Unmanned aerial vehicle track rendering method and device, electronic equipment and storage medium

Abstract

The invention provides an unmanned aerial vehicle track rendering method and device, electronic equipment and a storage medium, and belongs to the technical field of computer imageology, and the method comprises the steps: constructing a geographic space background; the real-time data stream of the unmanned aerial vehicle is received and then analyzed to obtain the operation state data of the unmanned aerial vehicle, and the operation state data comprises the distance between the unmanned aerial vehicle and the observation point; based on the distance, using a corresponding model to render the unmanned aerial vehicle on the geographic space background; the farther the distance is, the simpler the model is. The rendering details of the unmanned aerial vehicle are dynamically adjusted according to the distance between the unmanned aerial vehicle and the observer, so that unnecessary picture rendering is reduced, picture fluency is guaranteed, GPU / CPU load is reduced, memory occupation is reduced, and large-scale unmanned aerial vehicle trajectory stability and flow field display are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer graphics, and in particular to a UAV trajectory rendering method and device, electronic equipment and storage medium. BACKGROUND

[0002] With the continuous progress of UAV technology, its application field is also more and more widely, plays an important role in logistics, security, emergency and other fields. However, the real-time state monitoring and flight trajectory visualization of a large number of UAVs have become a technical bottleneck.

[0003] At present, the UAV visualization platform based on Cesium and other three-dimensional GIS engines can provide relatively smooth interactive experience when dealing with less than 100 UAVs, basically meeting the monitoring requirements. However, once facing thousands or even tens of thousands of concurrent data, the drawbacks of the existing technology are exposed. First, the rendering frame rate will drop sharply, causing serious frame freezing, and the monitoring personnel cannot grasp the real-time dynamics of the UAV in time and clearly, which may miss key information and affect the efficiency of emergency handling and decision-making. Secondly, the high GPU / CPU load will bring great pressure to the hardware, which is easy to cause browser crash, resulting in interruption of the monitoring system and unable to run normally. Thirdly, the memory occupation will continue to rise, and there is a risk of memory leakage, which may cause system failure for a long time, and frequent restarts, which seriously affects the stability and reliability of the system.

[0004] Therefore, how to ensure the smoothness of the rendering picture and reduce the load of the computing unit and the memory occupation has become a technical problem to be solved. SUMMARY

[0005] The present application provides a UAV trajectory rendering method, device, electronic equipment and storage medium to solve the defects of picture freezing, large GPU / CPU load and large memory occupation in the prior art.

[0006] The present application provides a UAV trajectory rendering method, comprising the following steps: constructing a geographic space background; receiving and analyzing a real-time data stream of a UAV to obtain running state data of the UAV, the running state data including the distance between the UAV and an observation point; based on the distance, rendering the UAV on the geographic space background using a corresponding model; the farther the distance, the simpler the model.

[0007] According to the UAV trajectory rendering method provided by the present application, the UAV is rendered on the geographic space background based on the distance using a corresponding model, which comprises: if the distance is less than or equal to a first threshold value, it is determined that the UAV is in a near distance, and the UAV is rendered on the geospatial context using a complete model; if the distance is greater than the first threshold value and less than a second threshold value, it is determined that the UAV is in a middle distance, and the UAV is rendered on the geospatial context using a simplified model; if the distance is greater than or equal to the second threshold value, it is determined that the UAV is in a far distance, and the UAV is rendered on the geospatial context as a point or a line segment.

[0008] According to the present application, a UAV trajectory rendering method is provided, and the UAV trajectory rendering method further comprises: when the UAV changes between the near distance, the middle distance or the far distance, a second interpolation function is used to switch the model used by the UAV.

[0009] According to the present application, a UAV trajectory rendering method is provided, and the UAV trajectory rendering method further comprises: based on the flight direction and speed of the UAV, the flight trajectory of the UAV is predicted; if the flight trajectory indicates that the UAV is about to switch from a far distance area to a middle distance area, the simplified model is pre-loaded into the memory; if the flight trajectory indicates that the UAV is about to switch from a middle distance area to a near distance area, the complete model is pre-loaded into the memory.

[0010] According to the present application, a UAV trajectory rendering method is provided, and the UAV trajectory rendering method further comprises: if the UAV is within the frustum geometry of the observation camera, the UAV is rendered on the geospatial context; if the UAV is not within the frustum geometry of the observation camera, the UAV is not rendered.

[0011] According to the present application, a UAV trajectory rendering method is provided, and the UAV trajectory rendering method further comprises: a sliding window sampling algorithm is used to sample the historical trajectory of the UAV to obtain key path points and store them.

[0012] The present application also provides a UAV trajectory rendering device, comprising the following modules: a background construction module, configured to construct a geospatial context; a data analysis module, configured to analyze the real-time data stream of the UAV after receiving the real-time data stream of the UAV to obtain the running state data of the UAV, wherein the running state data comprises the distance between the UAV and an observation point; a drone rendering module, configured to: based on the distance, render the drone on the geographical space background using a corresponding model; the farther the distance, the simpler the model.

[0013] The application further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the drone trajectory rendering method according to any one of the above when executing the computer program.

[0014] The application further provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the drone trajectory rendering method according to any one of the above.

[0015] The application further provides a computer program product, which includes a computer program, and the computer program is executable on a processor to implement the drone trajectory rendering method according to any one of the above.

[0016] The application provides a drone trajectory rendering method, device, electronic device and storage medium, a geographical space background is constructed; after receiving a real-time data stream of a drone, operation state data of the drone is obtained by analysis, the operation state data includes a distance between the drone and an observation point; based on the distance, the drone is rendered on the geographical space background using a corresponding model; the farther the distance, the simpler the model. When observing at a long distance, too many rendering details will sharply increase the rendering burden, and when observing at a short distance, it is difficult to accurately identify the state and characteristics of the drone due to insufficient details, the application dynamically adjusts the rendering details of the drone according to the distance between the drone and the observer, thereby reducing unnecessary picture rendering, ensuring picture fluency, reducing GPU / CPU load, reducing memory occupation, and realizing stable and smooth display of a large-scale drone trajectory. BRIEF DESCRIPTION OF DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0018] Figure 1 is a flowchart of the drone trajectory rendering method provided by the application; Figure 2 is a structural schematic diagram of the drone trajectory rendering system provided by the application; Figure 3 is a structural schematic diagram of the drone trajectory rendering device provided by the application; Figure 4is a structural schematic diagram of an electronic device provided by the present application. DETAILED DESCRIPTION

[0019] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0020] It should be noted that in the description of the embodiments of the present application, the terms "comprise", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitation, the element defined by the sentence "comprises a" does not exclude the presence of another identical element in the process, method, article or device comprising the element. The terms "upper", "lower" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application. Unless otherwise explicitly specified and limited, the terms "mount", "connect", "connect" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be connected inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0021] The terms "first", "second", and the like in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally a category and do not limit the number of objects, for example, the first object can be one or more. In addition, "and / or" means at least one of the connected objects, and the character " / ", generally means that the front and rear associated objects are in an "or" relationship.

[0022] The embodiments of the present application will be described below in conjunction with Figures 1-4 The unmanned aerial vehicle trajectory rendering method and device, electronic device and storage medium provided by the embodiments of the present application are described.

[0023] Figure 1 is a flowchart of the unmanned aerial vehicle trajectory rendering method provided by the present application, as shown in the figure, the method comprises the following: Figure 1 S110, constructing a geographic space background; S120, receiving and analyzing the real-time data stream of the unmanned aerial vehicle to obtain the running state data of the unmanned aerial vehicle, the running state data comprising the distance between the unmanned aerial vehicle and the observation point; S130, based on the distance, rendering the unmanned aerial vehicle on the geographic space background using a corresponding model; the farther the distance, the simpler the model.

[0024] In the embodiment of the present application, the execution subject of the unmanned aerial vehicle trajectory rendering method can be an unmanned aerial vehicle trajectory rendering device, which can include but is not limited to a server, a desktop computer, a notebook computer, a tablet computer and the like. The execution subject of the unmanned aerial vehicle trajectory rendering method can also be an unmanned aerial vehicle trajectory rendering system, which belongs to the unmanned aerial vehicle trajectory rendering device. For ease of understanding, the following embodiments take the unmanned aerial vehicle trajectory rendering system as the execution subject to describe the unmanned aerial vehicle trajectory rendering method provided by the present application.

[0025] Figure 2 is a structural diagram of the unmanned aerial vehicle trajectory rendering system provided by the present application, Figure 2 shows a schematic diagram of an exemplary architecture. For the purpose of description, the architecture drawn is only an example of a suitable environment, and does not impose any limitation on the use range or function of the present application. Neither should the system be interpreted as having any dependency or requirement on any component or combination thereof shown in Figure 2

[0026] In S110, a three-dimensional earth visualization environment is built based on Cesium engine, a realistic geographic space background is constructed by loading image layer, topographic map layer, annotation layer, 3D model, grid and other data. At the same time, the global coordinate conversion function is deeply integrated to ensure the accurate matching of unmanned aerial vehicle coordinates and three-dimensional scene; flexible camera view control is supported to facilitate monitoring personnel to observe the unmanned aerial vehicle running from different angles; the time axis playback function is realized based on Cesium Clock API, supporting time sequence playback, speed control and breakpoint continuation of trajectory data, meeting the needs of historical trajectory analysis and event review.

[0027] ​​In S120, a data receiving channel is constructed by using the MQTT protocol. By virtue of the lightweight, high real-time and reliable message queue mechanism, the real-time state data of the unmanned aerial vehicle, including OSD information, GPS coordinates, height, speed and other key parameters, is stably connected. After receiving the original data, the data stream is deeply processed by a customized data analysis module to convert it into structured data conforming to the system standard, so as to ensure that the data format is clear and standard. Then, the system stores the parsed structured data in the Redis cache database. Redis can quickly respond to data storage and reading requests due to its high-speed reading and writing performance and flexible data structure, and provides support for efficient data management. When the front end needs to obtain the unmanned aerial vehicle data for visual display, the system pushes the latest data stored in the Redis to the front end in real time through the WebSocket long connection. The WebSocket realizes two-way communication, ensures that the data can be transmitted to the front end page in time and accurately, synchronizes the monitoring picture with the actual running state of the unmanned aerial vehicle, and provides a solid and reliable data foundation for subsequent rendering operations.

[0028] In S130, a multi-detail level model system is constructed for each unmanned aerial vehicle entity, and the model integrity is determined according to the distance.

[0029] The unmanned aerial vehicle trajectory rendering method provided by the embodiment of the application constructs a geographic space background; after receiving a real-time data stream of an unmanned aerial vehicle, the running state data of the unmanned aerial vehicle is obtained by analysis, and the running state data includes the distance between the unmanned aerial vehicle and an observation point; based on the distance, a corresponding model is used to render the unmanned aerial vehicle on the geographic space background; the farther the distance, the simpler the model. When observing at a long distance, too many rendering details will sharply increase the rendering burden, and when observing at a short distance, it may be difficult to accurately identify the state and characteristics of the unmanned aerial vehicle due to insufficient details. The application dynamically adjusts the rendering details of the unmanned aerial vehicle according to the distance between the unmanned aerial vehicle and the observer, thereby reducing unnecessary picture rendering, ensuring picture fluency, reducing GPU / CPU load, reducing memory occupation, and realizing stable and smooth display of a large-scale unmanned aerial vehicle trajectory.

[0030] In an optional embodiment, the rendering of the unmanned aerial vehicle on the geographic space background based on the distance using a corresponding model comprises: If the distance is less than or equal to a first threshold value, it is determined that the unmanned aerial vehicle is at a short distance, and a complete model is used to render the unmanned aerial vehicle on the geographic space background; If the distance is greater than the first threshold value and less than a second threshold value, it is determined that the unmanned aerial vehicle is at a medium distance, and a simplified model is used to render the unmanned aerial vehicle on the geographic space background; If the distance is greater than or equal to the second threshold, it is determined that the UAV is at a far distance, and the UAV is rendered as a point or a line segment on the geographical space background.

[0031] In the embodiment of the present application, in a far distance scenario (usually more than 2000 meters), a point or a line segment is used as a simple representation, which greatly reduces the rendering calculation amount; in a middle distance scenario (usually between 500 meters and 2000 meters), a simplified gltf model is loaded to retain basic appearance characteristics; in a near distance scenario (usually less than 500 meters), a complete model is enabled to present fine animation effects and detailed labels, and the balance between details and performance is achieved.

[0032] The UAV trajectory rendering method provided in the embodiment of the present application uses a point or a line segment as a simple representation in a far distance, uses a simplified model in a middle distance, and enables a high-precision model in a near distance, which balances performance and user experience and achieves the balance between details and performance.

[0033] In an optional embodiment, the UAV trajectory rendering method further includes: When the UAV changes between the near distance, the middle distance or the far distance, a second interpolation function is used to switch the model used by the UAV.

[0034] In the embodiment of the present application, a second interpolation function is used to control model transition, which avoids flickering at the distance threshold. Specifically, during the flight of the UAV, as the distance between the UAV and the observer changes, the LOD (Level of Detail) model will switch between different levels of details, such as switching from a point model in a far distance to a simplified model in a middle distance. If the switching is direct and abrupt, the form of the UAV on the screen will suddenly change at the moment when the distance threshold is reached, which will cause flickering or jumping and seriously affect the visual experience. The second interpolation function can smoothly transition the parameters (such as vertex position and texture detail level) of the model when the distance approaches the threshold.

[0035] The UAV trajectory rendering method provided in the embodiment of the present application controls model transition through a second interpolation function, so that the UAV gradually changes from a low-definition picture to a high-definition picture when switching from a far distance to a near distance, instead of jumping to a high-definition picture, which ensures that the change process of the UAV model is natural and smooth and eliminates flickering.

[0036] In an optional embodiment, the UAV trajectory rendering method further includes: Based on the flight direction and speed of the UAV, the flight trajectory of the UAV is predicted; If the flight trajectory indicates that the UAV is about to switch from a far distance region to a middle distance region, the simplified model is preloaded into the memory; If the flight trajectory represents that the UAV is about to switch from a medium distance area to a close distance area, the complete model is preloaded into the memory.

[0037] In the embodiment of the present application, a priority queue is used to pre-load the complete model of the UAV about to enter the high-detail range, to ensure that there is no lag during switching. Specifically, when the UAV is about to enter the medium distance from the far distance, or enter the close distance from the medium distance, a higher detail model needs to be displayed. However, if the high-detail model is loaded after entering the range, the loading process may cause the screen to lag due to the large amount of model data. The priority queue can predict which UAVs will enter the higher detail display range first according to the flight direction and speed of the UAVs, and then load the corresponding high-detail model into the memory in advance. In this way, when the UAV really enters the range, the system can directly call the loaded model for rendering, avoiding the lag caused by temporary loading and ensuring smooth picture.

[0038] The UAV trajectory rendering method provided in the embodiment of the present application pre-loads the high-detail model, directly calls the loaded model for rendering when the UAV enters the close distance range, avoids the lag caused by temporary loading of the model, and ensures the smoothness of the picture.

[0039] In a large-scale UAV cluster real-time monitoring scene, there are a large number of UAV models in the scene. If all UAVs are rendered, GPU resources will be greatly consumed, resulting in low rendering efficiency. To solve this problem, the present application constructs a real-time and efficient visibility judgment system with the help of the view frustum detection mechanism provided by the Cesium engine. Specifically, the UAV trajectory rendering method further comprises: If the UAV is within the view frustum geometry range of the observation camera, the UAV is rendered on the geographic space background; If the UAV is not within the view frustum geometry range of the observation camera, the UAV is not rendered.

[0040] In the embodiment of the present application, the frustum is the area that the camera can observe in the three-dimensional space, and its shape is similar to the truncated base of a pyramid. When the system is running, the position, orientation and other parameters of the camera are obtained in real time, so as to determine the range of the current frustum. For each unmanned aerial vehicle, the system compares its position coordinates with the geometric range of the frustum to determine whether it is in the frustum. For the unmanned aerial vehicles in the frustum, it means that they are in the current camera field of view, and subsequent rendering operation needs to be performed to ensure that the monitoring personnel can see the state of these unmanned aerial vehicles. For the unmanned aerial vehicles beyond the range of the frustum, since they are not in the current field of view, even if rendering is performed, they cannot be observed by the monitoring personnel, so the system directly skips the rendering process of these unmanned aerial vehicles. Through this view distance clipping strategy, the number of unmanned aerial vehicles that need to be rendered can be effectively reduced, and a large number of invalid drawing operations are avoided. This not only reduces the load of the GPU, but also concentrates the GPU resources on rendering the unmanned aerial vehicles in the field of view, thereby improving the overall rendering efficiency of the system and making the picture more smooth.

[0041] The unmanned aerial vehicle trajectory rendering method provided by the embodiment of the present application only renders the unmanned aerial vehicles in the frustum range, thereby effectively reducing the number of unmanned aerial vehicles that need to be rendered, avoiding a large number of invalid drawing operations, improving the system rendering efficiency, and improving the picture smoothness.

[0042] In an optional embodiment, the Entity API is used in combination with the CallbackProperty technology to realize real-time dynamic updating of the position, attitude and trajectory of the unmanned aerial vehicle, so as to ensure that the monitoring picture is synchronized with the actual running state. At the same time, the Instanced Rendering technology of WebGL is introduced to batch draw the multiple unmanned aerial vehicle models, reduce the rendering state switching overhead, and significantly improve the drawing efficiency. Specifically: In the Cesium engine, the Entity API is a powerful tool for creating and managing entities (such as unmanned aerial vehicle models) in the scene. Each unmanned aerial vehicle entity can be created through the Entity API, and its initial position, attitude, trajectory and other attributes can be set. The CallbackProperty is a special property type that allows the value of the property to be dynamically calculated through a callback function at each frame rendering. Through this dynamic updating mechanism, the position of the unmanned aerial vehicle in the scene can change in real time according to the actual flight trajectory, the attitude can be adjusted according to the flight state (such as turning, accelerating, etc.), and the trajectory can be continuously extended and updated, thereby realizing high synchronization between the monitoring picture and the actual running state, and providing accurate real-time information for the monitoring personnel.

[0043] The core idea of the Instanced Rendering technology is to batch draw models of the same type (such as a drone model with the same geometry and material). For multiple drones with the same model, only the vertex data, index data, and material information of one model need to be stored in the GPU, and then different instance parameters (such as position, rotation angle, and scaling ratio) are provided for each drone, so that multiple drones can be drawn in one rendering call.

[0044] In an optional embodiment, the method further comprises: sampling the historical trajectory of the drone using a sliding window sampling algorithm to obtain key path points and store them.

[0045] In the embodiment, the sliding window sampling algorithm is used for data compression of the historical trajectory, and key path points are extracted. In the management of historical trajectory data, the system performs deep compression processing on the huge trajectory data by using the sliding window sampling algorithm. The algorithm dynamically determines the time or space window, analyzes the trajectory points in the window, and accurately extracts the path points that can reflect the overall shape and key features of the trajectory. In the compression process, the turning angle and speed change of the trajectory are fully considered to ensure that the key path points can completely reproduce the contour and trend of the drone flight trajectory, while ensuring the integrity of the trajectory shape, greatly reducing the redundant data, and significantly reducing the data storage and transmission pressure.

[0046] To effectively control the storage size of the trajectory data, the system sets a scientific trajectory length management mechanism. When the accumulated trajectory data reaches a certain upper limit, the system will automatically trigger the data cleaning process to remove the old data in the time sequence first, thereby ensuring the reasonable use of memory resources. This automatic cleaning mechanism can monitor the data size in real time, prevent the memory usage from being too high due to data accumulation, and thus cause performance problems such as slow system response and running lag, and ensure that the system always maintains an efficient and stable running state.

[0047] The method provided by the embodiment of the present application compresses the trajectory of the drone by using the sliding window sampling algorithm, extracts key path points, and greatly reduces redundant data while ensuring the integrity of the trajectory shape, thereby significantly reducing the data storage and transmission pressure.

[0048] In an optional embodiment, in order to solve the label display problem in the UAV monitoring picture, the system constructs a set of intelligent label display control logic based on the camera height parameter. When the camera is at a low height and the number of UAVs in the picture is small, the system will display the label information of all UAVs completely, facilitating the user to quickly identify and view. When the camera is raised to a high position and the number of UAVs in the field of view increases, the labels may overlap densely and the information may be chaotic, the system will intelligently select and display key labels and automatically hide secondary labels according to the importance and spatial distribution of the labels, so that the monitoring picture remains clear and concise and avoids information overload from interfering with the user.

[0049] In an optional embodiment, the system is deeply improved in interactive function optimization. The user only needs to click the UAV icon in the picture to quickly pop up a detailed information pop-up window, which integrates the flight parameters, device status, task information and other multi-dimensional data of the UAV, providing comprehensive and accurate information support for the user. The implementation of focusing on the aircraft function enables the user to lock the target of interest with one key, and the system automatically adjusts the picture perspective and display ratio to place the target UAV at the center of the picture, facilitating the user to observe in detail. In addition, the system also sets up an intelligent alarm prompt mechanism. Once an abnormal state of the UAV is detected, such as signal loss, flight attitude loss of control, low battery, etc., the system will immediately attract the user's attention through various ways such as prominent color change and flashing prompt, helping the user to discover and handle the abnormal situation in time, greatly improving the convenience and effectiveness of monitoring interaction.

[0050] In an optional embodiment, in order to ensure the long-term stable operation of the system, the system establishes a perfect resource recycling and memory management mechanism. By setting a long-term detection thread, the system will periodically scan the status of all UAVs, focusing on those UAVs that have not updated their position information for a long time and are in an idle state. Once such UAVs are found, the system will use asynchronous operation to quickly remove the corresponding three-dimensional model data and historical trajectory data. This asynchronous processing mechanism ensures that the resource recycling operation does not block the main thread, avoiding affecting the normal operation of the system and releasing the occupied memory resources in time to make more space for the system operation.

[0051] The UAV trajectory rendering method provided by the present application will be described below in conjunction with specific examples.

[0052] The low-altitude flight supervision platform needs to perform real-time trajectory monitoring on 10,000 simulated UAVs covering the entire city, including urban center high-rise buildings, suburban open areas and complex terrain areas. The system needs to meet the high-density UAV concurrent rendering demand, while ensuring the smoothness of the monitoring picture, the real-time data and the interactive response speed, in order to support the core businesses of air traffic flow management and illegal flight early warning.

[0053] Implementation process: 10000 drones are configured with three-level LOD model, through quadratic interpolation smooth switching algorithm, avoid model at distance threshold (such as 2000 meters, 500 meters) appear flicker; Using priority queue preloading mechanism, to the monitoring center flying unmanned aerial vehicle in advance load high detail model, ensure that there is no delay when switching; Based on Cesium view frustum detection mechanism, real-time calculation of each unmanned aerial vehicle and camera spatial position relationship. With monitoring center as the camera fixed point, when the unmanned aerial vehicle flies out of the view frustum range (such as horizontal distance more than 1000 meters and vertical height more than 1000 meters), directly skip the rendering process. According to the test, this strategy can filter out more than 60% of the invisible unmanned aerial vehicle, the single rendering object is reduced from 10000 to 4000 or less, greatly reducing the GPU rendering pressure.

[0054] This example verifies the technical feasibility and stability of the application in the scene of ten thousand unmanned aerial vehicles, breaks through the performance bottleneck of traditional three-dimensional GIS engine in large-scale object rendering. Its core technology (LOD combined with view distance clipping, GPU instantiation, trajectory compression) can be directly reused in the field of intelligent transportation, emergency rescue command and other fields that need high-density dynamic target visualization, providing efficient and reliable technical support for urban air traffic management.

[0055] The following describes the unmanned aerial vehicle trajectory rendering device provided by the embodiments of the application. The unmanned aerial vehicle trajectory rendering device described below can be correspondingly referred to the unmanned aerial vehicle trajectory rendering method described above.

[0056] Figure 3 is a structural schematic diagram of the unmanned aerial vehicle trajectory rendering device provided by the application, as Figure 3 shown, the unmanned aerial vehicle trajectory rendering device can include but is not limited to; The background construction module 310 is configured to construct a geographic space background. The data analysis module 320 is configured to analyze the real-time data stream of the unmanned aerial vehicle after receiving it, to obtain the running state data of the unmanned aerial vehicle, wherein the running state data includes the distance between the unmanned aerial vehicle and the observation point. The unmanned aerial vehicle rendering module 330 is configured to render the unmanned aerial vehicle on the geographic space background based on the distance using a corresponding model; the farther the distance, the simpler the model.

[0057] It should be noted that the unmanned aerial vehicle trajectory rendering device provided by the embodiments of the application can execute the unmanned aerial vehicle trajectory rendering method described in any of the above embodiments when actually running, and therefore the embodiments will not be described here.

[0058] Figure 4 An example of an electronic device is shown in the physical structure schematic diagram, Figure 4As shown, the electronic device can include a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 complete mutual communication through the communications bus 440. The processor 410 can invoke a logical instruction in the memory 430 to execute a drone trajectory rendering method, which includes: constructing a geospatial context; receiving and parsing a real-time data stream of a drone to obtain running state data of the drone, the running state data including a distance between the drone and an observation point; based on the distance, rendering the drone on the geospatial context using a corresponding model; the farther the distance, the simpler the model.

[0059] In addition, the logical instruction in the memory 430 described above can be implemented in the form of a software functional unit and sold or used as an independent product, which can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium, includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0060] On the other hand, the present application also provides a computer program product, which includes a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program is executed by a processor, and the computer can execute the drone trajectory rendering method provided by the above-mentioned method, which includes: constructing a geospatial context; receiving and parsing a real-time data stream of a drone to obtain running state data of the drone, the running state data including a distance between the drone and an observation point; based on the distance, rendering the drone on the geospatial context using a corresponding model; the farther the distance, the simpler the model.

[0061] In yet another aspect, the present application also provides a non-transitory computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the method for rendering a trajectory of a UAV provided by any of the above methods, the method comprising: constructing a geospatial context; receiving and parsing a real-time data stream of the UAV to obtain running state data of the UAV, the running state data comprising a distance between the UAV and an observation point; based on the distance, rendering the UAV on the geospatial context using a corresponding model; the farther the distance, the simpler the model.

[0062] The device embodiments described above are merely illustrative, wherein the units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, i.e., they can be located in one place, or distributed on multiple network units. Some or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0063] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus necessary general hardware platforms, and of course can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in terms of contribution to the prior art, can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0064] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for rendering the trajectory of a drone, characterized in that, include: Constructing a geospatial context; After receiving the real-time data stream from the UAV, the data is parsed to obtain the UAV's operational status data, which includes the distance between the UAV and the observation point. Based on the distance, the drone is rendered on the geographic spatial background using a corresponding model; the greater the distance, the simpler the model.

2. The UAV trajectory rendering method according to claim 1, characterized in that, The step of rendering the drone on the geospatial background using a corresponding model based on the distance includes: If the distance is less than or equal to the first threshold, the drone is determined to be at close range, and the drone is rendered on the geographic background using the full model; If the distance is greater than the first threshold and less than the second threshold, the drone is determined to be at a medium distance, and the drone is rendered on the geographic background using a simplified model; If the distance is greater than or equal to the second threshold, the drone is determined to be at a long distance, and the drone is rendered as a point or line segment on the geographic background.

3. The UAV trajectory rendering method according to claim 2, characterized in that, The drone trajectory rendering method also includes: When the drone changes between the short, medium, or long distances, a quadratic interpolation function is used to switch the model used by the drone.

4. The UAV trajectory rendering method according to claim 2, characterized in that, The drone trajectory rendering method also includes: Based on the flight direction and speed of the UAV, predict the flight trajectory of the UAV; If the flight trajectory indicates that the UAV is about to switch from a long-range area to a medium-range area, then the simplified model is preloaded into memory; If the flight trajectory indicates that the UAV is about to switch from a mid-range area to a short-range area, then the complete model is preloaded into memory.

5. The UAV trajectory rendering method according to claim 1, characterized in that, The drone trajectory rendering method also includes: If the drone is within the geometric range of the viewing cone of the observation camera, then the drone is rendered on the geographic background; If the drone is not within the view frustum geometry of the observation camera, the drone will not be rendered.

6. The UAV trajectory rendering method according to any one of claims 1-5, characterized in that, The drone trajectory rendering method also includes: The historical trajectory of the UAV is sampled using a sliding window sampling algorithm to obtain and store key path points.

7. A drone trajectory rendering device, characterized in that, include: The background building module is used to: build geospatial backgrounds; The data parsing module is used to: receive and parse the real-time data stream from the UAV to obtain the UAV's operational status data, which includes the distance between the UAV and the observation point; The drone rendering module is used to: render the drone on the geographic spatial background using a corresponding model based on the distance; the farther the distance, the simpler the model.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the UAV trajectory rendering method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the UAV trajectory rendering method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the UAV trajectory rendering method as described in any one of claims 1 to 6.

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