Low-altitude airspace digital Beidou grid coding implementation method based on Cesium

Abstract

The invention discloses a low-altitude airspace digital Beidou grid coding implementation method based on Cesium. The method comprises the following steps: realizing bidirectional accurate conversion between geographic coordinates and Beidou two-dimensional / three-dimensional grid coding based on the existing earth space subdivision and coding standard; constructing a large-scale grid dynamic visualization engine based on Cesium: constructing the engine in Cesium, and dynamically calculating and only rendering three-dimensional grids of effective areas and hierarchies by the engine according to a current window and a proportional scale; constructing a gridding coding and integrated management framework of the airspace elements: performing gridding coding and visualization on the airspace environment, structure and operation elements, and constructing the integrated management framework; and space-time grid coding expansion and four-dimensional visualization realization: space-time coding is expanded, and dynamic visualization of a grid occupation state is realized on a Cesium time axis. According to the invention, the national standard of Beidou grid coding can be successfully grounded to specific, efficient and interactive three-dimensional visual engineering application, and a technical scheme which can be directly deployed and implemented is provided for refined, digital and intelligent management of low-altitude airspace.

Description

Technical Field

[0001] This invention belongs to the fields of low-altitude airspace management, BeiDou grid and 3D visualization technology, and in particular a method for implementing digital BeiDou grid coding for low-altitude airspace based on Cesium. Background Technology

[0002] With the explosive growth of low-altitude aircraft such as drones and eVTOLs, low-altitude airspace management faces severe challenges, including scarce airspace resources and difficulties in aircraft supervision. To achieve refined management of airspace resources, airspace digitization based on the BeiDou grid location code has become an important direction. The national standards "BeiDou Grid Location Code" (GB / T 39409-2020) and "Earth Space Grid Coding Rules" (GB / T 40087-2021) have established a theoretical system for Earth space subdivision and coding. Related research (such as "Research on Key Technologies for Low-Altitude Airspace Management Based on BeiDou Grid") has also elucidated its application value in scenarios such as airspace planning, route management, and conflict early warning.

[0003] However, existing technologies have significant shortcomings: First, existing solutions mostly remain at the level of theoretical framework and coding rule description. For example, the industry standard "Technical Requirements for Digitalization of Airspace Information of Civil Unmanned Aerial Vehicles (Draft for Comments)" only has concepts such as "gridization" and "grid drawing", lacking a complete engineering implementation path for how to transform abstract coding rules into specific three-dimensional visualization graphics, resulting in "coding without display". Second, the coding algorithm and visualization engine are seriously disconnected. It does not provide an efficient conversion algorithm from geographic coordinates to standard coding, nor a specific method for reverse parsing the coding into three-dimensional geometry, nor does it solve the real-time rendering performance bottleneck of massive three-dimensional meshes in the WebGL environment. Specifically, as follows: (1) Limited to top-level design and rule description, lacking specific engineering visualization implementation methods: Existing solutions mainly remain at the level of conceptual description of management rules, coding formats and application scenarios. Although the intentions of "gridization" and "grid drawing" are mentioned, they do not involve the key engineering technology path of how to transform the abstract Beidou grid coding rules into real-time rendered and interactive visualization graphics in specific three-dimensional visualization platforms (especially mainstream Web three-dimensional earth engines such as Cesium). That is, there are only rules for "what to do", but no implementation of "how to do it". (2) Coding and algorithm, visualization are seriously disconnected: Existing technologies specify the coding structure of two-dimensional, three-dimensional and even spatiotemporal Beidou grids in detail, but do not provide efficient and batch conversion algorithms from actual geographic coordinates (latitude, longitude, elevation) to standard Beidou grid codes, and lack specific algorithms to reverse-parse the codes into geometric objects (such as polyhedra representing spatial units) that can be accurately drawn in three-dimensional scenes. This makes the coding rules like "castles in the air", unable to form an effective closed loop with three-dimensional visualization. (3) The performance bottleneck of large-scale three-dimensional grid visualization has not been solved: Low-altitude airspace management involves multi-scale grids from macro areas to micro fine airspaces, and faces the challenge of real-time rendering of massive three-dimensional geometric objects when visualizing. Existing technologies only propose the idea of ​​"dynamically using different levels of grids", but do not provide performance optimization schemes such as hierarchical detail management, view frustum clipping, and instantiation rendering of large-scale three-dimensional grid data in the Cesium engine. This is the technical problem that must be overcome to build a practical and smooth interactive visualization management system.

[0004] This has created a technological gap, the "last mile," between national standards and practical applications. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by providing a concrete and engineering-implementable method for digital BeiDou grid coding in low-altitude airspace based on Cesium. This invention bridges the gap between national standard coding and 3D visualization through a self-developed coding-geometry bidirectional conversion algorithm; it overcomes performance bottlenecks by integrating a large-scale grid rendering engine with dynamic window scheduling and LOD optimization; and ultimately constructs a low-altitude airspace management framework integrating coding, visualization, and interaction, while expanding spatiotemporal management capabilities.

[0006] The technical solution to achieve the purpose of this invention is: a method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium, the method comprising the following steps:

[0007] Step 1: Based on existing geospatial subdivision and coding standards, achieve accurate bidirectional conversion between geographic coordinates and BeiDou 2D / 3D grid coding;

[0008] Step 2, build a large-scale mesh dynamic visualization engine based on Cesium: build an engine in Cesium that dynamically calculates and renders only the effective area and level of the 3D mesh based on the current viewport and scale.

[0009] Step 3, Construct a grid-based coding and integrated management framework for airspace elements: Grid-based coding and visualization of airspace environment, structure, and operational elements to construct an integrated management framework;

[0010] Step 4, Spatiotemporal grid encoding extension and four-dimensional visualization implementation: Extend the spatiotemporal encoding and implement dynamic visualization of grid occupancy status on the Cesium time axis.

[0011] Furthermore, step 1 is specifically implemented through a two-way encoding-geometry conversion algorithm. This algorithm includes: a first algorithm that converts the latitude, longitude, and elevation coordinates of geographic points into standard BeiDou two-dimensional and three-dimensional grid codes based on the partitioning rules defined in the standard "BeiDou Grid Location Code"; and a second algorithm that reverse-parses the standard BeiDou grid codes into geometric outline coordinates that can be rendered in the Cesium three-dimensional scene. At the same time, a two-way automatic mapping relationship is established between the encoded data and the visualized graphics.

[0012] Furthermore, the first algorithm specifically includes:

[0013] (1) Coordinate to encoding conversion:

[0014] Based on the ten-level subdivision parameters of the BeiDou grid, the span of each grid level in the latitude, longitude and altitude directions is defined;

[0015] A first function is constructed to generate BeiDou two-dimensional grid codes. The input of the first function is the latitude B, longitude L and target level Level of a certain geographic point. The row and column positions of the geographic point in each level grid are calculated iteratively and then concatenated according to the national standard coding rules to generate the final BeiDou two-dimensional grid code string.

[0016] (2) Three-dimensional height domain encoding and calculation:

[0017] A second function is constructed to calculate the geodetic height of the bottom surface of each grid layer. This second function calculates the geodetic height of the bottom surface of the nth grid layer based on the BeiDou grid height subdivision formula. The specific calculation formula is as follows:

[0018]

[0019] In the formula, This represents the ground elevation of the nth grid layer. For the Earth's semi-major axis, This represents the radian value corresponding to 1°. This is the current latitude and longitude.

[0020] At the same time, a third function is constructed to infer the integer layer n in which a given height H is located;

[0021] Next, the derived n is converted into a 32-bit binary string according to the rules in Appendix C of the national standard, and then extracted and concatenated to form the height field encoding part of the three-dimensional code;

[0022] (3) Three-dimensional coding synthesis:

[0023] Combining the BeiDou two-dimensional grid code generated in (1) above with the height domain code generated in (2) above, a complete BeiDou three-dimensional grid code is synthesized according to the national standard format.

[0024] Furthermore, the second algorithm is used to calculate the grid spatial range from the BeiDou grid encoded string; the algorithm specifically includes:

[0025] For a given code, by parsing the row and column numbers of each level and combining them with the latitude and longitude span of the level, the latitude and longitude coordinates of the southwest corner (bottomLeftLon, bottomLeftLat) and the latitude and longitude coordinates of the northeast corner (topRightLon, topRightLat) of the grid space are calculated by summing them up, thereby determining the rectangular area of ​​the grid space in Cesium.

[0026] Further, step 2 specifically involves: integrating the algorithm used in step 1 into the Cesium 3D Earth engine to construct a dynamic mesh visualization engine; this dynamic mesh visualization engine dynamically calculates and renders only the 3D BeiDou mesh entities of the current level within the intersection area of ​​the user's current viewport range and the preset management airspace range, and combines the mesh level determined by the real-time calculated viewpoint height and scale, thereby achieving efficient loading of view-related meshes.

[0027] Furthermore, step 2 specifically includes:

[0028] Step 2-1, Dynamic monitoring and calculation of viewport: Use Cesiumr to monitor the user's mouse drag and scroll wheel operation events, and trigger the viewport update after the operation is completed; at the same time, use Cesiumr to calculate the rectangle of the latitude and longitude range of the current camera viewport on the Earth's surface in real time, that is, the current viewport range (viewExtent).

[0029] Step 2-2, Visualization Hierarchical Dynamic Decision: Calculate the scene scale based on the current camera viewpoint height and vertical field of view; dynamically determine the optimal grid level to be displayed, currentLevel, based on the preset mapping relationship between the scale range and the BeiDou grid levels.

[0030] Steps 2-3, Calculation of effective rendering area: Perform an intersection operation on the current view window range viewExtent and the predefined low-altitude airspace management area range givenRegion to obtain the effective area to be rendered, renderRegion; if the intersection is empty, no mesh rendering is performed.

[0031] Step 2-4, Dynamic Mesh Generation and Rendering: Based on the optimal mesh level currentLevel determined in Step 2-2, obtain the latitude and longitude span (lonStep, latStep) of this level; Starting from the southwest corner of the effective region renderRegion, traverse the mesh with a step size of (lonStep, latStep). For each mesh position traversed, call the algorithm used to implement Step 1 to generate its encoding, and add a rectangular entity with a specific height based on the mesh range to the scene using Cesium;

[0032] Steps 2-5, Rendering Optimization and Refresh: When user interaction causes changes in viewExtent or currentLevel, clear all mesh entities rendered in the previous frame, and re-execute steps 2-3 and 2-4 based on the new parameters to achieve dynamic and efficient mesh refresh.

[0033] Furthermore, step 3 specifically involves applying steps 1 and 2 to perform BeiDou grid coding on the core elements of low-altitude airspace management, including airspace environmental elements, airspace structural elements, and airspace operational elements. These elements are then classified, layered, visualized, rendered, and interactively managed in the Cesium 3D scene, forming an integrated "coding-visualization-interaction" low-altitude airspace digital management framework.

[0034] Furthermore, step 3 specifically includes:

[0035] Meshization of airspace environmental elements: The boundary coordinates of obstacles, no-fly zones, and preset specific areas are converted into a set of BeiDou grid codes covering their space through the method in step 1, and rendered as a semi-transparent fill of a specific color in Cesium to achieve visual isolation;

[0036] Airspace structural elements are gridded: fixed routes and dynamically planned routes are represented as a series of ordered BeiDou grid coding sequences; in Cesium, the route grid is rendered as a coherent channel, and coding labels can be attached to the center of the grid;

[0037] Grid-based airspace operation elements: The real-time position and historical trajectory of the aircraft are converted into corresponding grid codes and sequences through step 1; the highlighted display of the grid where the aircraft is located is updated in real time in Cesium, and the trajectory is rendered as a pipeline formed by the grid sequence; based on the overlapping relationship between the grid where the aircraft is located and the surrounding "three-dimensional nine-square grid", a visual and graded warning of conflict risk is realized.

[0038] Furthermore, step 4 specifically involves: on the basis of standard three-dimensional mesh coding, extending the time dimension, defining a spatiotemporal mesh coding structure that includes time windows, and visualizing this structure on the time axis module of Cesium to realize the dynamic display of the airspace mesh occupancy status over time, supporting four-dimensional track management and flight conflict early warning.

[0039] Furthermore, step 4 specifically includes:

[0040] Step 4-1, definition of the spatiotemporal coding structure;

[0041] The spatiotemporal grid encoding format is defined as: [3D BeiDou grid code] + [start timestamp] + [end timestamp], where the timestamp adopts the YYYYMMDDHHMMSS format;

[0042] Step 4-2, Spatiotemporal State Visualization: In Cesium, using Cesium tools or a custom clock-driven mechanism, associate mesh entities with time attributes with the time axis; based on the current clock time, determine and dynamically display the occupancy status of the mesh at the current moment, and express it by changing the visual attributes of the mesh entities;

[0043] Step 4-3, Application of 4D Conflict Detection: In flight plan management, the grid occupied by the aircraft plan and its time window are encoded as a spatiotemporal grid; by comparing the spatiotemporal grid encoding of different aircraft plans and their overlapping relationship in time and space, simulation is performed on the Cesium time axis to visualize and predict potential flight conflicts in advance.

[0044] Compared with the prior art, the significant advantages of this invention are:

[0045] (1) It solves the technical gap between the Beidou grid national standard and 3D visualization applications: Through the self-developed "encoding-geometry bidirectional conversion algorithm" (including core functions such as coordinate to encoding and encoding to geometry), the abstract national standard "Beidou grid location code" encoding rules are transformed into an engineering algorithm that can be accurately generated and parsed in the Cesium 3D engine, realizing the direct mapping from "theoretical encoding rules" to "specific visualization graphics", filling the gap in existing technology that only has rule descriptions and lacks implementation methods.

[0046] (2) Achieved high-performance, real-time visualization rendering of massive 3D mesh data in low-altitude airspace: Through the self-developed "dynamic mesh scheduling engine based on window and hierarchy", the engine integrates algorithms such as getViewExtent (get window range), getIntersection (calculate effective intersection), getLevel (dynamic decision level) and reFlashGrid (dynamic rendering), and only renders the mesh at the current optimal level within the user's current window range and intersecting with the management area. It also adopts optimization strategies such as batch addition of entities and rendering height layer limit, which effectively overcomes the performance bottleneck when rendering tens of thousands or even millions of 3D mesh entities in the WebGL environment, and ensures the smooth interactive experience of the system.

[0047] (3) A digital management framework for low-altitude airspace integrating “encoding-visualization-interaction” has been established: By deeply integrating the self-developed encoding algorithm with the Cesium visualization engine, and constructing business modules such as ObstacleGridManager (obstacle management), RouteGridManager (airway management), and AircraftGridManager (aircraft management), unified grid-based encoding, classified and layered 3D rendering and direct interactive operation of core elements such as airspace environment (obstacles, no-fly zones), airspace structure (fixed / dynamic routes), and airspace operation (aircraft position, trajectory) have been realized, making management rules intuitive and operable.

[0048] (4) Provides accurate and quantifiable flight conflict early warning and interval management visualization means: Based on the self-developed "three-dimensional nine-square grid" safety interval model and conflict detection algorithm (detectConflicts), the spatial relationship between aircraft is quantified into grid overlap relationship (red-red, yellow-red, yellow-yellow), and different levels of conflict risk (serious warning, warning, early warning) are highlighted in real time in the three-dimensional scene, making the originally abstract safety interval rules intuitive and accurate, and improving the real-time and accuracy of supervision.

[0049] (5) It realizes the four-dimensional (spatial + temporal) dynamic planning and conflict pre-simulation capability of low-altitude airspace resources: Through the self-defined spatiotemporal grid data structure and encoding extension, the time dimension is integrated into grid management, and visualization is driven by the Cesium time axis. This enables the system to perform four-dimensional spatiotemporal simulation of flight plans, and to discover and visualize potential future spatiotemporal conflicts in advance at the plan submission stage, providing a forward-looking analysis tool for dynamic airspace management and traffic optimization.

[0050] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0051] Figure 1 This is an overall method flowchart provided in one embodiment.

[0052] Figure 2 This is a flowchart illustrating the bidirectional conversion algorithm between BeiDou grid coordinates and codes in one embodiment.

[0053] Figure 3 This is a flowchart of the Cesium-based dynamic grid visualization engine workflow in one embodiment.

[0054] Figure 4 This is a schematic diagram illustrating the effect of mesh-based isolation of airspace obstacles in one embodiment.

[0055] Figure 5 This is a schematic diagram illustrating the display effect of fixed route gridding and coded labels in one embodiment.

[0056] Figure 6 This is a visualization diagram of flight conflict risk warning based on a three-dimensional nine-square grid in one embodiment. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0058] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0059] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0060] In one embodiment, combined Figure 1 This paper provides a method for implementing digital BeiDou grid coding in low-altitude airspace based on Cesium, the method comprising the following steps:

[0061] Step 1: Based on existing geospatial subdivision and coding standards, achieve accurate bidirectional conversion between geographic coordinates and BeiDou 2D / 3D grid coding;

[0062] Step 2, build a large-scale mesh dynamic visualization engine based on Cesium: build an engine in Cesium that dynamically calculates and renders only the effective area and level of the 3D mesh based on the current viewport and scale.

[0063] Step 3, Construct a grid-based coding and integrated management framework for airspace elements: Grid-based coding and visualization of airspace environment, structure, and operational elements to construct an integrated management framework;

[0064] Step 4, Spatiotemporal grid encoding extension and four-dimensional visualization implementation: Extend the spatiotemporal encoding and implement dynamic visualization of grid occupancy status on the Cesium time axis.

[0065] Furthermore, in one embodiment, step 1 is specifically implemented through a code-geometry bidirectional conversion algorithm. This algorithm includes: a first algorithm that converts the latitude, longitude, and elevation coordinates of geographic spatial points into standard BeiDou two-dimensional and three-dimensional grid codes based on the partitioning rules defined in the standard "BeiDou Grid Location Code"; and a second algorithm that reverse-parses the standard BeiDou grid codes into geometric contour coordinates that can be rendered in the Cesium three-dimensional scene, while establishing a bidirectional automatic mapping relationship between the encoded data and the visualized graphics.

[0066] Preferably, in some embodiments, the first algorithm specifically includes:

[0067] (1) Coordinate to encoding conversion:

[0068] Based on the ten-level subdivision parameters of the BeiDou grid, the span of each grid level in the latitude, longitude and altitude directions is defined;

[0069] A first function is constructed to generate BeiDou two-dimensional grid codes. The input of the first function is the latitude B, longitude L and target level Level of a certain geographic point. The row and column positions of the geographic point in each level grid are calculated iteratively and then concatenated according to the national standard coding rules to generate the final BeiDou two-dimensional grid code string.

[0070] (2) Three-dimensional height domain encoding and calculation:

[0071] A second function is constructed to calculate the geodetic height of the bottom surface of each grid layer. This second function calculates the geodetic height of the bottom surface of the nth grid layer based on the BeiDou grid height subdivision formula. The specific calculation formula is as follows:

[0072]

[0073] In the formula, This represents the ground elevation of the nth grid layer. For the Earth's semi-major axis, This represents the radian value corresponding to 1°. This is the current latitude and longitude.

[0074] At the same time, a third function is constructed to infer the integer layer n in which a given height H is located;

[0075] Next, the derived n is converted into a 32-bit binary string according to the rules in Appendix C of the national standard, and then extracted and concatenated to form the height field encoding part of the three-dimensional code;

[0076] (3) Three-dimensional coding synthesis:

[0077] Combining the BeiDou two-dimensional grid code generated in (1) above with the height domain code generated in (2) above, a complete BeiDou three-dimensional grid code is synthesized according to the national standard format.

[0078] Preferably, in some embodiments, the second algorithm is used to calculate the grid spatial range from the BeiDou grid encoded string; the algorithm specifically includes:

[0079] For a given code, by parsing the row and column numbers of each level and combining them with the latitude and longitude span of the level, the latitude and longitude coordinates of the southwest corner (bottomLeftLon, bottomLeftLat) and the latitude and longitude coordinates of the northeast corner (topRightLon, topRightLat) of the grid space are calculated by summing them up, thereby determining the rectangular area of ​​the grid space in Cesium.

[0080] Furthermore, in one embodiment, step 2 specifically involves: integrating the algorithm used to implement step 1 into the Cesium 3D Earth engine to construct a dynamic mesh visualization engine; this dynamic mesh visualization engine dynamically calculates and renders only the 3D BeiDou mesh entities of the current level within the intersection area of ​​the user's current viewport range and the preset management airspace range, and combines the mesh level determined by the real-time calculated viewpoint height and scale, thereby achieving efficient loading of view-related meshes.

[0081] Preferably, in some embodiments, step 2 specifically includes:

[0082] Step 2-1, Dynamic monitoring and calculation of viewport extent: Use Cesiumr's ScreenSpaceEventHandler to monitor the user's mouse drag and scroll wheel operation events, and trigger viewport update after the operation is completed; at the same time, use Cesiumr's viewer.scene.camera.computeViewRectangle method to calculate in real time the rectangle of latitude and longitude range of the current camera viewport on the Earth's surface, i.e., the current viewport extent (viewExtent).

[0083] Step 2-2, Dynamic decision-making for visualization hierarchy: Calculate the scene scale ratio based on the current camera viewpoint height (position.height) and vertical field of view (frustum.fov); dynamically determine the optimal grid level (currentLevel) to be displayed based on the mapping relationship between the preset scale interval and the BeiDou grid level.

[0084] Steps 2-3, Calculation of effective rendering area: Perform an intersection operation on the current view window range viewExtent and the predefined low-altitude airspace management area range givenRegion (defined by Cesium.Rectangle.fromDegrees) to obtain the effective area to be rendered, renderRegion; if the intersection is empty, no mesh rendering is performed.

[0085] Steps 2-4, Dynamic Mesh Generation and Rendering: Based on the optimal mesh level currentLevel determined in Step 2-2, obtain the latitude and longitude span (lonStep, latStep) of this level; starting from the southwest corner of the effective region renderRegion, traverse the mesh with a step size of (lonStep, latStep). For each mesh position traversed, call the algorithm used in Step 1 to generate its encoding, and add a rectangular entity with a specific height based on the mesh range to the scene using Cesium; here, batch management technology of entities or primitives is used to improve rendering performance;

[0086] Steps 2-5, Rendering Optimization and Refresh: When user interaction causes changes in viewExtent or currentLevel, clear all mesh entities rendered in the previous frame, and re-execute steps 2-3 and 2-4 based on the new parameters to achieve dynamic and efficient mesh refresh.

[0087] Here, step 2 is the key to improving the practicality of this invention. Through a series of sub-steps, such as dynamically monitoring changes in the viewport, calculating the scale to determine the level, finding the intersection between the viewport and the management area, and dynamically generating and optimizing the rendering mesh entities, high-performance visualization of "what you see is what you render" is achieved.

[0088] Furthermore, in one embodiment, step 3 specifically involves applying steps 1 and 2 to perform BeiDou grid coding on the core elements of low-altitude airspace management, including airspace environmental elements, airspace structural elements, and airspace operational elements, and then performing classified, layered visualization rendering and interactive management in the Cesium 3D scene to form an integrated low-altitude airspace digital management framework of "coding-visualization-interaction".

[0089] Preferably, in some embodiments, step 3 specifically includes:

[0090] Meshization of airspace environmental elements: The boundary coordinates of obstacles (such as high-rise buildings and communication towers), no-fly zones, and preset specific areas (such as schools and gas stations) are converted into a set of BeiDou grid codes covering their space through the method in step 1, and rendered in Cesium as a semi-transparent filler of a specific color (such as red) to achieve visual isolation.

[0091] Airspace structural elements are gridded: fixed routes and dynamically planned routes are represented as a series of ordered BeiDou grid coding sequences; in Cesium, the route grid is rendered as a coherent channel, and coding labels can be attached to the center of the grid;

[0092] Grid-based airspace operation elements: The real-time position and historical trajectory of the aircraft are converted into corresponding grid codes and sequences through step 1; the highlighted display of the grid where the aircraft is located is updated in real time in Cesium, and the trajectory is rendered as pipelines formed by the grid sequence; based on the overlapping relationship between the grid where the aircraft is located and the surrounding "three-dimensional nine-square grid", the visualization and hierarchical warning of conflict risks (early warning, warning, severe warning) is realized.

[0093] Furthermore, in one embodiment, step 4 specifically involves: extending the time dimension on the basis of standard three-dimensional mesh coding, defining a spatiotemporal mesh coding structure that includes time windows, and visually representing this structure on the time axis module of Cesium to realize the dynamic display of the airspace mesh occupancy status over time, supporting four-dimensional track management and flight conflict early warning.

[0094] Preferably, in some embodiments, step 4 specifically includes:

[0095] Step 4-1, definition of the spatiotemporal coding structure;

[0096] The spatiotemporal grid encoding format is defined as: [3D BeiDou grid code] + [start timestamp] + [end timestamp], where the timestamp adopts the YYYYMMDDHHMMSS format;

[0097] Step 4-2, Spatiotemporal State Visualization: In Cesium, using Cesium tools (Cesium.TimeDynamicImagery) or a custom clock-driven mechanism, associate mesh entities with time attributes with the time axis; based on the current clock time, determine and dynamically display the current occupancy status of the mesh (such as occupied or idle), and express it by changing the visual attributes of the mesh entity (such as color, transparency, etc.);

[0098] Step 4-3, Application of 4D Conflict Detection: In flight plan management, the grid occupied by the aircraft plan and its time window are encoded as a spatiotemporal grid; by comparing the spatiotemporal grid encoding of different aircraft plans and their overlapping relationship in time and space, simulation is performed on the Cesium time axis to visualize and predict potential flight conflicts in advance.

[0099] Here, steps 3 and 4 demonstrate the application integration and expansion capabilities of the present invention, specifically applying coding and visualization technologies to various business aspects of airspace management, and innovatively introducing the time dimension.

[0100] In summary, this invention has the following innovative aspects:

[0101] The first innovation (core methodological innovation): A set of engineering implementation algorithms was proposed that deeply integrates the national standard "BeiDou Grid Location Code" with the Cesium 3D visualization engine. Specifically, this includes: 1) A bidirectional encoding-geometry conversion algorithm: A batch-efficient conversion algorithm was designed from latitude, longitude, and elevation coordinates to standard BeiDou 3D grid encoding, as well as a precise algorithm for reverse parsing the encoding into Cesium-recognizable 3D geometries (such as polyhedra and wireframes), establishing an automatic mapping bridge between encoded data and visualized graphics. 2) A large-scale 3D mesh LOD (Level of Detail) rendering optimization method: Addressing the multi-scale management needs of low-altitude airspace, a dynamic scheduling mechanism based on line-of-sight and grid level was designed, enabling the instantiation and frustum clipping of massive 3D meshes in Cesium, effectively solving the visualization performance bottleneck.

[0102] The second innovation (application integration innovation) is the pioneering "encoding-visualization-interaction" integrated low-altitude airspace management framework based on Cesium. This framework not only realizes the BeiDou grid encoding and real-time 3D rendering of airspace environment (such as obstacles, no-fly zones), airspace structure (such as fixed / dynamic routes), and airspace operation (such as aircraft position and trajectory) elements, but also supports interactive operations such as querying and editing grid attributes (such as adjusting isolation zones) and conflict warning (such as highlighting overlapping grids) directly in the 3D scene, transforming abstract encoding rules into intuitive and operable visualization management tools.

[0103] The third innovation (data structure and extension innovation): A "spatiotemporal grid" data structure and encoding extension implementation adapted to dynamic management of low-altitude airspace were designed. Based on standard BeiDou grid encoding, the time dimension was integrated to achieve efficient encoding, storage, and visualization of airspace grid occupancy time windows. This method can directly and dynamically display the changes in the occupancy status of airspace resources (such as a certain route grid) over time on the Cesium timeline, providing a unified visual analysis foundation for conflict detection of flight plans and four-dimensional (spatial + temporal) trajectory management.

[0104] Through the above innovations, this invention has successfully implemented the national standard of BeiDou grid coding from the theoretical rule level to a specific, efficient, and interactive three-dimensional visualization engineering application, solving the key technical gap problem of "having coding but no display, having rules but no algorithm", and providing a directly implementable technical solution for the refined, digital, and intelligent management of low-altitude airspace.

[0105] In one embodiment, a low-altitude airspace digital BeiDou grid coding implementation system based on Cesium is provided, the system comprising:

[0106] The first module is used to achieve: based on the existing geospatial subdivision and coding standards, realize the bidirectional accurate conversion between geographic coordinates and BeiDou two-dimensional / three-dimensional grid coding;

[0107] The second module is used to implement: building a large-scale mesh dynamic visualization engine based on Cesium: building an engine in Cesium that dynamically calculates and renders only the effective area and level of the 3D mesh based on the current viewport and scale;

[0108] The third module is used to realize: constructing a grid-based coding and integrated management framework for airspace elements: grid-based coding and visualization of airspace environment, structure, and operational elements to construct an integrated management framework;

[0109] The fourth module is used to implement: spatiotemporal grid encoding extension and four-dimensional visualization: extend spatiotemporal encoding and realize dynamic visualization of grid occupancy status on the Cesium time axis.

[0110] Specific limitations regarding the Cesium-based low-altitude airspace digital BeiDou grid coding implementation system can be found in the limitations of the Cesium-based low-altitude airspace digital BeiDou grid coding implementation method described above, and will not be repeated here. Each module in the aforementioned Cesium-based low-altitude airspace digital BeiDou grid coding implementation system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0111] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements:

[0112] Step 1: Based on existing geospatial subdivision and coding standards, achieve accurate bidirectional conversion between geographic coordinates and BeiDou 2D / 3D grid coding;

[0113] Step 2, build a large-scale mesh dynamic visualization engine based on Cesium: build an engine in Cesium that dynamically calculates and renders only the effective area and level of the 3D mesh based on the current viewport and scale.

[0114] Step 3, Construct a grid-based coding and integrated management framework for airspace elements: Grid-based coding and visualization of airspace environment, structure, and operational elements to construct an integrated management framework;

[0115] Step 4, Spatiotemporal grid encoding extension and four-dimensional visualization implementation: Extend the spatiotemporal encoding and implement dynamic visualization of grid occupancy status on the Cesium time axis.

[0116] For specific limitations on each step, please refer to the limitations of the Cesium-based low-altitude airspace digital BeiDou grid coding implementation method above, which will not be repeated here.

[0117] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program being implemented when executed by a processor:

[0118] Step 1: Based on existing geospatial subdivision and coding standards, achieve accurate bidirectional conversion between geographic coordinates and BeiDou 2D / 3D grid coding;

[0119] Step 2, build a large-scale mesh dynamic visualization engine based on Cesium: build an engine in Cesium that dynamically calculates and renders only the effective area and level of the 3D mesh based on the current viewport and scale.

[0120] Step 3, Construct a grid-based coding and integrated management framework for airspace elements: Grid-based coding and visualization of airspace environment, structure, and operational elements to construct an integrated management framework;

[0121] Step 4, Spatiotemporal grid encoding extension and four-dimensional visualization implementation: Extend the spatiotemporal encoding and implement dynamic visualization of grid occupancy status on the Cesium time axis.

[0122] For specific limitations on each step, please refer to the limitations of the Cesium-based low-altitude airspace digital BeiDou grid coding implementation method above, which will not be repeated here.

[0123] As a specific example, the invention will be further described in one embodiment.

[0124] The method provided in this embodiment of the invention mainly includes four core modules.

[0125] I. Implementation of the bidirectional encoding-geometry conversion algorithm (corresponding to step 1 and...) Figure 2 )

[0126] This embodiment first defines the ten-level subdivision parameters of the BeiDou grid. Taking program code as an example:

[0127] 1. Define the meshing parameters:

[0128] const latLevel = [4, 0.5, 10 / 60, 1 / 60, 4 / 3600, 2 / 3600, ...]; / / Latitude span

[0129] const lonLevel = [6, 0.5, 15 / 60, 1 / 60, 4 / 3600, 2 / 3600, ...]; / / Longitude span

[0130] const heightLevel = [4, 0.5, 15 / 60, ...]; / / Height span (degrees)

[0131] const layers = [Math.pow(2,7-1), Math.pow(2,10-1), ...]; / / Number of layers in each height direction

[0132] 2. Coordinate Conversion and Encoding (Self-developed Algorithm): Implement the GetBD2DBM(B, L, Level) function. The core logic of this function is iterative calculation: For the i-th level, based on the corner point (Q, Y) determined by the previous level and the current level's span (dB, dL), calculate the row number (a = floor((BQ) / dB)+1) and column number (b = floor((LY) / dL)+1) of the point (B, L) in this level. Then, convert the row and column numbers into encoded characters according to national standard rules (e.g., the encoding for level 1 is N / S + area code + row letter). This process transforms the description of "traversing and drawing a grid based on latitude, longitude, and the number of layers or height" into a precise algorithm.

[0133] 3. Height Encoding Calculation (Self-developed Algorithm): Implement the functions calculateGridHeight(n, theta) and calculateN(theta0, theta, H). The former calculates the bottom height of the nth layer according to the formula; the latter calculates the number of layers n based on the given height H, converts n into a 32-bit binary string, and then extracts the parts a0, a21, a3, ... a11 according to Appendix C of the national standard to form the height dimension encoding.

[0134] 4. Encoding to Geometry: For a given encoding (such as N47H15B), by reversing the parsing of the row and column numbers at each level, the latitude and longitude of the southwest corner of the grid can be calculated by summing them up, thereby constructing the Rectangle coordinates of Cesium and realizing the mapping from encoding to visualization range.

[0135] II. Construction of a large-scale mesh dynamic visualization engine based on Cesium (corresponding to step 2 and...) Figure 3 )

[0136] The core of this embodiment lies in dynamism and optimization. Taking program code as an example:

[0137] 1. Initialization and Listening: Create a Cesium Viewer and define the management space range givenRegion.

[0138] 2. Dynamic Decision-Making Loop (Self-Developed Logic):

[0139] Event triggering: Listen for events such as LEFT_UP and WHEEL using ScreenSpaceEventHandler, and call changeMouse().

[0140] Calculate the level: The getLevel() function calculates the scale ratio based on the camera height and determines the currentLevel according to the preset mapping table (e.g., ratio<5 => level=10).

[0141] Calculating the rendering region: `getViewExtent()` retrieves the current viewport's `viewExtent`, and `getIntersection(viewExtent, givenRegion)` calculates the intersection, `renderRegion`. This is crucial for performance optimization, preventing the rendering of invisible areas.

[0142] 3. Dynamic rendering (independently developed logic):

[0143] In the reFlashGrid(level) function, first clear all old entities: viewer.entities.removeAll().

[0144] Starting from the southwest corner of renderRegion, perform a triple loop (longitude, latitude, and altitude layers) with the intervals of lonStep and latStep corresponding to currentLevel.

[0145] In the inner loop, the algorithm from step 1 is called to calculate the center point code of the current grid, and a rectangular entity (Cesium.RectangleGeometry or Entity) is created using viewer.entities.add(). Its coordinates, stretch height, and outline color are set, and a code label is added to the center position.

[0146] By limiting the number of rendering height layers (e.g., if (n>3) break;) and only rendering the intersection area, the rendering load is greatly reduced.

[0147] III. Implementation of the Grid-based Coding and Integrated Management Framework for Airspace Elements (corresponding to step 3 and...) Figures 4-6 )

[0148] By applying the aforementioned basic capabilities, business scenario integration can be achieved.

[0149] 1. Spatial environment gridding (e.g.) Figure 4 The obstacle outline coordinate set is converted into a batch of BeiDou grid codes by traversing the geographic coordinates it covers. In Cesium, these grids are rendered as red-filled cubes to achieve visual isolation. This corresponds to the idea of ​​"gridizing specific areas such as obstacles" in the program.

[0150] 2. Spatial structure gridding (e.g.) Figure 5 For fixed routes, the waypoint sequence is converted into a grid-coded sequence distributed along the route. This is rendered as a continuous grid channel in Cesium, and the encoding can be displayed at the center of the grid, such as... Figure 5 As shown, this realizes the transformation from "fixed route design" to concrete visualization.

[0151] 3. Airspace operation gridding and conflict early warning (e.g.) Figure 6 ):

[0152] Aircraft positioning: Calculate the grid where the aircraft is located based on its real-time (lon, lat, alt) and highlight it (in red).

[0153] Conflict warning: Define a "3D nine-square grid" as a safety interval (yellow grid) for each aircraft. Calculate the spatial relationship between the red and yellow grids for different aircraft in real time. For example... Figure 6 As shown, when the yellow grids of two aircraft overlap, a "warning" is triggered; when yellow and red grids overlap, a "warning" is triggered; and when red and red grids overlap, a "serious warning" is triggered. This transforms the textual descriptions of "flight spacing control" and "conflict risk warning" into intuitive visual logic.

[0154] IV. Spatiotemporal grid coding extension and four-dimensional visualization implementation (corresponding to step 4)

[0155] 1. Data Structure Extension: Define a grid object with the following attributes: {gridCode: “3D encoding”, startTime: “20241120103000”, endTime: “20241120103030”}.

[0156] 2. Cesium Timeline Integration: Utilizing Cesium.JulianDate and viewer.clock. In the clock callback, iterate through all spatiotemporal grid objects and determine if the current clock time falls within the [startTime, endTime] interval of a certain grid. If so, highlight the grid in the scene; otherwise, display it in its default state or hide it.

[0157] 3. Application: In the flight plan management interface, users can submit planned flight routes and their times. The system converts the plan into a spatiotemporal grid sequence and plays it on the Cesium timeline. Managers can intuitively see which grids in the airspace will be occupied at any future time, thus identifying spatiotemporally overlapping conflicting plans in advance.

[0158] In summary, this invention solves the core technical challenges in the digital management of low-altitude airspace, from coding standards to 3D visualization applications, through a complete technical solution encompassing both algorithms and integration. The method of this invention has advantages such as high engineering feasibility, excellent visualization performance, and strong business relevance, effectively supporting the safe, efficient, and intelligent management of low-altitude airspace.

[0159] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention without departing from its spirit and scope should be included within the protection scope of the present invention.

Claims

1. A method for implementing digital BeiDou grid coding in low-altitude airspace based on Cesium, characterized in that, The method includes the following steps: Step 1: Based on existing geospatial subdivision and coding standards, achieve accurate bidirectional conversion between geographic coordinates and BeiDou 2D / 3D grid coding; Step 2, build a large-scale mesh dynamic visualization engine based on Cesium: build an engine in Cesium that dynamically calculates and renders only the effective area and level of the 3D mesh based on the current viewport and scale. Step 3, Construct a grid-based coding and integrated management framework for airspace elements: Grid-based coding and visualization of airspace environment, structure, and operational elements to construct an integrated management framework; Step 4, Spatiotemporal grid encoding extension and four-dimensional visualization implementation: Extend the spatiotemporal encoding and implement dynamic visualization of grid occupancy status on the Cesium time axis.

2. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 1, characterized in that, Step 1 is specifically implemented through a two-way encoding-geometry conversion algorithm. This algorithm includes: a first algorithm that converts the latitude, longitude, and elevation coordinates of geographic points into standard BeiDou two-dimensional and three-dimensional grid codes based on the partitioning rules defined in the standard "BeiDou Grid Location Code"; and a second algorithm that reverse-parses the standard BeiDou grid codes into geometric outline coordinates that can be rendered in the Cesium three-dimensional scene. At the same time, a two-way automatic mapping relationship is established between the encoded data and the visualized graphics.

3. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 2, characterized in that, The first algorithm specifically includes: (1) Coordinate to encoding conversion: Based on the ten-level subdivision parameters of the BeiDou grid, the span of each grid level in the latitude, longitude and altitude directions is defined; A first function is constructed to generate BeiDou two-dimensional grid codes. The input of the first function is the latitude B, longitude L and target level Level of a certain geographic point. The row and column positions of the geographic point in each level grid are calculated iteratively and then concatenated according to the national standard coding rules to generate the final BeiDou two-dimensional grid code string. (2) Three-dimensional height domain encoding and calculation: A second function is constructed to calculate the geodetic height of the bottom surface of each grid layer. This second function calculates the geodetic height of the bottom surface of the nth grid layer based on the BeiDou grid height subdivision formula. The specific calculation formula is as follows: ； In the formula, Indicates the first The bottom surface of the layered grid is at ground level. For the Earth's semi-major axis, The difference in latitude / longitude span corresponding to the base grid defined for the initial subdivision range, in radians; This represents the difference in longitude or latitude span corresponding to the grid, in radians. At the same time, a third function is constructed to infer the integer layer n in which a given height H is located; Next, the derived n is converted into a 32-bit binary string according to the rules in Appendix C of the national standard, and then extracted and concatenated to form the height field encoding part of the three-dimensional code; (3) Three-dimensional coding synthesis: Combining the BeiDou two-dimensional grid code generated in (1) above with the height domain code generated in (2) above, a complete BeiDou three-dimensional grid code is synthesized according to the national standard format.

4. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 2, characterized in that, The second algorithm is used to calculate the grid spatial range from the BeiDou grid encoded string; the algorithm specifically includes: For a given code, by parsing the row and column numbers of each level and combining them with the latitude and longitude span of the level, the latitude and longitude coordinates of the southwest corner (bottomLeftLon, bottomLeftLat) and the latitude and longitude coordinates of the northeast corner (topRightLon, topRightLat) of the grid space are calculated by summing them up, thereby determining the rectangular area of ​​the grid space in Cesium.

5. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 1, characterized in that, Step 2 specifically involves integrating the algorithm used in Step 1 into the Cesium 3D Earth Engine to construct a dynamic mesh visualization engine. This dynamic mesh visualization engine dynamically calculates and renders only the 3D BeiDou mesh entities at the current level within the intersection area of ​​the user's current viewport and the preset management airspace range, combined with the mesh level determined by the real-time calculated viewpoint height and scale, thereby achieving efficient loading of view-related meshes.

6. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 5, characterized in that, Step 2 specifically includes: Step 2-1, Dynamic monitoring and calculation of viewport: Use Cesiumr to monitor the user's mouse drag and scroll wheel operation events, and trigger the viewport update after the operation is completed; at the same time, use Cesiumr to calculate the rectangle of the latitude and longitude range of the current camera viewport on the Earth's surface in real time, that is, the current viewport range (viewExtent). Step 2-2, Visualization Hierarchical Dynamic Decision: Calculate the scene scale based on the current camera viewpoint height and vertical field of view; dynamically determine the optimal grid level to be displayed, currentLevel, based on the preset mapping relationship between the scale range and the BeiDou grid levels. Steps 2-3, Calculation of effective rendering area: Perform an intersection operation on the current view window range viewExtent and the predefined low-altitude airspace management area range givenRegion to obtain the effective area to be rendered, renderRegion; if the intersection is empty, no mesh rendering is performed. Step 2-4, Dynamic Mesh Generation and Rendering: Based on the optimal mesh level currentLevel determined in Step 2-2, obtain the latitude and longitude span (lonStep, latStep) of this level; Starting from the southwest corner of the effective region renderRegion, traverse the mesh with a step size of (lonStep, latStep). For each mesh position traversed, call the algorithm used to implement Step 1 to generate its encoding, and add a rectangular entity with a specific height based on the mesh range to the scene using Cesium; Steps 2-5, Rendering Optimization and Refresh: When user interaction causes changes in viewExtent or currentLevel, clear all mesh entities rendered in the previous frame, and re-execute steps 2-3 and 2-4 based on the new parameters to achieve dynamic and efficient mesh refresh.

7. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 1, characterized in that, Step 3 specifically involves applying Step 1 and Step 2 to perform BeiDou grid coding on the core elements of low-altitude airspace management, including airspace environmental elements, airspace structural elements, and airspace operational elements. These elements are then classified, layered, visualized, rendered, and interactively managed in the Cesium 3D scene, forming an integrated "coding-visualization-interaction" low-altitude airspace digital management framework.

8. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 7, characterized in that, Step 3 specifically includes: Meshization of airspace environmental elements: The boundary coordinates of obstacles, no-fly zones, and preset specific areas are converted into a set of BeiDou grid codes covering their space through the method in step 1, and rendered as a semi-transparent fill of a specific color in Cesium to achieve visual isolation; Airspace structural elements are gridded: fixed routes and dynamically planned routes are represented as a series of ordered BeiDou grid coding sequences; in Cesium, the route grid is rendered as a coherent channel, and coding labels can be attached to the center of the grid; Grid-based airspace operation elements: The real-time position and historical trajectory of the aircraft are converted into corresponding grid codes and sequences through step 1; the highlighted display of the grid where the aircraft is located is updated in real time in Cesium, and the trajectory is rendered as a pipeline formed by the grid sequence; based on the overlapping relationship between the grid where the aircraft is located and the surrounding "3D nine-square grid", a visual and graded warning of conflict risk is realized.

9. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 1, characterized in that, Step 4 specifically involves: based on standard 3D mesh coding, extending the time dimension, defining a spatiotemporal mesh coding structure that includes time windows, and visualizing this structure on the Cesium time axis module to achieve dynamic display of airspace mesh occupancy status over time, supporting 4D track management and flight conflict early warning.

10. The method for implementing low-altitude airspace digital BeiDou grid coding based on Cesium according to claim 9, characterized in that, Step 4 specifically includes: Step 4-1, definition of the spatiotemporal coding structure; The spatiotemporal grid encoding format is defined as: [3D BeiDou grid code] + [start timestamp] + [end timestamp], where the timestamp adopts the YYYYMMDDHHMMSS format; Step 4-2, Spatiotemporal State Visualization: In Cesium, using Cesium tools or a custom clock-driven mechanism, associate mesh entities with time attributes with the time axis; based on the current clock time, determine and dynamically display the occupancy status of the mesh at the current moment, and express it by changing the visual attributes of the mesh entities; Step 4-3, Application of 4D Conflict Detection: In flight plan management, the grid occupied by the aircraft plan and its time window are encoded as a spatiotemporal grid; by comparing the spatiotemporal grid encoding of different aircraft plans and their overlapping relationship in time and space, simulation is performed on the Cesium time axis to visualize and predict potential flight conflicts in advance.

Images