Ground feature Beidou grid data generation method and device

Abstract

The invention discloses a ground feature Beidou grid data generation method. The method comprises the following steps: determining a ground feature polygonal patch set under a projection coordinate system according to a ground feature three-dimensional model; constructing an axial bounding box according to the polygonal patch set; determining an effective grid unit model of the ground object three-dimensional model according to the axial bounding box and the hierarchical precision of the Beidou grid; and calculating a Beidou grid code according to the central point geographic coordinate of each grid unit of the effective grid unit model, and adding Beidou grid attribute information corresponding to the Beidou grid code to the attribute of the corresponding grid unit to obtain ground feature Beidou grid data. According to the method, the spatial reference frame consistent with the Beidou grid system can be established for the three-dimensional universal model in any format, and the calculation efficiency is improved. The invention further discloses a device for implementing the method, electronic equipment and a storage medium.

Description

Technical Field

[0001] The present invention relates to the field of geographic information technology, and in particular to a method and device for generating Beidou grid data of land objects. Background Art

[0002] Beidou grid code, a spatial location encoding standard independently developed by my country, achieves globally unique spatial identification through a composite encoding of latitude, longitude, and hierarchy. Its refined hierarchical division (particularly centimeter-level grids with 23 to 32 levels) provides a foundational framework for high-precision spatial services. The essence of Beidou grid mapping technology is to embed three-dimensional models into a globally unified reference frame through the stereoscopic segmentation and discretization of Earth space. Its core concept is to divide the continuous three-dimensional geographic space into regular or irregular grid cells (voxels), assigning each cell a unique code. This achieves: standardized identification of spatial locations, eliminating heterogeneity across different coordinate systems and data formats; multi-scale representation: hierarchical grids (e.g., from kilometers to centimeters) support LOD (level of detail) model management; and efficient spatial computation: integer-coded grid operations (such as neighborhood queries and spatial relationship determination) replace traditional floating-point calculations.

[0003] Although Beidou grid mapping technology has shown great potential in the fields of three-dimensional spatial modeling, digital twins, smart cities, etc., it still has several key defects in practical applications, mainly including the following aspects: the voxelization process is time-consuming and computationally inefficient for large-scale models (such as city-level CIM), three-dimensional models from different sources (such as BIM, point clouds, and oblique photography) need to be uniformly converted into grid codes, and the algorithm for converting three-dimensional models to Beidou grid mapping is complex and cannot be unified. Summary of the Invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a method and device for generating Beidou grid data for ground objects. The technical problem to be solved by the present invention is achieved through the following technical solutions: A first aspect of an embodiment of the present invention provides a method for generating Beidou grid data of a ground feature, comprising the following steps: Determine the polygonal patch set of the feature in the projection coordinate system according to the three-dimensional model of the feature; Constructing an axial bounding box based on the polygonal facet set; Determining a valid grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid; The Beidou grid code is calculated according to the geographical coordinates of the center point of each grid cell of the valid grid cell model, and the Beidou grid attribute information corresponding to the Beidou grid code is added to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

[0005] In one embodiment of the present invention, constructing an axial bounding box based on the polygonal facet set includes: Constructing an axial bounding box of a three-dimensional model of a ground object according to the polygonal facet set; Determine the center grid cell where the center point of the feature is located by using the GeoSOT grid algorithm according to the coordinates of the center point of the feature in the geographic coordinate system of the three-dimensional model of the feature; Determining a grid reference origin of the finest level according to the projection coordinates of each vertex of the central grid unit; According to the grid reference origin, the axial bounding box of the three-dimensional model of the ground object is expanded with a single step size of the Beidou grid to generate an initial three-dimensional grid space and a corresponding initial three-dimensional Boolean matrix with an initial mark in an invalid state; Performing a subdivision process on the polygonal face set to obtain a sub-face set; An axial bounding box of each sub-patch is determined according to the sub-patch set.

[0006] In one embodiment of the present invention, determining the effective grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid includes: The geometric intersection of the axial bounding box of each sub-facet and the initial three-dimensional grid space is calculated, and the grid cells with the intersection are marked as valid in the initial three-dimensional Boolean matrix to obtain the valid grid cell model and the invalid grid cell model of the three-dimensional model of the ground object.

[0007] In one embodiment of the present invention, the step of calculating a Beidou grid code based on the geographic coordinates of the center point of each grid cell of the valid grid cell model, and adding Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell to obtain the ground feature Beidou grid data includes: The projection coordinates of the center point of each grid cell in the valid grid cell model are converted into geographic coordinates, and the Beidou grid code is calculated. The Beidou grid attribute information corresponding to the Beidou grid code is added to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

[0008] In one embodiment of the present invention, constructing an axial bounding box based on the polygonal facet set includes: Constructing an AABBTree structure according to the polygonal face set; At least one light source and light direction are set according to the coordinates of the vertices of the three-dimensional model of the ground object in the three-dimensional coordinate system of the Beidou grid; wherein the light density of the light source is the hierarchical accuracy of the bottom layer of the Beidou grid of the target; A plurality of axial bounding boxes are determined according to the AABBTree structure, intersection points of the light emitted by the light source according to the light direction and the light density and the plurality of polygonal facets.

[0009] In one embodiment of the present invention, the step of setting at least one light source and light direction according to the coordinates of the vertices of the three-dimensional model of the ground object in the Beidou grid three-dimensional coordinate system includes: Constructing an outer bounding box according to the coordinates of the vertices of the three-dimensional model of the ground object in the Beidou grid three-dimensional coordinate system; A light source is provided on at least one surface of the outer bounding box; wherein the light ray of the light source is parallel to one axis of the three-dimensional coordinate axis of the coordinate system of the Beidou grid, and the axis is perpendicular to the surface where the light source is located.

[0010] In one embodiment of the present invention, determining the effective grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid includes: The outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box; The axial bounding box is matched with the leaf nodes of the octree to generate a valid grid unit model and an invalid grid unit of the three-dimensional model of the ground object.

[0011] In one embodiment of the present invention, the outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box, including: Taking the outer bounding box as the root node of the octree; Matching the initial accuracy of the three-dimensional model of the ground object with the hierarchical accuracy of the Beidou grid, and determining the hierarchical accuracy of the bottom layer of the target Beidou grid as the cutting density; The outer bounding box is cut according to the Beidou grid subdivision rule and the cutting density to obtain multiple grid units of a three-dimensional grid structure, and the multiple grid units are leaf nodes of the octree.

[0012] In one embodiment of the present invention, the method further comprises: Generate an octree topology structure according to the ground feature Beidou grid data and the invalid grid unit; Determination step: based on the octree topology structure, determining whether any grid unit of a valid leaf node at each level of any perspective has an adjacent grid unit of a valid leaf node; If so, the grid cells of the adjacent multiple valid leaf nodes are determined as a connected region, and the determination step is returned to traverse all valid leaf nodes at each level to obtain a connected region set; Traversing each connected region in the connected region set, and determining the simplest contour of the connected region to generate a target contour set; Divide the target contour set according to a polygonal decomposition algorithm to generate a target polygonal grid set; Deduplicating vertices of the target polygonal grid set to obtain a heterogeneous grid octree structure; The heterogeneous grid octree structure is subjected to bottom-up node aggregation to generate a multi-level LOD model.

[0013] A second aspect of an embodiment of the present invention provides a device for generating Beidou grid data for ground objects, including: A determination module, for determining a polygonal facet set of a ground object in a projection coordinate system according to a three-dimensional ground object model; A construction module, configured to construct an axial bounding box according to the polygonal facet set; A generating module, configured to determine a valid grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid; The calculation module is used to calculate the Beidou grid code according to the geographical coordinates of the center point of each grid cell of the effective grid cell model, and add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

[0014] Beneficial effects of the present invention: The present invention establishes a spatial reference frame consistent with the Beidou grid system for a three-dimensional general model of any format through the axial bounding box of the three-dimensional model of the object and the hierarchical accuracy of the Beidou grid. The Beidou grid mapping method is simple and fast, which improves the calculation efficiency while ensuring the calculation accuracy.

[0015] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0016] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 A schematic diagram of a process for generating Beidou grid data of a ground feature provided by an embodiment of the present invention; Figure 2 A schematic block diagram of a device for generating Beidou grid data for ground features provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The present invention will be further described in detail below with reference to specific examples, but the embodiments of the present invention are not limited thereto.

[0019] like Figure 1 As shown, a first aspect of an embodiment of the present invention provides a method for generating Beidou grid data of a ground feature, comprising the following steps: Step 101: Determine a polygonal facet set of the object in a projection coordinate system according to the three-dimensional model of the object.

[0020] Step 102: construct an axial bounding box based on the polygonal facet set.

[0021] Step 103 : determining a valid grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid.

[0022] Step 104 , calculating the Beidou grid code according to the geographical coordinates of the center point of each grid cell of the valid grid cell model, adding the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell, and obtaining the Beidou grid data of the ground feature.

[0023] The present invention establishes a spatial reference frame consistent with the Beidou grid system for a three-dimensional general model of any format through the axial bounding box of the three-dimensional model of the object and the hierarchical accuracy of the Beidou grid. The Beidou grid mapping method is simple and fast, which improves the calculation efficiency while ensuring the calculation accuracy.

[0024] On the basis of the first aspect of the embodiment of the present invention, the second aspect of the embodiment of the present invention further describes in detail a method for generating Beidou grid data of a ground object. The second aspect of the embodiment of the present invention provides a method for generating Beidou grid data of a ground object, comprising the following steps: Step 201 : determining the coordinates of the center point of the feature in the geographic coordinate system according to the three-dimensional feature model and determining a polygonal facet set of the feature in the projection coordinate system according to the three-dimensional feature model.

[0025] In this step, the three-dimensional model of the ground object may be a model with triangular surfaces as units, and may be data in formats such as OBJ, PLY, and STL.

[0026] Specifically, the three-dimensional model of the ground object is converted into a set of triangular facets or quadrilateral facets. The following steps are specifically described using triangular facets as an example.

[0027] Step 202: construct an axial bounding box of the three-dimensional model of the ground object based on the set of triangle faces.

[0028] Step 203: Determine the center grid cell where the center point of the feature is located according to the GeoSOT grid algorithm. The center grid cell here is the top grid cell.

[0029] Step 204 : Determine the grid reference origin of the finest level according to the projection coordinates of each vertex of the central grid unit.

[0030] In this step, the spatial coordinates of the eight vertices of the central grid unit are obtained by parsing, and then the spatial coordinates of the eight vertices are converted into projection coordinates in a projection coordinate system, wherein the projection coordinates of any vertex are used as the grid reference origin of the finest level.

[0031] Step 205: Based on the grid reference origin, the axial bounding box of the three-dimensional model of the ground object is expanded along the X, Y, and Z axes with a single step size of the Beidou grid according to the Beidou grid subdivision rule to align it with the grid, generating a regular initial three-dimensional grid space with hierarchical accuracy based on the Beidou grid and a corresponding initial three-dimensional Boolean matrix with an initial mark as invalid.

[0032] Among them, all grid cells in the initial three-dimensional Boolean matrix are initially marked as false (invalid), representing the "unoccupied" state.

[0033] Step 206: Subdivide the triangular face set to obtain a sub-face set.

[0034] In this step, the triangular facet set is adaptively subdivided. When traversing each triangular facet, if its area or maximum edge length exceeds a preset threshold (S_threshold / L_threshold), the facet is recursively subdivided using a quartering algorithm. After subdivision, the algorithm determines whether the area or maximum edge length of each sub-facet exceeds the preset threshold. Sub-facets that exceed the threshold are further subdivided using the quartering algorithm until the area or maximum edge length of the sub-facet falls below the threshold, resulting in the final sub-facet set. A first-in, first-out queue dynamically manages the facets to be processed. The preset threshold is the hierarchical accuracy of the Beidou grid.

[0035] Step 207 calculates the geometric intersection of the axial bounding box of each sub-patch in the sub-patch set with the initial three-dimensional grid space. Grid cells with an intersection are marked as valid (i.e., occupied) in the initial three-dimensional Boolean matrix, while grid cells without an intersection are initially marked as invalid. Ultimately, the precise occupancy distribution of the model in the Beidou grid is obtained. This provides a model of valid and invalid grid cells.

[0036] Step 208 : convert the projection coordinates of the center point of each grid cell in the valid grid cell model into geographic coordinates, calculate the Beidou grid code, add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell, and obtain the Beidou grid data of the ground feature.

[0037] In this step, the center point projection coordinates of the valid grid cells are reverse-projected to the geographic coordinate system, and the GeoSOT encoding rules are applied to the center point geographic coordinates of the valid grid cells to calculate the unique GeoSOT grid code (GeoSOTCode). This grid code serves as the Beidou grid code and simultaneously stores the grid cell level (GeoSOTLevel), center point projection coordinates (Center) and custom attributes (such as BuildID, BuildName, and TimeStamp), giving structured attributes to the valid grid cells and realizing the standardized mapping of the three-dimensional model to the Beidou grid system.

[0038] Preferably, the BeiDou system identifier, other additional information required by the BeiDou system, or encrypted fields can be added to the GeoSOT grid code to obtain the final BeiDou grid code. The segmentation level can also be adjusted based on BeiDou positioning accuracy (e.g., centimeter level).

[0039] In this embodiment, the grid reference origin of the most refined level is determined by the three-dimensional model of the object, and the axial bounding box of the three-dimensional model of the object is then expanded to generate a three-dimensional grid space. Then, by subdividing the polygonal patch, the geometric intersection of the axial bounding box of the sub-patch and the grid space is calculated to determine the occupied valid grid cells. Based on the coordinates of the occupied grid center point, the GeoSOT encoding rules are used to generate a grid unique identifier GeoSOT grid code, which serves as the Beidou grid code. The Beidou grid mapping method of this embodiment is simple and fast, and can establish a spatial reference frame consistent with the Beidou grid system for a three-dimensional general model of any format, improving calculation efficiency while ensuring calculation accuracy.

[0040] On the basis of the first aspect of the embodiment of the present invention, the third aspect of the embodiment of the present invention further describes in detail a method for generating Beidou grid data of a ground object. The third aspect of the embodiment of the present invention provides a method for generating Beidou grid data of a ground object, comprising the following steps: Step 301: Determine a polygonal facet set of the object in a projection coordinate system according to the three-dimensional model of the object.

[0041] In this step, the three-dimensional model of the ground object may be a model with triangular surfaces as units, and may be data in formats such as OBJ, PLY, and STL.

[0042] Specifically, the three-dimensional model of the ground object is converted into a set of triangular facets or quadrilateral facets. The following steps are specifically described using triangular facets as an example.

[0043] Step 302: construct an AABBTree structure based on the triangle face set.

[0044] Specifically, step 302 includes steps 3021 to 3023: Step 3021: Use multiple triangles as leaf nodes of AABBTree to generate an AABBTree structure.

[0045] Step 3022: Calculate the relative distances of the plurality of triangular facets based on the coordinates of the triangular facets in the three-dimensional model space of the object. The relative distances refer to the distances between different axes of the triangular facets relative to the three-dimensional coordinate axes.

[0046] Step 3023: merge each pair of adjacent leaf nodes into a parent node of the AABBTree according to the relative distances of the multiple sub-triangle facets, and recursively construct until all leaf nodes are merged into a root node, thereby generating an AABBTree structure.

[0047] Calculate the distance variance of multiple triangles relative to different axes of the 3D coordinate axis, and use the axis with the smallest distance variance as the merging direction of the merging node. Merge each pair of adjacent leaf nodes into a parent node along the merging direction.

[0048] Step 303 : setting at least one light source and light direction according to the coordinates of the vertices of the three-dimensional model of the ground object in the Beidou grid three-dimensional coordinate system.

[0049] Among them, the light density of the light source is the hierarchical accuracy of the target's lowest-level Beidou grid.

[0050] In this step, the light source is set outside the 3D object model, that is, on the surface of the bounding box outside the 3D object model. The light orientation of the light source refers to the direction of the light source's illumination. The light density of the light source refers to the distance between adjacent parallel light beams. The smaller the distance between adjacent parallel light beams, the greater the light density of the light source, indicating a higher accuracy of the Beidou grid.

[0051] Specifically, step 303 includes steps 3031 and 3032: Step 3031: construct an outer bounding box according to the coordinates of the vertices of the three-dimensional model of the ground object in the Beidou grid three-dimensional coordinate system.

[0052] Step 3032: Set a light source on at least one surface of the outer bounding box.

[0053] The light direction of the light source is parallel to one axis of the three-dimensional coordinate axis of the coordinate system of the Beidou grid, and the axis is perpendicular to the surface where the light source is located.

[0054] In this step, the outer bounding box is a hexagon, and two of the six faces of the outer bounding box are parallel to the X, Y, and Z axes of the Beidou grid. In the embodiment of the present invention, light sources can be provided on any one, any two, or all three faces parallel to the X, Y, and Z planes.

[0055] Step 304 : Determine a plurality of axial bounding boxes based on the AABBTree structure and the intersection points of the light rays emitted by the light source according to the light direction and light density and the plurality of triangular facets.

[0056] In this step, intersection points include both intersection points and tangent points. The ray is projected end-to-end from the outer bounding box. During penetration, it intersects with many triangles within the 3D model. The calculation treats the triangles as a 3D grid, and a single projection calculates all triangles within a given distance range.

[0057] The intersection point can be determined by using the odd-even rule in computer graphics to determine the inner and outer points. The inner point is the intersection point, and the outer point is the tangent point.

[0058] The 3D model of the object is segmented according to the light density along the direction of the light. Each segmented subspace is called an axial bounding box. The axial bounding box is an axis-aligned cube or cuboid with its faces parallel to the coordinate axes.

[0059] In step 304, a plurality of axial bounding boxes are determined according to the intersection points of the light emitted by the light source according to the light direction and light density and the plurality of sub-triangular faces, which may include steps 3041 and 3042: Step 3041: obtain the intersection points and tangent points of the light emitted by the light source according to the light direction and light density and the multiple triangular faces through a parallel computing strategy and a spatial geometry search based on the AABBTree structure.

[0060] The AABBTree structure uses parallel computing strategies to detect multiple rays at the same time and obtain the intersection and tangent points of each ray with multiple triangles.

[0061] Step 3042: Connect two adjacent even-odd intersections passing through the triangular face to construct a grid unit and determine it as an axial bounding box. The even-odd intersection refers to an odd-numbered intersection and an adjacent even-numbered intersection.

[0062] In step 305 , the outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box.

[0063] Specifically, step 305 includes steps 3051 to 3053: Step 3051: Use the outer bounding box as the root node of the octree.

[0064] Step 3052: Match the initial accuracy of the three-dimensional model of the ground object with the hierarchical accuracy of the Beidou grid, and determine the hierarchical accuracy of the target bottom-layer Beidou grid as the cutting density.

[0065] In this step, based on the initial accuracy of the three-dimensional model of the ground object as the initial bottom-level accuracy, the bottom-level accuracy interval including the initial accuracy can be determined in the layer accuracy of the Beidou grid, and the layer accuracy higher than the initial accuracy is selected as the layer accuracy of the target bottom-level Beidou grid, which is also the bottom-level expected accuracy of this application. The initial bottom-level accuracy can also be set as needed. The accuracy of the top-level Beidou grid corresponding to the three-dimensional model of the ground object is set as needed.

[0066] Step 3053: Cut the outer bounding box according to the Beidou grid subdivision rule and cutting density to obtain multiple grid units of the three-dimensional grid structure, and the multiple grid units are leaf nodes of the octree.

[0067] In step 3053, the grid cells are constructed using the Beidou grid subdivision rule, expressed as center point coordinates and length, width, and height. To merge nodes, this embodiment of the present invention converts the grid structure into an octree structure, where each grid cell represents a leaf node in the octree. Subnodes are merged when a subtree is full, with the final leaf node being the merged grid cell data.

[0068] Step 306 : performing node matching between the axial bounding box and the leaf nodes of the octree to generate valid grid unit models and invalid grid units of the three-dimensional model of the ground object.

[0069] The specific steps of step 306 include: step 3061-step 3063: In step 3061, each axial bounding box is matched to the grid cell of the leaf node of the octree at the same location in the 3D model of the feature. An axial bounding box is a grid. Because the target Beidou grid's lowest level precision and light density are the same, the size of the axial bounding box is the same as the size (precision) of the grid cell.

[0070] Step 3062: When the axial bounding box successfully matches the grid cell, the grid cell of the leaf node is marked as valid and serves as the leaf node of the octree; when the axial bounding box fails to match the grid cell, the grid cell of the leaf node is marked as invalid, thereby obtaining valid grid cells and invalid grid cells.

[0071] Because the outer bounding box is larger than the 3D object model, some corners of the outer bounding box are not within the 3D object model. Valid grid cells are within the 3D object model, while invalid grid cells are within the outer bounding box but outside the 3D object model. The bounding box is matched to the grid cells. A successful match indicates a valid grid cell, while an unsuccessful match indicates an invalid grid cell.

[0072] Step 3063: merge the valid leaf nodes of the octree to generate a valid grid unit model.

[0073] The embodiment of the present invention aims to represent the 3D model of a terrain feature using as few bounding boxes as possible. After matching is complete, the octree structure of valid grid cells is merged. This embodiment of the present invention uses a depth-based post-order traversal algorithm to merge leaf nodes. After merging, invalid grid cells can be deleted.

[0074] Step 307 : convert the projection coordinates of the center point of each grid cell in the valid grid cell model into geographic coordinates, calculate the Beidou grid code, add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell, and obtain the Beidou grid data of the ground feature.

[0075] In this step, the geographic coordinates of the center point of the valid grid cell are calculated using the GeoSOT encoding rules to obtain the Beidou grid unique identification grid code (GeoSOTCode). The grid cell level (GeoSOTLevel), center point projection coordinates (Center) and custom attributes (such as BuildID, BuildName, TimeStamp) of the grid cell are simultaneously stored. This gives structured attributes to the valid grid cell and realizes the standardized mapping of the three-dimensional model to the Beidou grid system.

[0076] In this embodiment, AABBTree is used for collision detection during the ray-passing process. The grid unit construction rules are based on the Beidou grid rules. Finally, after the grid units are constructed, they are aggregated using the octree rules and the Beidou grid code is calculated. By introducing the AABBTree structure, setting the light source position, and designing a grid unit model generation algorithm under the Beidou grid rules, a high-precision, low-consumption three-dimensional model can be quickly generated. This greatly reduces the amount of data storage while ensuring accuracy. The Beidou grid mapping method of this embodiment is simple and fast, and can establish a spatial reference frame consistent with the Beidou grid system for a three-dimensional general model in any format, improving computational efficiency while ensuring computational accuracy.

[0077] A fourth aspect of the embodiment of the present invention provides, on the basis of the second aspect of the embodiment of the present invention, a method for generating an LOD model based on a method for generating Beidou grid data of ground objects, comprising the following steps: Step 401 : determining the coordinates of the center point of the feature in the geographic coordinate system according to the feature 3D model and determining a set of feature triangles in the projection coordinate system according to the feature 3D model.

[0078] Step 402: construct an axial bounding box of the three-dimensional model of the ground object based on the set of triangle faces.

[0079] Step 403: Determine the center grid cell where the center point of the feature is located according to the GeoSOT grid algorithm. The center grid cell here is the top grid cell.

[0080] Step 404 : Determine the grid reference origin of the finest level based on the projection coordinates of each vertex of the central grid unit.

[0081] Step 405: Based on the grid reference origin, the axial bounding box of the three-dimensional model of the feature is expanded along the X, Y, and Z axes with a single step size of the Beidou grid according to the Beidou grid subdivision rule to align it to the grid, generating a regular initial three-dimensional grid space with hierarchical accuracy based on the Beidou grid and a corresponding initial three-dimensional Boolean matrix with an initial mark as invalid.

[0082] Step 406: Subdivide the triangular face set to obtain a sub-face set.

[0083] Step 407 calculates the geometric intersection of the axial bounding box of each sub-patch in the sub-patch set with the initial 3D grid space. Grid cells with an intersection are marked as valid (i.e., occupied) in the initial 3D Boolean matrix, while grid cells without an intersection are initially marked as invalid. This ultimately yields the precise occupancy distribution of the model within the Beidou grid. This provides a model of valid and invalid grid cells.

[0084] Step 408 : convert the projection coordinates of the center point of each grid cell in the valid grid cell model into geographic coordinates, calculate the Beidou grid code, add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell, and obtain the Beidou grid data of the ground feature.

[0085] It should be noted that steps 401 to 408 are the same as the detailed steps of steps 201 to 208 in the second aspect of the embodiment of the present invention, and will not be repeated here.

[0086] Step 409: Generate an octree topology structure based on the Beidou grid data of the ground object and the invalid grid cells.

[0087] In this step, the depth-first traversal algorithm (DFS) is used to construct a regular octree structure.

[0088] Starting from the lowest level of fine grids (leaf nodes) in the BeiDou grid data, the process works backwards layer by layer: for leaf nodes with valid grid cells, the unique index value is recorded and passed upwards to the parent node. Parent node validity follows the "either null or valid" principle: if any child node is valid, the parent node automatically inherits the valid status. Furthermore, the parent node code is inferred from the hierarchical association of the child node grid codes (such as the bit order of GeoSOT codes), ensuring the logical derivability of the hierarchical tree structure. This process forms a complete octree topology from leaf to root node, providing a hierarchical spatial index foundation for subsequent heterogeneous grid generation.

[0089] Step 410 , based on the octree topology structure, determine whether the normal direction of the grid unit of any valid leaf node at each level at any perspective has a valid leaf node at an upper level.

[0090] In this step, a three-dimensional occlusion detection mechanism is introduced. When the normal direction of the mesh cell of the current valid leaf node exists in the direction of a valid leaf node above it, the mesh cell of the current valid leaf node is deleted. Specifically, if the normal direction of the current valid leaf node (e.g., vertically upward when looking from a top-down perspective) exists in the direction of a mesh cell of a valid leaf node above it, the valid leaf node is determined to be occluded from the current perspective and is directly removed. The next valid leaf node is then determined to be occluded. If not, step 411 is executed.

[0091] Step 411: If there is no occlusion, determine whether the grid unit of the current valid leaf node has a grid unit of an adjacent valid leaf node.

[0092] In this step, for example, if the perspective is top-down (a plane with its normal facing upward), the process starts at the top layer and traverses all valid leaf nodes in that layer. The process then determines whether the grid cells of leaf nodes adjacent to the grid cell of the current valid leaf node are also valid. Adjacent grid cells are those that share the same edge.

[0093] In step 412, if there are adjacent valid leaf node grid cells, the adjacent grid cells of multiple valid leaf nodes are determined as a connected region. The process returns to step 210 to traverse the next valid leaf node in the current level until all valid leaf nodes in the current level are traversed, obtaining the connected region set for the current level. The process then returns to step 210 to traverse the next level until all levels are traversed, obtaining the connected region set for all levels in the current view. This step ultimately outputs an unobstructed, visible, two-dimensional connected region set.

[0094] The grid cells of multiple adjacent connected leaf nodes are a connected area. If the grid cell of a valid leaf node has no adjacent grid cells of valid leaf nodes, it can be determined as a connected area and become an independent connected area. After all levels of the current perspective are traversed, the set of connected areas of all levels of the current perspective is obtained.

[0095] Step 413 : traverse each connected region in the connected region set of all levels of the current view, and determine the simplest contour of each connected region to generate a target contour set.

[0096] Step 413 includes steps 4131 to 4133: Step 4131: traverse each connected region in the connected region set, obtain the vertices of the boundary of each connected region, and detect whether adjacent points exist according to the starting preset direction.

[0097] In step 4132, if there are no adjacent points in the initial preset direction, it means that an inflection point has occurred. The projection coordinates of the current inflection point are stored, the direction is changed for detection, and the existence of adjacent points is detected according to the next preset direction until the points on the boundary of all connected areas are traversed.

[0098] If there are adjacent points, determine whether they are redundant points. If they are redundant points, skip them and continue to detect the next point.

[0099] Step 4133: Connect adjacent inflection points end to end in sequence, determine the simplest contour of each connected area, and generate the target contour.

[0100] Specifically, a boundary grid traversal is performed on each connected area: starting from any edge vertex, it moves along the grid cell boundary in a preset direction (clockwise priority is given to right turn detection, counterclockwise priority is given to left turn detection), and the change point of the travel direction is detected in real time. When the moving direction deflects, the projection coordinates of the inflection point are recorded and the forward direction is updated. After the traversal is completed, the consecutive inflection points are connected in the order of head and tail closure to generate a simplified polygon outline. In this process, the intermediate redundant nodes on the linear path are automatically skipped (points with the same normal vector between inflection points are skipped). For example, for a rectangular area, only four corner points are retained instead of all edge nodes, which greatly reduces the number of vertices. This method significantly reduces the computational load of subsequent triangle generation.

[0101] Step 414 , triangulating the target contour set according to a triangulation algorithm to generate a target triangular mesh set.

[0102] In this step, the extracted polygonal target outline is preferably fed into a constrained Delaunay triangulation algorithm to enforce the preservation of topological connectivity within the polygonal boundaries. This algorithm supports complex polygons with holes: if nested boundaries exist within the same connected region (e.g., an outer outline and an inner hole), the algorithm automatically identifies the relationship between inner and outer loops and generates a triangular mesh with no intersection or overlap. During the triangulation process, only inflection points are considered essential nodes for mesh construction, avoiding the interference of redundant intermediate points on triangle surface density. The final output is a highly simplified triangulated mesh model, which is also the target triangular mesh set.

[0103] After the current viewing angle completes the above steps 410 to 414, the next viewing angle, such as the front view or the side view, continues to execute steps 410 to 414 to obtain the entire target triangle mesh set.

[0104] Step 415 , deduplicate vertices of the target triangle mesh set to obtain a heterogeneous mesh octree structure.

[0105] Step 416 , performing bottom-up node aggregation on the heterogeneous grid octree structure to generate a multi-level LOD model.

[0106] Based on a heterogeneous mesh octree structure, a multi-level Level of Detail (LOD) model is generated through a bottom-up node aggregation strategy. Dynamic merging rules are designed based on node geometric complexity (number of triangles) and spatial extent (BoundingBox coverage). When the data volume of a child node falls below a set threshold and its spatial extent is small, a parent node fusion operation is triggered, merging the child node geometry into a low-precision representation; otherwise, independent nodes are retained to maintain local details. This process is recursively executed layer by layer, resulting in a multi-level Level of Detail (LOD) model with reduced data volume and no loss of accuracy. Dynamic switching of levels based on viewpoint distance is supported, achieving an optimal balance between rendering efficiency and visual fidelity.

[0107] This embodiment resolves the contradiction between traditional technologies in geometric accuracy and real-time rendering performance, providing a high-fidelity and high-efficiency 3D modeling solution for the low-altitude economy. In terms of geometric accuracy, a non-uniform grid merging strategy and a constrained Delaunay triangulation algorithm completely eliminate the geometric distortion caused by forced equal division simplification. Field measurements show that model simplification errors, such as those associated with building edges, are reduced from the layer-by-layer accumulation of errors in traditional methods to zero error, meeting the stringent centimeter-level accuracy requirements of drone obstacle avoidance systems. Furthermore, thanks to its lightweight design, the model offers smooth browsing experience, providing a reliable 3D digital foundation for the large-scale development of the low-altitude economy.

[0108] A fifth aspect of the embodiment of the present invention provides, on the basis of the third aspect of the embodiment of the present invention, a method for generating an LOD model based on a method for generating Beidou grid data of ground objects, comprising the following steps: Step 501: Determine a polygonal facet set of the object in a projection coordinate system according to the three-dimensional model of the object.

[0109] Step 502: construct an AABBTree structure based on the triangle face set.

[0110] Step 503 : setting at least one light source and light direction according to the coordinates of the vertices of the three-dimensional model of the ground object in the Beidou grid three-dimensional coordinate system.

[0111] Step 504 : Determine a plurality of axial bounding boxes based on the AABBTree structure and the intersection points of the light rays emitted by the light source according to the light direction and light density and the plurality of triangular facets.

[0112] Step 505: Use the outer bounding box as the root node of the octree, and determine the leaf nodes of the octree according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box.

[0113] Step 506 : performing node matching between the axial bounding box and the leaf nodes of the octree to generate valid grid unit models and invalid grid unit models of the three-dimensional model of the ground object.

[0114] Step 507 : convert the projection coordinates of the center point of each grid cell in the valid grid cell model into geographic coordinates, calculate the Beidou grid code, and add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground feature.

[0115] In the embodiment of the present invention, the specific steps of step 501 to step 507 are the same as the detailed steps of step 301 to step 307 in the third aspect of the embodiment of the present invention, and are not repeated here.

[0116] Step 508: Generate an octree topology structure based on the Beidou grid data of the ground object and the invalid grid cells.

[0117] In this step, the depth-first traversal algorithm (DFS) is used to construct a regular octree structure.

[0118] Starting from the lowest level of fine grids (leaf nodes) in the BeiDou grid data, the process works backwards layer by layer: for leaf nodes with valid grid cells, the unique index value is recorded and passed upwards to the parent node. Parent node validity follows the "either null or valid" principle: if any child node is valid, the parent node automatically inherits the valid status. Furthermore, the parent node code is inferred from the hierarchical association of the child node grid codes (such as the bit order of GeoSOT codes), ensuring the logical derivability of the hierarchical tree structure. This process forms a complete octree topology from leaf to root node, providing a hierarchical spatial index foundation for subsequent heterogeneous grid generation.

[0119] Step 509 : Based on the octree topology structure, determine whether the normal direction of the grid unit of any valid leaf node at each level at any perspective has a valid leaf node at the upper level.

[0120] Step 510: If there is no occlusion, determine whether the grid unit of the current valid leaf node has a grid unit of an adjacent valid leaf node.

[0121] Step 511: If there are adjacent grid cells of valid leaf nodes, the adjacent grid cells of multiple valid leaf nodes are determined as a connected area, and the process returns to step 510 to traverse all valid leaf nodes at each level to obtain a connected area set.

[0122] Step 512: traverse each connected region in the connected region set, and determine the simplest contour of each connected region to generate a target contour set.

[0123] Step 512 includes steps 5121 to 5123: Step 5121: traverse each connected region in the connected region set, obtain the vertices of the boundary of each connected region, and detect whether adjacent points exist according to the starting preset direction.

[0124] Step 5122: If there are no adjacent points in the initial preset direction, it means that an inflection point has occurred. The projection coordinates of the current inflection point are stored, and the direction is changed for detection. The presence of adjacent points is detected according to the next preset direction until the points on the boundary of all connected areas are traversed.

[0125] If there are adjacent points, determine whether they are redundant points. If they are redundant points, skip them and continue to detect the next point.

[0126] Step 5123: Connect adjacent inflection points end to end in sequence, determine the simplest contour of each connected area, and generate the target contour.

[0127] Step 513: triangulate the target contour set according to a triangulation algorithm to generate a target triangle mesh set.

[0128] After the current viewing angle executes the above steps 510 to 513, the next viewing angle, such as the front view or the side view, executes the above steps 510 to 513 to obtain the entire target triangle mesh set.

[0129] Step 514: deduplicate vertices of the target triangle mesh set to obtain a heterogeneous mesh octree structure.

[0130] Step 515 : Perform bottom-up node aggregation on the heterogeneous grid octree structure to generate a multi-level LOD model.

[0131] In the embodiment of the present invention, the specific steps of step 508 to step 515 are the same as the detailed steps of step 409 to step 416 in the fourth aspect of the embodiment of the present invention, and are not repeated here.

[0132] like Figure 2 As shown, a sixth aspect of an embodiment of the present invention provides a device for generating Beidou grid data of a ground feature, comprising: A determination module 61 is used to determine a polygonal patch set of the ground object in a projection coordinate system according to the three-dimensional ground object model; A construction module 62 is used to construct an axial bounding box based on the polygonal facet set; A generating module 63 is used to determine a valid grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid; The calculation module 64 is used to calculate the Beidou grid code according to the geographical coordinates of the center point of each grid cell of the valid grid cell model, and add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground feature.

[0133] In one embodiment of the present invention, constructing an axial bounding box based on a set of polygonal facets includes: Construct the axial bounding box of the three-dimensional model of the ground object based on the polygonal facet set; According to the coordinates of the center point of the feature in the geographic coordinate system of the three-dimensional model of the feature, the center grid cell where the center point of the feature is located is determined by the GeoSOT grid algorithm; Determine the grid reference origin of the finest level based on the projected coordinates of each vertex of the central grid cell; Based on the grid reference origin, the axial bounding box of the three-dimensional model of the ground feature is expanded with a single step size of the Beidou grid to generate an initial three-dimensional grid space and a corresponding initial three-dimensional Boolean matrix with the initial mark as invalid state; Performing a subdivision process on the polygonal face set to obtain a sub-face set; Determine the axial bounding box of each sub-patch based on the sub-patch set.

[0134] In one embodiment of the present invention, determining a valid grid unit model of a three-dimensional model of a ground object based on an axial bounding box and the hierarchical accuracy of a Beidou grid includes: The geometric intersection of the axial bounding box of each sub-face and the initial three-dimensional grid space is calculated, and the grid cells with the intersection are marked as valid in the initial three-dimensional Boolean matrix to obtain the valid grid cell model and invalid grid cell model of the three-dimensional model of the ground object.

[0135] In one embodiment of the present invention, a Beidou grid code is calculated based on the geographic coordinates of the center point of each grid cell of the valid grid cell model, and Beidou grid attribute information corresponding to the Beidou grid code is added to the attributes of the corresponding grid cell to obtain the ground feature Beidou grid data, including: The projection coordinates of the center point of each grid cell in the valid grid cell model are converted into geographic coordinates, and the Beidou grid code is calculated. The Beidou grid attribute information corresponding to the Beidou grid code is added to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

[0136] In one embodiment of the present invention, constructing an axial bounding box based on a set of polygonal facets includes: Construct AABBTree structure based on polygon face set; At least one light source and light direction are set according to the coordinates of the vertices of the three-dimensional model of the ground object in the three-dimensional coordinate system of the Beidou grid; wherein the light density of the light source is the hierarchical accuracy of the lowest layer of the Beidou grid of the target; According to the AABBTree structure, multiple axial bounding boxes are determined by the intersection points of the light emitted by the light source according to the light direction and light density and multiple polygonal facets.

[0137] In one embodiment of the present invention, setting at least one light source and light direction according to the coordinates of the vertices of the three-dimensional model of the ground object in the three-dimensional coordinate system of the Beidou grid includes: Construct an outer bounding box based on the coordinates of the vertices of the three-dimensional model of the ground object in the three-dimensional coordinate system of the Beidou grid; A light source is set on at least one surface of the outer bounding box; wherein the light direction of the light source is parallel to one axis of the three-dimensional coordinate axis of the Beidou grid coordinate system, and the axis is perpendicular to the surface where the light source is located.

[0138] In one embodiment of the present invention, determining a valid grid unit model of a three-dimensional model of a ground object based on an axial bounding box and the hierarchical accuracy of a Beidou grid includes: The outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined based on the hierarchical accuracy of the target's lowest-level Beidou grid and the outer bounding box. The axial bounding box is matched with the leaf nodes of the octree to generate valid grid unit models and invalid grid unit models of the three-dimensional model of the ground object.

[0139] In one embodiment of the present invention, the outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box, including: Use the outer bounding box as the root node of the octree; Match the initial accuracy of the 3D model of the object with the hierarchical accuracy of the Beidou grid, and determine the hierarchical accuracy of the lowest Beidou grid of the target as the cutting density; The outer bounding box is cut according to the Beidou grid subdivision rules and cutting density to obtain multiple grid units of the three-dimensional grid structure, and the multiple grid units are leaf nodes of the octree.

[0140] In one embodiment of the present invention, it further comprises: Generate an octree topology structure based on the Beidou grid data of the ground objects and invalid grid cells; Judgment step: Based on the octree topology structure, determine whether any grid unit of a valid leaf node at each level of any perspective has an adjacent grid unit of a valid leaf node; If so, the grid cells of the adjacent valid leaf nodes are determined as a connected region, and the judgment step is returned to traverse all valid leaf nodes at each level to obtain a connected region set; Traversing each connected region in the connected region set, determining the simplest contour of the connected region to generate a target contour set; Divide the target contour set according to the polygonal division algorithm to generate a target polygonal grid set; De-duplication of vertices of the target polygonal mesh set is performed to obtain a heterogeneous mesh octree structure; The heterogeneous grid octree structure is aggregated from bottom to top to generate a multi-level LOD model.

[0141] The seventh aspect of an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the program, a method for generating Beidou grid data of ground features provided by the above-mentioned embodiment of the present invention is implemented.

[0142] The eighth aspect of the embodiments of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for generating Beidou grid data of a ground feature provided by the above-mentioned embodiment of the present invention are implemented.

[0143] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage. Alternatively, the memory may be at least one storage device located away from the processor.

[0144] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware systems.

[0145] The method provided in the embodiments of the present invention can be applied to electronic devices. Specifically, the electronic devices can be desktop computers, portable computers, smart mobile terminals, servers, etc. This is not limited here; any electronic device that can implement the present invention falls within the scope of protection of the present invention.

[0146] As for the device / electronic device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0147] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0148] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0149] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0150] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for generating Beidou grid data of ground objects, characterized in that: The following steps are involved: Determine the polygonal patch set of the feature in the projection coordinate system according to the three-dimensional model of the feature; Constructing an axial bounding box based on the polygonal facet set; Determining a valid grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid; The Beidou grid code is calculated according to the geographical coordinates of the center point of each grid cell of the valid grid cell model, and the Beidou grid attribute information corresponding to the Beidou grid code is added to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

2. The method according to claim 1, wherein The step of constructing an axial bounding box according to the polygonal facet set includes: Constructing an axial bounding box of a three-dimensional model of a ground object according to the polygonal facet set; Determine the center grid cell where the center point of the feature is located by using the GeoSOT grid algorithm according to the coordinates of the center point of the feature in the geographic coordinate system of the three-dimensional model of the feature; Determining a grid reference origin of the finest level according to the projection coordinates of each vertex of the central grid unit; According to the grid reference origin, the axial bounding box of the three-dimensional model of the ground object is expanded with a single step size of the Beidou grid to generate an initial three-dimensional grid space and a corresponding initial three-dimensional Boolean matrix with an initial mark in an invalid state; Performing a subdivision process on the polygonal face set to obtain a sub-face set; An axial bounding box of each sub-patch is determined according to the sub-patch set.

3. The method according to claim 2, wherein The determining of the effective grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid includes: The geometric intersection of the axial bounding box of each sub-facet and the initial three-dimensional grid space is calculated, and the grid cells with the intersection are marked as valid in the initial three-dimensional Boolean matrix to obtain the valid grid cell model and the invalid grid cell model of the three-dimensional model of the ground object.

4. The method according to claim 1, wherein The method of calculating a Beidou grid code according to the geographic coordinates of the center point of each grid cell of the valid grid cell model, and adding Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell to obtain the ground feature Beidou grid data includes: The projection coordinates of the center point of each grid cell in the valid grid cell model are converted into geographic coordinates, and the Beidou grid code is calculated. The Beidou grid attribute information corresponding to the Beidou grid code is added to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

5. The method according to claim 1, wherein The step of constructing an axial bounding box according to the polygonal facet set includes: Constructing an AABBTree structure according to the polygonal face set; At least one light source and light direction are set according to the coordinates of the vertices of the three-dimensional model of the ground object in the three-dimensional coordinate system of the Beidou grid; wherein the light density of the light source is the hierarchical accuracy of the bottom layer of the Beidou grid of the target; A plurality of axial bounding boxes are determined according to the AABBTree structure, intersection points of the light emitted by the light source according to the light direction and the light density and the plurality of polygonal facets.

6. The method according to claim 5, wherein The step of setting at least one light source and light direction according to the coordinates of the vertices of the three-dimensional model of the ground object in the three-dimensional coordinate system of the Beidou grid includes: Constructing an outer bounding box according to the coordinates of the vertices of the three-dimensional model of the ground object in the Beidou grid three-dimensional coordinate system; A light source is provided on at least one surface of the outer bounding box; wherein the light ray of the light source is parallel to one axis of the three-dimensional coordinate axis of the coordinate system of the Beidou grid, and the axis is perpendicular to the surface where the light source is located.

7. The method according to claim 5, wherein The determining of the effective grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid includes: The outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box; The axial bounding box is matched with the leaf nodes of the octree to generate a valid grid unit model and an invalid grid unit of the three-dimensional model of the ground object.

8. The method according to claim 7, wherein The outer bounding box is used as the root node of the octree, and the leaf nodes of the octree are determined according to the hierarchical accuracy of the target bottom-level Beidou grid and the outer bounding box, including: Taking the outer bounding box as the root node of the octree; Matching the initial accuracy of the three-dimensional model of the ground object with the hierarchical accuracy of the Beidou grid, and determining the hierarchical accuracy of the bottom layer of the target Beidou grid as the cutting density; The outer bounding box is cut according to the Beidou grid subdivision rule and the cutting density to obtain multiple grid units of a three-dimensional grid structure, and the multiple grid units are leaf nodes of the octree.

9. The method according to claim 1, wherein The method further comprises: Generate an octree topology structure according to the ground feature Beidou grid data and the invalid grid unit; Determination step: based on the octree topology structure, determining whether any grid unit of a valid leaf node at each level of any perspective has an adjacent grid unit of a valid leaf node; If so, the grid cells of the adjacent multiple valid leaf nodes are determined as a connected region, and the determination step is returned to traverse all valid leaf nodes at each level to obtain a connected region set; Traversing each connected region in the connected region set, and determining the simplest contour of the connected region to generate a target contour set; Divide the target contour set according to a polygonal decomposition algorithm to generate a target polygonal grid set; Deduplicating vertices of the target polygonal grid set to obtain a heterogeneous grid octree structure; The heterogeneous grid octree structure is subjected to bottom-up node aggregation to generate a multi-level LOD model.

10. A device for generating Beidou grid data for ground objects, characterized in that: include: A determination module, for determining a polygonal facet set of a ground object in a projection coordinate system according to a three-dimensional ground object model; A construction module, configured to construct an axial bounding box according to the polygonal facet set; A generating module, configured to determine a valid grid unit model of the three-dimensional model of the ground object according to the axial bounding box and the hierarchical accuracy of the Beidou grid; The calculation module is used to calculate the Beidou grid code according to the geographical coordinates of the center point of each grid cell of the effective grid cell model, and add the Beidou grid attribute information corresponding to the Beidou grid code to the attributes of the corresponding grid cell to obtain the Beidou grid data of the ground object.

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