Terrain modeling method and system based on war game deduction

Abstract

The invention discloses a terrain modeling method and system based on war game deduction, and belongs to the technical field of terrain modeling, and the method comprises the following steps: 1, data collection and arrangement: extracting basic terrain data of a target region from a database, collecting military related geographic data for marking regions and elements with military importance, and storing the basic terrain data and the military related geographic data in the database; according to the terrain modeling method and system based on war chess deduction, field measurement is carried out on a specific war chess deduction scene, 2, terrain feature extraction and analysis are carried out, and based on collected terrain data, an image processing algorithm and a geographic analysis technology are applied. According to the method, the terrain model is optimized, the accuracy and efficiency of the terrain model can be improved, the integration degree of war game deduction and terrain modeling can be effectively increased by planning the war game deduction path, and integration of the war game deduction and the terrain modeling is facilitated.

Description

Technical Field

[0001] The present invention belongs to the technical field of terrain modeling, and specifically relates to a terrain modeling method and system based on war game deduction. Background Art

[0002] Terrain modeling for war game deduction refers to using various technical means and data to construct a virtual terrain environment for war game deduction. This environment can simulate the terrain and landforms in the real world, including various natural and human geographical elements such as mountains, rivers, plains, forests, and cities, providing a geospatial basis for the deployment, movement, and combat operations of military units.

[0003] In the existing terrain modeling process based on war game deduction, the lack of the ability to assist in generating and optimizing the terrain model will have a negative impact on the accuracy and operation efficiency of the terrain model. The characteristic that the war game deduction path needs to be obtained in real time will, to a certain extent, weaken the integration degree between war game deduction and terrain modeling, thereby causing many inconveniences and obstacles to the integration work of the two, making it difficult for the entire war game deduction system to achieve a high degree of coordination and fluency, and ultimately affecting the authenticity, strategy, and overall user experience of war game deduction.

[0004] In response to the above, this case proposes a terrain modeling method and system based on war game deduction, which solves the above technical problems by assisting in generating the terrain model, optimizing the terrain model, and planning the war game deduction path. Summary of the Invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art. For this purpose, the present invention proposes a terrain modeling method and system based on war game deduction, which solves the above technical problems by assisting in generating the terrain model, optimizing the terrain model, and planning the war game deduction path.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A terrain modeling method based on war game deduction includes the following steps:

[0008] Step 1, data collection and collation. Extract the basic terrain data of the target area from the database, collect military-related geographical data for marking areas and elements of military importance, and conduct on-site measurements for specific war game deduction scenarios.

[0009] Step 2: Terrain feature extraction and analysis. Based on the collected terrain data, use image processing algorithms and geographical analysis techniques to identify the main landform types, determine their boundary, area, elevation range parameters, calculate the roughness index of the terrain to evaluate the complexity of the terrain, analyze the terrain elements that are of key strategic significance for wargaming, and determine the positions, geometric shapes, and relationships with the surrounding terrain of these elements;

[0010] Step 3: Terrain model construction. According to the extracted terrain elevation data, construct an initial digital elevation model, use genetic algorithms to assist in generating the terrain model and optimizing terrain details, map the collected texture data onto the constructed terrain model, select appropriate texture images for mapping according to different landform types and characteristics of the terrain, and adjust and fuse texture coordinates;

[0011] Step 4: Integration of wargame rules and terrain model. According to the wargame rules, integrate the influence parameters of the terrain on the movement, vision, and combat capabilities of military units into the terrain model to determine the best path for wargaming;

[0012] Step 5: Model verification and optimization. Use historical battle case data or actual military geographical information for comparative verification, check whether the positions, shapes, and characteristics of the key terrain elements in the terrain model are accurate, judge the rationality and accuracy of the terrain model based on professional knowledge and experience, monitor the running performance of the terrain model, and take corresponding optimization measures if performance problems are found.

[0013] Furthermore, in Step 3, genetic algorithms are used to assist in generating the terrain model. Encode the parameters of the terrain as chromosomes, construct a fitness function, and find the best fitness value S for assisting in generating the terrain model mid 。

[0014] Furthermore, the specific steps for mid finding the best fitness value S for assisting in generating the terrain model are as follows:

[0015] S1: Set the evolution generation counter t = 0, determine the maximum number of evolution generations T, and randomly generate M individuals as the initial population P(0). Each individual is usually represented in a specific coding method;

[0016] S2: Calculate the fitness values of each individual in the population P(0). According to the fitness values of the individuals, select several individuals from the current population as parents according to the selection strategy to produce the next generation of individuals;

[0017] S3. Perform crossover operations on the selected parent individuals, and exchange some of their chromosomes with a certain probability to generate new individuals. With a small probability, change the gene values at the gene loci of the individuals to introduce new genetic material, maintain the diversity of the population, and prevent the algorithm from prematurely converging to a local optimal solution.

[0018] S4. Determine whether the termination condition is satisfied. If t ≤ T, then set t = t + 1 and return to step S2 to continue the iteration. If t > T, then terminate the algorithm and output the individual with the highest fitness in the current population as the optimal solution S. mid , which is the terrain model generated for assistance.

[0019] Furthermore, in step three, optimizing the terrain details is achieved by adjusting the elevation and slope parameters of the local terrain to increase the richness and realism of the terrain, making the terrain texture more natural and the transition smoother.

[0020] Furthermore, the method for adjusting the elevation parameter of the local terrain uses the constrained increase and decrease method. When adjusting the elevation, the increase and decrease values are determined according to the slope relationship of adjacent grid points. The slope parameter adjustment uses the moving average method. For each terrain grid point, calculate the average slope of the grid points within a certain range around it, and use this average value to replace the slope of the current point.

[0021] Furthermore, the specific steps for determining the best path of the military wargame are as follows:

[0022] A1. Convert the terrain data into a format suitable for path calculation, clarify the types of military units, and obtain parameters such as the movement speed, turning flexibility, and obstacle-crossing ability of the military units.

[0023] A2. According to the loaded terrain data, divide the entire military wargame map into discrete nodes and the edges connecting these nodes, and assign terrain-related attributes to each node.

[0024] A3. According to the scenario and mission objectives of the military wargame, determine the starting point and ending point of the military unit, and select a suitable path search algorithm.

[0025] A4. Starting from the starting point, gradually expand the search range according to the selected path search algorithm, evaluate the priority of each adjacent node. As the search progresses, continuously update the shortest path information of the discovered nodes. When the search algorithm reaches the ending point or meets the termination condition, construct the path from the starting point to the ending point by backtracking the predecessor nodes to obtain the optimal path.

[0026] Further, the search algorithm uses a heuristic search algorithm. The specific operation is as follows: Let f(n) be the comprehensive evaluation function of node n, g(n) be the actual cost from the starting point to node n, and h(n) be the estimated cost from node n to the target node. Then f(n) = g(n) + h(n). Add the starting point to the open list, set the g value of the starting point to 0, and the f value to h. When the open list is not empty, take out the node with the smallest f value as the current node. If the current node is the target node, construct the path by backtracking the parent node and return. For each adjacent node of the current node, calculate its g value, then calculate the f value and add the adjacent node to the open list. In the generation of the wargame path, the heuristic function h(n) can be designed according to the terrain and wargame rules.

[0027] Further, when designing the heuristic function h(n), terrain factors and military unit characteristics need to be considered. Terrain factors include elevation difference, landform type, and special terrain features. Military unit characteristics include differences in movement speed and the ability to cross obstacles.

[0028] Further, the optimal path of the wargame is visualized on the wargame map, and different colors or line styles are used to distinguish different types of paths.

[0029] A modeling system for a terrain modeling method based on wargame deduction. The modeling system includes a modeling system platform, a database, a data management module, a model construction module, a wargame integration module, and a path generation module;

[0030] The modeling system platform is used to control the operation and regulation of the terrain modeling system based on wargame deduction;

[0031] The database is used to store the basic terrain data of the target area and military-related geographical data, and at the same time collect the calculation data during the modeling process;

[0032] The data management module is used to manage the collected terrain data and identify it using image processing algorithms and geographical analysis techniques;

[0033] The model construction module constructs an initial digital elevation model based on the extracted terrain elevation data, and uses a genetic algorithm to assist in generating a terrain model and optimizing terrain details;

[0034] The wargame integration module integrates the influence parameters of the terrain on the movement, vision, and combat capabilities of military units into the terrain model according to the wargame deduction rules

[0035] The path generation module is used to generate the optimal path of the wargame deduction.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] 1. In the present invention, a terrain model is generated assisted by a genetic algorithm. The parameters of the terrain are encoded as chromosomes, and a fitness function is constructed to find the terrain combination that maximizes the fitness function, thereby automatically generating a terrain model and adjusting parameters such as the elevation and slope of the local terrain to increase the richness and realism of the terrain, making the terrain texture more natural and the transition smoother.

[0038] 2. In the present invention, the best deduction route can be accurately calculated based on terrain factors and military unit characteristics, which helps to make deduction decisions in line with the actual situation, can quickly find the optimal path, is applicable to the path planning of war games on large-scale maps and complex terrains, visualizes the best path of war game deduction on the war game map, and uses different colors or line styles to distinguish different types of paths, which helps to quickly understand the itinerary of war game deduction.

[0039] 3. In the present invention, by assisting in generating a terrain model during the terrain modeling process and optimizing the terrain model, the accuracy and efficiency of the terrain model can be improved. By planning the war game deduction path, the integration degree of war game deduction and terrain modeling can be effectively increased, facilitating the integration of war game deduction and terrain modeling. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flowchart of a terrain modeling method based on war game deduction according to the present invention;

[0041] Figure 2 is a system block diagram of a terrain modeling system based on war game deduction according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0042] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0043] As Figure 1 - Figure 2 shown, a terrain modeling method based on war game deduction includes the following steps:

[0044] Step 1, data collection and collation. Extract the basic terrain data of the target area from the database, collect military-related geographical data for marking areas and elements of military importance, and conduct on-site measurements for specific war game deduction scenarios.

[0045] Step 2: Terrain Feature Extraction and Analysis. Based on the collected terrain data, use image processing algorithms and geographical analysis techniques to identify the main landform types, determine their boundary, area, elevation range parameters, calculate the roughness index of the terrain to evaluate the terrain complexity, analyze the terrain elements that are of key strategic significance for wargaming, and determine the positions, geometric shapes, and relationships with the surrounding terrain of these elements;

[0046] Step 3: Terrain Model Construction. According to the extracted terrain elevation data, construct an initial digital elevation model, use genetic algorithms to assist in generating the terrain model and optimizing terrain details, map the collected texture data onto the constructed terrain model, select appropriate texture images for mapping according to different landform types and features of the terrain, and adjust and fuse texture coordinates;

[0047] Step 4: Integration of Wargame Rules and Terrain Model. According to the wargame rules, integrate the influence parameters of the terrain on the movement, vision, and combat capabilities of military units into the terrain model to determine the optimal path for wargaming;

[0048] Step 5: Model Verification and Optimization. Use historical battle case data or actual military geographical information for comparative verification, check whether the positions, shapes, and features of the key terrain elements in the terrain model are accurate, judge the rationality and accuracy of the terrain model based on professional knowledge and experience, monitor the running performance of the terrain model, and take corresponding optimization measures if performance problems are found.

[0049] It should be noted that after constructing the digital elevation model, smoothing processing and error correction are carried out to eliminate the noise and outliers that may be generated during the data acquisition process, making the terrain surface more natural and smooth. In flat plain areas, military units can move at a relatively fast speed, while in mountainous areas, due to the rugged terrain, the movement speed will be restricted and more physical strength or fuel may be consumed. For different types of military units, such as infantry, armored forces, cavalry, etc., considering their adaptability differences on different terrains, corresponding movement speed correction coefficients and action limit conditions are formulated. For example, infantry can use trees for concealment and cover in the forest, but their movement speed is relatively slow; armored forces may get stuck in swamps or river areas and cannot move normally;

[0050] In Step 3, genetic algorithms are used to assist in generating the terrain model. Encode the parameters of the terrain into chromosomes, construct a fitness function, and find the optimal fitness value S for assisting in generating the terrain model mid 。

[0051] It should be noted that the fitness function can be designed according to factors such as the naturalness and complexity of the terrain. Through multiple generations of evolution, genetic algorithms can find the chromosome combination that maximizes the fitness function, thus generating a realistic terrain model.

[0052] Find the optimal fitness value S for assisting in generating the terrain model mid The specific steps are as follows:

[0053] S1. Set the evolution generation counter t = 0, determine the maximum evolution generation T, and randomly generate M individuals as the initial population P(0). Each individual is usually represented by a specific coding method;

[0054] S2. Calculate the fitness values of each individual in the population P(0). According to the fitness values of the individuals, select several individuals from the current population as the parents according to the selection strategy for generating the next generation of individuals;

[0055] S3. Perform crossover operations on the selected parent individuals, and exchange some of their chromosomes with each other with a certain probability, so as to generate new individuals. With a small probability, change the gene values at the gene loci of the individuals, so as to introduce new genetic materials, maintain the diversity of the population, and prevent the algorithm from converging to the local optimal solution prematurely;

[0056] S4. Judge whether the termination condition is satisfied. If t ≤ T, then set t = t + 1 and return to step S2 to continue the iteration. If t > T, then terminate the algorithm and output the individual with the highest fitness in the current population as the optimal solution S mid , which is the terrain model generated by assistance.

[0057] It should be noted that the fitness function is designed according to the goal of the problem and is used to measure the degree of adaptation of each individual to the environment, that is, the quality of the solution. The larger the fitness value, the closer the solution represented by the individual is to the optimal solution. The termination condition can also be set according to the specific problem as reaching a certain fitness threshold, the optimal solution not changing for several consecutive generations, the calculation time or the number of iterations reaching the upper limit.

[0058] In step three, the terrain details are optimized by adjusting the elevation and slope parameters of the local terrain to increase the richness and realism of the terrain, making the terrain texture more natural and the transition smoother.

[0059] The elevation parameter of the local terrain is adjusted by the constraint increase and decrease method. When adjusting the elevation, the increase and decrease values are determined according to the slope relationship of adjacent grid points. The slope parameter is adjusted by the moving average method. For each terrain grid point, calculate the average value of the slopes of the grid points within a certain range around it, and use this average value to replace the slope of the current point.

[0060] It should be noted that when raising the terrain, according to the slope between the current grid point and the adjacent grid points, increase the elevation by a certain proportion so that the slope change of the terrain remains within a reasonable range. The moving average method can reduce the sudden change of the local slope and make the terrain smoother.

[0061] The specific steps to determine the optimal path for wargaming are as follows:

[0062] A1. Convert the terrain data into a format suitable for path calculation, clarify the types of military units, and obtain parameters such as the movement speed, turning flexibility, and obstacle-crossing ability of military units;

[0063] A2. According to the loaded terrain data, divide the entire wargame map into discrete nodes and the edges connecting these nodes, and assign terrain-related attributes to each node;

[0064] A3. According to the wargaming scenario and mission objectives, determine the starting point and ending point of the military unit, and select a suitable path search algorithm;

[0065] A4. Starting from the starting point, gradually expand the search scope according to the selected path search algorithm, evaluate the priority of each adjacent node. As the search progresses, continuously update the shortest path information of the discovered nodes. When the search algorithm reaches the end point or meets the termination condition, construct the path from the starting point to the end point by backtracking the predecessor nodes to obtain the optimal path.

[0066] It should be noted that parameters such as movement speed, turning flexibility, and obstacle-crossing ability are used to evaluate the movement cost between each path node, so as to determine the optimal path. According to the type of military unit and the terrain attributes of the node, initially evaluate the accessibility of each node to the military unit. When calculating the cost of moving from a plain node to an adjacent mountain node, factors such as speed reduction and increased energy consumption caused by terrain changes need to be considered.

[0067] The search algorithm adopts a heuristic search algorithm. The specific operation is to set f(n) as the comprehensive evaluation function of node n, g(n) as the actual cost from the starting point to node n, and h(n) as the estimated cost from node n to the target node. Then f(n) = g(n) + h(n). Add the starting point to the open list, set the g value of the starting point to 0, and the f value to h. When the open list is not empty, take out the node with the smallest f value as the current node. If the current node is the target node, construct the path by backtracking the parent node and return. For each adjacent node of the current node, calculate its g value, then calculate the f value and add the adjacent node to the open list. In wargame path generation, the heuristic function h(n) can be designed according to the terrain and wargame rules.

[0068] It should be noted that the Euclidean distance can be used as the estimated cost on flat terrain. When there are obstacles or complex terrain, the estimated cost can be appropriately increased to guide the search in a more likely direction, so as to quickly find the optimal or approximate optimal path, which is applicable to wargame path planning for large-scale maps and complex terrains.

[0069] When designing the heuristic function h(n), it is necessary to consider terrain factors and military unit characteristics. Terrain factors include elevation difference, landform type and special terrain features, and military unit characteristics include movement speed differences and the ability to cross obstacles.

[0070] It should be noted that when calculating the elevation difference between the starting point and the target point, for terrain with large elevation changes, such as mountains, going uphill will increase the difficulty and time of marching, and going downhill may require controlling the speed to avoid danger. A coefficient can be set according to the climbing ability of the military unit to quantify the impact of the elevation difference on the path cost. Different landform types have different effects on marching. For example, plains have fast marching speed and low cost, forest areas may reduce marching speed, and need to consider concealment and reconnaissance difficulties. Waters may need to find bridges or ferries to pass through. If there are none, the cost of wading or detours needs to be considered. Different weights can be assigned to different landform types, and special treatment is required for special terrains such as swamps, cliffs, and minefields.

[0071] The wargame optimal paths are visualized on the game map, using different colors or line styles to distinguish different types of paths.

[0072] It should be noted that marking important information on the route, such as the estimated time of arrival, possible terrain obstacles, etc., will help to better understand the marching plan of the military unit and make adjustments based on actual conditions.

[0073] A modeling system for terrain modeling method based on wargame simulation, the modeling system comprising a modeling system platform, a database, a data management module, a model building module, a wargame integration module and a path generation module;

[0074] The modeling system platform is used to control the operation and regulation of the terrain modeling system based on wargaming;

[0075] The database is used to store basic terrain data of the target area and military-related geographic data, and collects calculation data during the modeling process;

[0076] The data management module is used to manage the collected terrain data and identify them using image processing algorithms and geographic analysis techniques;

[0077] The model building module constructs the initial digital elevation model based on the extracted terrain elevation data, and uses genetic algorithms to assist in generating terrain models and optimizing terrain details;

[0078] The wargame integration module integrates the parameters of the terrain's impact on the movement, field of view, and combat capabilities of military units into the terrain model according to the wargame simulation rules.

[0079] The path generation module is used to generate the best path for war game simulation.

[0080] In the embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation; the modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the method of this embodiment.

[0081] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A terrain modeling method based on war game simulation, characterized by: The following steps are involved: Step 1: Data collection and organization: extract basic terrain data of the target area from the database, collect military-related geographic data to mark areas and elements of military importance, and conduct field measurements for specific war game scenarios; Step 2: Extract and analyze terrain features. Based on the collected terrain data, image processing algorithms and geographic analysis techniques are used to identify the main landform types, determine their boundaries, areas, and altitude range parameters, calculate the terrain roughness index to assess the complexity of the terrain, analyze the terrain elements that are of key strategic significance to the war game, and determine the location, geometry, and relationship of these elements with the surrounding terrain. Step 3: Terrain model construction: Based on the extracted terrain elevation data, an initial digital elevation model is constructed. The terrain model is generated and the terrain details are optimized through the genetic algorithm. The collected texture data is mapped to the constructed terrain model. According to the different landform types and characteristics of the terrain, the appropriate texture image is selected for mapping, and the texture coordinates are adjusted and fused. Step 4: Integrate the wargame rules with the terrain model. According to the wargame simulation rules, the parameters of the terrain's impact on the movement, field of view, and combat capability of military units are integrated into the terrain model to determine the best path for the wargame simulation. Step 5: Model verification and optimization. Use historical battle data or actual military geographic information for comparative verification to check whether the position, shape, and features of key terrain elements in the terrain model are accurate. Judge the rationality and accuracy of the terrain model based on professional knowledge and experience. Monitor the operating performance of the terrain model. If performance problems are found, take corresponding optimization measures.

2. The terrain modeling method based on war game simulation according to claim 1, characterized in that: In step 3, a terrain model is generated by using a genetic algorithm to encode the terrain parameters into chromosomes, construct a fitness function, and find the optimal fitness value S of the terrain model. mid .

3. The terrain modeling method based on war game simulation according to claim 2 is characterized in that: The optimal fitness value S of the auxiliary terrain model is found mid The specific steps are: S1, set the evolutionary generation counter t = 0, determine the maximum evolutionary generation T, randomly generate M individuals as the initial population P(0), and each individual is usually represented by a specific coding method; S2, calculate the fitness value of each individual in the population P(0), and select several individuals from the current population as parents according to the fitness value of the individual and the selection strategy to generate the next generation of individuals; S3, crossover operation is performed on the selected parent individuals, exchanging parts of their chromosomes with a certain probability to generate new individuals, and changing the gene values ​​on the gene loci of individuals with a small probability, thereby introducing new genetic material, maintaining the diversity of the population, and preventing the algorithm from converging to the local optimal solution too early; S4, determine whether the termination condition is met. If t≤T, set t=t+1 and return to step S2 to continue iterating. If t>T, terminate the algorithm and output the individual with the highest fitness in the current group as the optimal solution S mid , which is the auxiliary generated terrain model.

4. The terrain modeling method based on war game simulation according to claim 2 is characterized in that: In the step 3, the terrain details are optimized by adjusting the elevation and slope parameters of the local terrain to increase the richness and realism of the terrain, making the texture of the terrain more natural and the transition smoother.

5. The terrain modeling method based on war game simulation according to claim 4 is characterized in that: The elevation parameters of the local terrain are adjusted by the constrained increase and decrease method. When adjusting the elevation, the increase and decrease values ​​are determined according to the slope relationship of adjacent grid points. The slope parameter adjustment adopts the moving average method. For each terrain grid point, the average value of the slope of the grid points within a certain range around it is calculated, and this average value is used to replace the slope of the current point.

6. The terrain modeling method based on war game simulation according to claim 1, characterized in that: The specific steps of determining the best path for war game simulation are: A1, convert terrain data into a format suitable for path calculation, identify the type of military unit, and obtain parameters such as the movement speed, turning flexibility, and obstacle crossing ability of the military unit; A2, based on the loaded terrain data, divide the entire wargame map into discrete nodes and edges connecting these nodes, and assign terrain-related attributes to each node; A3. Determine the starting and ending points of military units and select appropriate path search algorithms based on the scenario and mission objectives of the war game simulation; A4. Starting from the starting point, the search scope is gradually expanded according to the selected path search algorithm, and the priority of each adjacent node is evaluated. As the search progresses, the shortest path information of the discovered nodes is continuously updated. When the search algorithm reaches the end point or meets the termination condition, the path from the starting point to the end point is constructed by backtracking the predecessor node to obtain the optimal path.

7. The terrain modeling method based on war game simulation according to claim 5 is characterized in that: The search algorithm adopts a heuristic search algorithm. The specific operation is to set f(n) as the comprehensive evaluation function of node n, g(n) as the actual cost from the starting point to node n, and h(n) as the estimated cost from node n to the target node, then f(n)=g(n)+h(n). The starting point is added to the open list, the g value of the starting point is set to 0, and the f value is set to h. When the open list is not empty, the node with the smallest f value is taken as the current node. If the current node is the target node, the path is constructed and returned by backtracking the parent node. For each adjacent node of the current node, its g value is calculated, and then the f value is calculated and the adjacent node is added to the open list. In the generation of the war game path, the heuristic function h(n) can be designed according to the terrain and the war game rules.

8. The terrain modeling method based on war game simulation according to claim 6 is characterized by: When designing the heuristic function h(n), terrain factors and military unit characteristics need to be considered. Terrain factors include elevation difference, landform type and special terrain features. Military unit characteristics include movement speed difference and obstacle crossing capability.

9. The terrain modeling method based on war game simulation according to claim 6, characterized in that: The wargame optimal paths are visualized on the wargame map, using different colors or line styles to distinguish different types of paths.

10. A modeling system according to any one of claims 1 to 9, characterized in that: The modeling system includes a modeling system platform, a database, a data management module, a model building module, a war game integration module and a path generation module; The modeling system platform is used to control the operation and regulation of the terrain modeling system based on war game simulation; The database is used to store basic terrain data of the target area and military-related geographical data, and collects calculation data in the modeling process; The data management module is used to manage the collected terrain data and identify it using image processing algorithms and geographic analysis techniques; The model building module builds an initial digital elevation model based on the extracted terrain elevation data, and uses a genetic algorithm to assist in generating a terrain model and optimizing terrain details; The wargame integration module integrates the parameters of the terrain's impact on the movement, field of view, and combat capability of military units into the terrain model according to the wargame simulation rules. The path generation module is used to generate the best path for war game simulation.

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