An electronic war game simulation system and method based on remote sensing battlefield environment

Abstract

The present invention relates to the technical field of war game simulation systems, and provides an electronic war game simulation system and method based on a remote sensing battlefield environment. The system includes data access, data processing, map generation and simulation modules, which realize the automation of the entire process from downloading and parsing remote sensing data to generating war game maps. The data processing module is specially designed with functions such as coordinate conversion, sensitive area shielding, attribute field extraction and cleaning to ensure the accuracy and applicability of map data. The map generation module adopts a gridding method to achieve accurate division of the map by calculating the center point and vertex coordinates of each grid. The simulation module dynamically adjusts the reconnaissance distance and detection probability according to real-time environmental factors to simulate military operations and tactical deployments. This system effectively combines remote sensing technology and war game simulation, improves the simulation degree of the simulation and the scientific nature of decision support, and has broad application prospects in military training and strategic analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of war game simulation systems, and in particular to an electronic war game simulation system and method based on remote sensing battlefield environment. Background Art

[0002] An electronic wargaming system is a tool that uses computer technology to simulate military operations, strategic decision-making, and tactical deployment. It represents a digital and virtual extension of traditional wargaming, adapted to modern technology. Through a highly digital approach, the system provides users with a virtual battlefield environment, enabling military researchers, strategists, and trainers to conduct war games, conduct tactical analysis, and conduct decision-making training without the need for actual physical exercises. The electronic wargaming system simulates a near-realistic battlefield environment, incorporating factors such as terrain, weather conditions, and lighting variations, making the simulations more realistic. The electronic wargaming system can simulate a wide range of complex scenarios, from tactical squad operations to strategic-level military operations, encompassing various military units, equipment, and support systems. Leveraging the powerful data processing capabilities of computers, the electronic wargaming system can calculate massive amounts of battlefield data in real time, such as unit movement, firepower coverage, and casualty calculations. Within the electronic wargaming system, users can interact through a graphical interface, adjust tactical or strategic decisions in real time, and receive immediate feedback on the results. The electronic wargaming system supports simultaneous multi-user online participation, simulating joint operations or confrontational exercises and improving teamwork and command and control capabilities. The digitized war games of the electronic war game simulation system allow combat simulations to be repeated indefinitely, facilitating the adjustment and optimization of tactics and strategies. It also facilitates detailed recording and analysis of the combat process and summarizing lessons learned.

[0003] The problems with traditional electronic wargaming systems primarily manifest themselves in the following areas: First, most electronic wargaming systems lack precise control over environmental factors (such as weather, seasons, and time of day). Most rely on preset rules or random dice rolls to determine the timing and duration of these factors, resulting in significant discrepancies between the simulation results and the actual battlefield environment. Second, traditional wargaming systems lack effective map grid management, making it difficult to finely divide and control the battlefield environment, resulting in crude simulation results. Third, line of sight judgment is inaccurate. Traditional wargaming systems rely primarily on preset rules or manual judgment, and are unable to accurately simulate the line of sight obstructions found in actual battlefield environments. Summary of the Invention

[0004] To solve the problems in the background technology, the present invention provides an electronic war game simulation system based on remote sensing battlefield environment, which includes:

[0005] Data access module, the data access module downloads and imports remote sensing map data, the remote sensing map data includes but is not limited to geographic information including terrain, roads and rivers;

[0006] Data processing module: The data processing module reads and parses remote sensing map data, converts the remote sensing map data into a unified data format, performs coordinate system conversion, shields sensitive areas, extracts and cleans attribute fields, converts attribute values ​​and unifies units, and marks terrain, roads, rivers, and coverings;

[0007] The map generation module generates a wargame map based on the processed remote sensing data. This involves cutting the map into regular hexagonal grids of uniform size, calculating the center point and vertex coordinates of each grid, and numbering and annotating each grid.

[0008] The simulation module simulates military operations, strategic decisions, and tactical deployments based on the generated wargame map, and dynamically adjusts the reconnaissance distance and detection probability according to environmental factors within the grid to realize wargame simulation.

[0009] In the preferred solution, the data access module selects map levels including provincial maps, municipal maps and action maps, which represent battlefield environments of different scales respectively; in the deduction module, environmental factors include but are not limited to terrain, weather, time, season, sunrise and sunset, and moonrise and moonset.

[0010] In a preferred solution, the data processing module specifically includes:

[0011] Remote sensing data reader, which parses remote sensing data into structured data;

[0012] Coordinate system converter, which converts the coordinates in remote sensing data into the WGS84 coordinate system;

[0013] Sensitive Area Blocker, identifies and removes sensitive areas on the map;

[0014] Attribute field extractor, extracts key geographic information fields from remote sensing data;

[0015] Attribute value cleaner, which cleans the extracted attribute data;

[0016] The attribute value converter converts the attribute field names of different data sources into a unified system attribute name and unifies the units of numerical type data.

[0017] In a preferred solution, the attribute value converter uses a topography and landform standard library, a weather standard library, a natural disaster standard library, a traffic standard library, a place name standard library and a building standard library to map and convert attribute values.

[0018] A method for conducting electronic war game simulation using an electronic war game simulation system based on a remote sensing battlefield environment comprises the following steps:

[0019] S1. Remote sensing map data: Download or retrieve remote sensing map data by selecting the map level, map area, and collection time period;

[0020] S2. Processing remote sensing data: Converting the received remote sensing data into unified structured data, including reading remote sensing data, converting coordinate systems, shielding sensitive areas, extracting and cleaning attribute fields, unifying attribute value units and converting attribute values, and generating a remote sensing map database;

[0021] S3. Map drawing: drawing a map based on the processed remote sensing map database, including setting contour lines, terrain texture, elevation background color, river roads and cover texture;

[0022] S4. Grid map: Cut the map into hexagonal grids of uniform size, number each grid, calculate the center point, and annotate the grid attributes;

[0023] S5. Apply environmental factors from remote sensing data to wargame rules: Read environmental factors from remote sensing data, dynamically adjust reconnaissance distance and detection probability, and apply relevant rules to wargame simulations.

[0024] Furthermore, the specific process of step S1 includes:

[0025] S11. Select the map level. Choose a provincial, city, or action map based on the needs of the wargame. Each map has a different grid size, reflecting a different level of geographic detail. Each grid on the provincial map represents 10 kilometers, making it suitable for simulating large-scale strategic layouts. Each grid on the city map represents 1 kilometer, making it suitable for simulating tactical operations at the city or town level. Each grid on the action map represents 10 meters, making it suitable for simulating details down to the level of buildings and trees. After selecting the map level, the pixel-to-actual distance ratio is further set based on the selected level, and the appropriate map zoom level is recommended.

[0026] S12. Selecting a map area: Using a map picker, select a rectangular area on the remote sensing map as the battlefield for simulation, ensuring that the simulation area matches the actual geographical environment.

[0027] S13. Select the collection time period: Select an appropriate collection time period based on the specific needs of the simulation. The time period will affect the simulation of topography, weather, and sunrise and sunset factors. For example, if the simulation requires simulating multiple time periods within a day, ensure that the collected data covers these time periods.

[0028] S14. Download remote sensing data: Download remote sensing data through manual data acquisition and automatic access. The specific process of manual data acquisition is: search and download data from public remote sensing data websites according to the set map level, area and time period; the downloaded data is imported through the system import function; the specific process of automatic access is: use the commercial remote sensing data interface to directly download files or data in the corresponding format.

[0029] Furthermore, in step S2, the specific process includes:

[0030] S21. Remote sensing data reading: Use a remote sensing data reader to parse the received remote sensing data into unified structured data. This step can be achieved using an open source library such as GeoTools, which supports multiple map data formats and can perform map data processing and geographic coordinate system conversion.

[0031] S22. Coordinate system conversion: Convert the coordinate systems of remote sensing data from different sources using different geographic coordinate systems to the unified coordinate system WGS84. You can use the GeoTools library or similar tools to perform coordinate system conversion to ensure the accuracy and consistency of map data.

[0032] S23, Sensitive Area Blocking: Remove preset sensitive areas from the map; use the sensitive area blocker to circle the coordinates of sensitive areas and exclude these areas from the map generation process;

[0033] S24, Attribute Field Extraction and Cleaning: Extract fields useful for wargaming from the large amount of annotated information contained in remote sensing data. Use the attribute field extractor to extract required attributes from remote sensing data based on pre-established field mapping relationships. Clean the extracted attribute values ​​to ensure data type accuracy, handle null values, and address missing data, making the data usable for subsequent processing.

[0034] S25. Unify attribute value units: Unify the units of attribute values ​​of data from different sources using different units. Convert all attribute values ​​to standard units according to the conversion formula in the unit conversion library.

[0035] S26, attribute value conversion: Convert the cleaned and unified attribute values ​​into a format usable by the wargaming system; use the attribute value converter to map the attribute values ​​of the external system to the standard attribute values ​​of the wargaming system based on the terrain and weather standard libraries;

[0036] S27. Generate a remote sensing map database: Store the normalized data in the database for subsequent query by the war game simulation system; the database stores the coordinate set of map geometric figures and corresponding attribute information.

[0037] Furthermore, in step S3, the specific process includes:

[0038] S31. Reading a remote sensing map database: reading coordinate sets and attribute information of all geometric figures from the processed remote sensing map database; such information includes but is not limited to map geometry, terrain, elevation, rivers, roads, and coverings;

[0039] S32. Set contour lines: Read geometric data from the database, set different contour line colors and styles for different geometric shapes to distinguish different geographical features; use a drawing library (such as the stream renderer in GeoTools) to draw these geometric shapes on the map to form a basic map outline;

[0040] S33, Terrain Texture Processing: Read the terrain attributes (such as plain, mountain, forest) of each geometric figure from the terrain and landform standard library, and search the map texture library for the corresponding texture image based on the terrain name; apply the found texture to each geometric figure to form map areas with different terrain characteristics;

[0041] S34. Set elevation background color: Read the elevation attributes of each geometric figure from the database; set different background colors according to the elevation range to distinguish different elevation areas; for example, low-lying areas can use darker colors, while high areas can use lighter colors;

[0042] S35. River road drawing: including:

[0043] S351, filter geometric figures: filter geometric figures representing rivers and roads from the database;

[0044] S352, texture application: according to the types of rivers and roads (such as rivers, streams, main roads, secondary roads), search and apply corresponding textures in the map texture library;

[0045] S353, Draw Lines: Use the drawing tools to draw these textures onto the map along the geometry of rivers and roads;

[0046] S36, Cover texture processing:

[0047] S361. Filtering geometric figures: Filtering geometric figures representing covering objects (such as buildings, trees, and artificial facilities) from the database;

[0048] S362, texture application: according to the type of covering object, search and apply the corresponding texture in the map texture library;

[0049] S363, Draw Overlay: Apply texture to the geometry of the overlay and draw it on the map;

[0050] S37. Layer merging: Draw each layer in the order of contour lines, terrain textures, elevation background colors, rivers and roads, and coverings; use a drawing library (such as GeoTools' stream renderer) to merge each layer into a map in the order to form the final war game simulation map.

[0051] Furthermore, in step S4, the specific process includes:

[0052] S41. Cut the map into hexagonal grids: Cut the drawn map into hexagonal grids of uniform size. Hexagonal grids have the advantages of uniformity and close arrangement, which helps to simplify spatial analysis and operator movement calculations.

[0053] S42. Grid numbering rule: A numbering rule is established to uniquely identify each grid. When the grid is divided into a maximum of 99x99 grids, the coding rule is: the first two digits represent the horizontal column number n, and if it is less than 0, the last two digits represent the vertical row number m, and if it is less than 0, the number is 0.

[0054] When the grid is divided into a larger size of 999x999, the encoding rules are expanded accordingly. The first three digits represent the horizontal column number n, and the remaining three digits represent the vertical row number m, and the remaining three digits are filled with zeros. For example, the grid at column 105 and row 203 will be numbered "105203".

[0055] S43. Calculate the coordinates of the main points of the hexagonal grid:

[0056] S431. Calculate the coordinates of the center point of the hexagonal grid:

[0057] Let the basic height of the regular hexagon be h, the width be w, and the radius be r;

[0058] For the hexagonal grid at the nth column and the mth row, the coordinates [x, y] of its center point are calculated as follows:

[0059] When n is an odd number, the y coordinate of the center point can be calculated using the following formula:

[0060]

[0061] When n is an even number, the center point coordinates [x, y] are calculated as follows:

[0062]

[0063] S432. The formula for calculating vertex coordinates of a regular hexagonal grid is:

[0064] To draw a hexagonal grid, you need to calculate the coordinates of six points: p1, p2, p3, p4, p5, and p6. The following is the formula for calculating the coordinates of the six points:

[0065] p1=[xr,y]

[0066]

[0067] p4=[x+r,y]

[0068]

[0069] S433. Dimension calculation in special cases: If you need to calculate the width w or radius r based on the height h, you can use the following formula:

[0070] The formula for calculating width w using height h is:

[0071]

[0072] The formula for calculating radius r using height h is:

[0073]

[0074] S44. Grid attribute annotation: Annotate the latitude and longitude coordinates of the map and their corresponding attributes (such as terrain, elevation, and weather conditions) onto the corresponding grid. This process involves the following steps:

[0075] S441. Read remote sensing database: obtain coordinates and attributes of all geometric figures;

[0076] S442. Calculate the grid to which the coordinates belong: For each coordinate point, use a specific formula to calculate the hexagonal grid number to which it belongs;

[0077] S443, merging grid attributes: searching for corresponding grid attributes in the grid database based on the grid number, and merging the newly acquired coordinate attributes with the original grid attributes; during the merging process, the priority of the attribute values ​​needs to be processed according to actual needs;

[0078] The specific process is as follows:

[0079] Assuming the height of the regular hexagon is h, the width is w, and the radius is r, the center point [x, y] of the hexagon closest to a certain coordinate [a, b] can be calculated using the following formula. The brackets in the formula indicate rounding.

[0080]

[0081] when When it is an even number, it indicates an even column;

[0082]

[0083] otherwise,

[0084]

[0085] Calculate the corresponding hexagonal grid, find the hexagonal grid number, find the hexagonal grid attribute from the grid map database through the hexagonal grid number, merge the coordinate attribute and the hexagonal grid attribute as the new hexagonal grid attribute.

[0086] Furthermore, in step S5, the specific process includes:

[0087] S51. Read environmental factors in remote sensing data: Read and analyze various environmental factors contained in remote sensing data. These environmental factors may include but are not limited to:

[0088] Weather conditions, including clear, snowy, rainy, misty, moderate fog, blizzard, and dense fog; seasonal changes; sunrise and sunset times; moonrise and moonset times; terrain features, including plains, mountains, forests, rivers, and roads; and elevation data;

[0089] S52. Extract and integrate environmental factors into the war game rule base:

[0090] Integrate environmental factors from remote sensing data with the wargame system's rule base; the rule base defines the various mechanisms and logic of the game, including action sequence, combat determination, movement restrictions, and victory and defeat conditions; these rules are dynamically adjusted based on the actual environmental factors in the remote sensing data;

[0091] S53. Apply relevant rules based on rounds and geographic location: Based on the current round number and operator, i.e., the geographic location of the action unit in the game, the corresponding environmental factors are read from the remote sensing map database and the corresponding rules are applied. The specific process includes:

[0092] S531. Determining the number of rounds: The deduction process will go through multiple rounds, each representing a certain time span; for example, one round may represent one hour, and 24 rounds may represent one day;

[0093] S532. Selection of collection time: Based on the real-time calculation to be performed, select the corresponding collection time period; this time period will be affected by factors such as topography, weather, sunrise and sunset;

[0094] S533. Determination of Geographic Location: The specific location of an operator on the deduction map determines which environmental factors affect it. The geographical location of an operator can be determined through the remote sensing map database.

[0095] S534, read environmental factors: read environmental factors related to the current round number and geographic location from the remote sensing map database; these factors may include weather conditions, terrain characteristics, lighting conditions, etc.;

[0096] S535, Apply Environmental Factor Rules: Apply corresponding rules based on the read environmental factors. For example, if the weather condition is foggy, it may affect the operator's field of view and movement speed. If the operator is located in a mountainous area, terrain obstruction may affect reconnaissance and communication. If the operator is near a river, the time and resources required to cross the river may need to be considered.

[0097] S536. Specific application of the rules: Determine the observation distance and probability of detection under different terrain and weather conditions based on the Terrain Visibility Determination Table and the Weather Day and Night Visibility Determination Table.

[0098] S54. Dynamically adjust the deduction parameters: Based on the environmental factors read, dynamically adjust various parameters in the deduction process, including:

[0099] S541. Read environmental factors: Read environmental factor data for the current simulation area from the remote sensing map database, including but not limited to weather conditions (such as clear, rainy, snowy, foggy, etc.), terrain features (such as plains, mountains, forests, water areas, etc.), elevation data, seasonal changes, sunrise and sunset times, and moonrise and moonset times;

[0100] S542. Analyze operator position and current turn: Track the geographic location and current turn number of each operator (i.e., the action unit in the game) in real time. The operator's position determines which environmental factors affect it, while the turn number helps the system determine the current time context (e.g., daytime, nighttime, season, etc.) and adjust accordingly.

[0101] S543, Dynamically adjust parameters: Based on the environmental factors read, the system dynamically adjusts various key parameters during the deduction process:

[0102] Reconnaissance Range: Dynamically adjusts the reconnaissance range based on the terrain, weather conditions, and time of day (e.g., day or night) of the reconnaissance unit and target unit. For example, in foggy conditions, the reconnaissance range will be significantly reduced, while in clear daylight conditions, the reconnaissance range may be increased.

[0103] Observation Probability: The system dynamically adjusts the observation probability based on environmental factors (such as cover, weather conditions, etc.) and the state of the target unit (such as concealment or mobility). For example, a unit concealed in a dense forest is more difficult to observe, so its observation probability will be reduced.

[0104] Movement Speed: Terrain characteristics and weather conditions directly affect a unit's movement speed. The system dynamically adjusts movement speed based on the current terrain (e.g., mountains, plains, swamps, etc.) and weather conditions (e.g., rain, snow, strong winds, etc.). For example, a unit's movement speed may slow down in mountainous terrain, while it may speed up on flat, dry plains.

[0105] S55. Perform line of sight determination to determine whether there is a line of sight obstruction between the operator and the target: the system determines whether there is a line of sight obstruction between the operator and the target based on terrain elevation data, obstacle locations, and environmental factors (such as weather conditions). The specific implementation process includes: connecting a straight line, i.e., the line of sight, between the operator and the target. If the line of sight is not obstructed, then line of sight is established; if the line of sight is only obstructed by high ground, determine whether the high ground is higher than the altitude of the reconnaissance unit and the target point; if so, line of sight is not established; if the altitude of the high ground is between the two points, mark the reconnaissance point, the obstacle, and the target point according to the terrain location and the number of grids of distance between them, and connect the reconnaissance point and the target point with a straight line; if the obstacle is above the straight line, then line of sight is not established; otherwise, line of sight is established. The specific steps are as follows:

[0106] S551. Find the terrain from the grid map database according to the hexagonal grid number where the operator is located;

[0107] S552, query the weather in the grid;

[0108] S553. If it is nighttime, find out the current brightness of the moon;

[0109] S554. Find the number of hexagonal grids from the Terrain Visibility Determination Table or the Weather Day / Night Visibility Determination Table and convert it into visual range.

[0110] S555. Calculate the distance between the operator and the target:

[0111]

[0112] S556, determining whether it is within the field of view;

[0113] S557, searching for all obstruction hexagonal grids between the current operator and the target operator;

[0114] S558. Substitute the operator, all obstruction hexagons, and the target operator into the formula to calculate whether it is blocked. If it is blocked, it is not visible. In this algorithm, the existence of unobstructed sight only depends on:

[0115]

[0116] in:

[0117] H: the difference between the elevation of the operator at a higher position and the elevation of the operator at a lower position;

[0118] D: distance from the high operator position to the low operator position;

[0119] h: the height of the possible obstruction minus the height of the lowest position operator;

[0120] d: The distance from the position of the possible obstacle to the lower position operator.

[0121] The beneficial effects achieved by the present invention are:

[0122] First, the electronic war game simulation system of the present invention takes into account the real-time application of environmental factors, greatly improving the authenticity and credibility of the simulation. The present invention uses remote sensing data to produce high-precision maps, realizing the real-time application of environmental factors in war game simulation rules in one step. During the simulation process, the present invention dynamically adjusts the simulation parameters based on the real-time read environmental factor data, so that the simulation results are closer to the actual battlefield environment. The present invention reads the environmental factor data of the current simulation area from the remote sensing map database, including weather conditions, seasonal changes, sunrise and sunset times, moonrise and moonset times, etc. The technical solution dynamically adjusts various parameters in the simulation process, such as reconnaissance distance, observation probability, movement speed, etc., based on the real-time read environmental factor data, to ensure that the simulation results are closer to the actual situation. This real-time application not only improves the authenticity and credibility of the simulation, but also provides decision makers with more accurate and scientific decision support.

[0123] Second, the present invention proposes a management method for gridded maps and fine-grained control. By cutting the map into hexagonal grids of uniform size and numbering and calculating the center point of each grid, grid-based map management is achieved. This method helps simplify objective rules, allowing each operator to be precisely placed within the grid and affected by objective factors within the grid. Each grid represents a certain geographical range, making the position of the operator on the map more precise. At the same time, objective factors such as terrain and weather within the grid can also be finely controlled, thereby improving the precision of the deduction. By dividing the battlefield environment into several small grids, the implementation of rules during the deduction process can be simplified. For example, unified parameters such as reconnaissance distance and observation probability can be established for each grid, thereby reducing the complexity of rule development. Gridded maps enable the system to independently manage and control each grid. During the deduction process, the system can adjust the environmental factor parameters within one or more grids as needed to achieve more refined deduction control.

[0124] Third, the present invention proposes a dynamic adjustment scheme for line-of-sight judgment and reconnaissance rules, designing a line-of-sight judgment algorithm based on a grid map. This algorithm dynamically adjusts the reconnaissance distance and detection probability based on factors such as terrain, weather, and time of day, making line-of-sight judgment during simulations more accurate and realistic. The algorithm considers the impact of obstacles such as mountains, forests, and buildings on line of sight, calculating the degree of line-of-sight obstruction based on the shape, height, and position of the obstacles. The algorithm also considers the impact of weather conditions such as rain, snow, and fog on line of sight. Inclement weather conditions shorten the reconnaissance distance and reduce the probability of detection. Time factors such as sunrise and sunset, and moonrise and moonset, also affect lighting conditions. At night or in low light, reconnaissance becomes more difficult, and line-of-sight judgment becomes more stringent. The algorithm dynamically adjusts parameters such as reconnaissance distance and detection probability based on these factors, ensuring more accurate and reasonable line-of-sight judgment during simulations. This dynamic adjustment not only improves the simulation's fidelity but also provides decision-makers with a simulation experience that is more realistic than actual combat. At the same time, through dynamic adjustment of reconnaissance rules, the system can more accurately simulate reconnaissance behavior in actual battlefield environments and provide decision makers with more reliable intelligence support. BRIEF DESCRIPTION OF THE DRAWINGS

[0125] Figure 1 This is a flowchart of the electronic war game simulation based on remote sensing battlefield environment of the present invention;

[0126] Figure 2 It is a schematic diagram of the topological structure of the data processing module;

[0127] Figure 3 It is a schematic diagram of the sensitive area shield processing geometry and sensitive area process;

[0128] Figure 4 This is a diagram of the process of data from the system API being processed by the attribute field extractor. Figure 1 ;

[0129] Figure 5 This is a diagram of the process of data from the system API being processed by the attribute field extractor. Figure 2 ;

[0130] Figure 6 It is a schematic diagram of the process of drawing a map;

[0131] Figure 7 is a grid coordinate number map;

[0132] Figure 8 This is a diagram to calculate the coordinates of the center point of the hexagon Figure 1 ;

[0133] Figure 9 This is a diagram to calculate the coordinates of the center point of the hexagon Figure 2 ;

[0134] Figure 10 Calculate the coordinates of the center point of the hexagon Figure 3 ;

[0135] Figure 11 This is a diagram to calculate the coordinates of the center point of the hexagon Figure 4 ;

[0136] Figure 12 Calculate the coordinates of the center point of the hexagon Figure 1 ;

[0137] Figure 13 This is a schematic diagram of the coordinates of the six vertices of the calculation grid;

[0138] Figure 14 It is a schematic diagram of the network annotation process;

[0139] Figure 15 It is a schematic diagram of the visual judgment process;

[0140] Figure 16 This is a schematic diagram of the line of sight judgment process in Example 1. DETAILED DESCRIPTION

[0141] The technical solutions of the present invention will be described clearly and completely below in conjunction with the drawings in the present invention. In addition, the forms of the various structures described in the following embodiments are merely examples. The present invention is not limited to the various structures described in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0142] First, let's explain the terminology used in this article. In traditional wargaming, the board represents the battlefield, the physical or virtual space where the game takes place. It's typically presented as a map at a specific scale, marked with terrain, important landmarks, roads, and other strategic points. In computerized wargaming systems, the "board" is a software-generated virtual environment capable of simulating a much larger and more complex battlefield environment, encompassing multiple dimensions such as land, sea, and air.

[0143] Operators: Operators represent action units in the game, such as troops, equipment, and commanders. In traditional board games, operators might be physical pieces or tokens, each representing a specific military force or equipment. In computer game systems, operators are entities in the data model that represent different military units with their own attributes and capabilities, such as firepower, defense, and movement speed.

[0144] Rules: Rules define the game's operational mechanisms, including action sequence, combat determination, movement restrictions, and victory and defeat conditions. These rules ensure the game's logic and fairness, simulating the strategic and tactical decisions of a real-world war. In computerized systems, rules are implemented through algorithms that can simulate complex interactions and events, including factors such as weather changes, logistical support, and the impact of morale.

[0145] Through the coordinated efforts of these three components, a wargaming system creates a near-realistic war simulation environment in which participants can plan strategies, execute tactical maneuvers, and observe combat outcomes, thereby honing their decision-making abilities, testing tactical plans, and conducting military training or scientific research.

[0146] Reference Figures 1-15 The present invention provides an electronic war game simulation system based on remote sensing battlefield environment, which includes:

[0147] Data access module, the data access module downloads and imports remote sensing map data, the remote sensing map data includes but is not limited to geographic information including terrain, roads and rivers;

[0148] Data processing module: The data processing module reads and parses remote sensing map data, converts the remote sensing map data into a unified data format, performs coordinate system conversion, shields sensitive areas, extracts and cleans attribute fields, converts attribute values ​​and unifies units, and marks terrain, roads, rivers, and coverings;

[0149] The map generation module generates a wargame map based on the processed remote sensing data. This involves cutting the map into regular hexagonal grids of uniform size, calculating the center point and vertex coordinates of each grid, and numbering and annotating each grid.

[0150] The simulation module simulates military operations, strategic decisions, and tactical deployments based on the generated wargame map, and dynamically adjusts the reconnaissance distance and detection probability according to environmental factors within the grid to realize wargame simulation.

[0151] The data access module accesses the remote sensing map. It is necessary to select the map level, map area, and collection time period, and then download or retrieve the remote sensing map data to select the map level.

[0152] Suppose the hexagonal grid in the game is set to 72 pixels high and 80 pixels wide.

[0153] There are three levels of maps involved in war game simulations: provincial maps, city maps, and action maps.

[0154] 1) Provincial level Figure 1 Each grid represents 10 kilometers;

[0155] 2) City-level Figure 1 Each grid represents 1 kilometer;

[0156] 3) Location of action Figure 1 Each grid represents 10 meters;

[0157] 10 kilometers (10,000 meters) corresponds to 70 pixels;

[0158] Distance represented by each pixel: 10,000 meters / 72 = 139 meters / pixel;

[0159] Recommended zoom level: Around level 10 or 11, at which the map shows an overview of a city or town.

[0160] 1 kilometer (1,000 meters) corresponds to 70 pixels;

[0161] Distance represented by each pixel: 1,000 meters / 80 = 13.9 meters / pixel;

[0162] Recommended zoom level: Around level 14 or 15, at which the map shows streets and some large buildings.

[0163] 10 meters corresponds to 70 pixels;

[0164] Distance represented by each pixel: 10 meters / 70 = 0.139 meters / pixel;

[0165] Recommended zoom level: Around level 18 to 19, at which the map shows details down to the level of individual buildings and trees.

[0166] Select a map area:

[0167] You can use the map picker to select a rectangular area on the remote sensing map and choose the collection time period;

[0168] The selected collection time can be short and can be calculated based on the real-time time to be deduced. For example, one round represents 1 hour, and 24 rounds represent 1 day, so a certain day can be selected.

[0169] The selected collection time period will be affected by factors such as topography, weather, sunrise and sunset, etc.

[0170] There are two ways to download remote sensing data: manual data acquisition and automatic access.

[0171] 1) Manually obtain data:

[0172] Based on the three conditions for searching remote sensing data in the previous step, search and download from public remote sensing data websites, and then import them through the system import function.

[0173] Here are some commonly used remote sensing data websites:

[0174] China Remote Sensing Data Sharing Network: This website boasts the longest archive period in China, offering free access to Landsat data and the ability to subscribe to commercial satellite data from overseas. After registering and passing the review process, users can directly download the data they need.

[0175] China Resources Satellite Application Center: One of my country's three major satellite application centers, it aggregates domestic satellite data. After registration, users can download HJ satellite data, though downloads of high-resolution data require approval.

[0176] Geospatial Data Cloud: Data resources are updated regularly, including Landsat series, China-Pakistan resource satellites, various MODIS data products, DEM digital elevation data, EO-1 data, NOAAA VHRR data products, Sentinel data, and more. After registration and approval, users can download the required data.

[0177] Global Change Science Research Data Publishing System: This system offers a wide variety of data covering a wide range of fields, allowing users to search for data based on their needs. Register an account and download the data you need directly.

[0178] 2) Automated access:

[0179] Based on the three conditions for searching remote sensing data in the previous step, call some commercial remote sensing data interfaces (such as the open data service of Costenda) to directly download files or data in the corresponding format to provide more accurate data. Processing remote sensing data supports some common file formats such as GeoJSON and Shapefile.

[0180] like Figure 2 As shown, processing remote sensing data requires the implementation of: remote sensing data reader, coordinate system converter, sensitive area shield, attribute field extractor, attribute value cleaner, unified attribute value unit, attribute value converter, and generation of remote sensing map database.

[0181] Remote sensing data reader;

[0182] The remote sensing data reader parses the received remote sensing data into unified structured data.

[0183] The accessed remote sensing data can be read using the GeoTools library;

[0184] Key features of GeoTools include:

[0185] Map data processing: It supports multiple map data formats, such as Shapefile, GeoJSON, etc., allowing developers to easily process geospatial data in different formats.

[0186] Geographic Coordinate System Management: GeoTools provides tools for managing and converting geographic coordinate systems (CRS). Developers can use GeoTools to define, convert, and project different coordinate systems to suit different geographic data needs.

[0187] Spatial Analysis: GeoTools provides a wealth of spatial analysis capabilities, including buffer analysis, spatial query, spatial overlay analysis, etc., to help users process and analyze geospatial data.

[0188] Users can also edit Excel by themselves to import the system. The Excel format is as follows;

[0189] The Excel file needs to contain two sheets:

[0190] 1)Geometry table;

[0191] Table 1 Coordinate set of map geometry

[0192]

[0193] Table 2 Field description of Table 1

[0194]

[0195]

[0196] 2) Properties table;

[0197] Table 3 is used to store the attributes corresponding to each geometric figure on the map, which is generally data generated by manual annotation or remote sensing recognition;

[0198] Table 3 Attributes corresponding to each geometric figure on the graph

[0199] geometryId name value 1 name Qingyang District 1 center 104.055731,30.667648 1 level district 1 elevation 100 meters ... ... ... n name Jinjiang District n center 104.080989,30.657689 n level district n elevation 31 meters n water depth 2 meters

[0200] Table 4 Field description of Table 3

[0201] Field Name Field Description geometryId Geometry ID Name Attribute Name Value Property Value

[0202] The geometryId in the Geometry table is associated with the geometryId in the Properties table.

[0203] Coordinate system converter:

[0204] WGS84 is an international standard for longitude and latitude, used as the coordinate system for data retrieved from GPS devices, and is also commonly used by international map providers (such as Google Maps International, OSM, and Mapbox). GCJ-02 is a Chinese standard used for coordinate data obtained by positioning on mobile devices published in China. The state stipulates that all domestically published map systems (including electronic forms) must use at least GCJ-02 for initial encryption of geographic locations. The Baidu Coordinate System (BD-09) is a Baidu standard used in Baidu SDK, Baidu Maps, Baidu GeoCoding, and more.

[0205] There may be significant deviations between different coordinate systems for marking the same location, which may lead to cumulative errors on the map. To ensure the accuracy and consistency of the map, we need to unify these coordinate systems to avoid any potential errors and make the map data more accurate and reliable.

[0206] GeoJSON uses the WGS-84 coordinate system by default, which is a global geographic coordinate system with longitude and latitude as units. Longitude ranges from -180 to 180 degrees, and latitude ranges from -90 to 90 degrees.

[0207] The coordinate system converter is responsible for converting all latitude and longitude coordinates in the imported remote sensing data into a coordinate system: WGS 84 coordinate system.

[0208] The coordinate system converter reads each latitude and longitude coordinate in the Geometry table and performs the following coordinate system conversions using the GeoTools library: Chinese Standard (GCJ-02) → WGS84 coordinate system, Baidu Coordinate System (BD-09) → WGS84 coordinate system, and writes the converted coordinates back to the Geometry table for later use.

[0209] Sensitive area shield:

[0210] The sensitive area blocker is responsible for removing preset sensitive areas from the map to prevent security information leakage.

[0211] 1) It is necessary to circle some sensitive areas on the map and save the sensitive areas to the sensitive area coordinate library.

[0212] 2) After the coordinate system converter has converted the coordinates, the GeoTools library can be used to perform a difference between each geometric figure and the sensitive area to obtain the coordinate set of the new area, such as Figure 3 The sensitive area masker sets the corresponding geometry to the coordinate set of the new area.

[0213] Attribute Field Extractor:

[0214] The attribute field extractor is used to filter and extract the various complex annotations contained in the attributes of the multiple remote sensing data sources read by the remote sensing data reader, and flexibly extract the required attributes from them.

[0215] As shown in the table, the attribute field names of each data source and the attribute field names of this system are mapped in advance and saved in the field mapping library.

[0216] Table 5 Field Mapping Library

[0217]

[0218] 1) The attribute field extractor will find the corresponding system attribute name list from the field mapping library based on the data source;

[0219] 2) Extract the data from the attribute data according to its system attribute name list;

[0220] 3) Then replace the corresponding system property name with this system property name.

[0221] In a preferred embodiment, the data of the system API is processed by the attribute field extractor as follows Figure 4 shown.

[0222] Attribute Value Cleaner:

[0223] The attribute value cleaner cleans the data extracted by the attribute field extractor to obtain usable attribute values.

[0224] 1) Use standard data types:

[0225] Make sure the property uses the correct data type, such as string, number, Boolean, etc.

[0226] Avoid mixing between strings and numbers, or using complex data structures where unnecessary.

[0227] 2) Handling null values ​​and missing data:

[0228] If an attribute doesn’t exist in some features, consider setting it to null or using a standard missing value representation. Avoid leaving empty strings or undefined values ​​in your data.

[0229] Unifying attribute value units is to unify the units of numerical type data after the attribute value cleaner completes cleaning.

[0230] 1) Length unit conversion:

[0231] Substitute the length unit of the data source system into the conversion formula in the numerical unit conversion library.

[0232] For example, if the length unit of a system is inches, it needs to be converted using the following formula;

[0233] Length = y inches x 0.0254 m / inch.

[0234] 2) Time zone conversion:

[0235] If the collected weather or earthquake occurrence time is recorded according to the time zone where the data is generated, the time zone needs to be converted to Beijing time.

[0236] Property Value Converter:

[0237] The attribute value converter is used to convert the cleaned attribute values ​​into values ​​that can be used in the war game.

[0238] As shown in the figure below, map the attribute values ​​of each data source with the attribute values ​​of this system in advance and save them in the field mapping library.

[0239] Table 6 Mapping relationship between attribute values ​​of various data sources and attribute values ​​of this system

[0240]

[0241]

[0242] 1) The attribute value converter will find the corresponding attribute name list of this system from the terrain and landform standard library, weather standard library, natural disaster standard library, traffic standard library, place name standard library, and building standard library according to the data source. The terrain and landform values ​​in the provincial map generally include: railways, highways, provincial roads, national roads, toll stations, gas stations, rest areas, railway stations, airports, ports, urban areas, villages and towns, large rivers, small rivers, bridges (levels 1, 2, and 3); the terrain and landform values ​​in the city map generally include: flat land, mountains, terraces, high-density buildings, airports, forests, Residential areas, factory areas, commercial areas, cultural areas, railways and roads, parking lots, squares, green spaces, flat land, trees, artificial lakes, driveways, sidewalks, information desks / ticket collection offices, entrances and exits, stairs, elevators, vents, railways, indoor areas, fences, walls, fast VIP channels, security checkpoints; the terrain and landform values ​​in the action map generally include: parking lots, squares, green spaces, flat land, trees, artificial lakes, driveways, sidewalks, information desks / ticket collection offices, entrances and exits, stairs, elevators, vents, railways, indoor areas, fences, walls, fast VIP channels, security checkpoints.

[0243] 2) Query the data in the attribute data according to the attribute name list of this system;

[0244] 3) Then replace the corresponding system property value with the current system property value.

[0245] In a specific implementation case, the data of the system API is processed by the attribute field extractor as follows: Figure 5 shown.

[0246] Generate remote sensing map database;

[0247] After being processed by the attribute value converter, the normalized GeoJSON data is obtained. The data can now be stored in the database for future queries in the war game.

[0248] It mainly contains two tables;

[0249] 1)Geometry table;

[0250] Table 7 Coordinate set of map geometry

[0251]

[0252] Table 8 Field Description of Table 7

[0253]

[0254]

[0255] 2) Properties table;

[0256] Table 9 is used to store the attributes corresponding to each geometric figure on the map, which is generally data generated by manual annotation or remote sensing recognition;

[0257] Table 9 Attributes corresponding to each geometric figure on the map

[0258] geometryId name value 1 name Qingyang District 1 center 104.055731,30.667648 1 level district 1 elevation 100 meters ... ... ... n name Jinjiang District n center 104.080989,30.657689 n level district n elevation 31 meters n water depth 2 meters

[0259] Table 10 Field description of Table 9

[0260]

[0261]

[0262] The geometryId in the Geometry table is associated with the geometryId in the Properties table.

[0263] The process of drawing a map is as follows:

[0264] 1) Read and process the remote sensing map database generated by remote sensing data, obtain all geometric figures, set the contour line color and place name font style, and output the contour layer;

[0265] 2) For all the geometries, filter the terrain attributes in the attributes according to the names in the terrain standard library to obtain the terrain geometries. Then, query the texture in the map texture library according to the terrain name, set a different texture for each geometry, and output the terrain layer.

[0266] 3) Filter all geometric shapes by the elevation attribute in the attributes to obtain elevation geometric shapes, set different elevation background colors according to different elevation ranges, and output the contour layer;

[0267] 4) Filter the river and road attributes in the attributes of all geometric figures according to the names in the terrain standard library to obtain the river and road geometries. Query the texture in the map texture library according to the river and road type, set a different texture for each geometric figure, and output the river and road layer;

[0268] 5) Filter the covering attributes in the attributes of all geometric figures according to the names in the terrain standard library to obtain the covering geometry. According to the covering type, query the texture in the map texture library to find the texture, set a different texture for each geometric figure, and output the covering layer;

[0269] 6) All layers are summarized in order to the plotter (stream renderer in the GeoTools library), and the plotter merges each layer in order and outputs it into a map.

[0270] Meshing process:

[0271] Gridding the map can simplify objective rules. Each operator in the war game needs to be placed in a grid, and the operator will be affected by objective factors within the grid (such as movement distance, stacking space, weather, altitude, etc.).

[0272] The grid coordinate numbering rules are as follows:

[0273] If the map is cut into a maximum of 99x99 grids, the encoding rules are:

[0274] 1) The first two digits represent the horizontal column number n, and any missing digits are filled with 0;

[0275] 2) The last two digits represent the vertical row number m, and any missing digits are supplemented with 0;

[0276] If the map is cut into a maximum of 999x999 grids, the encoding rules are:

[0277] 3) The first three digits represent the horizontal column number n, and any missing digits are filled with 0;

[0278] 4) The last three digits represent the vertical row number m, and any missing digits are supplemented with 0;

[0279] When 9999x9999, the same applies. Figure 7 shown.

[0280] Formula for calculating the coordinates of the center point of a hexagon:

[0281] like Figure 8 、 Figure 9 As shown, the generated map starts from the upper left corner and arranges regular hexagonal grids along the vertical axis y-axis. Each grid shares an edge, the odd-numbered columns are at the top of the grid, and the even-numbered columns are staggered by half a grid.

[0282] Assume that the height of the regular hexagonal grid is h, the width is w, the radius is r, and the coordinates of the center point are [x, y]. Now calculate the center point of the grid in the nth horizontal column and the mth vertical row.

[0283] When n is an odd number, removing the even number column will result in n r's, with each even number corresponding to one r; we get:

[0284]

[0285] The calculation formula for y is:

[0286]

[0287] like Figure 10 、 Figure 11 、 Figure 12 As shown, when n is an even number, the center coordinate x is r+r / 2 greater than the x coordinate of the n-1 grid;

[0288]

[0289] As shown in the figure below, the calculation formula for y is obtained:

[0290]

[0291] Calculate the coordinate formulas of the six vertices, such as Figure 13 As shown, assuming the height of the regular hexagonal grid is h, the width is w, and the radius is r, it can be calculated by the following formula;

[0292] Formula to calculate width using height:

[0293]

[0294] Formula for calculating radius using height:

[0295]

[0296]

[0297] Therefore, we only need to use the height h of the hexagonal grid and the coordinates of the center point c to determine the size and position of the hexagon.

[0298] To draw a hexagonal grid, you need to calculate the coordinates of six points: p1, p2, p3, p4, p5, and p6. The following is the formula for calculating the coordinates of the six points:

[0299] p1=[xr,y];

[0300]

[0301] p4=[x+r,y];

[0302]

[0303] The grid annotation process is as follows:

[0304] After the map is gridded, the grids need to be labeled. Grid labeling is to label the attributes corresponding to the latitude and longitude coordinates of the map to the corresponding grids.

[0305] Read the coordinates and attributes of all contour points in the remote sensing database into an array. The following is the process of calculating the hexagonal grid to which each coordinate in the remote sensing data belongs:

[0306] Assuming the height of a regular hexagon is h, the width is w, and the radius is r, the center point [x, y] of the hexagon closest to a certain coordinate [a, b] can be calculated using the following formula, where the brackets indicate rounding.

[0307]

[0308] when When it is an even number, it indicates an even column;

[0309]

[0310] otherwise;

[0311]

[0312] Calculate the corresponding hexagonal grid, find the hexagonal grid number, find the hexagonal grid attribute from the grid map database through the hexagonal grid number, merge the coordinate attribute and the hexagonal grid attribute as the new hexagonal grid attribute, and when merging, the numerical type needs to be merged according to actual needs, such as taking the maximum value for elevation and the maximum value for water depth. Figure 14 shown.

[0313] The application process of environmental factors in remote sensing data to war game rules:

[0314] Table 11 Terrain Status Visibility Decision Table (The data in the table are simulation data designed by the present invention based on practical experience)

[0315]

[0316] Note: If you move from a hexagonal grid inside the enemy's line of sight to a hexagonal grid outside the enemy's line of sight, you will automatically become a hidden unit.

[0317] Table 12 Weather Day and Night Visibility Decision Table (The data in the table are simulated data designed by the present invention based on practical experience)

[0318]

[0319]

[0320] Visual judgment process:

[0321] A straight line is drawn between the operator and the target, which is the line of sight. If the line of sight is not blocked by high ground, cities, towns, or forest grids, it is considered to be clear line of sight.

[0322] If the line of sight is blocked only by high ground, determine whether the high ground is higher than the altitude of both the reconnaissance counter and the target. If so, there is no line of sight. If the high ground is between the two points, use the line of sight determination table to make a determination. The line of sight determination table includes the terrain state line of sight determination table in Table 11 and the weather day and night line of sight determination table in Table 12.

[0323] The steps are:

[0324] Mark the reconnaissance points, obstacles, and target points in the table according to the terrain they are located on and the number of grids they are far from each other.

[0325] Connect the scout point and the target point with a straight line.

[0326] If the obstacle is above the straight line, the line of sight is blocked; otherwise, the line of sight is clear.

[0327] The implementation logic process is as follows:

[0328] 1) Find the terrain from the grid map database according to the hexagonal grid number where the operator is located;

[0329] 2) Check the weather in your grid;

[0330] 3) If it is nighttime, find out the current brightness of the moon;

[0331] 4) Find the hexagonal grid number from the terrain visibility determination table or the weather day and night visibility determination table and convert it into visibility distance;

[0332] 5) Calculate the distance between the operator and the target:

[0333]

[0334] 6) Determine whether it is within the field of view;

[0335] 7) Find all obstruction hexagons between the current operator and the target operator;

[0336] a. Find the grid within a rectangular range that is diagonally opposite the operator and the target operator, see Figure 15 ① in

[0337] b. Draw a straight line with a thickness of 2r between the operator and the target operator, see Figure 15 ② in the

[0338] c. Intersect ② with all grids. When the intersection area is greater than the area of ​​a single grid / 3, mark the grid as being on the line of sight. Figure 15 ③ in

[0339] 8) Substitute the operator, all obstruction hexagons, and the target operator into the formula to calculate whether it is blocked. If it is blocked, it is invisible;

[0340] In this algorithm, unobstructed sight lines exist only if:

[0341]

[0342] Where H is the difference in elevation (in meters) between the elevation of the higher operator and the elevation of the lower operator.

[0343] D: The distance from the higher operator position to the lower operator position (in meters).

[0344] h: The height of the possible obstruction minus the height of the lowest operator (in meters).

[0345] d: The distance from the location of the possible obstacle to the lower position counter (measured in meters).

[0346] 1.5: The default value is the height of the person or vehicle (in meters).

[0347] Note: Each contour line represents a vertical elevation of 20 meters. The horizontal distance between hexagons is 10 meters (mobile maps) and 1000 meters (city maps). All buildings and trees, if not marked in the scenario, are assumed to have a vertical elevation of 20 meters and are considered obstructions.

[0348] Example 1, as Figure 15 As shown, assuming that the distance between the observation point and the target point is D meters, the elevation of the target point is h1 meters, the elevation of the observation point is h2 meters, and the height of the obstacle is h meters, the following formula is obtained. It is obvious that target point 1 is in the line of sight. It can be seen that target 2 is blocked because it is too close to the obstacle and is not in the line of sight.

[0349]

[0350] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification, replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. An electronic war game simulation system based on remote sensing battlefield environment, characterized in that: It includes: Data access module, the data access module downloads and imports remote sensing map data, the remote sensing map data includes but is not limited to geographic information including terrain, roads and rivers; Data processing module: The data processing module reads and parses remote sensing map data, converts the remote sensing map data into a unified data format, performs coordinate system conversion, shields sensitive areas, extracts and cleans attribute fields, converts attribute values ​​and unifies units, and marks terrain, roads, rivers, and coverings; The map generation module generates a wargame map based on the processed remote sensing data. This involves cutting the map into regular hexagonal grids of uniform size, calculating the center point and vertex coordinates of each grid, and numbering and annotating each grid. The simulation module simulates military operations, strategic decisions, and tactical deployments based on the generated wargame map, and dynamically adjusts the reconnaissance distance and detection probability according to environmental factors within the grid to realize wargame simulation.

2. The electronic war game simulation system based on remote sensing battlefield environment according to claim 1 is characterized in that: The data access module selects map levels including provincial maps, municipal maps and action maps, which represent battlefield environments of different scales; in the deduction module, environmental factors include but are not limited to terrain, weather, time, season, sunrise and sunset, and moonrise and moonset.

3. The electronic war game simulation system based on remote sensing battlefield environment according to claim 1 is characterized in that: The data processing module specifically includes: Remote sensing data reader, which parses remote sensing data into structured data; Coordinate system converter, which converts the coordinates in remote sensing data into the WGS84 coordinate system; Sensitive Area Blocker, identifies and removes sensitive areas on the map; Attribute field extractor, extracts key geographic information fields from remote sensing data; Attribute value cleaner, which cleans the extracted attribute data; The attribute value converter converts the attribute field names of different data sources into a unified system attribute name and unifies the units of numerical type data.

4. The electronic war game simulation system based on remote sensing battlefield environment according to claim 3 is characterized in that: The attribute value converter uses a topography and landform standard library, a weather standard library, a natural disaster standard library, a traffic standard library, a place name standard library and a building standard library to map and convert attribute values.

5. A method for conducting electronic war game simulation using the electronic war game simulation system based on remote sensing battlefield environment as described in any one of claims 1 to 4, characterized in that: It includes the following steps: S1. Remote sensing map data: Download or retrieve remote sensing map data by selecting the map level, map area, and collection time period; S2. Processing remote sensing data: Converting the received remote sensing data into unified structured data, including reading remote sensing data, converting coordinate systems, shielding sensitive areas, extracting and cleaning attribute fields, unifying attribute value units and converting attribute values, and generating a remote sensing map database; S3. Map drawing: drawing a map based on the processed remote sensing map database, including setting contour lines, terrain texture, elevation background color, river roads and cover texture; S4. Grid map: Cut the map into hexagonal grids of uniform size, number each grid, calculate the center point, and annotate the grid attributes; S5. Apply environmental factors from remote sensing data to wargame rules: Read environmental factors from remote sensing data, dynamically adjust reconnaissance distance and detection probability, and apply relevant rules to wargame simulations.

6. The method according to claim 5, characterized in that The specific process of step S1 includes: S11. Select the map level. Choose between a provincial map, a city map, or an action map based on the needs of the wargame. Each map has a different grid size, reflecting a different level of geographic detail. The provincial map has each grid representing 10 kilometers, making it suitable for simulating large-scale strategic deployments. The city map has each grid representing 1 kilometer, making it suitable for simulating tactical operations at the city or town level. The action map has each grid representing 10 meters, making it suitable for simulating details down to the level of buildings and trees. After selecting the map level, you can further set the pixel-to-actual distance ratio based on the selected level, and recommend a map zoom level. S12. Selecting a map area: Using a map picker, select a rectangular area on the remote sensing map as the battlefield for simulation, ensuring that the simulation area matches the actual geographical environment. S13. Select the collection time period: Select an appropriate collection time period based on the specific needs of the simulation. The selection of the time period will affect the simulation of topography, weather, and sunrise and sunset factors. S14. Download remote sensing data: Download remote sensing data through manual data acquisition and automatic access. The specific process of manual data acquisition is: search and download data from public remote sensing data websites according to the set map level, area and time period; the downloaded data is imported through the system import function; the specific process of automatic access is: use the commercial remote sensing data interface to directly download files or data in the corresponding format.

7. The method according to claim 5, characterized in that In step S2, the specific process includes: S21. Remote sensing data reading: Use the remote sensing data reader to parse the received remote sensing data into unified structured data; S22. Coordinate system conversion: Convert the coordinate systems of remote sensing data from different sources using different geographic coordinate systems to a unified coordinate system, WGS84. S23. Sensitive area shielding: Remove pre-set sensitive areas from the map; use the sensitive area shield to circle the coordinates of sensitive areas and exclude these areas from the map generation process. S24, Attribute Field Extraction and Cleaning: Extract fields useful for wargaming from the large amount of annotated information contained in remote sensing data. Use the attribute field extractor to extract required attributes from remote sensing data based on pre-established field mapping relationships. Clean the extracted attribute values ​​to ensure data type accuracy, handle null values, and address missing data, making the data usable for subsequent processing. S25. Unify attribute value units: Unify the units of attribute values ​​of data from different sources using different units. Convert all attribute values ​​to standard units according to the conversion formula in the unit conversion library. S26, attribute value conversion: Convert the cleaned and unified attribute values ​​into a format usable by the wargaming system; use the attribute value converter to map the attribute values ​​of the external system to the standard attribute values ​​of the wargaming system based on the terrain and weather standard libraries; S27. Generate a remote sensing map database: Store the normalized data in the database for subsequent query by the war game simulation system; the database stores the coordinate set of map geometric figures and corresponding attribute information.

8. The method according to claim 6, characterized in that In step S3, the specific process includes: S31. Reading a remote sensing map database: reading coordinate sets and attribute information of all geometric figures from the processed remote sensing map database; such information includes but is not limited to map geometry, terrain, elevation, rivers, roads, and coverings; S32. Setting contour lines: Reading geometric data from the database, setting different contour line colors and styles for different geometric shapes to distinguish different geographical features; using the drawing library to draw these geometric shapes on the map to form a basic map outline; S33, terrain texture processing: read the terrain attributes of each geometric figure from the terrain standard library, and search the corresponding texture image in the map texture library according to the terrain name; apply the found texture to each geometric figure to form map areas with different terrain features; S34. Set elevation background color: Read the elevation attributes of each geometric figure from the database; set different background colors according to the elevation range to distinguish different elevation areas; S35. River and road drawing: including: S351, filter geometric figures: filter geometric figures representing rivers and roads from the database; S352, texture application: according to the types of rivers and roads, search and apply the corresponding textures in the map texture library; S353, Draw Lines: Use the drawing tools to draw these textures onto the map along the geometry of rivers and roads; S36, Cover texture processing: S361, screening geometric figures: screening geometric figures representing covering objects from the database; S362, texture application: according to the type of covering object, search and apply the corresponding texture in the map texture library; S363, Draw Overlay: Apply texture to the geometry of the overlay and draw it on the map; S37. Layer merging: Draw each layer separately in the order of contour lines, terrain textures, elevation background colors, rivers and roads, and coverings; use the drawing library to merge each layer into a map in the order to form the final war game simulation map.

9. The method according to claim 5, characterized in that In step S4, the specific process includes: S41. Cut the map into hexagonal grids: Cut the drawn map into hexagonal grids of uniform size. Hexagonal grids have the advantages of uniformity and close arrangement, which helps to simplify spatial analysis and operator movement calculations. S42. Grid numbering rule: A numbering rule is established to uniquely identify each grid. When the grid is divided into a maximum of 99x99 grids, the coding rule is: the first two digits represent the horizontal column number n, and the missing digits are supplemented with 0; the last two digits represent the vertical row number m, and the missing digits are supplemented with 0; When the grid is divided into a larger size of 999x999, the encoding rules are expanded accordingly. The first three digits represent the horizontal column number n, and the remaining three digits represent the vertical row number m, and the remaining three digits are filled with 0. S43. Calculate the coordinates of the main points of the hexagonal grid: S431. Calculate the coordinates of the center point of the hexagonal grid: Let the height of the regular hexagon be h, the width be w, and the radius be r; For the hexagonal grid at the nth column and the mth row, the coordinates [x, y] of its center point are calculated as follows: When n is an odd number, the y coordinate of the center point can be calculated using the following formula: When n is an even number, the center point coordinates [x, y] are calculated as follows: S432. The formula for calculating vertex coordinates of a regular hexagonal grid is: To draw a hexagonal grid, you need to calculate the coordinates of six points: p1, p2, p3, p4, p5, and p6. The following is the formula for calculating the coordinates of the six points: p1=[xr,y] p4=[x+r,y] S433. Dimension calculation in special cases: If you need to calculate the width w or radius r based on the height h, you can use the following formula: The formula for calculating width w using height h is: The formula for calculating radius r using height h is: S44. Grid attribute annotation: Annotate the latitude and longitude coordinates of the map and their corresponding attributes to the corresponding grid. This process involves the following steps: S441. Read remote sensing database: obtain coordinates and attributes of all geometric figures; S442. Calculate the grid to which the coordinates belong: for each coordinate point, calculate the hexagonal grid number to which it belongs; S443, merging grid attributes: searching for corresponding grid attributes in the grid database based on the grid number, and merging the newly acquired coordinate attributes with the original grid attributes; during the merging process, the priority of the attribute values ​​needs to be processed according to actual needs; The specific process is as follows: Assuming the height of the regular hexagon is h, the width is w, and the radius is r, the center point [x, y] of the hexagon closest to a certain coordinate [a, b] can be calculated using the following formula. The brackets in the formula indicate rounding. when When it is an even number, it means an even column; otherwise, Calculate the corresponding hexagonal grid, find the hexagonal grid number, find the hexagonal grid attribute from the grid map database through the hexagonal grid number, merge the coordinate attribute and the hexagonal grid attribute as the new hexagonal grid attribute.

10. The method according to claim 5, characterized in that In step S5, the specific process includes: S51. Read environmental factors in remote sensing data: Read and analyze various environmental factors contained in remote sensing data, including but not limited to: Weather conditions, including clear, snowy, rainy, misty, moderate fog, blizzard, and dense fog; seasonal changes; sunrise and sunset times; moonrise and moonset times; terrain features, including plains, mountains, forests, rivers, and roads; and elevation data; S52. Extract and integrate environmental factors into the war game rule base: Integrate environmental factors from remote sensing data with the wargame system's rule base; the rule base defines the various mechanisms and logic of the game, including action sequence, combat determination, movement restrictions, and victory and defeat conditions; these rules are dynamically adjusted based on the actual environmental factors in the remote sensing data; S53. Apply relevant rules based on rounds and geographic location: Based on the current round number and operator, i.e., the geographic location of the action unit in the game, the corresponding environmental factors are read from the remote sensing map database and the corresponding rules are applied. The specific process includes: S531. Determination of the number of rounds: The deduction process will go through multiple rounds, each round representing a time span; S532. Selection of collection time: Based on the real-time time calculation to be performed, select the corresponding collection time period; this time period will be affected by factors such as topography, weather, and sunrise and sunset; S533. Determination of Geographic Location: The specific location of an operator on the deduction map determines which environmental factors affect it. The geographical location of an operator can be determined through the remote sensing map database. S534, read environmental factors: read environmental factors related to the current round number and geographical location from the remote sensing map database; these factors include weather conditions, terrain characteristics, and lighting conditions; S535, Apply Environmental Factor Rules: Apply corresponding rules based on the read environmental factors. For example, if the weather condition is foggy, it will affect the operator's field of view and movement speed. If the operator is located in a mountainous area, terrain obstruction will affect reconnaissance and communication. If the operator is near a river, the time and resources required to cross the river need to be considered. S536. Specific application of the rules: Determine the observation distance and probability of detection under different terrain and weather conditions based on the Terrain Visibility Determination Table and the Weather Day and Night Visibility Determination Table. S54. Dynamically adjust the deduction parameters: According to the environmental factors read, dynamically adjust various parameters in the deduction process, as follows: S541. Read environmental factors: Read environmental factor data of the current simulation area from the remote sensing map database, including but not limited to weather conditions, terrain features, elevation data, seasonal changes, sunrise and sunset times, and moonrise and moonset times; S542. Analyze operator location and current round: Track each operator's geographic location and current round number in real time. The operator's location determines which environmental factors affect it, while the round number helps the system determine the current time context and adjust the corresponding environmental factors. S543. Dynamic Parameter Adjustment: Based on the environmental factors it reads, the system dynamically adjusts various key parameters during the simulation: Reconnaissance distance is dynamically adjusted based on the terrain and weather conditions of the reconnaissance and target operators, as well as the current time; observation probability is dynamically adjusted based on environmental factors and the state of the target unit; and movement speed is dynamically adjusted based on the current terrain and weather conditions, as terrain features and weather conditions directly affect the movement speed of the unit. S55. Perform line of sight determination to determine whether there is line of sight obstruction between the operator and the target: The system determines whether there is line of sight obstruction between the operators based on terrain elevation data, obstacle locations, and environmental factors. The specific implementation process includes: connecting a straight line (line of sight) between the operator and the target. If the line of sight is not obstructed, line of sight is established. If the line of sight is only obstructed by high ground, determine whether the high ground is higher than the altitude of the reconnaissance unit and the target point. If so, line of sight is not established. If the high ground is between the two points, mark the reconnaissance point, obstacle, and target point according to the terrain location and the number of grids of distance between them, and connect the reconnaissance point and the target point with a straight line. If the obstacle is above the straight line, line of sight is not established. Otherwise, line of sight is established. The specific steps are as follows: S551, finding the terrain from the grid map database according to the hexagonal grid number where the operator is located; S552, query the weather in the grid; S553. If it is nighttime, find out the current brightness of the moon; S554. Find the number of hexagonal grids from the Terrain Visibility Determination Table or the Weather Day / Night Visibility Determination Table and convert it into visibility distance. S555. Calculate the distance between the operator and the target: S556, determining whether it is within the field of view; S557, searching for all obstruction hexagonal grids between the current operator and the target operator; S558. Substitute the operator, all obstruction hexagons, and the target operator into the formula to calculate whether it is blocked. If it is blocked, it is not visible. The existence of unobstructed vision only depends on: in: H: the difference between the elevation of the operator at a higher position and the elevation of the operator at a lower position; D: distance from the high operator position to the low operator position; h: the height of the possible obstruction minus the height of the lowest position operator; d: The distance from the position of the possible obstacle to the low position operator.

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