Grid generation method and device, electronic equipment and readable storage medium

Abstract

The embodiment of the invention provides a grid generation method and device, electronic equipment and a readable storage medium. The grid generation method comprises the steps that the number, area and common vertexes of basic grid units mapped by a to-be-observed vector region are obtained; if the number is greater than 1 and less than or equal to a first preset value, determining a central point of a to-be-generated intermediate layer grid unit according to the common vertex of the basic grid unit, and determining the area of the to-be-generated intermediate layer grid unit according to the area of the basic grid unit; according to a central point and an area of a to-be-generated intermediate layer grid unit, aggregating the basic grid units mapped by the to-be-observed vector region to obtain the intermediate layer grid unit; if the number is greater than the first preset value, obtaining an effective degree of the basic grid unit; and aggregating the basic grid units mapped by the vector area to be observed according to the effective degree to obtain a middle-layer grid unit, thereby reducing the space loss and the pressure of satellite planning and scheduling.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite applications, and particularly relates to a grid generation method, device, electronic device and readable storage medium. Background Art

[0002] The current characterization scheme for satellite observation tasks mainly uses a traditional seamless and non-overlapping hexagonal dissection grid to characterize the target area. Specifically, it means that the target area is first mapped through a seamless and non-overlapping hexagonal grid, and then the vector target area is discretized to form a set of grid cells, and the complex planar object is characterized through grid coding. Then, it is used as the input for subsequent satellite scheduling planning to provide the basic unit of the model for large-scale satellite constellation planning and scheduling.

[0003] However, there are some problems when characterizing in the above manner. First, when the target area is mapped to the grid corner points during mapping, simple spatial aggregation is difficult to control the resolution, and even in the worst case, it is impossible to achieve a single grid mapping when aggregating to the 0th layer, and there will be more dead spaces at this time. Second, when the target area is large, due to the limitation of the grid scale, the number of mapped grids will also increase accordingly. The excessive number of grids will increase the number of satellite shootings, resulting in more use of satellite resources and increasing the pressure on satellite planning and scheduling. Summary of the Invention

[0004] The present invention provides a grid generation method, device, electronic device and readable storage medium to solve the problem that the existing task characterization method is limited by the satellite swath width, which may cause a large number of dead spaces during grid mapping, and at the same time increase the number of mapped grids, thereby resulting in more use of satellite resources and increasing the pressure on satellite planning and scheduling.

[0005] To solve the above technical problems, the present invention is implemented as follows:

[0006] In a first aspect, the present invention provides a grid generation method, and the method includes:

[0007] Obtain key information of the basic grid cells mapped by the vector area to be observed, where the key information includes the number, area and common vertices of the basic grid cells;

[0008] If the number is greater than 1 and less than or equal to a first preset value, determine the center points of the intermediate layer grid cells to be generated according to the common vertices of the basic grid cells, and determine the areas of the intermediate layer grid cells to be generated according to the areas of the basic grid cells;

[0009] Aggregate the basic grid cells mapped by the vector area to be observed according to the center points and areas of the intermediate layer grid cells to be generated to obtain intermediate layer grid cells;

[0010] If the quantity is greater than a first preset value, obtain the effective degree of the basic grid unit, where the effective degree refers to the number of basic grid units adjacent to the basic grid unit and not aggregated.

[0011] Aggregate the basic grid units mapped by the vector region to be observed according to the effective degree to obtain intermediate layer grid units.

[0012] Optionally, obtaining the key information of the basic grid units mapped by the vector region to be observed includes:

[0013] Obtain the swath width of the satellite performing the observation task, the shape and area of the vector region to be observed;

[0014] Determine the level of the basic grid units mapped by the vector region to be observed according to the swath width;

[0015] Determine the area of the basic grid units mapped by the vector region to be observed according to the level;

[0016] Determine the number of the basic grid units mapped by the vector region to be observed according to the area of the basic grid units and the area of the vector region to be observed;

[0017] Determine the position distribution of the basic grid units mapped by the vector region to be observed according to the shape of the vector region to be observed;

[0018] Determine the common vertices of the basic grid units mapped by the vector region to be observed according to the position distribution;

[0019] Optionally, after aggregating the basic grid units mapped by the vector region to be observed according to the effective degree to obtain intermediate layer grid units, it further includes:

[0020] Obtain the 64-bit grid code of the basic grid unit;

[0021] Add the grid code representing the intermediate layer grid unit to the 1st - 4th bits of the 64-bit grid code;

[0022] Add the grid code representing the vertices of the intermediate layer grid unit to the 5th - 7th bits of the 64-bit grid code;

[0023] Add the grid code representing the level of the intermediate layer grid unit to the 8th - 11th bits of the 64-bit grid code, where the level of the intermediate layer grid unit is the intermediate value of the level of the basic grid unit and the upper level of the basic grid unit.

[0024] Optionally, determining the center point of the intermediate layer grid cell to be generated according to the common vertices of the basic grid cells, and determining the area of the intermediate layer grid cell to be generated according to the area of the basic grid cells includes:

[0025] Obtain the target quantity and coding combination of the basic grid cells to which the common vertices belong;

[0026] If the maximum value of the target quantity is the first preset value, determine the corresponding common vertex as the center point of the intermediate layer grid cell to be generated;

[0027] If the maximum value of the target quantity is the second preset value, then screen out the center point of the intermediate layer grid cell to be generated from the common vertices corresponding to the target quantity being the third preset value according to the coding combination;

[0028] Determine three times the area of the basic grid cell as the area of the intermediate layer grid cell to be generated.

[0029] Optionally, the aggregating the basic grid cells mapped to the vector region to be observed according to the effective degrees to obtain intermediate layer grid cells further includes:

[0030] Obtain the minimum value of the effective degrees from the effective degrees;

[0031] If the minimum value is 1, aggregate the first basic grid cell corresponding to the minimum value of the effective degrees and the basic grid cells adjacent to the first basic grid cell to obtain an intermediate layer grid cell;

[0032] If the minimum value is greater than 1, obtain the second basic grid cell adjacent to the first basic grid cell;

[0033] When it is determined that the first basic grid cell and the second basic grid cell are combined into a combination of three mutually adjacent basic grid cells, obtain the target effective degree sum of the combination of the three basic grid cells;

[0034] Aggregate the combination of the three basic grid cells with the minimum target effective degree sum to obtain an intermediate layer grid cell.

[0035] Optionally, after obtaining the minimum value of the effective degrees from the effective degrees, it further includes:

[0036] If the minimum value is 0, change the effective degree of the basic grid cell corresponding to the minimum value of the effective degrees to the target value;

[0037] Determine the third basic grid cell participating in the aggregation;

[0038] Change the effective degree of the third basic grid cell to the target value;

[0039] End the aggregation operation when it is detected that the effective degrees of the basic grid cells mapped by the to-be-observed vector region are all target values.

[0040] Optionally, after determining the third basic grid cell participating in the aggregation, it further includes:

[0041] Obtain the adjacency relationship of the basic grid cells;

[0042] Generate an adjacency list according to the adjacency relationship;

[0043] Traverse the adjacency list to obtain the fourth basic grid cell adjacent to the third basic grid cell;

[0044] Decrease the effective degree of the fourth basic grid cell by one.

[0045] In a second aspect, the present invention provides a grid generation device, and the device includes:

[0046] A first acquisition module, configured to acquire key information of basic grid cells mapped by a to-be-observed vector region, where the key information includes the number, area, and common vertices of the basic grid cells;

[0047] A first determination module, configured to, if the number is greater than 1 and less than or equal to a first preset value, determine the center point of the to-be-generated intermediate layer grid cell according to the common vertices of the basic grid cells, and determine the area of the to-be-generated intermediate layer grid cell according to the area of the basic grid cells;

[0048] A first aggregation module, configured to aggregate the basic grid cells mapped by the to-be-observed vector region according to the center point and area of the to-be-generated intermediate layer grid cell to obtain intermediate layer grid cells;

[0049] A second acquisition module, configured to, if the number is greater than the first preset value, acquire the effective degree of the basic grid cells, where the effective degree refers to the number of basic grid cells adjacent to and not aggregated by the basic grid cells;

[0050] A second aggregation module, configured to aggregate the basic grid cells mapped by the to-be-observed vector region according to the effective degree to obtain intermediate layer grid cells.

[0051] In a third aspect, the present invention provides an electronic device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor, where the processor implements the above grid generation method when executing the program.

[0052] Fourthly, the present invention provides a readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the above-mentioned grid generation method.

[0053] In an embodiment of the present invention, key information of a basic grid unit for mapping a vector region to be observed is obtained. The key information includes the number, area, and common vertices of the basic grid unit. If the number is greater than 1 and less than or equal to a first preset value, the center point of an intermediate layer grid unit to be generated is determined according to the common vertices of the basic grid units, and the area of the intermediate layer grid unit to be generated is determined according to the area of the basic grid units. Determining the center point of the intermediate layer grid unit through the common vertices ensures the consistency of the spatial relationship between the newly generated grid unit and the basic grid unit, avoiding topological errors or data breaks caused by grid division. And determining the area of the intermediate layer grid unit according to the area ensures the continuity and proportional consistency of the data in space. According to the center point and area of the intermediate layer grid unit to be generated, the basic grid units for mapping the vector region to be observed are aggregated to obtain the intermediate layer grid unit. If the number is greater than the first preset value, the effective degree of the basic grid unit is obtained. The effective degree refers to the number of basic grid units adjacent to the basic grid unit and not yet aggregated. Aggregating the basic grid units for mapping the vector region to be observed according to the effective degree to obtain the intermediate layer grid unit. By introducing the concept of the effective degree, adjacent and unaggregated units are preferentially aggregated, reducing repeated calculations and redundant operations, and improving the calculation efficiency. In this application, by aggregating the basic grid units to generate the intermediate layer grid units, the problems of excessive dead space and insufficient accuracy that may be brought by simple spatial aggregation are avoided, and the problem of too many mapped grids, resulting in an increase in the number of satellite shootings, excessive use of satellite resources, and excessive satellite planning and scheduling, is also avoided. Thereby reducing spatial loss, and covering with as few intermediate layer grids and basic level grids as possible, saving time and space loss for subsequent constellation planning, reducing the pressure of satellite planning and scheduling, and enabling the constellation planning to be carried out efficiently. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0055] Figure 1 It is a schematic diagram of a vector target characterization grid provided by an embodiment of the present invention;

[0056] Figure 2 It is a grid generation method provided by an embodiment of the present invention;

[0057] Figure 3 is Figure 2 The flowchart of step 101 in a grid generation method provided by an embodiment of the present invention as shown;

[0058] Figure 4 is Figure 2 The schematic diagram of simple grid aggregation in a grid generation method provided by an embodiment of the present invention as shown;

[0059] Figure 5 is Figure 2 The schematic diagram of determining the center points of intermediate layer grid cells in a grid generation method provided by an embodiment of the present invention as shown;

[0060] Figure 6 is Figure 2 The schematic diagram of converting a grid into a graph structure in a grid generation method provided by an embodiment of the present invention as shown;

[0061] Figure 7 is Figure 2 The schematic diagram of grid indexing in a grid generation method provided by an embodiment of the present invention as shown;

[0062] Figure 8 is Figure 2 The schematic diagram of an adjacency list in a grid generation method provided by an embodiment of the present invention as shown;

[0063] Figure 9 is Figure 2 The flowchart of a greedy algorithm in a grid generation method provided by an embodiment of the present invention as shown;

[0064] Figure 10 The structure diagram of a grid generation device provided by an embodiment of the present invention;

[0065] Figure 11 The structure diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0066] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0067] The current satellite observation task characterization scheme relies on open-source discrete global grid systems and grid dissection theoretical models during implementation. Among them, the open-source discrete global grid systems include the large open-source discrete grid dissection system H3 and DGGRID. Among them, the H3 system is based on the seven-aperture hexagonal dissection and provides 16 levels of multi-resolution grids. The functions provided include, but are not limited to, the mutual conversion between grids, grid vertices, grid edges and longitude-latitude coordinates and the grid index of the specified resolution, the nearest neighbor query based on grid distance, the shortest path search between grids, the gridification of geometric polygons, etc. DGGRID operates with an icosahedron as the basic polyhedron, and its core function is to group point data into DGGS cells at a selected resolution. DGGRID allows the generated DGGS to be exported in a standard GIS format. The greatest advantage of DGGRID is that the dissection method (triangle, quadrilateral or hexagon) can be selected. In addition, the projection direction and projection method can also be defined. It should be noted that both of these systems are implementations based on the Discrete Global Grid System (DGGS). DGGS is a multi-resolution discrete earth reference model formed by recursively dissecting the entire earth space. DGGS has three regular geographic grids, including: triangles, quadrilaterals, and hexagons. Among them, the hexagonal grid system has less deformation in the polar regions, has consistent connectivity and good angular resolution characteristics, is suitable for generating global large-scale heat map grids, and is more meaningful for the grid-based satellite planning and scheduling. The grid dissection theoretical model can be a multi-scale grid system constructed on an icosahedron with a hexagon as the basic dissection unit, using the inverse Schnyder equal-area polyhedron projection to construct a global hexagonal grid system, or it can be a global hexagonal grid system generation algorithm designed by approximating the earth with an octahedron and combining the Fuller-Gray projection and Luo Junren's C-IV dissection method. Through the above methods, the satellite planning and scheduling tasks based on hexagonal grids can be realized.

[0068] However, due to its seamless and non-overlapping and static dissection properties, and being restricted by the satellite swath width, the above-mentioned hexagonal discrete grid dissection system often uses a single-scale grid for mapping during task characterization. Therefore, the number of generated grids will be significantly larger than the number of tasks, causing pressure on satellite planning and scheduling. If the vector target characterization grid set is directly aggregated into the upper-level grid unit, there will be multiple situations. The first situation is that the vector target is within the grid, as shown in the left figure of Figure 1 , in which case a single grid (small hexagon) can complete the coverage. Another situation is when the vector target is at the grid corner, as shown in Figure 1As shown in the right figure, at this time, simple aggregation (corresponding to the largest hexagonal grid in the figure) cannot achieve single-grid mapping, and problems such as the grid diameter being larger than the satellite swath width and the grid area being significantly larger than the area of the observation task object will occur. Therefore, the grid number inflation formed by single-scale grid mapping will bring huge pressure to subsequent satellite planning and scheduling. Based on this, an embodiment of the present invention proposes a grid generation method that can generate new intermediate-layer grid cells (corresponding to the intermediate-sized hexagonal grid cells including vector targets in the figure).

[0069] Referring to Figure 2 , Figure 2 is a step flowchart of a grid generation method provided by an embodiment of the present invention. As Figure 2 shown, the method may include:

[0070] Step 101, obtain key information of the basic grid cells mapped to the vector region to be observed. The key information includes the number, area, and common vertices of the basic grid cells.

[0071] In the embodiment of the present invention, a new hexagonal multi-scale extended grid needs to be generated on the basis of the original grid. Therefore, it is necessary to first determine the key information of the basic grid cells mapped to the vector region to be observed. The key information includes the number, area, and common vertices of the basic grid cells. To obtain this information, first obtain the swath width of the satellite performing the observation task, the shape and area of the vector region to be observed. Among them, the swath width of the satellite is the ground width that the satellite can cover during one pass, which is an important parameter for determining the observation range. The shape and area of the vector region to be observed directly affect the complexity of grid division and the number of grid cells. According to the satellite swath width and observation requirements, the resolution of the grid cells, that is, the level, can be determined. The higher the level, the smaller the grid cells and the higher the resolution. The side lengths of different levels are fixed, so the area of the grid cells can be directly determined according to the level. Then, according to the area of the basic grid cells and the area of the vector region to be observed, the number of basic grid cells mapped to the vector region to be observed can be determined, that is, the number of basic grid cells = the area of the observation region / the area of a single grid cell. The shape of the vector region to be observed can determine the distribution position of the basic grid cells mapped to the vector region to be observed, and the common vertices of the basic grid cells mapped to the vector region to be observed can be determined according to the distribution position. Specifically, step 101, as Figure 3 shown:

[0072] Step 1011, obtain the swath width of the satellite performing the observation task, the shape and area of the vector region to be observed.

[0073] Step 1012, determine the level of the basic grid cells mapped to the vector region to be observed according to the swath width.

[0074] Step 1013: Determine the area of the basic grid cells for mapping the vector region to be observed according to the hierarchy.

[0075] Step 1014: Determine the number of basic grid cells for mapping the vector region to be observed based on the area of the basic grid cells and the area of the vector region to be observed.

[0076] Step 1015: Determine the position distribution of the basic grid cells for mapping the vector region to be observed according to the shape of the vector region to be observed.

[0077] Step 1016: Determine the common vertices of the basic grid cells for mapping the vector region to be observed according to the position distribution.

[0078] For example, if the satellite swath width is 20 km, the area of the region to be observed is an irregular polygon with an area of 100 square kilometers, and the basic grid system used is the H3 hexagonal grid. Since the closest and smaller grid cells than the satellite swath width are the 6th-level grid cells (average side length of 10 km), the hierarchy of the basic grid cells for mapping is determined to be the sixth level, with an area of 1.23 square kilometers. At this time, the number of basic grid cells required = 100 / 1.23 ≈ 82. According to the boundary of the irregular polygon, 82 6th-level grid cells that are completely or partially within the region are selected, and the common vertices of these grid cells are determined (the common vertices are the vertices shared by two, three, or more grid cells).

[0079] In the above steps, by accurately calculating the number and distribution of grid cells, the observation path and resource allocation of the satellite can be optimized, reducing repeated observations and resource waste. Determining the common vertices helps the subsequent aggregation and optimization of grid cells, reducing the complexity of data processing.

[0080] Step 102: If the number is greater than 1 and less than or equal to the first preset value, determine the center points of the intermediate-level grid cells to be generated according to the common vertices of the basic grid cells, and determine the area of the intermediate-level grid cells to be generated according to the area of the basic grid cells.

[0081] In the embodiment of the present invention, after obtaining the key information of the basic grid cells for mapping the vector region to be observed, the center points and areas of the intermediate-level grid cells to be generated are determined based on this key information, and then aggregation is performed based on the obtained information. When aggregating, when the vector region to be observed is small, it can be covered by only 1 - 3 6th-level H3 grid cells. At this time, when it is converted to a multi-scale adaptive grid, only one intermediate-level grid (intermediate-level grid cell) is required to complete the coverage. For example Figure 4As shown, if there is only one basic grid cell in the sixth level of the mapped area of the vector to be observed, it indicates that this basic grid cell can directly cover the vector area to be observed without further aggregation. If there are two or three adjacent basic grid cells in the sixth level of the mapped area of the vector to be observed, aggregation is required to obtain an intermediate level. When the task area is large, multiple grid cells of the 6th level are needed to cover it.

[0082] Here, aggregation is performed according to the first method, so the first preset value is 3. In this aggregation method, the center point and area of the intermediate level need to be determined first. The center point is selected from the common vertices. Since the common vertex refers to the vertex shared by multiple basic grid cells, each common vertex may belong to multiple basic grid cells, and the number of these grid cells is called the "target number". In addition, each basic grid cell has a unique code (such as the H3 index in the H3 grid system), and these code combinations can be used to identify the grid cells to which the common vertex belongs. Because the aggregation may be 2 or 3, the value of the target number is 2 or 3. Obtain the maximum value of the target number. If the value of the target number is 3, it indicates that the basic grid cells are adjacent to each other at this time, and the common vertex corresponding to the value of 3 can be directly determined as the center point of the intermediate-level grid cell to be generated. As Figure 5 shown, the vertex within the circle is the common vertex of three adjacent sub-grid cells and is also the center point of the intermediate-level grid cell to be generated. When the maximum value of the target number is 2, it indicates that the adjacent sub-grid cells are adjacent in pairs. According to Figure 4 the content, when adjacent in pairs, there are two common vertices, and any one of them can be selected as the center point. If the number of basic grid cells is 3, coded as A, B, and C, and the distribution is adjacent in pairs, then there are 4 common vertices. There are two common vertices a and b between A and B, and two common vertices c and d between B and C. The code combinations corresponding to a and b are the same, and the code combinations corresponding to c and d are the same. At this time, when screening the common vertices, any one of a and b is selected, and any one of c and d is selected. After determining the center point, the area of the intermediate-level grid cell to be generated is also determined based on the area of the basic grid cell. The area of each intermediate-level grid cell to be generated is 3 times the area of the basic grid cell that makes it up. For example, if the area of the basic grid cell is 1.23 square kilometers, then the area of the intermediate-level grid cell is 1.23×3 = 3.69 square kilometers.

[0083] The specific steps include:

[0084] Obtain the target number and code combination of the basic grid cell to which the common vertex belongs;

[0085] If the maximum value of the target quantity is the first preset value, determine the corresponding common vertex as the center point of the intermediate layer grid cell to be generated;

[0086] If the maximum value of the target quantity is the second preset value, then screen out the center point of the intermediate layer grid cell to be generated from the common vertices corresponding to the target quantity of the third preset value according to the coding combination;

[0087] Determine three times the area of the basic grid cell as the area of the intermediate layer grid cell to be generated.

[0088] Among them, the first preset value is 3 and the second preset value is 2. The coding combination refers to the combination of the codes of all the basic grid cells to which the common vertex belongs. For example, there are 3 basic grid cells to which the common vertex A belongs, namely basic grid cell 1, basic grid cell 2, and basic grid cell 3, and the corresponding codes are 001, 002, and 003. Then the coding combination corresponding to the common vertex A obtained is 001002003. It should be noted that if the generated intermediate layer grid cells are adjacent, then these two adjacent intermediate layer grid cells overlap with each other, and the overlap degree is 16 / 27, approximately 59.3%, as Figure 5 shown.

[0089] In the above steps, by selecting the common vertex with the largest target quantity as the center point, it is possible to effectively aggregate the surrounding basic grid cells, reduce data redundancy, and at the same time facilitate the coding of the intermediate layer grid cells.

[0090] Step 103: Aggregate the basic grid cells mapped by the area to be observed vector according to the center point and area of the intermediate layer grid cell to be generated to obtain the intermediate layer grid cell.

[0091] In the embodiment of the present invention, after determining the center point and area of the intermediate layer grid cell, the position and coverage range of the intermediate layer grid cell can be directly determined. At this time, the basic grid cells can be deleted, and the aggregated intermediate layer grid cells are used to cover the corresponding area to be observed vector.

[0092] For example, assume that the center point of the intermediate layer grid cell is determined to be A, which is adjacent to the basic grid cells (B, C, D). The area of one basic grid cell is 1.23 square kilometers. Therefore, the area of the intermediate layer grid cell is 3 times the area of the basic grid cell, which is 3.69 square kilometers. Determine the side length of the intermediate layer grid cell according to the area, determine the position of the intermediate layer grid cell according to the center point, aggregate B, C, and D into one intermediate layer grid cell, and at the same time remove the basic grid cells B, C, and D. Then continue to select the next center point to generate a new intermediate layer grid cell until all the basic grid cells are aggregated.

[0093] Step 104: If the quantity is greater than the first preset value, obtain the effective degree of the basic grid cell. The effective degree refers to the number of basic grid cells that are adjacent to the basic grid cell and have not been aggregated.

[0094] In the above process, the embodiment of the present invention aims at the aggregation strategy when the vector region to be observed is small. When the vector region to be observed is large, multiple grid cells of the sixth level are required for coverage at this time. In order to minimize the pressure of subsequent constellation planning to the greatest extent, the number of task grid cells needs to be reduced as much as possible.

[0095] Based on the above requirements, the embodiment of the present invention proposes a grid number optimization algorithm, which can cover any irregular region with as few multi-scale adaptive grids as possible. This algorithm needs to first convert the grid cells into a graph structure. That is, each hexagonal grid can actually be regarded as a graph node, and the adjacency of two grids can be considered as the connection between nodes. Thus, the number of basic grid cells adjacent to a certain basic grid cell (node) can be regarded as the degree of this grid (node), and these basic grid cells can also be regarded as an undirected connected graph. As Figure 6 shown, the degrees of each basic grid cell (node) are marked in the figure, which are 3, 3, 3, 6, 3, 3, 3 from top to bottom and from left to right in sequence.

[0096] The meaning of the degree is explained above. However, in the embodiment of the present invention during aggregation, sometimes some basic grid cells may have been aggregated. To avoid repeated aggregation of these aggregated basic grid cells, the embodiment of the present invention calculates the number of basic grid cells that are adjacent to the basic grid cell and have not been aggregated. At this time, the degree is the effective degree.

[0097] Step 105: Aggregate the basic grid cells mapped by the vector region to be observed according to the effective degree to obtain the intermediate layer grid cells.

[0098] After obtaining the effective degrees in the embodiments of the present invention, the basic grid cells mapped to the observation vector region can be aggregated according to the effective degrees. During the aggregation, a greedy strategy is adopted, and the grid with the lowest effective degree is processed first to obtain an optimal solution locally and then globally optimal. That is, at the beginning of each iteration, the first basic grid cell (node) with the smallest effective degree is selected, and the degree is denoted as n. If n is equal to 1, it means that the cell has only one adjacent unaggregated cell, and it can be directly aggregated with the adjacent cell. If n is greater than 1, it indicates that each cell has multiple adjacent unaggregated cells, and the best combination needs to be further screened. At this time, the aggregation of three basic grid cells can be performed. When aggregating, it is first required that the three grid cells are adjacent to each other. If there are multiple combinations of three mutually adjacent grid cells, at this time, calculate the target effective degree sum of the combination of three adjacent basic grid cells, and select the combination with the smallest sum for aggregation. Because the smaller the target effective degree sum, the fewer the adjacent unaggregated cells in the combination, and it is more suitable for priority aggregation. The specific steps include:

[0099] Obtain the minimum value of the effective degrees from the effective degrees;

[0100] If the minimum value is 1, aggregate the first basic grid cell corresponding to the minimum value of the effective degrees and the basic grid cell adjacent to the first basic grid cell to obtain an intermediate layer grid cell;

[0101] If the minimum value is greater than 1, obtain the second basic grid cell adjacent to the first basic grid cell;

[0102] In the case where it is determined that the combination of the first basic grid cell and the second basic grid cell is a combination of three mutually adjacent basic grid cells, obtain the target effective degree sum of the combination of the three basic grid cells;

[0103] Aggregate the combination of the three basic grid cells with the smallest target effective degree sum to obtain an intermediate layer grid cell.

[0104] For example, if the minimum value of the effective degrees is 2, the corresponding basic grid cells are A, C, D, the cells adjacent to A are B, C, the cells adjacent to C are A, D, E, and the cells adjacent to D are C, E. At this time, the combinations of three adjacent basic grid cells are: Combination 1: A, B, C, target effective degree sum = 2(A) + 1(B) + 3(C) = 6; Combination 2: C, D, E, target effective degree sum = 3(C) + 2(D) + 1(E) = 6. At this time, select Combination 1 or Combination 2 for aggregation.

[0105] In the above steps, by dynamically aggregating the basic grid cells through the effective degrees to generate the intermediate layer grid cells, it not only avoids the generation of isolated cells, but also optimizes the aggregation order, improves the calculation efficiency, and is applicable to satellite observation planning and data processing in complex regions.

[0106] It should be noted that during aggregation, after selecting the basic grid cells to participate in aggregation, the specific aggregation method still determines the position and size of the intermediate-layer grid cells for aggregation by finding the center point and determining the area. In addition, after processing the basic grid cells that need to participate in aggregation, there are still isolated basic grid cells. At this time, the effective degree is 0. In order to distinguish the isolated basic grid cells, the basic grid cells that have already participated in aggregation, and the basic grid cells that need to be processed in the next iteration without participating in aggregation, to avoid repeated processing of these cells in subsequent aggregation operations. In the embodiments of the present invention, the effective degrees of these basic grid cells that do not need to participate in aggregation are set to the target value, indicating that the cell has been marked as in the "non-aggregable" state. If the effective degrees of all basic grid cells are the target value, it means that all cells have been marked as in the "non-aggregable" state, and the iteration ends, and the aggregation operation can end. The specific steps include:

[0107] If the minimum value is 0, change the effective degree of the basic grid cell corresponding to the minimum effective degree to the target value;

[0108] Determine the third basic grid cell participating in aggregation;

[0109] Change the effective degree of the third basic grid cell to the target value;

[0110] End the aggregation operation when it is detected that the effective degrees of the basic grid cells mapped by the vector region to be observed are all the target value.

[0111] For example, assuming the target value is 100, there are basic grid cells A, B, C, D, E, F. Among them, the initial effective degree situation is: A: 2 (adjacent to B, C), B: 1 (adjacent to A), C: 3 (adjacent to A, D, E), D: 0 (no adjacent unaggregated cells), E: 2 (adjacent to C, D), F: 0 (no adjacent unaggregated cells). Because the effective degrees of D and F are 0, update them to 100. Then E participates in aggregation and change its effective degree to 100 as well. The effective degrees after the first update are A: 2, B: 1, C: 3, D: 100, E: 100, F: 100. There are cells (A, B, C) with effective degrees not equal to 100, continue the aggregation operation until the effective degrees of all cells are the target value - 100.

[0112] In the above steps, by marking the cells with effective degree 0 and the cells that have already participated in aggregation as the target value, repeated processing of the aggregated or isolated cells is avoided. It should be noted that the effective degree is the number of basic grid cells adjacent to the basic grid cell and not yet aggregated. Therefore, after some basic grid cells are aggregated, the effective degrees of the basic grid cells adjacent to them will also change correspondingly. The specific steps include:

[0113] Obtain the adjacency relationship of the basic grid cells;

[0114] Generate an adjacency list according to the adjacency relationship;

[0115] Traverse the adjacency list to obtain the fourth basic grid cell adjacent to the third basic grid cell;

[0116] Decrease the effective degree of the fourth basic grid cell by one.

[0117] Among them, the adjacency relationships of the basic grid cells are stored in the adjacency list. For example, Figure 7 As shown, first set indexes for the basic grid cells, which are 1, 2, 3, 4, 5, 6, 7 from top to bottom and from left to right in sequence, and then store the adjacency relationships of the indexed basic grid cells into the adjacency list. For example, Figure 8 As shown, the indexes of the basic grid cells adjacent to grid 1 are 2, 3, 4; the indexes of the basic grid cells adjacent to grid 2 are 1, 4, 5; the indexes of the basic grid cells adjacent to grid 3 are 1, 4, 6; the indexes of the basic grid cells adjacent to grid 4 are 1, 2, 3, 5, 6, 7; the indexes of the basic grid cells adjacent to grid 5 are 2, 4, 7; the indexes of the basic grid cells adjacent to grid 6 are 3, 4, 7; the indexes of the basic grid cells adjacent to grid 7 are 4, 5, 6.

[0118] The overall process of the above greedy algorithm is as Figure 9 shown. First, obtain the minimum effective degree n of the basic grid cells. When n = 0, modify the effective degree of this basic grid cell to 100 (the target value); when n = 1, aggregate this grid and the adjacent grids, and at the same time update the effective degree of this basic grid cell to 100; when n >= 2 (it can also be considered as n > 1) and n < 100, at this time, preferentially select the grid with the smallest degree and the second smallest degree among the adjacent grids, and the precondition for selection is to ensure that these 3 grids are adjacent to each other. Cover these three grids with an intermediate-level grid, and then update the effective degree of this basic grid cell to the target value. Finally, record the encoding of the grid with n = 100 into the target effective degree array. Among them, the target effective degree array records the encodings of the aggregated intermediate-level grid cells and the encodings of the basic grid cells that do not need to participate in the aggregation.

[0119] It should be noted that the encoding of the basic grid cells can be automatically obtained through the encoding scheme of Uber-H3, while the intermediate-level grid cells need to be set by oneself. The embodiments of the present invention are based on the encoding scheme of Uber-H3 for extended setting. The specific steps include:

[0120] Obtain the 64-bit grid encoding of the basic grid cells;

[0121] Add the grid code representing the intermediate layer grid cells to the 1st - 4th bits of the 64 - bit grid code;

[0122] Add the grid code representing the vertices of the intermediate layer grid cells to the 5th - 7th bits of the 64 - bit grid code;

[0123] Add the grid code representing the level of the intermediate layer grid cells to the 8th - 11th bits of the 64 - bit grid code, where the level of the intermediate layer grid cells is the intermediate value of the level of the basic grid cells and the level of the layer above the basic grid cells.

[0124] Except for the above - mentioned codes, other codes are the same as or related to Uber - H3. Further explanations are as follows: At the 0th bit: Reserved bit, with a value of 0. At the 1st - 4th bits: In H3, this represents the index mode of the cell. 1(0001) represents the grid code, 2(0010) represents the code of the unidirectional edge, 3(0011) refers to the code of the bidirectional edge, 4(0100) represents the vertex code, and other values are meaningless. Based on H3, for the intermediate layer grid, 8(1000) is added here to indicate the grid code of the intermediate layer grid, indicating that this code is for the intermediate layer grid. At the 5th - 7th bits: If the value of the index mode at the 1st - 4th bits is 2(0010) or 3(0011), it represents which edge of this H3 hexagonal grid this edge is, and the value range is 1 - 6(001 - 110); if the value of the index mode is 4, it represents the vertex number of this vertex as the owner, and the value range is 0 - 5(000 - 101); if the index mode is other values, the values at the 5th - 7th bits are meaningless; if the 1st - 4th bits are 8(1000), then this represents the center point of this intermediate layer grid, that is, the vertex of the basic grid, and it belongs to the vertex number of the northernmost hexagonal grid among the three basic H3 grids that make up the intermediate layer grid, with a value range of 0 - 5(000 - 101), and the coding order of the vertices is randomly set. In case of a pentagon, it is 0 - 4(000 - 100), and so on. The 8th - 11th bits represent the coding level corresponding to the H3 grid or the intermediate layer grid, with a range of [0,15]. For example, the coding level of the basic grid cells is 6, and the coding level of the corresponding intermediate layer grid is 6.5. The 12th - 18th bits represent the 122 basic units of the global division when the coding level is 0, with a range of [0,121], indicating which basic unit at the 0th level this H3 grid or the intermediate layer grid belongs to; for the 19th - 63rd bits, every 3 bits represent the values in the coordinate system of the corresponding face from coding level 1 to coding level 15 in turn, a total of 45 bits, covering the recursive relationship between the parent - child grids. Among them, the values of the intermediate layer grid in this part are the same as those of the northernmost H3 grid in its child grids, that is, the intermediate layer grid inherits this recursive relationship. If there is no northernmost H3 grid, the intermediate layer grid can be the same as the first H3 grid starting from the due north direction in the counter - clockwise direction.

[0125] In addition, when performing grid aggregation in the embodiments of the present invention, the differences in the thermal values of different grids are also considered. Only the basic grid units with the same thermal value and adjacent to each other will be aggregated into intermediate layer grid units.

[0126] In the embodiments of the present invention, the key information of the basic grid units mapped to the vector region to be observed is obtained. The key information includes the number, area, and common vertices of the basic grid units. If the number is greater than 1 and less than or equal to the first preset value, the center point of the intermediate layer grid unit to be generated is determined according to the common vertices of the basic grid units, and the area of the intermediate layer grid unit to be generated is determined according to the area of the basic grid units. Determining the center point of the intermediate layer grid unit through the common vertices ensures the consistency of the spatial relationship between the newly generated grid unit and the basic grid unit, avoiding topological errors or data breaks caused by grid division. Determining the area of the intermediate layer grid unit according to the area ensures the continuity and proportional consistency of the data in space. According to the center point and area of the intermediate layer grid unit to be generated, the basic grid units mapped to the vector region to be observed are aggregated to obtain the intermediate layer grid units. If the number is greater than the first preset value, the effective degree of the basic grid units is obtained. The effective degree refers to the number of basic grid units adjacent to the basic grid unit and not yet aggregated. The basic grid units mapped to the vector region to be observed are aggregated according to the effective degree to obtain the intermediate layer grid units. By introducing the concept of effective degree, adjacent and unaggregated units are preferentially aggregated, reducing repeated calculations and redundant operations, and improving the calculation efficiency. By aggregating the basic grid units to generate the intermediate layer grid units, the present application avoids the problem of excessive dead space and insufficient accuracy that may be brought by simple spatial aggregation, and also avoids the problems of too many mapped grids, resulting in an increase in the number of satellite shootings, excessive use of satellite resources, and excessive satellite planning and scheduling. Thereby reducing space loss, and using as few intermediate layer grids and basic level grids as possible for coverage, saving time and space loss for subsequent satellite constellation planning, reducing the pressure of satellite planning and scheduling, and enabling the satellite constellation planning to be carried out efficiently.

[0127] Figure 10 It is a structural diagram of a grid generation device provided by an embodiment of the present invention. The device may include:

[0128] The first acquisition module 201 is configured to acquire the key information of the basic grid units mapped to the vector region to be observed. The key information includes the number, area, and common vertices of the basic grid units.

[0129] The first determination module 202 is configured to, if the number is greater than 1 and less than or equal to the first preset value, determine the center point of the intermediate layer grid unit to be generated according to the common vertices of the basic grid units, and determine the area of the intermediate layer grid unit to be generated according to the area of the basic grid units.

[0130] The first aggregation module 203 is configured to aggregate the basic grid cells mapped by the to-be-observed vector region according to the center point and area of the intermediate layer grid cells to be generated, so as to obtain the intermediate layer grid cells.

[0131] The second acquisition module 204 is configured to, if the quantity is greater than a first preset value, acquire the effective degree of the basic grid cells, where the effective degree refers to the number of basic grid cells adjacent to the basic grid cells and not aggregated.

[0132] The second aggregation module 205 is configured to aggregate the basic grid cells mapped by the to-be-observed vector region according to the effective degree, so as to obtain the intermediate layer grid cells.

[0133] Optionally, the first acquisition module 201 specifically includes:

[0134] The first acquisition sub-module is configured to acquire the swath width of the satellite performing the observation task, the shape and area of the to-be-observed vector region.

[0135] The first determination sub-module is configured to determine the level of the basic grid cells mapped by the to-be-observed vector region according to the swath width.

[0136] The second determination sub-module is configured to determine the area of the basic grid cells mapped by the to-be-observed vector region according to the level.

[0137] The third determination sub-module is configured to determine the number of the basic grid cells mapped by the to-be-observed vector region according to the area of the basic grid cells and the area of the to-be-observed vector region.

[0138] The fourth determination sub-module is configured to determine the position distribution of the basic grid cells mapped by the to-be-observed vector region according to the shape of the to-be-observed vector region.

[0139] The fifth determination sub-module is configured to determine the common vertices of the basic grid cells mapped by the to-be-observed vector region according to the position distribution.

[0140] Optionally, the grid generation device further includes:

[0141] The third acquisition module is configured to acquire the 64-bit grid code of the basic grid cells.

[0142] The first addition module is configured to add the grid code representing the intermediate layer grid cells to the 1st - 4th bits of the 64-bit grid code.

[0143] The second addition module is configured to add the grid code representing the vertices of the intermediate layer grid cells to the 5th - 7th bits of the 64-bit grid code.

[0144] A third addition module, configured to add a grid code representing the level of the intermediate-layer grid cells to bits 8-11 of the 64-bit grid code, where the level of the intermediate-layer grid cells is the intermediate value between the level of the basic grid cells and the level of the layer above the basic grid cells.

[0145] Optionally, the first determination module 202 specifically includes:

[0146] A second acquisition sub-module, configured to acquire the target quantity and coding combination of the basic grid cells to which the common vertex belongs.

[0147] A sixth determination sub-module, configured to, if the maximum value of the target quantity is a first preset value, determine the corresponding common vertex as the center point of the to-be-generated intermediate-layer grid cells.

[0148] A screening sub-module, configured to, if the maximum value of the target quantity is a second preset value, screen out the center point of the to-be-generated intermediate-layer grid cells from the common vertices corresponding to the third preset value of the target quantity according to the coding combination.

[0149] A seventh determination sub-module, configured to determine three times the area of the basic grid cells as the area of the to-be-generated intermediate-layer grid cells.

[0150] Optionally, the second aggregation module 205 specifically includes:

[0151] A third acquisition sub-module, configured to acquire the minimum value of the effective degrees from the effective degrees.

[0152] A first aggregation sub-module, configured to, if the minimum value is 1, aggregate the first basic grid cells corresponding to the minimum value of the effective degrees and the basic grid cells adjacent to the first basic grid cells to obtain intermediate-layer grid cells.

[0153] A fourth acquisition sub-module, configured to, if the minimum value is greater than 1, acquire second basic grid cells adjacent to the first basic grid cells.

[0154] A fifth acquisition sub-module, configured to, in the case of determining that the first basic grid cells and the second basic grid cells are combined into a combination of three mutually adjacent basic grid cells, acquire the target effective degree sum of the combination of the three basic grid cells.

[0155] A second aggregation sub-module, configured to aggregate the combination of the three basic grid cells with the minimum target effective degree sum to obtain intermediate-layer grid cells.

[0156] A first modification sub-module, configured to, if the minimum value is 0, change the effective degree of the basic grid cells corresponding to the minimum value of the effective degrees to a target value.

[0157] An eighth determination sub-module, configured to determine third basic grid cells participating in the aggregation.

[0158] A second modification sub-module, configured to change the valid degree of the third basic grid cell to a target value.

[0159] A detection sub-module, configured to end the aggregation operation when it is detected that the valid degrees of the basic grid cells mapped by the vector region to be observed are all target values.

[0160] A sixth acquisition sub-module, configured to acquire the adjacency relationship of the basic grid cells.

[0161] An adjacency list generation sub-module, configured to generate an adjacency list according to the adjacency relationship.

[0162] A seventh acquisition sub-module, configured to traverse the adjacency list to acquire a fourth basic grid cell adjacent to the third basic grid cell.

[0163] A third modification sub-module, configured to subtract one from the valid degree of the fourth basic grid cell.

[0164] In an embodiment of the present invention, key information of basic grid cells mapped by a vector region to be observed is acquired. The key information includes the number, area, and common vertices of the basic grid cells. If the number is greater than 1 and less than or equal to a first preset value, the center point of the intermediate layer grid cell to be generated is determined according to the common vertices of the basic grid cells, and the area of the intermediate layer grid cell to be generated is determined according to the area of the basic grid cells. Determining the center point of the intermediate layer grid cell through the common vertices ensures the consistency of the spatial relationship between the newly generated grid cell and the basic grid cell, and avoids topological errors or data breaks caused by grid division. Determining the area of the intermediate layer grid cell according to the area ensures the continuity and proportional consistency of the data in space. According to the center point and area of the intermediate layer grid cell to be generated, the basic grid cells mapped by the vector region to be observed are aggregated to obtain the intermediate layer grid cell. If the number is greater than the first preset value, the valid degree of the basic grid cell is acquired. The valid degree refers to the number of basic grid cells adjacent to the basic grid cell and not yet aggregated. The basic grid cells mapped by the vector region to be observed are aggregated according to the valid degree to obtain the intermediate layer grid cell. By introducing the concept of valid degree, adjacent and unaggregated cells are preferentially aggregated, reducing repeated calculations and redundant operations, and improving the calculation efficiency. By aggregating the basic grid cells to generate the intermediate layer grid cell, the present application avoids the problem of excessive dead space and insufficient accuracy that may be brought by simple spatial aggregation, and also avoids the problems of too many mapped grids, increased satellite shooting times, excessive use of satellite resources, and excessive satellite planning and scheduling. Thereby reducing spatial loss, and using as few intermediate layer grids and basic level grids as possible for coverage, saving time and space loss for subsequent satellite constellation planning, reducing the pressure of satellite planning and scheduling, and enabling efficient satellite constellation planning.

[0165] The present invention also provides an electronic device. Figure 11 It is a structural block diagram of an electronic device provided by an embodiment of the present invention. Refer to Figure 11 , including a processor 301, a memory 302, and a computer program 3021 stored in the memory and executable on the processor. When the processor executes the program, the following steps of the grid generation method are implemented:

[0166] Obtain the key information of the basic grid cells mapped by the vector region to be observed. The key information includes the number, area, and common vertices of the basic grid cells;

[0167] If the number is greater than 1 and less than or equal to a first preset value, determine the center points of the intermediate layer grid cells to be generated according to the common vertices of the basic grid cells, and determine the areas of the intermediate layer grid cells to be generated according to the areas of the basic grid cells;

[0168] Aggregate the basic grid cells mapped by the vector region to be observed according to the center points and areas of the intermediate layer grid cells to be generated to obtain the intermediate layer grid cells;

[0169] If the number is greater than the first preset value, obtain the effective degree of the basic grid cells. The effective degree refers to the number of basic grid cells adjacent to the basic grid cells and not aggregated;

[0170] Aggregate the basic grid cells mapped by the vector region to be observed according to the effective degree to obtain the intermediate layer grid cells.

[0171] The present invention also provides a readable storage medium. When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the grid generation method of the foregoing embodiment.

[0172] For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiment.

[0173] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. From the above description, the structures required to construct such a system are obvious. In addition, the present invention is not directed to any particular programming language. It should be understood that the content of the present invention described herein can be implemented using various programming languages, and the description of the specific language above is for disclosing the best implementation mode of the present invention.

[0174] In the specification provided herein, a large number of specific details are set forth. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail so as not to obscure the understanding of this description.

[0175] Similarly, it should be understood that, in order to streamline the present invention and assist in understanding one or more of the various inventive aspects, in the foregoing description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, the disclosed method should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, the inventive aspects lie in less than all the features of the single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0176] Those skilled in the art will appreciate that the modules in the devices in the embodiments can be adaptively changed and disposed in one or more devices different from those of the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and in addition, they can be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all the features disclosed in this specification (including the accompanying claims, abstract and drawings) and all the processes or units of any method or device so disclosed. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract and drawings) can be replaced by an alternative feature that provides the same, equivalent or similar purpose.

[0177] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art should understand that in practice, a microprocessor or a digital signal processor (DSP) can be used to implement some or all of the functions of some or all of the components in the sorting device according to the present invention. The present invention can also be implemented as a device or apparatus program for performing part or all of the methods described herein. Such a program for implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0178] It should be noted that the above embodiments are illustrative of the present invention rather than restrictive thereof, and those skilled in the art can design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in the claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention can be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim listing several devices, several of these devices may be embodied by the same item of hardware. The use of the words first, second, and third, etc. does not denote any order. These words may be interpreted as names.

[0179] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0180] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

[0181] The above description is only the specific implementation manners of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention and should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

[0182] It should be noted that in the embodiments of this application, the processes of obtaining various data are all carried out on the premise of complying with the corresponding data protection regulations and policies of the country where the location is located and obtaining the authorization given by the owner of the corresponding device.

Claims

1. A grid generation method, characterized in that, The method includes: Obtaining key information of the basic grid cells for mapping the vector region to be observed, where the key information includes the number, area, and common vertices of the basic grid cells; If the number is greater than 1 and less than or equal to a first preset value, determining the center point of the intermediate layer grid cells to be generated according to the common vertices of the basic grid cells, and determining the area of the intermediate layer grid cells to be generated according to the area of the basic grid cells; Aggregating the basic grid cells for mapping the vector region to be observed according to the center point and area of the intermediate layer grid cells to be generated to obtain intermediate layer grid cells; If the number is greater than the first preset value, obtaining the effective degree of the basic grid cells, where the effective degree refers to the number of basic grid cells adjacent to the basic grid cells and not aggregated; Aggregating the basic grid cells for mapping the vector region to be observed according to the effective degree to obtain intermediate layer grid cells.

2. The method according to claim 1, characterized in that, The obtaining of the key information of the basic grid cells for mapping the vector region to be observed includes: Obtaining the swath width of the satellite performing the observation task, the shape and area of the vector region to be observed; Determining the level of the basic grid cells for mapping the vector region to be observed according to the swath width; Determining the area of the basic grid cells for mapping the vector region to be observed according to the level; Determining the number of the basic grid cells for mapping the vector region to be observed according to the area of the basic grid cells and the area of the vector region to be observed; Determining the position distribution of the basic grid cells for mapping the vector region to be observed according to the shape of the vector region to be observed; Determining the common vertices of the basic grid cells for mapping the vector region to be observed according to the position distribution.

3. The method according to claim 2, characterized in that, After aggregating the basic grid cells for mapping the vector region to be observed according to the effective degree to obtain intermediate layer grid cells, it further includes: Obtaining the 64-bit grid code of the basic grid cells; Adding a grid code representing the intermediate layer grid cells to the 1st - 4th bits of the 64-bit grid code; Adding a grid code representing the vertices of the intermediate layer grid cells to the 5th - 7th bits of the 64-bit grid code; Adding a grid code representing the level of the intermediate layer grid cells to the 8th - 11th bits of the 64-bit grid code, where the level of the intermediate layer grid cells is the intermediate value of the level of the basic grid cells and the upper level of the basic grid cells.

4. The method according to claim 1, wherein The determining of the center point of the intermediate layer grid cells to be generated according to the common vertices of the basic grid cells, and determining the area of the intermediate layer grid cells to be generated according to the area of the basic grid cells includes: Obtaining the target number and code combination of the basic grid cells to which the common vertices belong; If the maximum value of the target number is the first preset value, determining the corresponding common vertex as the center point of the intermediate layer grid cells to be generated; If the maximum value of the target number is the second preset value, then screening out the center point of the intermediate layer grid cells to be generated from the common vertices corresponding to the target number being the third preset value according to the code combination; Determine three times the area of the basic grid cell as the area of the intermediate layer grid cell to be generated.

5. The method according to claim 1, wherein The aggregating the basic grid cells mapped to the vector region to be observed according to the effective degree to obtain intermediate layer grid cells further includes: Obtain the minimum value of the effective degrees from the effective degrees; If the minimum value is 1, aggregate the first basic grid cell corresponding to the minimum value of the effective degrees and the basic grid cells adjacent to the first basic grid cell to obtain an intermediate layer grid cell; If the minimum value is greater than 1, obtain a second basic grid cell adjacent to the first basic grid cell; When it is determined that the combination of the first basic grid cell and the second basic grid cell forms a combination of three mutually adjacent basic grid cells, obtain the sum of the target effective degrees of the three basic grid cell combinations; Aggregate the combination of the three basic grid cell combinations with the minimum sum of the target effective degrees to obtain an intermediate layer grid cell.

6. The method according to claim 5, wherein After obtaining the minimum value of the effective degrees from the effective degrees, it further includes: If the minimum value is 0, change the effective degree of the basic grid cell corresponding to the minimum value of the effective degrees to a target value; Determine a third basic grid cell participating in the aggregation; Change the effective degree of the third basic grid cell to a target value; When it is detected that the effective degrees of all the basic grid cells mapped to the vector region to be observed are the target values, end the aggregation operation.

7. The method according to claim 6, characterized in that, After determining the third basic grid cell participating in the aggregation, it further includes: Obtain the adjacency relationship of the basic grid cells; Generate an adjacency list according to the adjacency relationship; Traverse the adjacency list to obtain a fourth basic grid cell adjacent to the third basic grid cell; Decrease the effective degree of the fourth basic grid cell by one.

8. A grid generation device, characterized in that, The device includes: A first acquisition module, configured to acquire key information of the basic grid cells mapped to the vector region to be observed, where the key information includes the number, area, and common vertices of the basic grid cells; A first determination module, configured to, if the number is greater than 1 and less than or equal to a first preset value, determine the center point of the intermediate layer grid cell to be generated according to the common vertices of the basic grid cells, and determine the area of the intermediate layer grid cell to be generated according to the area of the basic grid cells; A first aggregation module, configured to aggregate the basic grid cells mapped to the vector region to be observed according to the center point and area of the intermediate layer grid cell to be generated, to obtain an intermediate layer grid cell; A second acquisition module, configured to, if the number is greater than the first preset value, acquire the effective degrees of the basic grid cells, where the effective degree refers to the number of basic grid cells adjacent to and not aggregated with the basic grid cell; A second aggregation module, configured to aggregate the basic grid cells mapped to the vector region to be observed according to the effective degrees, to obtain an intermediate layer grid cell.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory is used for storing a computer program; When the processor executes the program stored in the memory, it implements the grid generation method according to any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon that, when executed by one or more processors, cause the processors to execute the grid generation method according to any one of claims 1-7.

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