Radar simulation model target intervisibility calculation method and system based on terrain shielding table

Abstract

The invention provides a radar simulation model target intervisibility calculation method and system based on a terrain shielding table, and the method comprises the steps: collecting and calculating elevation data based on the elevation data in a TIF format, carrying out the arrangement management through employing a tile pyramid model, and carrying out the hierarchical management of the elevation data. Before simulation operation, terrain shielding tables are generated in batches according to radar deployment positions and basic performance parameters. In the simulation operation process, the radar model calculates the oblique distance, azimuth angle and pitch angle parameters of the target in the effective detection range, all shielding points of the terrain shielding table are traversed until the shielding point closest to the target point is found, and the target pitch angle is compared with the shielding angle of the shielding point to determine the target pitch angle. And calculating an intervisibility result of the radar model and the target. According to the method, an algorithm which considers the influence of a terrain shielding factor on a radar detection result is improved, the accuracy of intervisibility calculation of an aerial target in an effective detection range by the model is greatly improved, and the confidence coefficient of a simulation result is ensured.

Description

Technical Field

[0001] This invention relates to the technical field of cross-application of geographic information and system simulation, specifically to a method and system for calculating target visibility in radar simulation models based on terrain masking tables. Background Technology

[0002] With the rapid development of satellite telemetry and computer simulation technologies, geographic information services provide users with a wealth of geographic information services, such as real-time positioning, path planning, and terrain masking, by establishing a multi-scale, multi-resolution, and multi-type regional geospatial data framework and geospatial information resource sharing system. These services are widely used in military combat simulation, telemetry antenna visibility analysis, military radar masking calculation, and calculation of the impact of terrain masking on solar radiation.

[0003] Regarding geographic information service platforms, Google Maps is one of the world's most well-known. It not only provides global map data, navigation, geographic search, and location ratings, but also offers powerful geographic information services through large-scale geographic data collection and high-performance map rendering technology. Furthermore, Google Maps provides global 3D map browsing and exploration capabilities through tools like Google Earth. In China, Gaode Maps is a leading geographic information service platform. It provides nationwide map data, map browsing, navigation, location search, and public transportation queries. Through big data analysis and real-time traffic information, it provides users with accurate navigation and traffic updates, meeting diverse user needs for geographic information. In addition, these platforms offer developers a wealth of tools and interfaces, promoting innovation and application of geographic information services.

[0004] A patent document with publication number CN119903683A discloses a method, apparatus, device, and medium for calculating visibility based on a digital elevation model. The method includes: acquiring the geographic coordinates of an observation point and a target point; converting the geographic coordinates into observation grid points and target grid points based on the digital elevation model; acquiring the elevation values ​​of the observation grid points; calculating the minimum visible height value of each grid point in the digital elevation model based on the coordinate values ​​and elevation values ​​of the observation grid points; using the set of minimum visible height values ​​corresponding to all grid points as minimum visible height data; acquiring the minimum visible height value corresponding to the target grid point from the minimum visible height data based on the coordinate values ​​of the target grid point; determining whether the elevation value of the observation grid point is greater than or equal to the minimum visible height value of the target grid point; if so, visibility is established between the target point and the observation point. Existing technologies have studied the problem of calculating terrain shading blind zones under the influence of Earth's curvature, improving the accuracy of calculation results caused by the influence of Earth's curvature during terrain shading calculation. By thinning and indexing elevation line data on digital topographic maps, elevation lines meeting the angle calculation conditions are selected, enabling rapid calculation of shading angles in various directions. GPU computing is used to calculate the detection power of radar networks, achieving 15.4 times faster performance than CPU algorithms and yielding better computational results. A fast algorithm based on dialing reptile objects analyzes the calculation model under the influence of terrain shading blind zones and Earth's curvature, improving the efficiency of terrain shading calculation.

[0005] In increasingly complex battlefield environments, in addition to the detection performance of the radar equipment itself, the complex terrain environment near the radar deployment location also directly affects the radar model's line-of-sight calculation results for aerial targets. Therefore, how to improve the accuracy and confidence of the radar sensor model's line-of-sight calculation results for aerial targets while meeting simulation efficiency is an urgent problem to be solved, and there is also the issue of whether the radar model calculates line-of-sight for targets within the effective detection range during simulation.

[0006] Therefore, a new technical solution is needed to address the aforementioned technical problems. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the purpose of this invention is to provide a method and system for calculating target line-of-sight in radar simulation models based on terrain masking tables.

[0008] According to the present invention, a method for calculating the line-of-sight of a target in a radar simulation model based on a terrain masking table is provided, the method comprising the following steps:

[0009] Step S1: Obtain the longitude and latitude of the deployment locations of all radar models participating in the simulation, and obtain the altitude of each deployment location based on the pre-loaded elevation data in the database;

[0010] Step S2: Obtain the basic performance parameters of all radars participating in the simulation. The basic performance parameters include radar height H. r Radar antenna azimuth pointing to A r Calculate the radar azimuth coverage α, and calculate the minimum and maximum detection ranges of all radars respectively;

[0011] Step S3: Based on factors such as solution accuracy, computational efficiency, network latency, number of threads, and computer performance, obtain the terrain masking table generation parameters, which include axial resolution and radial resolution, and generate a radar parameter information index table.

[0012] Step S4: The radar model sends a request to the geographic information server to generate a terrain masking table via the network. The geographic information server extracts the valid information stored in the radar information index table, generates a terrain masking table for all radar effective detection ranges according to a fixed format, and downloads it to the local machine.

[0013] Step S5: During the simulation, calculate the target t relative to the radar R when it enters the radar detection range. i The deployment location's azimuth, elevation, and slant range parameters are calculated. The target's slant range and azimuth are matched with a terrain masking table to obtain the nearest masking point. The target's elevation angle is compared with the masking angle of the masking point to obtain the line-of-sight calculation result. For all aerial targets t1, t2, t3, ..., t within the radar R's detection range... n Repeat step S5 until there are no targets within the effective detection range of the radar;

[0014] For all radar models R1, R2, ..., R n Repeat step S5 until all radar models involved in the simulation have been traversed, at which point the simulation ends.

[0015] Preferably, step S1 involves acquiring Earth surface elevation data collected by remote sensing satellites. This elevation data is stored in TIF format and managed hierarchically based on a tile pyramid model. The elevation data includes multi-level digital elevation model (DEM) data downloaded from the Google Earth platform, stored according to preset levels, row numbers, and column numbers. The elevation data is hierarchically organized using the tile pyramid model to achieve hierarchical scheduling and rapid retrieval. Based on the latitude and longitude coordinates of the radar deployment location, the elevation value H corresponding to the location is extracted from the elevation data. r The altitude at which the radar is deployed.

[0016] Preferably, the radar mounting height H in step S2 is... r Radar antenna azimuth pointing to A rThe radar azimuth coverage range α is an inherent parameter of the radar model; under interference-free conditions, the maximum detection slant range of the radar model for a typical RCS target at a specified altitude is calculated according to the radar equation.

[0017] Preferably, step S3 involves traversing all radar models R1, R2, ..., R3 participating in the simulation using the simulation system. n Obtain the following parameter information for each radar model: radar identifier ID; deployment location coordinates (Lon, Lat); radar elevation H. r Detection range [R] min R max Antenna azimuth pointing to A r ; Azimuth coverage α; Axial resolution θ, satisfying 0 < θ ≤ α; Radial resolution r, satisfying 0 < r ≤ R max A radar information index table is generated based on the parameter information, and the index table is transmitted to a geographic information server via the network as input parameters for generating a terrain masking table.

[0018] Preferably, in step S4, after the geographic information server receives the terrain masking table generation request sent by the simulation system, it calls the locally stored elevation data, which is the Earth surface elevation data collected by the remote sensing satellite in step S1; based on the elevation data, it generates terrain masking table files corresponding to each radar simulation model in batches, and the terrain masking table files contain the following parameter groups: radial distance, azimuth angle, elevation value, and masking angle; the generated terrain masking table files are stored in a preset directory path; and the simulation system calls the terrain masking table files to perform radar model calculations during runtime.

[0019] Preferably, in step S5, when target t1 enters the effective detection range of radar R1, the elevation angle E of target t1 relative to the deployment position of radar R1 is calculated in the Cartesian coordinate system established in step S4. t1 ; Traverse all terrain-shading points P ij Determine the occlusion point P that is closest to the target t1 coordinate point. t Retrieve the shading point P from the terrain shading table file. t Corresponding terrain shielding angle A t1 Compare the pitch angle E. t1 With the shading angle A t1 : when E t1 >A t1 When, it is determined that there is a line-of-sight condition between radar R1 and target t1; when E t1 ≤A t1 At that time, it is determined that there is no line-of-sight between radar R1 and target t1.

[0020] The present invention also provides a target line-of-sight calculation system for radar simulation models based on terrain masking tables, the system comprising the following modules:

[0021] Module M1: Obtains the longitude and latitude of the deployment locations of all radar models participating in the simulation, and obtains the altitude of each deployment location based on the pre-loaded elevation data in the database;

[0022] Module M2: Obtains the basic performance parameters of all radars participating in the simulation, including radar height H. r Radar antenna azimuth pointing to A r Calculate the radar azimuth coverage α, and calculate the minimum and maximum detection ranges of all radars respectively;

[0023] Module M3: Based on factors such as solution accuracy, computational efficiency, network latency, number of threads, and computer performance, it obtains the terrain masking table generation parameters, including axial resolution and radial resolution, and generates a radar parameter information index table.

[0024] Module M4: The radar model sends a request to the geographic information server to generate a terrain masking table via the network. The geographic information server extracts the valid information stored in the radar information index table, generates a terrain masking table for all radar effective detection ranges according to a fixed format, and downloads it to the local machine.

[0025] Module M5: During simulation, it calculates the target t entering the radar detection range relative to the radar R. i The deployment location's azimuth, elevation, and slant range parameters are calculated. The target's slant range and azimuth are matched with a terrain masking table to obtain the nearest masking point. The target's elevation angle is compared with the masking angle of the masking point to obtain the line-of-sight calculation result. For all aerial targets t1, t2, t3, ..., t within the radar R's detection range... n Repeatedly call module M5 until there are no targets within the radar's effective detection range;

[0026] For all radar models R1, R2, ..., R n Repeatedly call module M5 until all radar models involved in the simulation have been traversed, and the simulation ends.

[0027] Preferably, module M1 acquires Earth surface elevation data collected by remote sensing satellites. This elevation data is stored in TIF format and managed hierarchically based on a tile pyramid model. The elevation data includes multi-level digital elevation model (DEM) data downloaded from the Google Earth platform, stored according to preset levels, row numbers, and column numbers. The elevation data is hierarchically organized using the tile pyramid model, enabling hierarchical scheduling and rapid retrieval. Based on the latitude and longitude coordinates of the radar deployment location, the elevation value H corresponding to the location is extracted from the elevation data.r The altitude of the radar deployment point;

[0028] The radar tower height H in module M2 r Radar antenna azimuth pointing to A r The radar azimuth coverage range α is an inherent parameter of the radar model; under interference-free conditions, the maximum detection slant range of the radar model for a typical RCS target at a specified altitude is calculated according to the radar equation.

[0029] Preferably, module M3 iterates through all radar models R1, R2, ..., R3 participating in the simulation using the simulation system. n Obtain the following parameter information for each radar model: radar identifier ID; deployment location coordinates (Lon, Lat); radar elevation H. r Detection range [R] min R max Antenna azimuth pointing to A r ; Azimuth coverage α; Axial resolution θ, satisfying 0 < θ ≤ α; Radial resolution r, satisfying 0 < r ≤ R max A radar information index table is generated based on the parameter information, and the index table is transmitted to a geographic information server via the network as input parameters for generating a terrain masking table.

[0030] After receiving the terrain masking table generation request sent by the simulation system, the geographic information server in module M4 calls the locally stored elevation data, which is the Earth's surface elevation data collected by the remote sensing satellite in module M1. Based on the elevation data, it generates terrain masking table files corresponding to each radar simulation model in batches. The terrain masking table file contains the following parameter groups: radial distance, azimuth angle, elevation value, and masking angle. The generated terrain masking table files are stored in a preset directory path for the simulation system to call for radar model calculation during runtime.

[0031] Preferably, in module M5, when target t1 enters the effective detection range of radar R1, the elevation angle E of target t1 relative to the deployment position of radar R1 is calculated in the Cartesian coordinate system established by module M4. t1 ; Traverse all terrain-shading points P ij Determine the occlusion point P that is closest to the target t1 coordinate point. t Retrieve the shading point P from the terrain shading table file. t Corresponding terrain shielding angle A t1 Compare the pitch angle E. t1 With the shading angle A t1 : when E t1 >A t1 When, it is determined that there is a line-of-sight condition between radar R1 and target t1; when Et1 ≤A t1 At that time, it is determined that there is no line-of-sight between radar R1 and target t1.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. This invention provides a reference for the altitude of radar deployment locations by calling high-precision elevation data, avoiding conflicts between radar deployment and terrain. While meeting simulation efficiency requirements, when the radar sensor model is deployed in a complex geographical environment, it can provide a reliable calculation method to determine whether targets entering its effective detection range are undetectable due to terrain obstruction, thus improving the accuracy and confidence of radar model simulation results.

[0034] 2. This invention improves upon the impact of terrain obstruction on radar detection results, greatly enhancing the accuracy of the radar model's line-of-sight calculation for aerial targets within the effective detection range and ensuring the confidence level of the simulation results. By preloading terrain and elevation data, it provides calculation services for all-around terrain obstruction data of radar deployment points and can generate radar terrain obstruction tables, providing backend support for the radar model to quickly calculate the visibility of aerial targets within the effective detection range.

[0035] 3. Before simulation, this invention can generate a terrain masking table by loading terrain elevation data of the area near the radar deployment location. During the simulation, it can provide a new approach for radar sensor models to calculate the visibility of air targets within their effective detection range. Attached Figure Description

[0036] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0037] Figure 1 This is a schematic representation of the radar information index of the present invention;

[0038] Figure 2 This invention generates a schematic diagram of the terrain shading point principle.

[0039] Figure 3 This is a partial representation of terrain masking in the present invention;

[0040] Figure 4 This is a schematic diagram illustrating the method for determining whether a target is obscured by terrain according to the present invention.

[0041] Figure 5 This is a flowchart illustrating the principle of the present invention. Detailed Implementation

[0042] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0043] Example 1:

[0044] Reference Figure 5 According to the present invention, a method for calculating the line-of-sight of a target in a radar simulation model based on a terrain masking table is provided, the method comprising the following steps:

[0045] Step S1: Obtain the longitude and latitude of all radar model deployment locations participating in the simulation, and obtain the altitude of each deployment location based on the pre-loaded elevation data in the database; acquire the Earth's surface elevation data collected by remote sensing satellites, which is stored in TIF format and hierarchically managed based on a tile pyramid model; the elevation data includes multi-level digital elevation model (DEM) data downloaded from the Google Earth platform, stored according to preset levels, row numbers, and column numbers; perform hierarchical organization of the elevation data through the tile pyramid model to achieve hierarchical scheduling and rapid retrieval of the data; extract the corresponding elevation value H from the elevation data based on the longitude and latitude coordinates of the radar deployment location. r The altitude at which the radar is deployed.

[0046] Step S2: Obtain the basic performance parameters of all radars participating in the simulation. The basic performance parameters include radar height H. r Radar antenna azimuth pointing to A r 1. Calculate the radar azimuth coverage α, and calculate the minimum and maximum detection ranges of all radars; 2. Calculate the radar elevation H. r Radar antenna azimuth pointing to A r The radar azimuth coverage range α is an inherent parameter of the radar model; under interference-free conditions, the maximum detection slant range of the radar model for a typical RCS target at a specified altitude is calculated according to the radar equation.

[0047] Step S3: Based on factors such as solution accuracy, computational efficiency, network latency, number of threads, and computer performance, obtain the terrain masking table generation parameters, including axial resolution and radial resolution, and generate a radar parameter information index table; traverse all radar models R1, R2, ..., R... participating in the simulation through the simulation system. n Obtain the following parameter information for each radar model: radar identifier ID; deployment location coordinates (Lon, Lat); radar elevation H. r Detection range [R] min Rmax Antenna azimuth pointing to A r ; Azimuth coverage α; Axial resolution θ, satisfying 0 < θ ≤ α; Radial resolution r, satisfying 0 < r ≤ R max A radar information index table is generated based on the parameter information, and the index table is transmitted to a geographic information server via the network as input parameters for generating a terrain masking table.

[0048] Step S4: The radar model sends a request to the geographic information server (GIS) to generate a terrain masking table via the network. The GIS extracts valid information from the radar information index table, generates terrain masking tables for all radar effective detection ranges according to a fixed format, and downloads them locally. After receiving the terrain masking table generation request from the simulation system, the GIS calls the locally stored elevation data, which is the Earth surface elevation data collected by the remote sensing satellite in step S1. Based on the elevation data, terrain masking table files corresponding to each radar simulation model are generated in batches. The terrain masking table files contain the following parameter groups: radial distance, azimuth angle, elevation value, and masking angle. The generated terrain masking table files are stored in a preset directory path for the simulation system to call for radar model calculation during runtime.

[0049] Step S5: During the simulation, calculate the target t relative to the radar R when it enters the radar detection range. i The deployment location's azimuth, elevation, and slant range parameters are determined. The target's slant range and azimuth are matched with a terrain masking table to obtain the nearest masking point. The target's elevation angle is compared with the masking angle of the masking point to obtain the line-of-sight calculation result. When target t1 enters the effective detection range of radar R1, the elevation angle E of target t1 relative to the deployment location of radar R1 is calculated in the Cartesian coordinate system established in step S4. t1 ; Traverse all terrain-shading points P ij Determine the occlusion point P that is closest to the target t1 coordinate point. t Retrieve the shading point P from the terrain shading table file. t Corresponding terrain shielding angle A t1 Compare the pitch angle E. t1 With the shading angle A t1 : when E t1 >A t1 When, it is determined that there is a line-of-sight condition between radar R1 and target t1; when E t1 ≤A t1 At that time, it is determined that there is no line-of-sight between radar R1 and target t1. For all aerial targets t1, t2, t3, ..., t1 within the detection range of radar R... n Repeat step S5 until there are no targets within the radar's effective detection range.

[0050] For all radar models R1, R2, ..., R n Repeat step S5 until all radar models involved in the simulation have been traversed, at which point the simulation ends.

[0051] The present invention also provides a target line-of-sight calculation system for radar simulation models based on terrain masking tables. The target line-of-sight calculation system for radar simulation models based on terrain masking tables can be implemented by executing the process steps of the target line-of-sight calculation method for radar simulation models based on terrain masking tables. That is, those skilled in the art can understand the target line-of-sight calculation method for radar simulation models based on terrain masking tables as a preferred embodiment of the target line-of-sight calculation system for radar simulation models based on terrain masking tables.

[0052] Example 2:

[0053] The present invention also provides a target line-of-sight calculation system for radar simulation models based on terrain masking tables, the system comprising the following modules:

[0054] Module M1: Acquires the longitude and latitude of all radar model deployment locations participating in the simulation, and obtains the altitude of each deployment location based on pre-loaded elevation data from the database; acquires Earth surface elevation data collected by remote sensing satellites, which is stored in TIF format and hierarchically managed based on a tile pyramid model; the elevation data includes multi-level digital elevation model (DEM) data downloaded from the Google Earth platform, stored according to preset levels, row numbers, and column numbers; performs hierarchical organization of the elevation data through the tile pyramid model to achieve hierarchical scheduling and rapid retrieval of the data; extracts the corresponding elevation value H from the elevation data based on the longitude and latitude coordinates of the radar deployment location. r The altitude of the radar deployment point;

[0055] Module M2: Obtains the basic performance parameters of all radars participating in the simulation, including radar height H. r Radar antenna azimuth pointing to A r 1. Calculate the radar azimuth coverage α, and calculate the minimum and maximum detection ranges of all radars; 2. Calculate the radar elevation H. r Radar antenna azimuth pointing to A r The radar azimuth coverage range α is an inherent parameter of the radar model; under interference-free conditions, the maximum detection slant range of the radar model for a typical RCS target at a specified altitude is calculated according to the radar equation.

[0056] Module M3: Based on factors such as solution accuracy, computational efficiency, network latency, number of threads, and computer performance, it obtains the terrain masking table generation parameters, including axial resolution and radial resolution, and generates a radar parameter information index table; it then iterates through all participating radar models R1, R2, ..., R... using the simulation system. n Obtain the following parameter information for each radar model: radar identifier ID; deployment location coordinates (Lon, Lat); radar elevation H. r Detection range [R] min R max Antenna azimuth pointing to A r ; Azimuth coverage α; Axial resolution θ, satisfying 0 < θ ≤ α; Radial resolution r, satisfying 0 < r ≤ R max A radar information index table is generated based on the parameter information, and the index table is transmitted to a geographic information server via the network as input parameters for generating a terrain masking table.

[0057] Module M4: The radar model sends a request to the geographic information server (GIS) via the network to generate a terrain masking table. The GIS extracts valid information from the radar information index table, generates terrain masking tables for all radar effective detection ranges according to a fixed format, and downloads them locally. After receiving the terrain masking table generation request from the simulation system, the GIS calls the locally stored elevation data, which is the Earth surface elevation data collected by the remote sensing satellites mentioned in Module M1. Based on the elevation data, terrain masking table files corresponding to each radar simulation model are generated in batches. The terrain masking table files contain the following parameter groups: radial distance, azimuth angle, elevation value, and masking angle. The generated terrain masking table files are stored in a preset directory path for the simulation system to call for radar model calculation during runtime.

[0058] Module M5: During simulation, it calculates the target t entering the radar detection range relative to the radar R. i The deployment location's azimuth, elevation, and slant range parameters are determined. The target's slant range and azimuth are matched with a terrain masking table to obtain the nearest masking point. The target's elevation angle is compared with the masking angle of the masking point to obtain the line-of-sight calculation result. When target t1 enters the effective detection range of radar R1, the elevation angle E of target t1 relative to the deployment location of radar R1 is calculated in the Cartesian coordinate system established by module M4. t1 ; Traverse all terrain-shading points P ij Determine the occlusion point P that is closest to the target t1 coordinate point. t Retrieve the shading point P from the terrain shading table file. t Corresponding terrain shielding angle A t1 Compare the pitch angle E. t1With the shading angle A t1 : when E t1 >A t1 When, it is determined that there is a line-of-sight condition between radar R1 and target t1; when E t1 ≤A t1 At that time, it is determined that there is no line-of-sight between radar R1 and target t1. For all aerial targets t1, t2, t3, ..., t1 within the detection range of radar R... n Repeatedly call module M5 until there are no targets within the radar's effective detection range.

[0059] For all radar models R1, R2, ..., R n Repeatedly call module M5 until all radar models involved in the simulation have been traversed, and the simulation ends.

[0060] Example 3:

[0061] This invention proposes a target visibility calculation method for radar simulation models based on terrain masking tables. In increasingly complex battlefield environments, in addition to the detection performance of the radar equipment itself, the complex terrain environment near the radar deployment location directly affects the radar model's visibility calculation results for aerial targets. Therefore, how to improve the accuracy and confidence of the radar sensor model's visibility calculation results for aerial targets while meeting simulation efficiency is a pressing problem to be solved. This invention provides a calculation service for all-round terrain masking data of radar deployment points by preloading terrain and elevation data, and can generate radar terrain masking tables, providing background support for the rapid calculation of the visibility of aerial targets within the effective detection range of the radar model.

[0062] This invention proposes a target visibility calculation method for radar simulation models based on a terrain masking table. It collects and stores elevation data in TIF format and employs a tile pyramid model for hierarchical management of the elevation data. Before simulation, a terrain masking table can be generated by loading terrain elevation data from the vicinity of the radar deployment location. During simulation, this provides a new approach for calculating the visibility of airborne targets within the effective detection range of the radar sensor model.

[0063] This invention proposes a target line-of-sight calculation method based on a terrain masking table in a radar simulation model, comprising the following steps:

[0064] Step 1: Determine the longitude and latitude of all radar model deployment locations participating in the simulation, and obtain the altitude of each deployment location based on the pre-loaded elevation data in the database. Earth surface elevation data is collected from remote sensing satellites and stored in TIF format. The elevation data primarily stores elevation images downloaded from Google Earth at various levels. The elevation data is stored according to different levels, rows, and columns, and arranged using a tile pyramid model to achieve hierarchical management of the elevation data. This supports viewing elevation images, video images, and model data. Finally, the radar elevation data is loaded using the latitude and longitude information of the radar deployment location to obtain the altitude of the deployment point, Hr.

[0065] Step 2: Define the basic performance parameters of all radars participating in the simulation, including radar height Hr (m), radar antenna azimuth Ar (°), and radar azimuth coverage α (°). Calculate the minimum and maximum detection ranges for each radar. Considering the absence of interference, based on the fundamental principles of radar target detection, the maximum detection slant range of the radar model for a typical RCS target at a specified height can be calculated using radar equations. For radars with shared transmit and receive antennas, the formula for calculating the maximum detection slant range using radar equations is as follows:

[0066]

[0067] In the formula:

[0068] P r Target echo power;

[0069] P t Radar transmit power;

[0070] G Ant Radar antenna gain;

[0071] σ: Radar echo area (RCS) of the target;

[0072] λ: The wavelength of the electromagnetic waves emitted by radar;

[0073] L: Radar power loss factor

[0074] Taking into account factors such as solution accuracy, computational efficiency, network latency, number of threads, and computer performance, parameters such as axial resolution and radial resolution are determined, and a radar information index table is generated.

[0075] Step 3: The simulation system iterates through all radar model entities R1, R2…Rn participating in this simulation, extracting the radar ID, deployment longitude Lon (°), deployment latitude Lat (°), radar elevation Hr (m), minimum detection range Rmin (m), maximum detection range Rmax (m), azimuth Ar (°), azimuth coverage α (°), axial resolution θ (°), and radial resolution r (m). All valid information parameters are required, including 0 < θ ≤ α and 0 < r ≤ Rmax. A radar valid information index table is generated as input. A terrain masking table generation request is sent to the elevation data database of the geographic information server via the network.

[0076] Step 4: Simulation begins. After receiving the request from the simulation system to generate a terrain masking table, the geographic information server first establishes a rectangular coordinate system with the radar model deployment location as the origin, the east direction as the X-axis, and the north direction as the Y-axis. At this time, the number of masking lines generated by the radar model in the radial direction is Mp = (Rmax - Rmin) / r, and the number of masking lines generated in the axial direction is Mq = α / θ. Then, a total of Mp × Mq masking points Pij are generated within the effective detection range of the radar, where i = 1, 2, ..., Mp, j = 1, 2, ..., Mq. The geographic information server calls the TIF format elevation data of the Earth's surface collected by remote sensing satellites stored locally, and generates terrain masking table files for all radar effective detection ranges in batches according to a fixed format. These files contain four sets of data: radial distance (m), azimuth (°), elevation (m), and masking angle (°) of the masking point. The data is stored and downloaded to a folder directory in a specified path on the local machine for the radar model to call and solve during simulation.

[0077] Step 5: During the simulation, when target t enters the effective detection range of radar model R, calculate the elevation angle of the target relative to the radar deployment position in the Cartesian coordinate system established in step 4. In the formula, Ht is the altitude of target t, Hr is the altitude of radar R's deployment location, and h is the radar's elevation. At this point, the coordinates of target t relative to radar R are (Xt, At), where Xt is the distance between the projection point of target t on the XOY plane of radar R1 and the radar deployment point, and At is the angle between the line connecting the projection point of target t on the XOY plane and the radar deployment point and the positive Y-axis. All terrain-obscured points Pij are traversed, and the obscured point Pt closest to the target t's coordinates is found. The terrain obscuration angle At of this point is obtained by retrieving the terrain obscuration table file. Finally, the target's elevation angle Et is compared with the obscuration angle At. If Et > At, the radar model and the target have a line of sight; otherwise, if Et ≤ At1, the radar model and the target do not have a line of sight.

[0078] Step 6: Repeat step 5 for all aerial targets tn within the detection range of radar R in each simulation cycle until there are no targets within the effective detection range of radar R.

[0079] Step 7: Repeat steps 5 and 6 for all radar models R1, R2, R3, ..., Rn in each simulation cycle until all radar models Rn participating in the simulation have been traversed, and the simulation ends.

[0080] The specific implementation involves two steps: generating a terrain masking table before the simulation begins and calculating the visibility of the radar model during the simulation.

[0081] Step 1:

[0082] Input: Reference Figure 1 The information index table for all radar models includes the following: ID of all radar models participating in the simulation, radar deployment longitude, radar deployment latitude, radar elevation, minimum detection range, maximum detection range, axial resolution, radial resolution, radar antenna azimuth pointing, radar azimuth coverage, and ten other parameters.

[0083] Processing procedure: Refer to Figure 2 Using the radar deployment location as the center and the radar's effective detection range as the radius, with an axial resolution of θ (°) and a radial resolution of r (m), Mp and Mq masking lines are generated in the radial and axial directions respectively. Finally, Mp × Mq possible masking points, Pij, are generated within the radar's effective detection range, where i = 1, 2, ..., Mp, j = 1, 2, ..., Mq. The geographic information server acquires the Earth's surface elevation data collected by remote sensing satellites, performs elevation data collection and calculation based on TIF format, and stores the elevation data according to various levels, rows, and columns. A tile pyramid model is used for arrangement and management to achieve hierarchical management of the elevation data. After receiving a request from the simulation system to generate a terrain masking table, the geographic information server extracts the effective parameter information of all radars in the radar information index table, and simultaneously calls the highest-level elevation data to batch generate terrain masking table files near the deployment location.

[0084] Output: Reference Figure 3 The system generates terrain masking table files for all radars and stores them in a folder directory under a specified path, which are then used by the radar model for calculation during simulation. The specific content of the terrain masking table includes four sets of data: radial distance (m), azimuth (°), elevation (m), and masking angle (°) of the masking points within the effective detection range of the radar relative to the radar deployment location.

[0085] Step Two:

[0086] Input: Terrain obstructions within the radar's effective detection range, and the locations of all targets within the radar's effective detection range;

[0087] Processing procedure: Refer to Figure 4 The simulation begins. When a target enters the radar's effective detection range, the elevation angle Et of the target t relative to the radar's deployment location is calculated. Simultaneously, all terrain masking points Pij in the radar's terrain masking table file are traversed until the nearest terrain masking point Pt and its corresponding terrain masking angle At are found. Finally, the target's elevation angle Et is compared with the masking point's masking angle At. If Et > At, the radar model and the target have a line of sight; otherwise, if Et ≤ At, the radar model and the target do not have a line of sight. This process is repeated until no target remains within the radar's effective detection range.

[0088] Output: Calculation results of the visibility of targets within the effective detection range of the radar.

[0089] Those skilled in the art can understand this embodiment as a more specific description of Embodiment 1 and Embodiment 2.

[0090] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0091] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for calculating the visibility of a radar simulation model target based on a terrain masking table, characterized in that, The method comprises the following steps: Step S1: Obtain the longitude and latitude of the deployment position of all radar models participating in simulation, and obtain the altitude of the respective deployment position according to the preloaded elevation data in the database; Step S2: Obtain the basic performance parameters of all radars participating in the simulation, including radar height H r , radar antenna azimuth pointing A r , radar azimuth coverage α, and calculate the minimum and maximum detection ranges of all radars respectively; Step S3: Obtain terrain shadow table generation parameters including axial resolution and radial resolution based on calculation accuracy, calculation efficiency, network delay, thread number and computer performance factors, and generate a radar parameter information index table; Step S4: The radar model sends a request for generating a terrain shadow table to the geographic information server through the network, the geographic information server extracts the effective information stored in the radar information index table, generates a terrain shadow table within the effective detection range of all radars in a fixed format, and downloads it to the local; Step S5: During the simulation running, the relative position of the target t entering the radar detection range to the radar R is calculated i The azimuth, pitch, and slant distance parameters of the deployment position; the slant distance and azimuth angle of the target are matched with the terrain shielding table to obtain the closest shielding point, and the pitch angle of the target is compared with the shielding angle of the shielding point to obtain the line-of-sight calculation result; for all air targets t1, t2, t3, …, t n Repeat step S5 until there is no target in the effective detection range of the radar. for all radar models R1, R2,..., R n Step S5 is repeated until all radar models participating in the simulation have been traversed and the simulation is finished.

2. The method of claim 1, wherein, The step S1 acquires the earth surface elevation data collected by a remote sensing detection satellite, the elevation data is stored in a TIF format and is hierarchically managed based on a tile pyramid model; the elevation data includes multi-level digital elevation model DEM data downloaded from a Google Earth platform and is stored according to preset levels, row numbers and column numbers; the tile pyramid model is used to perform layered organization on the elevation data, so that hierarchical scheduling and fast retrieval of data are realized; and according to the longitude and latitude coordinates of a radar deployment position, the elevation value H of the corresponding position in the elevation data is extracted as the altitude of the radar deployment point. r , as the altitude of the radar deployment point.

3. The method of claim 1, wherein, The radar height H in the step S2 r The radar antenna azimuth pointing A r And the radar azimuth coverage α is an inherent parameter of the radar model; under the condition of no interference, the maximum detection slant range of the radar model to the typical RCS target at a specified height is calculated according to the radar equation.

4. The method of claim 1, wherein, Step S3 involves traversing all radar models R1, R2, ..., R3 participating in the simulation using the simulation system. n Obtain the following parameter information for each radar model: radar identifier ID; deployment location coordinates (Lon, Lat); radar elevation H. r Detection range [R] min R max Antenna azimuth pointing to A r ; Azimuth coverage α; Axial resolution θ, satisfying 0 < θ ≤ α; Radial resolution r, satisfying 0 < r ≤ R max A radar information index table is generated based on the parameter information, and the index table is transmitted to a geographic information server via a network as input parameters for generating a terrain masking table.

5. The method of claim 1, wherein, After the geographic information server in the step S4 receives the terrain shadow table generation request sent by the simulation system, the local stored elevation data is called, the elevation data is the earth surface elevation data collected by the remote sensing detection satellite in the step S1; based on the elevation data, the terrain shadow table files corresponding to each radar simulation model are batch generated, the terrain shadow table files contain the following parameter groups: radial distance, azimuth angle, elevation value, shadow angle; the generated terrain shadow table files are stored to a preset directory path; the terrain shadow table files are called by the simulation system during running to perform radar model calculation.

6. The method of claim 1, wherein, In step S5, when target t1 enters the effective detection range of radar R1, the elevation angle E of target t1 relative to the deployment position of radar R1 is calculated in the Cartesian coordinate system established in step S4. t1 ; Traverse all terrain-shading points P ij Determine the occlusion point P that is closest to the target t1 coordinate point. t Retrieve the shading point P from the terrain shading table file. t Corresponding terrain shielding angle A t1 Compare the pitch angle E. t1 With the shading angle A t1 : when E t1 >A t1 When, it is determined that there is a line-of-sight condition between radar R1 and target t1; when E t1 ≤A t1 At that time, it is determined that there is no line-of-sight between radar R1 and target t1.

7. A target line-of-sight calculation system for radar simulation models based on terrain masking tables, characterized in that, The system comprises the following modules: Module M1: Obtain the longitude and latitude of the deployment position of all radar models participating in simulation, and obtain the altitude of the respective deployment position according to the preloaded elevation data in the database; Module M2: Obtain basic performance parameters of all radars participating in the simulation, including radar height H r , radar antenna azimuth pointing A r , radar azimuth coverage α, and calculate the minimum and maximum detection ranges of all radars, respectively; Module M3: Obtain terrain shadow table generation parameters including axial resolution and radial resolution based on calculation accuracy, calculation efficiency, network delay, thread number and computer performance factors, and generate a radar parameter information index table; Module M4: The radar model sends a request for generating a terrain shadow table to the geographic information server through the network, the geographic information server extracts the effective information stored in the radar information index table, generates a terrain shadow table within the effective detection range of all radars in a fixed format, and downloads it to the local; Module M5: During the simulation process, the target t entering the radar detection range is calculated relative to the radar R i azimuth, elevation, slant range parameters of the deployment position; match the target's slant range and azimuth angle with the terrain shielding table and get the closest shielding point, compare the target's elevation angle with the shielding angle of the shielding point to get the visibility calculation result; for all air targets t1, t2, t3, …, t n Repeat the call to module M5 until there is no target in the radar effective detection range; For all radar models R1, R2,..., R n The call to module M5 is repeated until all radar models participating in the simulation have been iterated through, and the simulation is finished.

8. The terrain-mask-table-based radar model target line-of-sight computation system of claim 7, wherein, The module M1 acquires Earth surface elevation data collected by remote sensing satellites. This elevation data is stored in TIF format and managed hierarchically based on a tile pyramid model. The elevation data includes multi-level digital elevation model (DEM) data downloaded from the Google Earth platform, stored according to preset levels, row numbers, and column numbers. The tile pyramid model is used to hierarchically organize the elevation data, enabling hierarchical scheduling and rapid retrieval. Based on the latitude and longitude coordinates of the radar deployment location, the module extracts the corresponding elevation value H from the elevation data. r The altitude of the radar deployment point; The radar height H in the module M2 r The radar antenna azimuth pointing A r And the radar azimuth coverage α is an inherent parameter of the radar model; under the condition of no interference, the maximum detection slant range of the radar model to the typical RCS target at a specified height is calculated according to the radar equation.

9. The terrain-mask-table-based radar model target line-of-sight computation system of claim 7, wherein, The module M3 traverses all radar models R1, R2,..., Rn participating in the simulation through the simulation system, obtains the following parameter information of each radar model: radar identification ID; deployment position coordinates (Lon, Lat); radar height H; detection range [Rmin, Rmax]; antenna azimuth pointing A; azimuth coverage range a; axial resolution 0, satisfying 0 < 0 < a; radial resolution r, satisfying 0 < r < Rmax; generates a radar information index table based on the parameter information, and transmits the index table to a geographic information server through a network as an input parameter for generating a terrain shielding table. n r min max r max The module M3 traverses all radar models R1, R2,..., Rn participating in the simulation through the simulation system, obtains the following parameter information of each radar model: radar identification ID; deployment position coordinates (Lon, Lat); radar height H; detection range [Rmin, Rmax]; antenna azimuth pointing A; azimuth coverage range a; axial resolution 0, satisfying 0 < 0 < a; radial resolution r, satisfying 0 < r < Rmax; generates a radar information index table based on the parameter information, and transmits the index table to a geographic information server through a network as an input parameter for generating a terrain shielding table.​​​​​ After the geographic information server in the step S4 receives the terrain shadow table generation request sent by the simulation system, the local stored elevation data is called, the elevation data is the earth surface elevation data collected by the remote sensing detection satellite in the step S1; based on the elevation data, the terrain shadow table files corresponding to each radar simulation model are batch generated, the terrain shadow table files contain the following parameter groups: radial distance, azimuth angle, elevation value, shadow angle; the generated terrain shadow table files are stored to a preset directory path; the terrain shadow table files are called by the simulation system during running to perform radar model calculation.

10. The terrain-mask-table-based radar model target line-of-sight computation system of claim 7, wherein, In module M5, when target t1 enters the effective detection range of radar R1, the elevation angle E of target t1 relative to the deployment position of radar R1 is calculated in the Cartesian coordinate system established by module M4. t1 ; Traverse all terrain-shading points P ij Determine the occlusion point P that is closest to the target t1 coordinate point. t Retrieve the shading point P from the terrain shading table file. t Corresponding terrain shielding angle A t1 Compare the pitch angle E. t1 With the shading angle A t1 : when E t1 >A t1 When, it is determined that there is a line-of-sight condition between radar R1 and target t1; when E t1 ≤A t1 At that time, it is determined that there is no line-of-sight between radar R1 and target t1.

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