable enemy, this paper proposes a similarity analysis method based on the characteristic decomposition of threat target and constructs the similarity model of simulated threat aircraft. And the proposed method and model are used to evaluate the similarity of the target drones and analyze the difference between the target drones and the typical simulated objects. On this basis, this paper studies the current methods of building typical threat situation and analyzes the deficiency. According to the above results, this paper puts forward some thoughts on how to improve the ability to simulate the formidable enemy anti-ship missile target, how to improve the air defense and anti-missile training effect and how to build a systematic air blue force. These considerations provide the basis of the construction of the air threat situation for the firing range.
In order to give full play to the maneuverability of sea-based ballistic missile defense force and expand the level of sea-based ballistic missile defense, this paper studies the deployment of early warning and detection ship in ballistic missile defense operations, and establishes the radar detection model of early warning and detection ship from the aspects of ballistic missile movement characteristics, radar detection power and visual range limitation. Taking medium-range ballistic missiles with a range of 500 km-5 500 km as an example, three trajectory forms of minimum energy trajectory, low launch trajectory and high launch trajectory are distinguished, and the detection capability of the early warning detection ship against the incoming ballistic missile under different deployment positions is simulated and analyzed. Based on this, the corresponding deployment method of early warning detection ship is given. The conclusions obtained can provide reference for the force deployment in sea-based ballistic missile defense operations.
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 electro-hydraulic position servo system of a single rod hydraulic cylinder is used in a large number of engineering applications due to its compact structure, but due to its asymmetric structure and complex mathematical model, many factors cannot be accurately analysed by mathematical methods. To address this problem, a physical model of the electro-hydraulic servo system of a single rod hydraulic cylinder is established using Matlab/Simulink multi-domain physical modelling method to study and analyse its performance. The response graphs and Bode plots are obtained by inputting sinusoidal and square wave signals respectively. The simulation results show that: the physical model of the electro-hydraulic position servo system of a single rod hydraulic cylinder can directly add the corresponding components and environmental influence factors according to the working principle, the model accuracy is high, no transfer function is required, and the simulation results are more accurate and closer to the actual situation, which is conducive to the analysis of the control performance of the electro-hydraulic position servo system and has a more effective reference value to improve the accuracy of the system model simulation.
Aiming at some "pain points" in data access of the wargame system, a bus-based real-time data collection and management platform for wargame is designed by absorbing the experience and lessons of domestic and foreign wargame systems. The distributed storage platform is introduced as the underlying storage foundation, and the in-memory database is introduced as the external service interface. The bus-based data collection is used as the collection source, and data cleaning and branch management based on data segments are performed. The system as a whole is divided into three modules, namely collection module, management module, and service module. It realizes real-time collection, cleaning, storage and management of wargame data. The practical application shows that the platform provides high-speed and reliable data access support for other modules in the wargame system.
Aiming at the lack of simulation test means for unmanned equipment at the firing range, this paper designs a simulation test training system for unmanned vehicle motion control based on CoppeliaSim simulation software and on the basis of the construction of unmanned vehicle dynamics model and motion model, and constructs three controllers, PID, synovium and fuzzy PID. The Navmesh routing algorithm is selected to realize the path planning of the unmanned boat simulation platform. The system fills the gap in the simulation test of unmanned equipment at the firing range, solves the problem of the lack of simulation training means of unmanned boat, and can provide basic support for the digital test evaluation of unmanned equipment.
Aiming at the demand for real-time numerical/semi-physical simulation in the research process of automated aerial refueling for unmanned aerial vehicle (UAV), this paper develops an automated aerial refueling distributed simulation system based on ZeroMQ and C++/Qt. Firstly, the simulation communication network of distributed simulation system is designed. Then, the program framework is designed and the management node and simulation node are defined. Finally, the above mentioned context is programmed through ZeroMQ and C++/Qt. The distributed simulation system can realize the real-time simulation for automated aerial refueling, and leave the convenient interface for semi-physical simulation.
The characteristics of airborne early warning radar and the difficulties of clutter suppression are introduced in this paper. The research process of clutter simulation is then reviewed. On the basis of the analysis of the clutter model of airborne early warning radar and the conventional clutter suppression methods, a cognitive clutter suppression method based on high fidelity clutter simulation is proposed. This method uses digital elevation map data, land cover and land use data to carry out signal level airborne radar clutter inversion. It supplements homogeneous clutter samples, improves clutter suppression performance under heterogeneous environment, and points out a new way for the application of clutter simulation in airborne early warning radar. Finally, according to the typical parameters of airborne early warning radar and geographical environment, the effectiveness of this method is verified by simulation.
Explorative simulation experiment is an important mean to understand and study warfare, but it often faces problems such as high complexity of scenario sample space and explosion of space dimensions. To solve all above problems, a qualitative and quantitative method for screening experimental factors based on multi-label learning(MLL)is proposed. First, based on qualitative analysis, a pre-simulation experiment is designed and implemented, experimental data are collected and processed, and the problem of missing machine learning sample data is solved. Then, the input control layer is introduced to build a deep neural network, and sparse regularization is introduced to achieve feature selection during multi-label model training. Then, regression qualitative analysis is used to supplement and improve the experimental factors. Finally, the simulation of stereoscopic projection action is used for experimental verification. The experimental result shows that the method is feasible and valuable in military.
The guidance and control semi physical simulation system plays an important role in the development of guided weapons, and is an important way to verify the correctness of missile guidance and control system design and software design. The traditional Windows operating system has poor real-time performance, which brings many uncertainties to the hardware in the loop simulation test. Therefore, this paper uses the Windows+RTX scheme to complete the hardware and software design of the hardware in the loop simulation system. Through shared memory, the communication between Windows processes and RTX processes is realized to ensure the accuracy of data transmission and the real-time performance of the system. The final missile guidance and control semi physical simulation test results show that the designed semi physical simulation system is reasonable, and has good real-time performance, high reliability, and strong universality.
Aiming at the uncertainty problem in the current evaluation of synthetic brigade equipment maintenance support capability, a cloud model-based evaluation method for synthetic brigade equipment support capability is constructed. Based on five aspects of command and control, maintenance preparation, establishment of field emergency repair institutions, equipment rescue and equipment emergency repair, the evaluation index system of synthetic brigade equipment maintenance support capability is constructed. The combination of analytic hierarchy process (AHP) and entropy weight method is used to determine the weights of evaluation indicators, avoiding the one-sidedness of weight calculation. By establishing evaluation standard cloud, evaluation index cloud and calculating comprehensive evaluation cloud, the evaluation level is determined, and the feasibility of the evaluation method is verified by an example, and the effective evaluation of the maintenance support capability of synthetic brigade equipment is realized.
Battlefield rush repair is an important mean to effectively maintain and quickly restore the technical state of equipment to ensure combat effectiveness. In different combat stages, the specific deployment position of the emergency repair detachment will not only directly affect its own security, but also directly affect the completion of the time limit of the emergency repair task. By analyzing the factors influencing the location selection of equipment emergency repair unit, the evaluation index system of location selection decision was constructed. The combination weighting method of G1 method and CRITIC method (Criteria Importance Through Intercriteria Correlation) was used to determine index weights. Cloud model is used to determine the location decision level of each participant and analyze its advantages and disadvantages. This paper takes three groups of site selection schemes under the same simulation conditions as an example to evaluate the site selection decision-making ability of each participant scientifically. This method provides a new idea for the periodical capability evaluation of wartime equipment rush repair.
