A method for constructing WebGIS scene of satellite-station link

Abstract

The present invention discloses a cloud-based star-station link WebGIS scene construction method. This method uses cloud service technology to share part of the data processing business on the user side, optimizes the consumption strategy of the user-side computer resources, optimizes the rendering strategy of the GIS situation scene, and improves the service capacity of the server side. This method can fully utilize the advantages of the large number of cores of the autonomous controllable processor, overcome the weakness of the slow speed of a single core of the autonomous controllable processor, and optimize the scene presentation and interactive effects of large-scale situations under domestic hardware conditions. By optimizing the application strategy of hardware resources, the present invention optimizes the rendering effect and service capacity of the WebGIS situation scene, provides an optimization method for carrying out WebGIS situation scene applications under autonomous controllable computer systems, and solves the technical problems of poor three-dimensional scene rendering effect and low frame rate under the conditions of autonomous controllable processors and image processing chips, and low availability of constructed star-station link WebGIS scenes.

Description

Technical Field

[0001] The present invention relates to the field of geographic information application technology, and in particular to a method for constructing a satellite-station link WebGIS scene. Background Art

[0002] As the number of space satellites increases, the measurement, control and data transmission tasks between ground systems and satellites are becoming more frequent. The use of scene restoration methods based on digital earth can present the measurement and control process of satellite orbits and star station tracking more clearly and intuitively.

[0003] However, since large-scale satellite-station link scenarios based on Digital Earth have very high performance requirements for the computer system's central processing unit (CPU) and graphics processing unit (GPU), usually, when the scene rendering terminal uses existing domestic graphics workstations or computers, its three-dimensional scene rendering effect is poor and the frame rate is low, and the usability of the satellite-station link WebGIS scenario constructed in this way is not high. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method for constructing a star-station link WebGIS scene, aiming to solve the technical problem that when the current scene rendering terminal uses existing domestic graphics workstations or computers, its three-dimensional scene rendering effect is poor and the frame rate is low, and the usability of the star-station link WebGIS scene constructed in this way is low.

[0005] To achieve the above objectives, the present invention provides a method for constructing a WebGIS scene based on a cloud service, the method comprising the following steps:

[0006] S1: Cloud platform service initialization;

[0007] S2: The user sends a WebGIS scene generation request to the cloud platform;

[0008] S3: The cloud scenario service generates a satellite-station link scenario script based on Digital Earth and pushes it to the user end;

[0009] S4: The user side parses the scenario to generate a script and subscribes to GIS resources from the cloud platform based on the scenario's demand for GIS resources.

[0010] S5: The cloud platform generates a GIS resource folder and pushes it to the user end. The user end builds a synchronized GIS resource directory structure and buffers the GIS resources to the local disk.

[0011] S6: The user terminal generates scripts and GIS resources based on the received scene, builds and renders the initial star station scene;

[0012] S7: The user terminal initiates a star station status subscription application to the cloud platform and establishes a data push channel between the WebSocket and the star station status service;

[0013] S8: When the cloud platform collects new station status data, it pushes the latest status data to the user end through the WebSocket channel;

[0014] S9: After receiving the satellite station status, the user terminal moves the satellite model according to the latest satellite position, analyzes the tracking status of the ground tracking station on the satellite, and generates the satellite station link tracking segment;

[0015] S10: The user end renders the scene of the star station link according to the initial star station scene and the link segment to obtain the final star station link WebGIS scene.

[0016] Optionally, step S1 specifically includes:

[0017] S11: The cloud platform virtualizes hardware resources;

[0018] S12: The cloud platform stores GIS resources of different fine-grained levels and deploys and publishes GIS resource services pointing to the corresponding storage paths of GIS resources;

[0019] S13: The cloud platform deploys and releases the star station status collection service and the star station status push service;

[0020] S14: The cloud platform deploys and publishes WebGIS scene generation services.

[0021] Optionally, the GIS resources include satellite images, vector layers, and scene 3D models.

[0022] Optionally, the star station status collection service deployed by the cloud platform specifically includes: the cloud platform continuously collects the link status of satellites and ground tracking and control stations from external systems, calculates the latest orbital positions of all satellites, and monitors user-side subscription applications; the star station status push service deployed by the cloud platform specifically includes: the cloud platform monitors user-side star station status subscription applications, establishes and manages user-side lists, and uses WebSocket to establish network links and information push channels with subscribed users.

[0023] Optionally, the WebGIS scene generation service deployed by the cloud platform specifically includes: the cloud platform caches the digital earth platform scripts, scene object model files, and scene generation script resources required for the scene, accepts the user's scene access application, and pushes the digital earth platform, object model resources, scene construction script and other data to the user end, so that the user end can use the resources to perform scene construction.

[0024] Optionally, before step S2, the method further includes: starting a user-side application, accessing the URL address of the WebGIS scene generation service through the Http protocol, and establishing a persistent session with the WebGIS scene generation service of the cloud platform.

[0025] Optionally, step S3 specifically includes:

[0026] S31: The WbeGIS scene generation service of the cloud platform receives the request from the user;

[0027] S32: The cloud platform collects digital earth resource files and scene model resource files and generates scene construction scripts;

[0028] S33: Create a scenario generation script folder based on the satellite model file, ground equipment model file, and antenna model file in the scenario model;

[0029] S34: Push the scene generation script folder to the user end through the web protocol.

[0030] Optionally, the step S10 specifically includes: the user end constructs a rendering timer, sets a GPU priority rendering strategy, and renders objects such as the digital globe, satellite models, device models, link segments, and labels in the star-station link.

[0031] The present invention provides a cloud-based method for constructing a WebGIS scenario for a star-station link. This method uses cloud service technology to share some of the data processing tasks on the user side, optimizes the consumption strategy of the user-side computer resources, optimizes the rendering strategy of the GIS situation scenario, and increases the service capacity of the server side. This method can fully leverage the advantages of a large number of cores in an autonomous and controllable processor, overcome the weakness of a single core of an autonomous and controllable processor being slow, and optimize the presentation and interaction effects of large-scale star-station link situations under domestic hardware conditions. By optimizing the application strategy of hardware resources, the present invention optimizes the rendering effect and service capacity of the WebGIS situation scenario, providing an optimized approach for carrying out WebGIS situation scenario applications under autonomous and controllable computer systems. This solves the technical problem that when the current scene rendering terminal uses existing domestic graphics workstations or computers, the three-dimensional scene rendering effect is poor and the frame rate is low, resulting in low usability of the star-station link WebGIS scenario constructed using such a workstation. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a flow chart of a method for constructing a WebGIS scene for a satellite-station link according to the present invention;

[0033] Figure 2 A schematic diagram of the principle of a method for constructing a satellite-station link WebGIS scene according to the present invention;

[0034] Figure 3This is a first schematic diagram of the information interaction relationship between the cloud platform server and the user terminal of the present invention;

[0035] Figure 4 This is a second schematic diagram of the information interaction relationship between the cloud platform server and the user terminal of the present invention;

[0036] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0037] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] At present, in the relevant technical field, when the existing scene rendering terminal uses existing domestic graphics workstations or computers, its three-dimensional scene rendering effect is poor and the frame rate is low, and the star station link WebGIS scene constructed based on this has the technical problem of low availability.

[0039] To address this issue, various embodiments of the present invention's method for constructing a WebGIS scenario for a satellite-station link are proposed. This method utilizes cloud service technology to offload some data processing tasks from the user end, optimizing hardware resource utilization strategies and the rendering quality and service capacity of the WebGIS situational scenario. This method provides an optimized approach for implementing WebGIS situational scenario applications on autonomous and controllable computer systems, resolving the technical issues associated with the poor three-dimensional scene rendering quality and low frame rate of existing domestic graphics workstations or computers used as scene rendering terminals, resulting in low usability of the resulting WebGIS scenario for a satellite-station link.

[0040] The embodiment of the present invention provides a method for constructing a WebGIS scene of a star station link, referring to Figure 1 , Figure 1 This is a flow chart of an embodiment of the method for constructing a WebGIS scenario for a star-station link according to the present invention.

[0041] In this embodiment, the method for constructing a WebGIS scene of a satellite-station link includes the following steps:

[0042] S1: Cloud platform service initialization;

[0043] S2: The user sends a WebGIS scene generation request to the cloud platform;

[0044] S3: The cloud service generates a satellite-station link scenario script based on Digital Earth and pushes it to the user end;

[0045] S4: The user side parses the scenario to generate a script and subscribes to GIS resources from the cloud platform based on the scenario's demand for GIS resources.

[0046] S5: The cloud platform generates a GIS resource folder and pushes it to the user end. The GIS resource directory structure is built on the user end, and the GIS resources are buffered to the local disk.

[0047] S6: The user terminal generates scripts and GIS resources based on the received scene, builds and renders the initial star station scene;

[0048] S7: The user terminal initiates a star station status subscription application to the cloud platform and establishes a data push channel between the WebSocket and the star station status service;

[0049] S8: When the cloud platform collects new station status data, it pushes the latest status data to the user end through the WebSocket channel;

[0050] S9: After receiving the satellite station status, the user terminal moves the satellite model according to the latest satellite position, analyzes the tracking status of the ground tracking station on the satellite, and generates the satellite station link tracking segment;

[0051] S10: The user end renders the scene of the star station link according to the initial star station scene and the link segment to obtain the final star station link WebGIS scene.

[0052] In order to explain this application more clearly, the following is a detailed description of the method for constructing the WebGIS scene of the star station link in this application. Figure 2 shown.

[0053] Step S01: Virtualization processing of cloud resources.

[0054] Using Huawei's virtual cloud technology (FusionSphere 8.0 in this example), the processors and memory of the domestic Taishan servers are virtualized for management. This creates a dynamically allocated resource pool, divided into 10-20 virtual computer nodes. The domestic Kylin operating system (Kylin V10 in this example) is deployed, and the PaaS platform is deployed on the virtual computer nodes. This platform integrates service image management, automatic deployment, service registration, configuration management, load balancing, file system services, and persistent storage management capabilities. This creates conditions for dynamic multi-instance operation of cloud services.

[0055] Step S02: GIS resource publishing.

[0056] Build a persistent storage area on the NFS file system of the Paas platform on the cloud, import GIS resources of different fine-grained levels, including satellite images, vector layers, scene 3D models and other file resources, deploy WebGIS services on the Paas platform, point the resource path to the persistent storage path, and publish GIS resource services to the entire network through the Http protocol.

[0057] Step S03: Release the star station link service.

[0058] Deploy star station status collection service and star station status push service on the Paas platform on the cloud.

[0059] The satellite station status collection service continuously collects the link status between satellites and ground tracking and control stations from external systems, calculates the latest orbital positions of all satellites, monitors user-side subscription applications, uses multiple copies to achieve load balancing, and provides a 4-core 8G mirror operating environment for each copy.

[0060] The Star Station Status Push Service listens for subscriber requests for Star Station Status subscriptions, establishes and manages user subscription lists, and uses WebSocket to establish network links and information push channels with subscribers. Once established, it delivers satellite data and link status data to the user in real time. The Star Station Status Push Service uses multiple replicas for load balancing, providing each replica with a 4-core, 8GB mirrored operating environment through the Paas platform, ensuring that service instances can be dynamically added as the number of users increases.

[0061] Step S04: WebGIS scene generation service publishing.

[0062] The Paas platform is deployed on the cloud and publishes WebGIS scene generation services, and caches the digital earth platform scripts, scene object model files, scene generation scripts and other resources required for the scene. It accepts user scene access applications and pushes data such as the digital earth platform, object model resources, and scene construction scripts to the user end so that the user end can use these resources to start scene construction.

[0063] The service uses multiple copies to achieve load balancing, providing each copy with a 4-core 8G mirror operating environment.

[0064] Step S05: User-side GPU application control.

[0065] The user end uses the domestic Feiteng computer as the situation scenario access terminal, and the operating system is the Kylin operating system. The graphics card GPU enable parameters are set through the operating system, the GPU application optimization strategy is specified, the user end application accessing the star station link scenario is set to the highest priority, and the 3DPython mode is turned on.

[0066] Step S06: Apply for satellite station situation scenario.

[0067] Start the client application, access the URL of the Star Station scene generation service through the Http protocol, and establish a persistent session with the scene generation service of the cloud platform.

[0068] Step S07: Pushing the scene script.

[0069] The WebGIS scene generation service of the cloud platform collects digital earth resource files and scene model resource files based on user applications and generates scene construction scripts. The scene model contains model resources such as coarse-grained satellite model files, ground equipment model files, and antenna model files, forming a scene generation script folder, which is pushed to the user-side application through the web protocol. The user-side buffers the model to the local disk.

[0070] Step S08: GIS resource subscription.

[0071] The user-side parses the scene to generate a script, which automatically links to the GIS resource publishing service based on the Digital Earth's demand for GIS resources, and applies to download resources such as geographic information images, national boundary vector maps, etc. that support the Digital Earth.

[0072] Step S09: GIS resource push.

[0073] The cloud platform's GIS resource service collects geographic information tile images, national boundaries, elevation data, and other resource files based on user requests, creates a GIS resource folder, and pushes it to the user application via the Web protocol. The user builds the GIS resource directory structure and caches all GIS resources to the local disk.

[0074] Step S10: Star station scene construction and rendering.

[0075] After the user collects the scenario script and GIS resources, it begins constructing the satellite-station link situation scenario based on the scenario script. It initializes the Digital Earth platform and loads imagery resources, national boundary vectors, administrative divisions, elevations, and other information from the local disk. Using elevation data, it creates a three-dimensional terrain on the Digital Earth. The satellite imagery is rendered as the Digital Earth surface texture, and layered with national boundaries, country names, administrative divisions, and other data. The sphere is annotated with information such as various levels of measurement and control equipment and landmark cities. Coarse-grained satellite models and equipment models are placed on the Earth based on the initial position information. Light objects are added to the scene, and their positions and lighting properties are set. A camera object is added, and parameters such as the camera position, focal length, viewing angle, and field of view are set. The rendering strategy is configured, and GPU priority is enabled before the scene rendering begins.

[0076] Step S11: Star station status and link subscription.

[0077] After the user side builds the initial situation scenario, it establishes a location buffer for the satellite and ground tracking and control station, initiates a subscription request to the cloud platform link status service, and builds a WebSocket to establish a data push channel with the satellite station status service.

[0078] Step S12: collecting and pushing the status of the satellite station.

[0079] After receiving a user's subscription request, the Cloud Station Link Status Service pushes the latest collected information, including satellite orbit position, link tracking status, and tracking parameters, to the user. It also adds the user's IP address to the user's service list. When new station status data is collected or calculated, it is compared with the user's subscription list and pushed to the user via the WebSocket channel.

[0080] Step S13: scene model control.

[0081] After receiving the satellite station status, the user end moves the satellite model according to the latest satellite position, analyzes the ground tracking status of the satellite by the ground measurement and control station, and analyzes the tracking status of each ground device on the satellite one by one. For the satellite being tracked, a satellite station link tracking segment is generated. As the satellite position moves, the start and end positions of the star station link tracking segment are dynamically updated. For the satellite that stops being tracked, the tracking link segment between the device and the satellite is destroyed or hidden.

[0082] Step S14: Situation scene rendering.

[0083] The model viewing distance is calculated by using the positional relationship between the observation point and the model in the scene. The visibility of GIS resources and 3D models of different granularities is controlled according to the viewing distance range. Models with close viewing distance are displayed with high precision, models with medium longitude are displayed with intermediate viewing distance, and models with far viewing distance are displayed with low precision. Models beyond the viewing distance range are hidden, thus minimizing GPU resource consumption.

[0084] The user-side application builds a rendering timer, sets the GPU priority rendering strategy and rendering frequency (set to 2HZ in this example), and regularly renders objects such as the digital globe, satellite model, device model, link segments, and labels in the situation scene.

[0085] It should be noted that in this embodiment, a method for constructing a satellite-station link WwbGIS scenario is provided, which includes (1) optimizing the consumption strategy of computer resources on the user side; (2) optimizing the rendering strategy of the GIS situation scene; and (3) improving the service capacity of the server side. Specifically:

[0086] a) Optimize the consumption strategy of user-side computer resources.

[0087] The user-side computer is directly facing the user and is mainly responsible for human-computer interaction and scene rendering. In order to improve the user experience, it is necessary to ensure that the GIS situation scene based on the digital earth runs smoothly and reduce the resource consumption on domestic computers during system operation. The main strategy is to reduce the consumption ratio of domestic computers in three aspects: CPU, GPU, and memory. Usually, under the domestic Kylin operating system, the CPU resource consumption ratio of the GIS situation scene is controlled below 70%, the GPU is controlled below 90%, and the memory consumption is controlled below 4G.

[0088] The main strategies are as follows:

[0089] 1) Strategies to reduce the consumption of domestic CPU resources;

[0090] Since the domestic Kylin system performs CPU resource scheduling at the sub-process granularity, the single-core performance of the domestic CPU is not high, but the number of cores is sufficient. Therefore, the satellite station link status system designs the user front-end in a multi-process / sub-process manner, separating data I / O and processing services from the main process to form independent sub-processes. The main process only handles human-computer interaction services, and the operating system is responsible for load balancing among multiple cores to ensure that data processing and human-computer interaction services are handled in different CPU cores to prevent delays, freezes, and other phenomena in user interactions.

[0091] 2) Strategies to reduce the consumption of domestic GPU resources;

[0092] Since the GPU cannot share tasks across multiple cores, reducing GPU consumption mainly focuses on reducing the rendering burden of the scene as it moves in the field of view, counting the number of lines and surfaces in the scene in real time, switching object models of different fineness as needed based on model distance and focus requirements, reducing the number of lines and surfaces in the model in the scene, and lowering the scene lighting level.

[0093] 3) Strategies to reduce memory resource consumption;

[0094] Human-computer interaction and scene rendering are mainly processed on the user side. If the memory usage on the user side is too high, it will also cause delays, freezes and other phenomena in user interaction. Therefore, the user side only buffers business data that affects scene rendering, such as satellite orbit queues, measurement and control equipment positions, link start and end points, real-time parameter values ​​of pages, and other data. Historical data is not cached. All data that is not required for scene rendering is buffered on the server side and pushed to the user side in two ways. The first way is that when the business data changes, the background service actively pushes it to the user side. The data that is required for the scene is cached, and the data that is not required for the scene is discarded. The second way is that when historical business data needs to be extracted due to scene switching, it is actively obtained from the background service through the API to prevent large-scale situation scenes from buffering data that is not related to scene rendering for a long time.

[0095] b) Optimize the rendering strategy of GIS situation scenes.

[0096] When a user computer accesses a GIS scene in a situation, it needs to subscribe to a large amount of geographic information data such as satellite image files, vector layer files, administrative division data, elevation data, etc. from the server cluster. In order to reduce the computational workload of scene rendering and minimize the file size and number of model lines that need to be loaded in the scene, the main measures are as follows:

[0097] 1) Optimize the dynamic analysis method of GIS resource loading;

[0098] In the case of a far field of view, the scene is presented in a global manner, the number of grid lines of the digital earth is reduced, the surface texture of the earth is loaded with low-precision satellite image files, the elevation rendering effect is turned off, and other vector layer files are downloaded to the user's computer according to the default shutdown method; when the user's field of view is focused on a local area of ​​the earth, the earth's viewing distance is calculated, and higher-precision satellite image files are dynamically loaded according to the viewing distance. When the viewing distance is close to a certain extent, local elevation data is downloaded and the mountain rendering effect is turned on.

[0099] 2) Optimize the dynamic loading method of model objects;

[0100] Models of varying levels of detail (usually 3-4) are created for the satellites and TT&C equipment in the scene, based on their classification. When a user accesses a situational scene, they observe the global scene from a relatively long viewing distance and calculate the distance between the observation point and the satellites and TT&C equipment in the scene. For satellites with a closer viewing distance, higher-precision model files are loaded, while for satellite objects with a closer viewing distance, lower-precision model files are loaded. As the field of view moves, the distance between the observation point and the satellites and TT&C equipment in the scene is dynamically calculated, switching objects with a longer viewing distance to lower-precision model files and those with a closer viewing distance to higher-precision model files.

[0101] 3) Optimize GPU usage strategy;

[0102] Open the Kylin OS resolution settings dialog box, select Advanced Graphics Mode in the window, set GPU resources to be used only for image calculations, prioritize GPU resources for application image processing, enable 3DPython mode, and establish a GPU timing rendering strategy.

[0103] c) Methods to increase service capacity on the server side.

[0104] 1) Optimize the server structure;

[0105] Huawei virtualization technology virtualizes all processors and memory hardware in a server cluster into vCPU pools and memory pools. When deploying server-side applications, the number of vCPU cores and memory size are allocated based on application needs.

[0106] The server includes four types of applications: 1) Situational scenario frontend, which is responsible for basic digital earth scenario generation, and the user end downloads the scenario through gateway access; 2) Business data push service, which pushes real-time business data to connected user ends through WebService; 3) GIS resource service, which pushes the geographic information resources required for the scenario to the user end through subscription; 4) Data collection service, which collects and caches all business data required for the star station link scenario from external systems through various methods such as message queues (MessageQueue), database access, and network multicast.

[0107] 2) Dynamic resource allocation strategy on the server side;

[0108] All server-side applications respond to user requests in a stateless service manner and deploy multiple replicas based on the number of users supported in parallel. The number of replicas (Instances) required for each type of service is determined by the number of users responding in parallel (M) and the number of users responding to a single replica (I), as expressed by:

[0109] X = M / I

[0110] The server application is deployed using the Kubernetes architecture, with vCPU and memory allocated based on the resource consumption requirements of a single instance. When a client initiates a connection request to the server, the system responds with a relatively idle replica based on the vCPU and memory usage of the current instance. As the number of users increases, more service replicas are launched to scale the number of users served. As the number of concurrent users decreases, the number of service replicas is reduced, reclaiming shared resources such as vCPU and memory from the server cluster.

[0111] 3) Scalability of the number of user-side connections;

[0112] All server-side applications are stateless services. When responding to user requests, the processing of a single request does not depend on other requests. The business collection service and the business data push service obtain data through third-party components such as in-memory databases, relational databases, or file systems. When the business data collection service collects data from external systems, it stores the data in the third-party component and queries the real-time data demand table of the user-side scenario to confirm which business push service instance has reported the demand data. Based on the query results, the API interface (Apolicationg Programing Interface) of the business push service instance is called to push the data to the business data push service in need. After the business push service obtains the data, it confirms which connected user-side scenario needs the data and pushes it to the user via WebSocket.

[0113] The information interaction relationship between the cloud platform server and the user end is as follows Figure 3 and Figure 4 shown.

[0114] 4) Data collection service response method dynamic resource allocation strategy;

[0115] The data cache component handles data sharing between multiple service types and formulates data orchestration rules based on the storage format of business data in the cache component. These include key-value orchestration rules in in-memory databases, table design in relational databases, file naming rules in file systems, and cursor offset rules within files. When the business data collection service collects data from external systems, it stores it in the corresponding cache system according to these orchestration rules. As the external system grows, if a single replica becomes unable to receive and store data in a timely manner, load balancing can be used to activate additional service replicas. As the amount of data in the external system decreases, collection service replicas are reduced to reclaim system resources. This enables dynamic resource allocation for business data collection from external systems.

[0116] This embodiment provides a method for constructing a WebGIS scenario for a star-station link based on cloud technology. By optimizing the application strategy of hardware resources through cloud service technology, the rendering effect and service capacity of the WebGIS situation scenario are optimized. This method can fully utilize the advantages of the large number of cores of an autonomous and controllable processor and overcome the weakness of the slow speed of a single core of an autonomous and controllable processor. This method provides an optimized approach for carrying out WebGIS situation scenario applications on autonomous and controllable computer systems and solves the technical problem that when the scene rendering terminal currently uses an autonomous and controllable graphics workstation or computer, the three-dimensional scene rendering effect is poor and the frame rate is low, resulting in low availability of the star-station link WebGIS scenario constructed in this way.

[0117] The above are only preferred embodiments of the invention and are not intended to limit the patent scope of the invention. Any equivalent structure or equivalent process transformation made using the contents of the invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the invention.

Claims

1. A method for constructing a WebGIS scene for a satellite-station link, characterized in that: The method comprises the following steps: S1: Cloud platform service initialization; S2: The user sends a WebGIS scene generation request to the cloud platform; S3: The cloud service generates a satellite-station link scenario script based on Digital Earth and pushes it to the user end; S4: The user side parses the scenario to generate a script and sends a request to the cloud service to subscribe to GIS resources based on the demand for GIS resources; S5: Based on the application for subscribing to GIS resources, the cloud platform generates and pushes GIS resource files, builds the GIS resource directory structure on the user side, and buffers the GIS resources to the local disk; S6: The user terminal generates scripts and GIS resources based on the received scene, builds and renders the initial star station scene; S7: The user terminal initiates a star station status subscription application to the cloud platform and establishes a data push channel between the WebSocket and the star station status service; S8: When the cloud platform collects new station status data, it pushes the latest status data to the user end through the WebSocket channel; S9: After receiving the satellite station status, the user terminal moves the satellite model according to the latest satellite position, analyzes the tracking status of the satellite by the ground tracking and control station, and generates the satellite station link tracking line segment; S10: The user end renders the scene of the star station link according to the initial star station scene and the link segment to obtain the final star station link WebGIS scene.

2. The method for constructing a WebGIS scene for a star-station link according to claim 1, wherein: The step S1 specifically includes: S11: The cloud platform virtualizes hardware resources; S12: The cloud platform stores GIS resources of different fine-grained levels and deploys and publishes GIS resource services pointing to the corresponding storage paths of GIS resources; S13: The cloud platform deploys and releases the star station status collection service and the star station status push service; S14: The cloud platform deploys and publishes WebGIS scene generation services.

3. The method for constructing a WebGIS scene for a star-station link according to claim 2, wherein: The GIS resources include satellite images, vector layers, and scene 3D models.

4. The method for constructing a WebGIS scene for a star-station link according to claim 2, wherein: The star station status collection service deployed by the cloud platform specifically includes: the cloud platform continuously collects the link status of satellites and ground tracking and control stations from external systems, calculates the latest orbital positions of all satellites, and monitors user-side subscription applications; the star station status push service deployed by the cloud platform specifically includes: the cloud platform monitors user-side star station status subscription applications, establishes and manages user-side lists, and uses WebSocket to establish network links and information push channels for subscribing users.

5. The method for constructing a WebGIS scene for a star-station link according to claim 2, wherein: The WebGIS scene generation service deployed by the cloud platform specifically includes: the cloud platform caches the digital earth platform scripts, scene object model files, and scene generation script resources required for the scene, accepts the user's scene access application, and pushes the digital earth platform, object model resources, scene construction script and other data to the user end, so that the user end can use the resources to execute scene construction.

6. The method for constructing a WebGIS scene for a star-station link according to claim 2, wherein: Before step S2, the method further includes: starting a user-side application, accessing the URL address of the WebGIS scene generation service through the Http protocol, and establishing a persistent session with the WebGIS scene generation service of the cloud platform.

7. The method for constructing a WebGIS scene for a star-station link according to claim 2, wherein: The step S3 specifically includes: S31: The WebGIS scene generation service of the cloud platform receives the request from the user; S32: The cloud platform collects digital earth resource files and scene model resource files and generates scene construction scripts; S33: Create a scenario generation script folder based on the satellite model file, ground equipment model file, and antenna model file in the scenario model; S34: Push the scene generation script folder to the user end through the web protocol.

8. The method for constructing a WebGIS scene for a star-station link according to claim 1, wherein: The step S10 specifically includes: the user end constructs a rendering timer, sets and enables a GPU priority rendering strategy, and renders objects such as the digital globe, satellite models, device models, link segments, and labels in the satellite-station link.

Images