Simulation training environment generation system and method based on target training equipment

Abstract

The invention provides a simulation training environment generation system and method based on target training equipment, and the system comprises an information obtaining unit which is connected with a data analysis unit and is used for obtaining the related information of the target training equipment and transmitting the related information to the data analysis unit; the data analysis unit is connected with the training environment generation unit and is used for receiving related information of the target training equipment, performing targeted analysis and transmitting an analysis result of the target training equipment to the training environment generation unit; and the training environment generation unit is used for receiving the analysis result of the target training equipment, constructing our-party training rules and conditions through a decision tree, and generating a simulation training environment matched with the target training equipment by utilizing Simulink simulation software according to the training rules and conditions. According to the method, the simulated training environment is established according to the target training equipment data, so that the performance of our training equipment is checked, and the potential breakthrough of the target training equipment is mined and analyzed through the check data.

Description

Technical Field

[0001] The present invention relates to the technical field of simulation environments, and in particular, to a simulation training environment generation system and method based on the training equipment of the target party. Background Art

[0002] Today, with the coexistence of traditional and non-traditional security threats, the national security threats faced by each country are becoming increasingly diverse. Therefore, different security requirements are presented in different training directions, and the development of equipment must also take into account the actual situation of the coexistence of various training styles. The diversification of training styles inevitably requires training personnel to pay attention to the construction of core training capabilities while taking into account the balanced development of various training capabilities. To meet the needs of anti-missile training capability construction under the new situation, the training equipment research and development department should follow relevant concepts, proceed from the actual training, carry out equipment system demonstration and optimization design. However, the construction of existing simulation training environments is designed based on external environmental factors and the training objectives of training personnel, lacking an effective simulation training environment construction system for optimizing and upgrading training equipment. Summary of the Invention

[0003] The purpose of the present invention is to provide a simulation training environment generation system and method based on the training equipment of the target party, aiming to solve the above problems in the prior art.

[0004] An embodiment of the present invention provides a simulation training environment generation system based on the training equipment of the target party, including:

[0005] An information acquisition unit, connected to the data analysis unit, for acquiring information related to the training equipment of the target party and transmitting the information related to the training equipment of the target party to the data analysis unit;

[0006] A data analysis unit, connected to the information acquisition unit and the training environment generation unit, for receiving the information related to the training equipment of the target party, performing targeted analysis on the information related to the training equipment of the target party, and transmitting the analysis result of the training equipment of the target party to the training environment generation unit;

[0007] A training environment generation unit, connected to the data analysis unit, for receiving the analysis result of the training equipment of the target party, constructing our training rules and conditions based on the analysis result of the training equipment of the target party through a decision tree, and generating a simulation training environment matching the training equipment of the target party by using Simulink simulation software according to the training rules and conditions.

[0008] An embodiment of the present invention provides a simulation training environment generation method based on the training equipment of the target party, including:

[0009] Obtain the relevant information of the target party's training equipment through the information acquisition unit, and transmit the relevant information of the target party's training equipment to the data analysis unit;

[0010] Receive the relevant information of the target party's training equipment through the data analysis unit, conduct targeted analysis on the relevant information of the target party's training equipment, and transmit the analysis result of the target party's training equipment to the training environment generation unit;

[0011] Receive the analysis result of the target party's training equipment through the training environment generation unit, construct our training rules and conditions based on the analysis result of the target party's training equipment through a decision tree, and generate a simulation training environment matching the target party's training equipment using Simulink simulation software according to the training rules and conditions.

[0012] An embodiment of the present invention also provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps of the above-mentioned simulation training environment generation method based on the target party's training equipment are implemented.

[0013] An embodiment of the present invention also provides a computer-readable storage medium, on which an implementation program for information transmission is stored. When the program is executed by a processor, the steps of the above-mentioned simulation training environment generation method based on the target party's training equipment are implemented.

[0014] The adoption of the embodiment of the present invention may include the following beneficial effects: By acquiring the relevant data of the target party's training equipment and conducting targeted analysis, the embodiment of the present invention builds a simulation training environment matching its training layout for our side, and summarizes the defects, inconveniences in operation, and limitations in tactical application of the target party's training equipment found during the training process, providing a theoretical basis for the improvement and technological innovation of our subsequent training equipment. Description of the Drawings

[0015] In order to more clearly illustrate the technical solutions in one or more embodiments of this specification or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in this specification. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a schematic diagram of a simulation training environment generation system based on the target party's training equipment in an embodiment of the present invention;

[0017] Figure 2 It is a structural flowchart of the actor-critic algorithm in an embodiment of the present invention;

[0018] Figure 3 It is a flowchart of a method for generating a simulation training environment based on the training equipment of the target party according to an embodiment of the present invention. Detailed implementation manners

[0019] In order to enable those skilled in the art of this technology to better understand the technical solutions in one or more embodiments of this specification, the following will clearly and completely describe the technical solutions in one or more embodiments of this specification in conjunction with the accompanying drawings in one or more embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, rather than all the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this document.

[0020] System embodiments

[0021] According to an embodiment of the present invention, there is provided a system for generating a simulation training environment based on the training equipment of the target party. Figure 1 It is a schematic diagram of a system for generating a simulation training environment based on the training equipment of the target party according to an embodiment of the present invention. As Figure 1 shown, the system for generating a simulation training environment based on the training equipment of the target party according to an embodiment of the present invention specifically includes:

[0022] An information acquisition unit 10, connected to a data analysis unit, for acquiring information related to the training equipment of the target party and transmitting the information related to the training equipment of the target party to the data analysis unit. Specifically, it is used for:

[0023] Acquiring satellite images and photos of the training layout of the target party taken by drones, performing visual analysis on the acquired images using a convolutional neural network (CNN), identifying and classifying the training equipment of the target party, and collecting basic information of the training equipment of the target party through public channels and our training equipment database for the identified training equipment of the target party; and intercepting the electronic signals of the target party and analyzing the electronic signals to obtain other information of the training equipment of the target party; integrating the basic information of the training equipment of the target party and the other information of the training equipment of the target party to obtain information related to the training equipment of the target party.

[0024] Among them, the information related to the training equipment of the target party includes the technical generation and performance parameters of the training equipment of the target party, adaptability and flexibility, systemized training ability, development trend, and the usage and location information of each training equipment in the training layout of the target party.

[0025] The technical generation and performance parameters include the range, strike accuracy, stealth ability, overall architecture, type, functional attributes, intact state, design principle, and current working parameters of the training equipment of the target party.

[0026] The adaptability and flexibility refer to the adaptability and rapid deployment ability of the training equipment of the target party in different training environments;

[0027] The systematic training ability includes the linkage of the command and control system to which the training equipment of the target party belongs, the tightness of the reconnaissance-strike-evaluation chain, the flexibility of the logistics support system, and the common means of deploying psychological warfare and information warfare;

[0028] The development trend includes the new training technologies, new training concepts, and new R & D directions adopted by the target party;

[0029] The data analysis unit 12, connected to the information acquisition unit and the training environment generation unit, is used to receive the information related to the training equipment of the target party, conduct targeted analysis on the information related to the training equipment of the target party, and transmit the analysis result of the training equipment of the target party to the training environment generation unit. Specifically, it is used for:

[0030] Classify the information related to the training equipment of the target party, automatically detect the image data through the target detection model Faster R-CNN, identify specific equipment in the image and mark it; conduct text mining and sentiment analysis on the text data through the natural language processing NLP model to obtain the key information of the training equipment of the target party and the views and attitudes of the public towards the training equipment of the target party; conduct statistical analysis on the historical data to obtain the usage patterns and deployment rules of the training equipment of the target party; use the deep neural network LSTM to process the time series data to obtain the long-term trends and periodic changes in the use of the training equipment of the target party; use the GIS tool to conduct spatial analysis on the location and movement trajectory of the training equipment of the target party to obtain the comprehensive geographical information of the training equipment of the target party; integrate several data results obtained from the analysis to obtain the analysis result of the training equipment of the target party;

[0031] The training environment generation unit 14, connected to the data analysis unit, is used to receive the analysis result of the training equipment of the target party, construct our training rules and conditions based on the analysis result of the training equipment of the target party through a decision tree, and use the Simulink simulation software to generate a simulation training environment that matches the training equipment of the target party according to the training rules and conditions;

[0032] The system further includes:

[0033] The training result acquisition unit, connected to the training environment generation unit and the training result analysis unit, is used to obtain the training results of our training equipment in the simulation training environment, arrange the training results according to the importance level, generate an electronic report, and send it to the training result analysis unit;

[0034] Among them, the training results include the operation proficiency of our training equipment, the systematic training ability, the system integration and coordination efficiency, the practical application ability, and the maintenance and logistics support;

[0035] The practical application ability includes training efficiency, training applicability, strike accuracy, survivability, and continuous training efficiency;

[0036] The training result analysis unit is connected to the training result acquisition unit and the feedback unit, and is used to receive the electronic report, analyze the breakthrough points of the target party's training equipment according to the electronic report, and send the obtained breakthrough point analysis result to the optimization unit;

[0037] The breakthrough point analysis result includes the information system security vulnerabilities of the target party's training equipment, the coverage blind area, the vulnerability of the training equipment logistics support, the performance limitations of the old equipment, and the immature application degree of emerging technologies;

[0038] The optimization unit is connected to the training result analysis unit, and is used to receive the breakthrough point analysis result and optimize and upgrade our training equipment and training layout plan based on the breakthrough point analysis result.

[0039] The following will specifically describe the above technical solutions of the embodiments of the present invention in detail in combination with the specific situation of the simulation training environment generation system based on the target party's training equipment of the embodiments of the present invention.

[0040] There is a close causal relationship between the optimization and upgrade of training equipment and the construction of a simulation training environment. First of all, the upgrade of training equipment often drives the change of the training environment. With the introduction of new technologies and new equipment, training personnel need to adapt to these changes during training to ensure that they can effectively utilize the performance advantages of new equipment. This requires the simulation training environment to simulate conditions similar to actual combat, allowing training personnel to familiarize themselves with the operation and tactical application of new training equipment in an environment close to the real battlefield. Secondly, the construction of the simulation training environment in turn can promote the further optimization and upgrade of training equipment. The data and feedback collected through actual combat training can reveal the limitations and potential problems of our equipment and the target party's equipment in actual application, thus further providing corresponding improvement directions for the training equipment research and development department. For example, identifying problems such as the decline in the efficiency of a certain training equipment in a specific environment or the lack of user-friendliness of the operation interface, so as to guide the subsequent improvement and design innovation of training equipment.

[0041] In addition to the above points, the embodiments of the present invention believe that when constructing a simulation training environment, how to perform an adaptable equipment layout for our training equipment (that is, achieving accurate strikes without wasting our training equipment resources) and subsequent corresponding optimization and upgrade also need to comprehensively consider the following key aspects of the target party's equipment to ensure that the equipment update has pertinence and confrontation advantages:

[0042] 1. Technical Generation and Performance Parameters: Analyze the technical level of the target's equipment, including core performance indicators such as the range, accuracy, stealth ability, and electronic warfare ability of its training equipment. Understand the latest development trends of the target's equipment to ensure that our equipment maintains at least parity in similar systems and strive for an advantage in the technology generation gap.

[0043] 2. Systemized Training Capability: Study the integration degree of the target's equipment in systemized training, such as the linkage of the command and control system, the tightness of the reconnaissance-strike-evaluation chain, the flexibility of the logistics support system, and common means of laying out psychological warfare and information warfare. In response to the target's systemized training capability, when upgrading our equipment, we need to focus on enhancing the effectiveness of our own systemized training and improving the collaborative training ability among multiple types and platforms.

[0044] 3. Adaptability and Flexibility: Examine the adaptability and rapid deployment ability of the target's equipment in different geographical environments and climatic conditions. When upgrading our equipment, we need to pay attention to improving the all-terrain and all-weather training capabilities, as well as rapid response and mobility.

[0045] 4. Future Development Trends: Predict the future development trends of the target's equipment, including new technologies and new concepts that may be adopted (such as unmanned training, hypersonic training equipment, etc.). We should make a forward-looking layout, research and develop the technology of the next generation of training equipment, and avoid falling behind in the technology generation gap. In summary, our training equipment upgrade strategy should revolve around the dynamic balance of the strength of the training equipment of both sides.

[0046] At the same time, the embodiments of the present invention also start from the following aspects to analyze the relationship between the optimization and upgrading of training equipment and the construction of a simulation training environment:

[0047] 1. Adaptive Layout of Training Equipment: After the upgrade of training equipment, more advanced technologies are usually introduced in training, such as artificial intelligence and network training capabilities. The training environment needs to simulate the application scenarios of these technologies, enabling training personnel to learn to operate training equipment under complex technical conditions and understand the potential of new equipment; at the same time, through training, discover the problems that various equipment technologies may encounter in actual applications, providing a basis for technical adjustment and equipment optimization.

[0048] 2. Innovation of Tactics and Battle Methods: The addition of new equipment often triggers the innovation of tactics and battle methods. The simulation training environment needs to promptly incorporate new tactical concepts, layout according to new tactical concepts, and set up corresponding confrontation drills to promote training personnel to explore training modes suitable for new equipment. This two-way interaction not only maximizes the effectiveness of equipment but also accelerates the integration and innovation of theory and practice.

[0049] 3. Inspection of the comprehensive support system: The upgrade of training equipment also involves changes in aspects such as logistics support, maintenance, etc. The simulation training environment should simulate the maintenance, rapid repair, and supply processes of equipment under various conditions to ensure the continuous training ability of the equipment. Through training, the effectiveness of the comprehensive support system is inspected, and optimization suggestions for the support plan are provided for actual training deployment.

[0050] 4. Improvement of personnel quality: High-tech training equipment requires operators to have higher professional skills and tactical qualities. The simulation training environment improves the emergency response ability, teamwork ability, and command and decision-making level of training personnel by simulating high-difficulty and high-intensity actual combat situations, ensuring the best combination of people and equipment.

[0051] 5. Cost-benefit analysis: When planning the construction of the training environment, the economic costs brought about by the upgrade of training equipment also need to be considered. By simulating and analyzing the cost-benefits of different training plans, the training method with the highest efficiency ratio is selected to ensure the generation of training ability while reasonably controlling resource consumption.

[0052] Combined with the above key point analysis, the embodiment of the present invention proposes a simulation training environment generation system based on the training equipment of the target party, which specifically includes:

[0053] I. Information acquisition unit, which is used to acquire information related to the training equipment of the target party. This module is the most basic and crucial part of the system. Because when we layout the training equipment in the simulation training environment, to meet the combat requirements without wasting resources, the first thing is to fully understand the relevant data of the training equipment of the target party. The key information of the target party's equipment that needs to be mastered mainly includes the technical generation and performance parameters, adaptability and flexibility, systematic training ability, and future development trend of the target party's training equipment.

[0054] In this module, the embodiment of the present invention collects information about the training equipment of the target party through public channels (such as the Internet, social media, news reports, etc.); it can also intercept and analyze electronic signals such as the communication signals and radar signals of the target party to obtain the usage situation and location information of the target party's training equipment; it can also use satellite images, photos taken by unmanned aerial vehicles, etc. for visual analysis to identify and locate the target party's training equipment; and integrate the intelligence data from different channels to form unified data, improving the integrity and accuracy of the information.

[0055] Second, the data analysis unit is used to receive the information related to the training equipment of the target party obtained, and then conduct targeted analysis on these data to obtain an adaptability analysis result suitable for the layout of our training environment. This analysis result quantifies the technical generation and performance parameters, adaptability and flexibility, systemized training ability, and development trend of the target party's training equipment, and converts them into corresponding standard numerical values that can be used for comparative analysis, so as to facilitate subsequent model calculations. Some information about the target party's training equipment has been analyzed above and will not be elaborated here.

[0056] Among the data of the target party's training equipment obtained in the first part, there are various types of data such as text and images. Therefore, corresponding analysis methods need to be adopted according to the corresponding data types. The embodiments of the present invention use the following several analysis methods:

[0057] 1. Image recognition and processing:

[0058] ① Computer vision (CV): Using deep learning algorithms (such as convolutional neural network CNN) to automatically identify and classify the training equipment in the image data.

[0059] ② Object detection: Automatically detecting and annotating specific equipment in the image data through models such as YOLO and Faster R-CNN.

[0060] 2. Natural language processing (NLP):

[0061] ① Text mining: Extracting key information from a large number of documents and reports, such as the name, model, and performance parameters of the target party's training equipment.

[0062] ② Sentiment analysis: Analyzing the comments and discussions on the target party on social media to understand the public's views and attitudes towards the target party's training equipment, so as to facilitate subsequent psychological warfare analysis.

[0063] 3. Data analysis and modeling:

[0064] ① Statistical analysis: Through statistical analysis of historical data or the target party's equipment data in our database, identifying the usage patterns, deployment rules, etc. of the target party's training equipment.

[0065] ② Prediction model: Establishing a time series model (such as ARIMA), a regression model, or a machine learning model (such as random forest, support vector machine SVM) to predict the future trends of the target party's training equipment.

[0066] 4. Artificial intelligence and machine learning:

[0067] ① Deep learning: Using deep neural networks (such as RNN, LSTM) to process time series data and identify the long-term trends and periodic changes in the usage of the target party's training equipment.

[0068] ② Reinforcement learning: The intelligent agent learns the optimal strategy in the simulated environment to optimize the countermeasures against the training equipment of the target party.

[0069] 5. Geographic Information System (GIS); Spatial analysis: Use GIS tools to perform spatial analysis on the location, movement trajectory, etc. of the training equipment of the target party, and generate visual results such as heat maps and path maps for easy observation.

[0070] III. Training environment generation unit, which is used to receive the analysis results after corresponding analysis of various indicators of the training equipment of the target party, and generate training rules and training conditions for our training equipment through a decision tree according to the analysis results. Because the decision tree can help the system better understand the configuration and usage strategy of the training equipment of the target party, use simulation software Simulink (or MATLAB, etc.) based on our training rules and training conditions to generate a simulation training environment that matches the training equipment of the target party. In the basic structure of arranging our joint training equipment system, the training equipment mainly includes various offensive weaponry, the information support equipment mainly includes training reconnaissance equipment, information offensive equipment and information defensive equipment, and the comprehensive support equipment mainly includes training support equipment, technical support equipment and logistics support equipment.

[0071] After the simulation scenario design, an equipment intelligent decision-making model can also be constructed in this module, including the information received by the equipment, the possible strategies / actions to be executed, the ability parameters of the equipment, and the equipment solution model; the equipment solution model includes an equipment simulation model, a result adjudication model and an effectiveness calculation model. This decision-making model is used to guide how each training equipment in the simulation training scenario conducts intelligent training simulation deduction, and use the relevant parameters of the intelligent decision-making model to perform state space design, action space design, state transition function design, and reward function design. The decision-making model can be constructed using a neural network based on policy gradient, such as the actor-critic algorithm, which has two network structures. Actor (player): To play this game and get the highest possible reward, a strategy is needed: input the state and output the action (this function can be approximated by a neural network, and the remaining task is how to train the neural network to get a higher reward, and this network is called the actor).

[0072] Critic (judge): Since the actor is based on the policy, a critic is needed to calculate the value corresponding to the actor and feedback it to the actor to tell him how well he is performing. Therefore, the previous Q value needs to be used (this Q-function can also be approximated by a neural network, and this network is called the critic).

[0073] Its structure is asFigure 2 As shown in the figure, the specific implementation is as follows:

[0074] Actor network: Using the policy function, according to the current state s, output the probability of each action, select the appropriate action a according to the probability, interact with the environment to obtain the next state s' and the reward r.

[0075] Critic network: Using the value function, calculate the value function in state s and the value function in state s', and calculate the TD error (temporal difference error).

[0076] IV. Training result acquisition unit, which is used to obtain the training results of our training equipment in the simulation training environment, including the operation proficiency, systematic training ability, system integration and cooperation efficiency, practical application ability, maintenance and logistics support of our training equipment, such as the degree of equipment damage after the war, the performance integrity of the equipment after the war, the completion degree of the target side's strike, etc., and arrange them according to the importance level to generate the corresponding electronic report;

[0077] After training in the simulation training environment, it is necessary to mine the training results of our training equipment from the following key aspects:

[0078] 1. Equipment operation proficiency: Evaluate the operation proficiency of the trainees on newly upgraded or existing training equipment, including the quick response time, the ability to execute instructions accurately, and the troubleshooting efficiency, analyze the adaptability of the trainees to the new equipment and the improvement of their skills, and put forward personalized training needs to ensure that each training personnel can give full play to the effectiveness of the training equipment.

[0079] 2. System integration and cooperation efficiency: Analyze the performance of the training equipment system in a multi-type joint training environment, and verify whether the information sharing, coordination and task allocation among systems are smooth and efficient.

[0080] 3. Practical application ability: According to the results of the simulated training exercises, examine the application effect of the training equipment in the simulated real battlefield environment, including the strike accuracy, survivability and continuous training effectiveness.

[0081] 4. Maintenance and logistics support: Evaluate the maintenance requirements, loss conditions and logistics support response speed of the equipment during training to ensure that the equipment can maintain a good state during high-intensity training.

[0082] 5. Systematized Training Ability: Systematized training ability refers to an advanced form of training ability that, in a complex and ever-changing training environment, integrates various training equipment systems and information resources to achieve cross-domain coordination, precise command and control, and comprehensive firepower strikes. Systematized training ability emphasizes seamless docking and efficient coordination among training units, as well as comprehensive control of the training environment, in order to achieve training objectives at the lowest cost. The key elements of the systematized training ability of our training equipment considered in the embodiments of the present invention mainly include the following:

[0083] (1) Integration of Command Information Systems: We need to build an efficient and secure command and communication network to enable the rapid flow and sharing of intelligence, decision-making, and actions, ensuring that the command center can real-time grasp the training environment situation and make rapid and accurate command decisions.

[0084] (2) Joint Training of Multiple Types of Personnel: Close cooperation among multiple types of training personnel forms a training system that combines offense and defense. Each type of training personnel plays a unique role in training according to its characteristics, forming an overall training effectiveness.

[0085] (3) Informationized Training Ability: Make full use of our informationized means to improve training efficiency, including but not limited to the extensive application of unmanned aerial vehicle reconnaissance, electronic warfare, network attack and defense, precision-guided training equipment, as well as big data and artificial intelligence-assisted decision-making.

[0086] (4) Flexible Logistics Support System: We need to establish a rapid response logistics support mechanism to ensure the timely supply and mobility of materials, equipment, and personnel, supporting the continuous training of front-line personnel.

[0087] (5) Rapid Maneuver and Deployment Ability: Our training personnel can quickly assemble, be remotely transported to the designated training area, and quickly launch training operations to adapt to the rapidly changing training environment.

[0088] (7) Psychological Warfare and Information Warfare: Use means such as media publicity and network information operations to influence the psychological activities of the training personnel of the target party and disrupt its command system, creating favorable conditions for our physical training.

[0089] V. Training Result Analysis Unit, which is used to deeply mine the training results after receiving them (the analysis methods can refer to the methods used in the Data Analysis Unit), thereby analyzing and quantifying the breakthrough points of the training equipment of the target party, and then presenting the quantified result data in a visual form, facilitating scientific research personnel to conduct more intuitive research on it;

[0090] The analysis of the weaknesses and potential breakthrough points of the training equipment of the target party can be mined from the following aspects:

[0091] 1. Information system security vulnerabilities: Modern simulation training highly relies on the information-based training system. The security of its command and control system and data link becomes crucial. Therefore, we can identify the weaknesses of the target's encryption protocol and the loopholes in network protection as breakthrough points.

[0092] 2. Coverage blind spots of air defense and anti-missile systems: Analyze the deployment of the target's air defense network and identify its detection blind spots and blank areas in the interception range.

[0093] 3. Vulnerabilities in equipment logistics support: The security of the logistics supply line, the insufficiency of rapid repair capabilities, and the dependence on the supply chain of key components may all be factors restricting the target's sustainable training ability.

[0094] 4. Performance limitations of old equipment: Some old equipment still in service with the target may have significant weaknesses due to insufficient maintenance and outdated technology, such as slow speed, weak protection, and poor electronic countermeasure capabilities.

[0095] 5. Immature application of emerging technologies: When the target tries to apply cutting-edge technologies such as artificial intelligence and hypersonic training equipment, it may expose flaws due to unstable technology and unskilled operation.

[0096] VI. Optimization unit, which is used to receive the final breakthrough analysis result, and based on the breakthrough analysis result, put forward improvement suggestions for our training equipment, so as to optimize and upgrade our training equipment.

[0097] That is, by combining the training results of our training equipment in the simulation environment and the breakthrough analysis results of the target's training equipment, the overall optimization and upgrade of our subsequent training equipment can generally be carried out around the following core aspects:

[0098] 1. Training effectiveness evaluation: Analyze the strike accuracy, lethality, response time, and continuous training ability of our training equipment under simulated combat conditions, compare the expected training effect with the actual training result, and identify the effectiveness gap.

[0099] 2. System compatibility and integration: Examine the interoperability between different training equipment systems, evaluate the collaborative operation ability of the command and control system, and ensure smooth information flow and training needs.

[0100] 3. Reliability and maintainability: Statistically analyze the failure rate, repair time, and maintenance difficulty of training equipment, evaluate the stability and maintainability of training equipment under high-intensity use, and facilitate the subsequent proposal of suggestions to improve the maintenance support process.

[0101] 4. Personnel operation skills: Evaluate the familiarity and skill level of training personnel with the equipment, including operation speed, correctness, and the ability to handle emergencies, and adjust the training plan accordingly.

[0102] 5. Adaptability and Flexibility: Examine the applicability of training equipment in various terrains, climates, and training scenarios, analyze the matching degree between the configuration of training equipment and tactical requirements, and propose diversified strategies to promote the use of training equipment.

[0103] 6. Technological Innovation and Upgrade Potential: Evaluate the technological level of existing training equipment, explore whether new technologies can be incorporated or upgraded to improve the overall training efficiency, and consider the cost-benefit ratio at the same time.

[0104] 7. Logistics Support and Sustainability: Analyze the efficiency of logistics support during training and the replenishment cycle of training equipment, ensure that training equipment can maintain high-efficiency operation during long-term training, and propose measures to optimize the supply chain.

[0105] 8. Safety and Risk Control: Evaluate the safety of equipment operation during training, identify potential safety hazards, formulate corresponding risk mitigation strategies, and protect the safety of training personnel and equipment.

[0106] Method Embodiment

[0107] According to an embodiment of the present invention, a method for generating a simulation training environment based on the training equipment of the target party is provided. Figure 3 It is a flowchart of the method for generating a simulation training environment based on the training equipment of the target party according to an embodiment of the present invention. As Figure 3 shown, the method for generating a simulation training environment based on the training equipment of the target party according to an embodiment of the present invention specifically includes:

[0108] Step S301, obtain the information related to the training equipment of the target party through the information acquisition unit, and transmit the information related to the training equipment of the target party to the data analysis unit, specifically including:

[0109] Obtain satellite images and photos of the training layout of the target party taken by drones through the information acquisition unit, perform visual analysis on the obtained images using the convolutional neural network CNN, identify and classify the training equipment of the target party, collect the basic information of the training equipment of the target party through public channels and our training equipment database; and intercept the electronic signals of the target party, and analyze the electronic signals to obtain other information of the training equipment of the target party; integrate the basic information of the training equipment of the target party and the other information of the training equipment of the target party to obtain the information related to the training equipment of the target party.

[0110] Step S302, receive the information related to the training equipment of the target party through the data analysis unit, perform targeted analysis on the information related to the training equipment of the target party, and transmit the analysis result of the training equipment of the target party to the training environment generation unit, specifically including:

[0111] Classify the information related to the training equipment of the target party. Automatically detect the image data through the target detection model Faster R-CNN, identify specific equipment in the image and make annotations; perform text mining and sentiment analysis on the text data through the natural language processing NLP model to obtain the key information of the target party's training equipment and the public's views and attitudes towards the target party's training equipment; conduct statistical analysis on the historical data to obtain the usage patterns and deployment rules of the target party's training equipment; use the deep neural network LSTM to process the time series data to obtain the long-term trends and periodic changes in the use of the target party's training equipment; use GIS tools to perform spatial analysis on the location and movement trajectories of the target party's training equipment to obtain the comprehensive geographical information of the target party's training equipment; integrate several data results obtained from the analysis to obtain the analysis results of the target party's training equipment.

[0112] In step S303, the training environment generation unit receives the analysis results of the target party's training equipment, constructs our training rules and conditions based on the analysis results of the target party's training equipment, and uses the Simulink simulation software to generate a simulation training environment that matches the target party's training equipment according to the training rules and conditions.

[0113] The method further includes:

[0114] The training result acquisition unit obtains the training results of our training equipment in the simulation training environment, arranges the training results according to the importance level, generates an electronic report and sends it to the training result analysis unit.

[0115] The training result analysis unit receives the electronic report, conducts a breakthrough analysis on the target party's training equipment according to the electronic report, and sends the obtained breakthrough analysis result to the optimization unit.

[0116] The optimization unit receives the breakthrough analysis result and optimizes and upgrades our training equipment and training layout plan based on the breakthrough analysis result.

[0117] The embodiment of the present invention is a method embodiment corresponding to the above system embodiment. The specific implementation manners of each step can be understood with reference to the description of the system embodiment and will not be elaborated here.

[0118] In summary, a virtuous cycle has formed between the optimization and upgrading of training equipment and the construction of a simulation training environment: the upgrading of training equipment prompts the simulation training environment to be closer to actual combat requirements, while a high-quality training environment provides an empirical basis for the continuous optimization of training equipment. Therefore, the two complement each other and are mutually causal. The embodiment of the present invention conducts simulation modeling on our training environment based on the training equipment of the target party, scientifically analyzes the contribution rate of the matching of the equipment of both sides in the simulation training environment to the training system's capabilities, theoretically analyzes the scope of capabilities covered by the training equipment in the training environment and the training effectiveness, and excavates and analyzes the potential breakthrough points of the training equipment of the target party, so as to deeply understand the functions, roles of our training equipment in the training system and the interaction relationship with other training equipment, and thus realize the theoretical demonstration and optimization design of our training equipment under the system framework.

[0119] Device Embodiment 1

[0120] The embodiment of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, the steps described in the method embodiment are implemented.

[0121] Device Embodiment 2

[0122] The embodiment of the present invention provides a computer-readable storage medium, on which an implementation program for information transmission is stored. When the program is executed by a processor, the steps described in the method embodiment are implemented.

[0123] The computer-readable storage medium described in this embodiment includes, but is not limited to: ROM, RAM, magnetic disk, optical disc, etc.

[0124] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A simulation training environment generation system based on target training equipment, characterized in that include: an information acquisition unit, connected to the data analysis unit, for acquiring information related to the target party's training equipment, and transmitting the information related to the target party's training equipment to the data analysis unit; A data analysis unit, connected to the information acquisition unit and the training environment generation unit, configured to receive information related to the target party's training equipment, perform targeted analysis on the information related to the target party's training equipment, and transmit the target party's training equipment analysis result to the training environment generation unit; A training environment generating unit is connected to the data analyzing unit, and is used for receiving the analysis result of the target party's training equipment, constructing our training rules and conditions through a decision tree based on the analysis result of the target party's training equipment, and generating a simulation training environment matching the target party's training equipment using Simulink simulation software according to the training rules and conditions.

2. The system according to claim 1, characterized in that The system further comprises: A training result acquisition unit, connected to the training environment generation unit and the training result analysis unit, is used to acquire the training results of our training equipment in the simulation training environment, arrange the training results according to the importance level, generate an electronic report and send it to the training result analysis unit; The training results include the operational proficiency, systematic training capability, system integration and synergy effectiveness, practical application capability, and maintenance and logistics support of our training equipment; The practical application capabilities include training effectiveness, training applicability, strike accuracy, survivability and sustained training effectiveness; A training result analysis unit, connected to the training result acquisition unit and the feedback unit, configured to receive the electronic report, perform a breakthrough analysis on the target party's training equipment according to the electronic report, and send the obtained breakthrough analysis result to the optimization unit; The breakthrough analysis results include information system security loopholes of the target party's training equipment, coverage blind spots, vulnerabilities of training equipment logistics support, performance limitations of old equipment and immature application of emerging technologies; The optimization unit is connected to the training result analysis unit, and is used to receive the breakthrough analysis result, and optimize and upgrade our training equipment and training layout plan based on the breakthrough analysis result.

3. The system according to claim 1, characterized in that The information acquisition unit is specifically used for: Obtain satellite images and photos of the target party's training layout taken by drones, use convolutional neural networks (CNNs) to perform visual analysis on the acquired images, identify and classify the target party's training equipment, and collect basic information about the identified target party's training equipment through public channels and our training equipment database; and intercept the target party's electronic signals and analyze the electronic signals to obtain other information about the target party's training equipment; Integrate the basic information of the target party's training equipment and other information of the target party's training equipment to obtain relevant information of the target party's training equipment; The target party's training equipment-related information includes the target party's training equipment's technical generation and performance parameters, adaptability and flexibility, systematic training capabilities, development trends, and the use and location information of each training equipment in the target party's training layout; The technical generation and performance parameters include the range, strike accuracy, stealth capability, overall architecture, type, functional attributes, intact state, design principles and current working parameters of the target party's training equipment; The adaptability and flexibility refer to the adaptability and rapid deployment capability of the target party's training equipment in different training environments; The systemic training capability includes the linkage of the command and control system of the target party's training equipment, the closeness of the reconnaissance-strike-assessment chain, the flexibility of the logistics support system, and the common means of deploying psychological warfare and information warfare; The development trends include new training technologies, new training concepts and new research and development directions adopted by the target party.

4. The system according to claim 1, characterized in that The data analysis unit is specifically used for: Classify the information related to the target party's training equipment, automatically detect the image data through the target detection model Faster R-CNN, identify the specific equipment in the image and mark it; perform text mining and sentiment analysis on the text data through the natural language processing (NLP) model to obtain the key information of the target party's training equipment and the public's views and attitudes towards the target party's training equipment; perform statistical analysis on historical data to obtain the usage pattern and deployment rules of the target party's training equipment; use the deep neural network LSTM to process time series data to obtain the long-term trend and periodic changes in the use of the target party's training equipment; use GIS tools to perform spatial analysis on the location and movement trajectory of the target party's training equipment to obtain the comprehensive geographic information of the target party's training equipment; Integrate the several data results obtained from the analysis to obtain the target party's training equipment analysis results.

5. A method for generating a simulation training environment based on target training equipment, characterized in that include: Acquire the target party's training equipment related information through the information acquisition unit, and transmit the target party's training equipment related information to the data analysis unit; Receiving target party training equipment related information through a data analysis unit, performing targeted analysis on the target party training equipment related information, and transmitting the target party training equipment analysis result to a training environment generation unit; The target party's training equipment analysis results are received through a training environment generation unit, and our training rules and conditions are constructed through a decision tree based on the target party's training equipment analysis results. According to the training rules and conditions, a simulation training environment matching the target party's training equipment is generated using Simulink simulation software.

6. The method according to claim 5, characterized in that The method further comprises: The training result acquisition unit acquires the training result of our training equipment in the simulation training environment, arranges the training results according to the importance level, generates an electronic report and sends it to the training result analysis unit; The training result analysis unit receives the electronic report, performs a breakthrough analysis on the target party's training equipment according to the electronic report, and sends the obtained breakthrough analysis result to the optimization unit; The breakthrough analysis result is received through the optimization unit, and our training equipment and training layout plan are optimized and upgraded based on the breakthrough analysis result.

7. The method according to claim 5, characterized in that The information acquisition unit obtains the target party's training equipment related information including: The information acquisition unit obtains satellite images and photos of the target party's training layout taken by drones, performs visual analysis on the acquired images using a convolutional neural network (CNN), identifies and classifies the target party's training equipment, and collects basic information about the identified target party's training equipment through public channels and our training equipment database; intercepts the target party's electronic signal, analyzes the electronic signal, and obtains other information about the target party's training equipment; integrates the basic information of the target party's training equipment and other information about the target party's training equipment to obtain information related to the target party's training equipment.

8. The method according to claim 5, characterized in that The targeted analysis of the target party's training equipment related information specifically includes: The information related to the target party's training equipment is classified, and the image data is automatically detected through the target detection model Faster R-CNN to identify and mark the specific equipment in the image; text mining and sentiment analysis are performed on the text data through the natural language processing (NLP) model to obtain the key information of the target party's training equipment and the public's views and attitudes towards the target party's training equipment; historical data are statistically analyzed to obtain the usage pattern and deployment rules of the target party's training equipment; the deep neural network LSTM is used to process time series data to obtain the long-term trend and periodic changes in the use of the target party's training equipment; the location and movement trajectory of the target party's training equipment are spatially analyzed using GIS tools to obtain the comprehensive geographic information of the target party's training equipment; and several types of data results obtained by the analysis are integrated to obtain the analysis results of the target party's training equipment.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the steps of the method for generating a simulation training environment based on target training equipment as described in any one of claims 5 to 8 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an implementation program for information transmission, and when the program is executed by a processor, the steps of the method for generating a simulation training environment based on target training equipment as described in any one of claims 5 to 8 are implemented.

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