Electronic war game deduction system and method based on remote sensing battlefield environment

Abstract

The invention relates to the technical field of war game deduction systems, and provides an electronic war game deduction system and method based on a remote sensing battlefield environment, and the system comprises a data access module, a data processing module, a map generation module and a deduction module, and achieves the automation of the whole process from the downloading and analysis of remote sensing data to the generation of a war game map. The data processing module is specially designed with the functions of coordinate conversion, sensitive area shielding, attribute field extraction and cleaning and the like, and accuracy and applicability of map data are ensured. And the map generation module adopts a gridding method to realize accurate division of the map by calculating coordinates of a central point and a vertex of each grid. The deduction module dynamically adjusts the reconnaissance distance and the discovery probability according to the real-time environmental factors, and simulates military actions and tactical deployment. According to the system, the remote sensing technology and war game deduction are effectively combined, the deduction simulation degree and decision support scientificity are improved, and the system has wide military training and strategic analysis application prospects.

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] The electronic war game simulation system is a tool that uses computer technology to simulate military operations, strategic decisions and tactical deployment. It is a digital and virtual extension of traditional war games under modern technological conditions. The system provides users with a virtual battlefield environment in a highly digital way, allowing military researchers, strategists and trainers to conduct war games, tactical analysis and decision-making training without actually conducting physical exercises. The electronic war game simulation system can simulate a battlefield environment close to the real one, including terrain, weather conditions, lighting changes and other factors, making the simulation more realistic. The electronic war game simulation system can simulate various complex situations from tactical squad actions to strategic-level military operations, covering different military units, equipment, support systems, etc. With the powerful data processing capabilities of computers, the electronic war game simulation system can calculate a large amount of battlefield data in real time, such as unit movement, firepower coverage, casualty calculations, etc. In the electronic war game simulation system, users can interact through a graphical interface, adjust tactical or strategic decisions in real time, and immediately see feedback on the decision results. The electronic war game simulation system supports multiple users to participate online at the same time, simulate joint operations or confrontation exercises, and improve 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 the detailed recording and analysis of the combat process and the summary of lessons learned.

[0003] The problems with traditional electronic war game simulation systems are mainly manifested in the following aspects: First, most electronic war game simulation systems do not have sufficient control over environmental factors (such as weather, seasons, time changes, etc.). Most of them use preset rules or random dice to determine the timing and duration of their occurrence, resulting in large differences between the simulation results and the actual battlefield environment. Second, the traditional war game simulation system lacks effective map grid management, making it difficult to finely divide and control the battlefield environment, resulting in rough simulation results. Third, the line of sight judgment is inaccurate. In traditional war game simulation systems, line of sight judgment mainly relies on preset rules or manual judgment, and cannot accurately simulate the line of sight obstruction in the actual battlefield environment. Summary of the invention

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

[0005] A data access module, which downloads and imports remote sensing map data, including but 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] Map generation module, the map generation module generates a war game map based on the processed remote sensing data, including cutting the map into regular hexagonal grids of uniform size, calculating the center point coordinates and vertex coordinates of each grid, and numbering and attribute labeling each grid;

[0008] The simulation module simulates military operations, strategic decisions and tactical deployments based on the generated war game map, dynamically adjusts the reconnaissance distance and detection probability according to the environmental factors within the grid, and realizes war game 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 proportions 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 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 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] The method for conducting electronic war game simulation using an electronic war game simulation system based on 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 acquisition 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 according to 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 in remote sensing data to war game rules: Read environmental factors in remote sensing data, dynamically adjust reconnaissance distance and detection probability, and apply relevant rules to war game simulations.

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

[0025] S11. Select the map level. Choose provincial map, city map or action map according to the needs of war game simulation. Each map has different grid sizes, which reflects different levels of geographical details. Each grid of the provincial map represents 10 kilometers, which is suitable for simulating large-scale strategic layouts; each grid of the city map represents 1 kilometer, which is suitable for simulating tactical operations at the city or town level; each grid of the action map represents 10 meters, which is suitable for simulating details accurate to the level of buildings and trees; after selecting the map level, further set the ratio of pixels to actual distance according to the selected level, and recommend the appropriate map zoom level;

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

[0027] S13. Select the collection time period: Select an appropriate collection time period according to the specific needs of the simulation. The selection of the time period will affect the simulation of topography, weather, and sunrise and sunset factors. For example, if the simulation needs to simulate multiple time periods in a day, it is necessary to 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] Further, in step S2, the specific process includes:

[0030] S21. Remote sensing data reading: Use the remote sensing data reader to parse the received remote sensing data into unified structured data. This step can be achieved through open source libraries 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 into a unified coordinate system WGS84; GeoTools library or similar tools can be used for coordinate system conversion to ensure the accuracy and consistency of map data;

[0032] S23, sensitive area shielding: remove preset sensitive areas from the map; circle the coordinates of sensitive areas through the sensitive area shielding device, and exclude these areas in the map generation process;

[0033] S24, attribute field extraction and cleaning: Extract fields useful for wargaming from a large amount of annotation information contained in remote sensing data; extract required attributes from remote sensing data through attribute field extractor according to pre-established field mapping relationships; clean the extracted attribute values ​​to ensure the correct data type, handle null values ​​and missing data, and make the data available for subsequent processing;

[0034] S25. Unify attribute value units: unify the units of attribute values ​​of data from different sources using different units, and convert all attribute values ​​into 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 that can be used by the war game simulation system; use the attribute value converter to map the attribute values ​​of the external system into the standard attribute values ​​of the war game system according to the terrain and landform standard library and the weather standard library;

[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 the corresponding attribute information.

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

[0038] S31, reading 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 the geometric shape, terrain, elevation, rivers, roads and coverings of the map;

[0039] S32. Setting contour lines: reading geometric data from the database, setting different contour line colors and styles for different geometric shapes to distinguish different geographic features; using a drawing library (such as a stream renderer in GeoTools) to draw these geometric shapes on the map to form a basic map contour;

[0040] S33, terrain texture processing: read the terrain attributes (such as plains, mountains, forests) of each geometric figure from the terrain and landform standard library, and search for the corresponding texture image in the map texture library according to the terrain name; apply the found texture to each geometric figure to form a map area with different terrain features;

[0041] S34. Set elevation background color: read the elevation attribute 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 use lighter colors;

[0042] S35. River road drawing: including:

[0043] S351, filtering geometric figures: filtering 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, screening geometric figures: screening geometric figures representing covering objects (such as buildings, trees, 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, drawing the overlay: applying the texture to the geometric shape of the overlay and drawing it on the map;

[0050] S37. Layer merging: Draw each layer separately 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 of sequence to form the final wargame map.

[0051] Further, 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 calculation of operator movement;

[0053] S42. Grid numbering rule: Formulate a numbering rule 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, it 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 last three digits represent the vertical row number m, and the number is filled with 0. For example, the grid at the 105th column and the 203rd row 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 in 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 by 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 vertex coordinate calculation formula of the 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 the radius r using the 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, 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, calculating the grid to which the coordinates belong: for each coordinate point, using 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 according to 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 number of columns;

[0082]

[0083] otherwise,

[0084]

[0085] The corresponding hexagonal grid is calculated, the hexagonal grid number is found, the hexagonal grid attribute is found from the grid map database through the hexagonal grid number, and the coordinate attribute and the hexagonal grid attribute are merged as the new hexagonal grid attribute.

[0086] Further, 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, snow, rain, mist, 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; elevation data;

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

[0090] Integrate the environmental factors in the remote sensing data with the rule base of the war game system; the rule base defines the various mechanisms and logics in the game process, including action sequence, combat judgment, movement restrictions, and victory and defeat conditions; dynamically adjust these rules according to the actual environmental factors in the remote sensing data;

[0091] S53, applying relevant rules according to rounds and geographical locations: according to the current round number and operator, that is, the action unit in the deduction, and the geographical location, read the corresponding environmental factors from the remote sensing map database and apply the corresponding rules; the specific process includes:

[0092] S531. Determination of the number of rounds: During the deduction process, there will be multiple rounds, each round represents 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: according to 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, sunrise and sunset;

[0094] S533, determination of geographical location: the specific location of the operator on the deduction map determines which environmental factors affect it; the geographical location of the operator can be determined through the remote sensing map database;

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

[0096] S535, apply environmental factor rules: apply corresponding rules according to the read environmental factors; 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 shielding may affect reconnaissance and communication; if the operator is close to a river, it may need to consider the time and resources for crossing the river;

[0097] S536. Specific application of the rules: Determine the observation distance and detection probability under different terrain and weather conditions according to the Terrain Status Visibility Decision Table and the Weather Day and Night Visibility Decision Table;

[0098] S54, dynamically adjust the deduction parameters: According to the environmental factors read, dynamically adjust various parameters in the deduction process, including:

[0099] 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 (such as clear, rainy, snowy, foggy, etc.), terrain features (such as plains, mountains, forests, waters, etc.), elevation data, seasonal changes, sunrise and sunset times, and moonrise and moonset times;

[0100] S542, analyzing the position of operators and the current round: real-time tracking of the geographical location and the current round number of each operator (i.e., the action unit in the game); the position of the operator determines which environmental factors affect it, and the round number helps the system determine the current time background (such as day, night, season, etc.), so as to adjust the corresponding environmental factors;

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

[0102] Scouting distance: Dynamically adjusts the Scouting distance based on the terrain, weather conditions, and current time (e.g. day or night) of the Scouting Unit and the target unit; for example, in foggy conditions, the Scouting distance will be significantly reduced, while in clear daytime, the Scouting distance 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 features and weather conditions directly affect the movement speed of units. The system dynamically adjusts the movement speed based on the current terrain (such as mountains, plains, swamps, etc.) and weather conditions (such as rain, snow, strong winds, etc.). For example, in mountainous terrain, the movement speed of units may slow down; while on flat and dry plains, the movement speed may speed up.

[0105] S55, perform line of sight judgment 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 according to terrain elevation data, obstacle positions and environmental factors (such as weather conditions); the specific implementation process includes: connecting a straight line between the operator and the target, that is, the line of sight. If the line of sight is not blocked, it is line of sight; if the line of sight is only blocked by high ground, determine whether the high ground is higher than the height of the reconnaissance unit and the target point; if so, there is no line of sight; if the height of the high ground is between the two points, mark the reconnaissance point, the obstacle, and the target point according to the terrain and the number of grids of the mutual distance, and connect the reconnaissance point and the target point with a straight line; if the obstacle is above the straight line, there is no line of sight; otherwise, there is line of sight; the specific steps are as follows:

[0106] S551, finding out the terrain from the grid map database according to the hexagonal grid number where the operator is located;

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

[0108] S553, if it is night time, find out the current brightness of the moon;

[0109] S554. Find the number of hexagonal grids from the terrain status visibility determination table or the weather day and night visibility determination table, and convert it into the visible distance;

[0111] S555. Calculate the distance between the operator and the target:

[0112]

[0113] S556, determining whether it is within the field of view;

[0114] S557, searching for all obstruction hexagonal grids between the current operator and the target operator straight line;

[0115] S558, the operator, all the obstruction hexagonal grids, and the target operator are substituted 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 lies in:

[0116]

[0117] in:

[0118] H: The difference between the elevation of the operator at a high position and the elevation of the operator at a low position;

[0119] D: The distance from the high operator position to the low operator position;

[0120] h: the height of the possible obstacle minus the height of the low position operator;

[0121] d: The distance from the position of the possible obstacle to the lower operator.

[0122] The beneficial effects achieved by the present invention are:

[0123] 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, and realizes 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 according to the environmental factor data read in real time, 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 technical solutions such as weather conditions, seasonal changes, sunrise and sunset times, moon rise and moon set times, etc., and dynamically adjusts various parameters in the simulation process, such as reconnaissance distance, observation probability, moving speed, etc., according to the environmental factor data read in real time, 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.

[0124] Second, the present invention proposes a management method for grid maps and fine control. By cutting the map into hexagonal grids of the same size, and numbering and calculating the center point of each grid, the grid management of the map is realized. This method helps to simplify objective rules so that each operator can be accurately placed in the grid and affected by objective factors in the grid. Each grid represents a certain geographical range, making the position of the operator on the map more accurate. At the same time, objective factors such as terrain and weather in 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 in the deduction process can be simplified. For example, unified parameters such as reconnaissance distance and observation probability can be formulated for each grid, thereby reducing the complexity of rule formulation. The grid map enables the system to independently manage and control each grid. During the deduction process, the system can adjust the environmental factor parameters in one or some grids as needed to achieve more refined deduction control.

[0125] Third, the present invention proposes a dynamic adjustment scheme for line of sight judgment and reconnaissance rules, and designs a line of sight judgment algorithm based on a grid map. The algorithm dynamically adjusts the reconnaissance distance and detection probability according to factors such as terrain, weather, and time, so that the line of sight judgment in the deduction process is closer to the actual battlefield situation. The algorithm takes into account the influence of the following factors: the influence of obstacles such as mountains, forests, and buildings on the line of sight, and calculates the degree of obstruction of the line of sight according to the shape, height, and position of the obstacles. The algorithm takes into account the influence of weather factors such as rain, snow, fog, and other weather conditions on line of sight propagation. Under severe weather conditions, the reconnaissance distance will be shortened and the probability of detection will also be reduced. Time factors such as sunrise and sunset, moonrise and moonset time affect lighting conditions. At night or under low light conditions, the difficulty of reconnaissance will increase, and the line of sight judgment will be more stringent. The algorithm of the present invention dynamically adjusts parameters such as reconnaissance distance and detection probability according to the above factors to ensure that the line of sight judgment in the deduction process is more accurate and reasonable. This dynamic adjustment not only improves the simulation degree of the deduction, but also provides decision makers with a deduction experience that is closer to 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 more reliable intelligence support for decision makers. BRIEF DESCRIPTION OF THE DRAWINGS

[0126] Figure 1 It is a flowchart of electronic war game deduction based on remote sensing battlefield environment of the present invention;

[0127] Figure 2 It is a schematic diagram of the topological structure of the data processing module;

[0128] Figure 3 It is a schematic diagram of the processing geometry of the sensitive area shield and the sensitive area process;

[0129] Figure 4 This is a diagram of the process of data from the system API being processed by the attribute field extractor. Figure 1 ;

[0130] Figure 5 This is a diagram of the process of data from the system API being processed by the attribute field extractor. Figure 2 ;

[0131] Figure 6 It is a schematic diagram of the process of drawing a map;

[0132] Figure 7 is a grid coordinate number map;

[0133] Figure 8 This is a diagram to calculate the coordinates of the center point of the hexagon Figure 1 ;

[0134] Fig. 9 This is a diagram to calculate the coordinates of the center point of the hexagon Figure 2 ;

[0135] Fig.10 Calculate the coordinates of the center point of the hexagon Figure 3 ;

[0136] Fig.11 This is a diagram to calculate the coordinates of the center point of the hexagon Figure 4 ;

[0137] Fig.12 Calculate the coordinates of the center point of the hexagon Figure 1 ;

[0138] Fig.13 This is a schematic diagram of the coordinates of the six vertices of the calculation grid;

[0139] Fig.14 It is a schematic diagram of the network annotation process;

[0140] Fig.15 It is a schematic diagram of the visual judgment process;

[0141] Fig.16 This is a schematic diagram of the visual identification process in Example 1. DETAILED DESCRIPTION

[0142] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. In addition, the forms of the various structures recorded in the following embodiments are merely illustrative, and the present invention is not limited to the various structures recorded in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0143] First, the terms used in the present invention are explained. Board: In traditional war games, the board represents the battlefield and is the physical or virtual space for game activities. It is usually presented as a map with a specific scale, with terrain, important landmarks, roads and other strategic points marked on it. In a computerized war game system, the "board" is a virtual environment generated by software, which can simulate a wider and more complex battlefield environment, including different dimensions such as ground, sea and air.

[0144] Operators: Operators represent action units in the game, such as troops, equipment, and commanders. In traditional board games, operators may be physical pieces or tokens, each representing a specific military force or equipment. In computer game systems, operators are entities in the data model, which represent different military units and have their own attributes and capabilities, such as firepower, defense, movement speed, etc.

[0145] Rules: Rules define the operation mechanism of the game, including the order of actions, combat determination, movement restrictions, winning and losing conditions, etc. The rules ensure the logic and fairness of the game and simulate the strategic and tactical decision-making in a real war environment. In a computerized system, the rules are implemented through algorithms, which can simulate complex interactions and events, including weather changes, logistical support, morale effects and other factors.

[0146] The war game system uses these three basic components to work together to create a close-to-real war simulation environment, in which participants can make strategic arrangements, execute tactical actions, and observe combat results, thereby exercising decision-making capabilities, testing tactical plans, and conducting military training or scientific research.

[0147] Reference Figure 1-Figure 15 The present invention provides an electronic war game simulation system based on remote sensing battlefield environment, which includes:

[0148] A data access module, which downloads and imports remote sensing map data, including but not limited to geographic information including terrain, roads and rivers;

[0149] 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;

[0150] Map generation module, the map generation module generates a war game map based on the processed remote sensing data, including cutting the map into regular hexagonal grids of uniform size, calculating the center point coordinates and vertex coordinates of each grid, and numbering and attribute labeling each grid;

[0151] The simulation module simulates military operations, strategic decisions and tactical deployments based on the generated war game map, dynamically adjusts the reconnaissance distance and detection probability according to the environmental factors within the grid, and realizes war game simulation.

[0152] 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.

[0153] Suppose the hexagonal grid in the chessboard is set to 72 pixels high and 80 pixels wide.

[0154] There are three levels of maps involved in war game simulations: provincial maps, city maps, and action maps.

[0155] 1) Provincial level Figure 1 Each grid represents 10 kilometers;

[0156] 2) City level Figure 1 Each grid represents 1 kilometer;

[0157] 3) Action location Figure 1 Each grid represents 10 meters;

[0158] 10 km (10,000 m) corresponds to 70 pixels;

[0159] Distance represented by each pixel: 10,000 meters / 72 = 139 meters / pixel;

[0160] Recommended zoom level: About level 10 or 11, at which the map shows an overview of a city or town.

[0161] 1 kilometer (1,000 meters) corresponds to 70 pixels;

[0162] Distance represented by each pixel: 1,000 meters / 80 = 13.9 meters / pixel;

[0163] Recommended zoom level: About level 14 or 15, at which the map shows streets and some large buildings.

[0164] 10 meters corresponds to 70 pixels;

[0165] The distance represented by each pixel: 10 meters / 70 = 0.139 meters / pixel;

[0166] Recommended zoom level: Around level 18 to 19, at which the map can show details down to the level of individual buildings and trees.

[0167] Select a map area:

[0168] You can use the map picker to select a rectangular area on the remote sensing map and choose the collection time period;

[0169] 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.

[0170] The selected collection time period will be affected by factors such as topography, weather, sunrise and sunset, etc.

[0171] There are two ways to download remote sensing data: manual data acquisition and automatic access.

[0172] 1) Manually obtain data:

[0173] 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.

[0174] Here are some commonly used remote sensing data websites:

[0175] China Remote Sensing Data Sharing Network: The data website with the longest archive period in China, which shares Landsat data for free and can also order foreign commercial satellite data. After registering an account and passing the review, users can directly download the required data.

[0176] China Resources Satellite Application Center: One of the three major satellite application centers in my country, it collects domestic satellite data. After registration, users can download HJ satellite data, and high-resolution data downloads require review.

[0177] Geospatial Data Cloud: Data resources are updated relatively stably, including Landsat series, China-Pakistan resource satellites, various MODIS data products, DEM digital elevation data, EO-1 data, NOAAA VHRR data products, Sentinel data, etc. After registration and passing the review, users can download the required data.

[0178] Global Change Science Research Data Publishing System: The data types are very rich and cover many fields. Users can search for data according to their needs. After registering an account, you can directly download the required data.

[0179] 2)Automated access:

[0180] According to the three conditions for searching remote sensing data in the previous step, some commercial remote sensing data interfaces (such as the open data service of Costenda) are called to directly download files or data in the corresponding format to provide more accurate data. The processing of remote sensing data supports some common file formats such as GeoJSON, Shapefile and other format data.

[0181] 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.

[0182] Remote sensing data reader;

[0183] The remote sensing data reader parses the received remote sensing data into unified structured data.

[0184] The accessed remote sensing data can be read using the GeoTools library;

[0185] Key features of GeoTools include:

[0186] Map data processing: It supports multiple map data formats such as Shapefile, GeoJSON, etc., allowing developers to easily process geospatial data in different formats.

[0187] 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 meet different geographic data needs.

[0188] Spatial Analysis: GeoTools provides a wealth of spatial analysis functions, including buffer analysis, spatial query, spatial overlay analysis, etc., which help users process and analyze geospatial data.

[0189] Users can also edit Excel to import the system. The Excel format is as follows;

[0190] The Excel file needs to contain two sheets:

[0191] 1) Geometry table;

[0192] Table 1 Coordinate set of map geometry

[0193]

[0194] Table 2 Field description of Table 1

[0195]

[0196]

[0197] 2) Properties table;

[0198] Table 3 is used to save the attributes corresponding to each geometric figure on the map, which is generally data generated by manual annotation or remote sensing recognition;

[0199] Table 3 Attributes corresponding to each geometric figure on the graph

[0200] 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

[0201] Table 4 Field description of Table 3

[0202] Field Name Field Description geometryId Geometry ID Name Property name Value Property Value

[0203] The geometryId in the Geometry table is associated with the geometryId in the Properties table.

[0204] Coordinate system converter:

[0205] WGS84 is an international latitude and longitude standard. It is the coordinate system of data retrieved from GPS devices and is also a coordinate system commonly used by international map providers (such as Google Maps overseas, osm, mapbox). GCJ-02 is a Chinese standard used for coordinate data obtained by positioning in domestic mobile devices. The state stipulates that various map systems published in China (including electronic forms) must use at least GCJ-02 for the first encryption of geographic location. Baidu Coordinate System (BD-09) is a Baidu standard used in Baidu SDK, Baidu Maps, Baidu GeoCoding, etc.

[0206] There may be significant deviations between different coordinate systems for marking the same location, which may lead to accumulated errors on the map. In order 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.

[0207] GeoJSON uses the WGS 84 coordinate system by default, which is a global geographic coordinate system in longitude and latitude. Longitude ranges from -180 to 180 degrees, and latitude ranges from -90 to 90 degrees.

[0208] The coordinate system converter is responsible for converting all the latitude and longitude coordinates in the imported remote sensing data into a coordinate system: WGS 84 coordinate system.

[0209] The coordinate system converter reads each longitude and latitude coordinate in the Geometry table, and performs the following coordinate system conversions through 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.

[0210] Sensitive area jammer:

[0211] The sensitive area blocker is responsible for removing preset sensitive areas from the map to avoid security information leakage.

[0212] 1) It is necessary to circle some sensitive areas on the map and save the sensitive areas to the sensitive area coordinate library.

[0213] 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 region masker sets the corresponding geometry to the coordinate set of the new region.

[0214] Attribute Field Extractor:

[0215] The attribute field extractor is used to filter and extract various complex annotations contained in the attributes of various remote sensing data sources read by the remote sensing data reader, and flexibly extract the required attributes therefrom.

[0216] 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.

[0217] Table 5 Field Mapping Library

[0218]

[0219] 1) The attribute field extractor will find the corresponding system attribute name list from the field mapping library according to the data source;

[0220] 2) Extract the data from the attribute data according to its system attribute name list;

[0221] 3) Then replace the corresponding system property name with this system property name.

[0222] In a preferred embodiment, the data of the system API is processed by the attribute field extractor as follows Figure 4 shown.

[0223] Attribute Value Cleaner:

[0224] The attribute value cleaner cleans the data extracted by the attribute field extractor to obtain usable attribute values.

[0225] 1) Use standard data types:

[0226] Make sure the property uses the correct data type, such as string, number, boolean, etc.

[0227] Avoid mixing up strings and numbers, or using complex data structures where they are not necessary.

[0228] 2) Handling null values ​​and missing data:

[0229] If an attribute does not 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.

[0230] Unifying attribute value units is to unify the units of numerical type data after the attribute value cleaner has cleaned it.

[0231] 1) Length unit conversion:

[0232] Substitute the length unit of the data source system into the conversion formula of the numerical unit conversion library.

[0233] For example, if the length unit of a system is inches, it needs to be converted using the following formula;

[0234] Length = y inches x 0.0254 m / inch.

[0235] 2) Time zone conversion:

[0236] 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.

[0237] Property Value Converter:

[0238] The attribute value converter is used to convert the cleaned attribute values ​​into values ​​that can be used in the game.

[0239] 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.

[0240] Table 6 Mapping relationship between attribute values ​​of each data source and attribute values ​​of this system

[0241]

[0242]

[0243] 1) The attribute value converter will find the corresponding attribute name list of this system from the terrain and geomorphology 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 geomorphology 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 geomorphology values ​​in the city map generally include: flat land, mountainous land, 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, pedestrian paths, information desks / ticket 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, pedestrian paths, information desks / ticket offices, entrances and exits, stairs, elevators, vents, railways, indoor areas, fences, walls, fast VIP channels, security checkpoints.

[0244] 2) Query the data in the attribute data according to the attribute name list of this system;

[0245] 3) Then replace the corresponding system attribute value with this system attribute value.

[0246] In a specific implementation case, the data of the system API is processed by the attribute field extractor as follows: Figure 5 shown.

[0247] Generate remote sensing map database;

[0248] After being processed by the attribute value converter, the standardized GeoJSON data is obtained. At this time, the data can be stored in the database for later query in the war game.

[0249] It mainly contains two tables;

[0250] 1) Geometry table;

[0251] Table 7 Coordinate set of map geometry

[0252]

[0253] Table 8 Field description of Table 7

[0254]

[0255]

[0256] 2) Properties table;

[0257] 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;

[0258] Table 9 Attributes corresponding to each geometric figure on the map

[0259] 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

[0260] Table 10 Field description of Table 9

[0261]

[0262]

[0263] The geometryId in the Geometry table is associated with the geometryId in the Properties table.

[0264] The process of drawing a map is as follows:

[0265] 1) Read the remote sensing map database generated by processing remote sensing data, obtain all geometric figures, set the contour line color and place name font style, and output the contour layer;

[0266] 2) Filter the terrain attributes in the attributes of all geometric figures according to the names in the terrain standard library to obtain the terrain geometry, query the texture in the map texture library according to the terrain name, set different textures for each geometric figure, and output the terrain layer;

[0267] 3) Filter the elevation attributes in the attributes of all geometric figures to obtain elevation geometric figures, set different elevation background colors according to different elevation ranges, and output the contour layer;

[0268] 4) Filter the river and road attributes in the attributes of all geometric figures according to the names in the terrain and landform standard library to obtain the river and road geometries, query the texture from the map texture library according to the river and road types, set different textures for each geometric figure, and output the river and road layer;

[0269] 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, query the texture in the map texture library according to the covering type, set different textures for each geometric figure, and output the covering layer;

[0270] 6) All layers are summarized in sequence to the plotter (stream renderer in the GeoTools library), and the plotter merges each layer in sequence and outputs it into a map.

[0271] Meshing process:

[0272] After the map is gridded, the objective rules can be simplified. 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 moving distance, stacking space, weather, altitude, etc.).

[0273] The grid coordinate numbering rules are as follows:

[0274] If the map is cut into a maximum of 99x99 grids, the encoding rules are:

[0275] 1) The first two digits represent the horizontal column number n, and any missing digits are supplemented with 0;

[0276] 2) The last two digits represent the vertical row number m, and any missing digits are supplemented with 0;

[0277] If the map is cut into a maximum of 999x999 grids, the encoding rules are:

[0278] 3) The first three digits represent the horizontal column number n, and any missing digits are supplemented with 0;

[0279] 4) The last three digits represent the vertical row number m, and any missing digits are supplemented with 0;

[0280] When it is 9999x9999, the same applies. Figure 7 shown.

[0281] Calculate the coordinates of the center point of the hexagon:

[0282] like Figure 8 , Fig. 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.

[0283] 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.

[0284] When n is an odd number, removing the even number column will result in n r's, one for each even number; we get:

[0285]

[0286] The calculation formula for y is:

[0287]

[0288] like Fig.10 , Fig.11 , Fig.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;

[0289]

[0290] As shown in the figure below, the calculation formula for y is obtained:

[0291]

[0292] Calculate the coordinate formulas of the six vertices, such as Fig.13 As shown, assuming that 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;

[0293] Formula to calculate width using height:

[0294]

[0295] Formula for calculating radius using height:

[0296]

[0297]

[0298] 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.

[0299] 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:

[0300] p1=[xr,y];

[0301]

[0302] p4=[x+r,y];

[0303]

[0304] The grid annotation process is as follows:

[0305] 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 grid.

[0306] 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:

[0307] Assuming that 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 coordinate [a, b] can be calculated using the following formula. The brackets in the formula indicate rounding.

[0308]

[0309] when When it is an even number, it indicates an even number of columns;

[0310]

[0311] otherwise;

[0312]

[0313] 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, if you encounter a numerical type, you need to merge it according to actual needs, such as taking the maximum value for elevation and the maximum value for water depth, such as Fig.14 shown.

[0314] The application process of environmental factors in remote sensing data in war game rules:

[0315] Table 11 Terrain status visibility determination table (the data in the table are simulation data designed by the present invention based on practical experience)

[0316]

[0317] 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.

[0318] Table 12 Weather day and night visibility determination table (the data in the table are simulated data designed by the present invention based on practical experience)

[0319]

[0320]

[0321] Visual judgment process:

[0322] A straight line between the operator and the target is the line of sight. If the line of sight is not blocked by high ground, cities, towns, or forest grids, it is clear line of sight.

[0323] If the line of sight is only blocked by high ground, determine whether the high ground is higher than the height of the reconnaissance operator and the target point. If so, there is no line of sight. If the height of the high ground is between the two points, the line of sight determination table can be used to make a judgment. 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.

[0324] The steps are:

[0325] Mark the reconnaissance points, obstacles, and target points in the table according to the terrain they are located in and the number of grids they are far from each other.

[0326] Connect the scout point and the target point with a straight line.

[0327] If the obstacle is above the straight line, the line of sight is blocked; otherwise, the line of sight is clear.

[0328] The implementation logic process is as follows:

[0329] 1) Find the terrain from the grid map database according to the hexagonal grid number where the operator is located;

[0330] 2) Check the weather in the grid;

[0331] 3) If it is night time, find out the current brightness of the moon;

[0332] 4) Find the number of hexagonal grids from the terrain visibility determination table or the weather day and night visibility determination table and convert it into the visible distance;

[0333] 5) Calculate the distance between the operator and the target:

[0334]

[0335] 6) Determine whether it is within the field of vision;

[0336] 7) Find all the obstruction hexagonal grids between the current operator and the target operator;

[0337] a. Find the grid within a rectangular range that is diagonally opposite to the operator and the target operator, see Fig.15 ① in the;

[0338] b. Draw a straight line with a thickness of 2r between the operator and the target operator. Fig.15 ② in the;

[0339] 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. Fig.15 ③ in the;

[0340] 8) Substitute the operator, all obstacle hexagons, and the target operator into the formula to calculate whether it is blocked. If it is blocked, it is invisible;

[0341] In this algorithm, unobstructed sight lines exist only if:

[0342]

[0343] Where H is the difference in elevation (in meters) between the elevation of the higher operator and the elevation of the lower operator.

[0344] D: The distance from the higher operator position to the lower operator position (in meters).

[0345] h: The height of the possible obstruction minus the height of the lowest operator (in meters).

[0346] d: The distance from the location of the possible obstacle to the lower position counter (measured in meters).

[0347] 1.5: The default is the height of the person or vehicle (in meters).

[0348] Note: Each contour line represents a vertical elevation of 20 meters, and the horizontal distance of the hexagonal grid is 10 meters (mobile map) and 1000 meters (city map). All buildings and trees are assumed to have a vertical elevation of 20 meters if they are not marked, and are considered obstacles.

[0349] Embodiment 1, as Fig.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.

[0350]

[0351] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification, replacement and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An electronic war game simulation system based on remote sensing battlefield environment, characterized in that: It includes: A data access module, which downloads and imports remote sensing map data, including but 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; Map generation module, the map generation module generates a war game map based on the processed remote sensing data, including cutting the map into regular hexagonal grids of uniform size, calculating the center point coordinates and vertex coordinates of each grid, and numbering and attribute labeling each grid; The simulation module simulates military operations, strategic decisions and tactical deployments based on the generated war game map, dynamically adjusts the reconnaissance distance and detection probability according to the environmental factors within the grid, and realizes war game simulation.

2. The electronic war game simulation system based on remote sensing battlefield environment according to claim 1 is characterized in that: The map levels selected in the data access module include provincial maps, municipal maps and action maps, which represent battlefield environments of different scales. In the simulation 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 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 performing 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 according to 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 in remote sensing data to war game rules: Read environmental factors in remote sensing data, dynamically adjust reconnaissance distance and detection probability, and apply relevant rules to war game simulations.

6. The method according to claim 5, characterized in that The specific process of step S1 includes: S11. Select the map level. Choose provincial map, city map or action map according to the needs of war game simulation. Each map has different grid sizes, which reflects different levels of geographical details. Each grid of the provincial map represents 10 kilometers, which is suitable for simulating large-scale strategic layouts; each grid of the city map represents 1 kilometer, which is suitable for simulating tactical operations at the city or town level; each grid of the action map represents 10 meters, which is suitable for simulating details accurate to the level of buildings and trees; after selecting the map level, further set the ratio of pixels to actual distance according to the selected level, and recommend the appropriate map zoom level; S12. Selecting a map area: using a map picker, select a rectangular area on the remote sensing map as a simulation battlefield, ensuring that the simulation area matches the actual geographical environment; S13. Select the collection time period: Select an appropriate collection time period according to the specific needs of the simulation; the selection of the time period will affect the simulation of topography, weather, 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: using a remote sensing data reader to parse the received remote sensing data into unified structured data; S22. Coordinate system conversion: convert the coordinate system of remote sensing data from different sources using different geographic coordinate systems into a unified coordinate system WGS84; S23. Sensitive area shielding: remove preset sensitive areas from the map; circle the coordinates of sensitive areas through the sensitive area shielding device, and exclude these areas during the map generation process; S24, attribute field extraction and cleaning: Extract fields useful for wargaming from a large amount of annotation information contained in remote sensing data; extract required attributes from remote sensing data through attribute field extractor according to pre-established field mapping relationships; clean the extracted attribute values ​​to ensure the correct data type, handle null values ​​and missing data, and make the data available for subsequent processing; S25. Unify attribute value units: unify the units of attribute values ​​of data from different sources using different units, and convert all attribute values ​​into 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 that can be used by the war game simulation system; use the attribute value converter to map the attribute values ​​of the external system into the standard attribute values ​​of the war game system according to the terrain and landform standard library and the weather standard library; 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 the corresponding attribute information.

8. The method according to claim 6, characterized in that In step S3, the specific process includes: S31, reading 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 the geometric shape, terrain, elevation, rivers, roads and coverings of the map; S32, setting contour lines: reading geometric data in 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 contour; S33, terrain texture processing: read the terrain attributes of each geometric figure from the terrain and landform standard library, and search for the corresponding texture image in the map texture library according to the terrain name; apply the found texture to each geometric figure to form a map area with different terrain features; S34. Set the elevation background color: read the elevation attribute of each geometric figure from the database; set different background colors according to the elevation range to distinguish different elevation areas; S35. River road drawing: including: S351, filtering geometric figures: filtering geometric figures representing rivers and roads from the database; S352, texture application: according to the types of rivers and roads, search and apply 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, filtering geometric figures: filtering geometric figures representing covering objects from a database; S362, texture application: according to the type of covering object, search and apply the corresponding texture in the map texture library; S363, drawing the overlay: applying the texture to the geometric shape of the overlay and drawing 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 of sequence 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 calculation of operator movement; S42. Grid numbering rule: Formulate a numbering rule 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, it is 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 basic height of the regular hexagon be h, the width be w, and the radius be r; For the hexagonal grid in 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 by the following formula: When n is an even number, the center point coordinates [x, y] are calculated as follows: S432. The vertex coordinate calculation formula of the 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 the radius r using the height h is: S44, grid attribute labeling: labeling 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, calculating the grid to which the coordinates belong: for each coordinate point, using a specific formula to calculate the hexagonal grid number to which it belongs; S443, merging grid attributes: searching for corresponding grid attributes in the grid database according to 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 indicates an even number of columns; otherwise, The corresponding hexagonal grid is calculated, the hexagonal grid number is found, the hexagonal grid attribute is found from the grid map database through the hexagonal grid number, and the coordinate attribute and the hexagonal grid attribute are merged as the new hexagonal grid attribute.

10. The method according to claim 5, characterized in that In step S5, the specific process includes: S51. Reading environmental factors in remote sensing data: reading and analyzing various environmental factors contained in remote sensing data, including but not limited to: Weather conditions, including clear, snow, rain, mist, 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; elevation data; S52. Extract and integrate environmental factors into the war game rule base: Integrate the environmental factors in the remote sensing data with the rule base of the war game system; the rule base defines the various mechanisms and logics in the game process, including action sequence, combat judgment, movement restrictions, and victory and defeat conditions; dynamically adjust these rules according to the actual environmental factors in the remote sensing data; S53, applying relevant rules according to rounds and geographical locations: according to the current round number and operator, that is, the action unit in the deduction, and the geographical location, read the corresponding environmental factors from the remote sensing map database and apply the corresponding rules; the specific process includes: S531. Determination of the number of rounds: There will be multiple rounds in the deduction process, and each round represents a certain time span; S532, selection of collection time: according to 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, sunrise and sunset; S533, determination of geographical location: the specific location of the operator on the deduction map determines which environmental factors affect it; the geographical location of the operator can be determined through the remote sensing map database; S534, reading environmental factors: reading environmental factors related to the current round number and geographical location from the remote sensing map database; these factors include weather conditions, terrain features, lighting conditions, etc.; S535, apply environmental factor rules: apply corresponding rules according to the read environmental factors; 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 shielding will affect reconnaissance and communication; if the operator is close to a river, the time and resources for crossing the river need to be considered; S536. Specific application of the rules: Determine the observation distance and detection probability under different terrain and weather conditions according to the Terrain Status Visibility Decision Table and the Weather Day and Night Visibility Decision 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, analyzing the operator position and current round: real-time tracking of the geographical location and current round number of each operator; the position of the operator determines which environmental factors affect it, and the round number helps the system determine the current time background, thereby adjusting the corresponding environmental factors; S543, Dynamically adjust parameters: Based on the environmental factors read, the system dynamically adjusts various key parameters in the deduction process: dynamically adjusts the reconnaissance distance based on the terrain, weather conditions and current time where the reconnaissance operator and the target operator are located; dynamically adjusts the observation probability based on environmental factors and the state of the target unit; terrain characteristics and weather conditions directly affect the movement speed of the unit, and the movement speed is dynamically adjusted based on the current terrain and weather conditions; S55, perform line of sight judgment 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 according to terrain elevation data, obstacle positions and environmental factors; the specific implementation process includes: connecting a straight line between the operator and the target, that is, the line of sight. If the line of sight is not blocked, it is line of sight; if the line of sight is only blocked by high ground, determine whether the high ground is higher than the height of the two points of the reconnaissance unit and the target; if so, there is no line of sight; if the height of the high ground is between the two points, mark the reconnaissance point, the obstacle, and the target point according to the terrain and the number of grids of the mutual distance, and connect the reconnaissance point and the target point with a straight line; if the obstacle is above the straight line, there is no line of sight; otherwise, there is line of sight; 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 of the grid; S553, if it is night time, find out the current brightness of the moon; S554. Find the number of hexagonal grids from the terrain status visibility determination table or the weather day and night visibility determination table, and convert it into the visible 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 obstacle hexagonal grids between the current operator and the target operator straight line; S558, the operator, all the obstruction hexagonal grids, and the target operator are substituted 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 lies in: in: H: The difference between the elevation of the operator at a high position and the elevation of the operator at a low position; D: The distance from the high operator position to the low operator position; h: the height of the possible obstacle minus the height of the low position operator; d: The distance from the position of the possible obstacle to the lower operator.

Images