Hexagonal prism space partitioning method suitable for flight missions

Abstract

The application discloses a hexagonal prism space partitioning method suitable for flight tasks, and comprises the following steps: adopting a space hexagonal prism mode to partition the space, the upper hexagon of the space hexagonal prism is larger than the lower hexagon, Uber H3 coding is adopted in the horizontal direction, the vertical direction is coded in the height rounding mode, and the coordinate system is expanded from (i, j, k) to (i, j, k, h); according to the different tasks, the appropriate coding bit number and speed calculation mode are selected, wherein the flight tasks include unmanned aerial vehicle formation flight, striking, civil aviation flight and missile striking. The hexagonal prism space partitioning method based on the task is established by combining the diversity of the task and the advantages of the hexagonal prism space partitioning, and the hexagonal prism space partitioning retrieval and calculation method based on the task can meet the needs of various scenes.

Description

Technical Field

[0001] This invention belongs to the field of flight control technology, and in particular relates to a hexagonal prism space partitioning method suitable for flight missions. Background Technology

[0002] Spatial partitioning methods are primarily involved in air traffic management and flight path planning. These methods help to manage air traffic more effectively, ensure flight safety, and optimize flight efficiency. Common spatial partitioning methods include sector partitioning, altitude layer partitioning, grid partitioning, and waypoint partitioning.

[0003] Sector partitioning divides airspace into different sectors, each managed by a dedicated air traffic controller, which helps reduce workload and improve control efficiency. Sector design can be flexibly adjusted based on factors such as flight traffic, terrain, and weather. However, sector boundaries may lead to discontinuities in flight paths, increasing the maneuverability requirements for aircraft. Furthermore, coordination between sectors is a challenge, requiring effective communication and cooperation between controllers in different sectors.

[0004] Layered air traffic management, by dividing the airspace into different layers, can reduce conflicts between aircraft at different altitudes. This helps improve flight safety and optimize flight efficiency. However, the division of airspace can be affected by factors such as terrain and weather, leading to flight restrictions in certain areas. Furthermore, changes in airspace may increase the maneuverability requirements of aircraft and increase flight costs.

[0005] Mesh partitioning divides airspace into regular grid cells, facilitating automated computer processing and management. This method can simplify flight path planning and improve flight efficiency. However, mesh partitioning may not be suitable for all airspaces, especially in areas with complex terrain and highly variable air traffic. Furthermore, the size and shape of the grid need to be optimized based on specific circumstances to balance flight efficiency and safety.

[0006] Waypoint segmentation divides a flight path into different segments by defining specific waypoints. This method helps simplify aircraft navigation and control, improving flight safety. Furthermore, waypoints can be flexibly set according to flight requirements and airspace characteristics. However, waypoint settings may be affected by various factors such as terrain, weather, and air traffic flow, requiring comprehensive consideration. In addition, too many waypoints can lead to complex flight paths and increased flight costs. Summary of the Invention

[0007] In view of this, the present invention combines the diversity of tasks and the advantages of hexagonal prism space partitioning to establish a task-based hexagonal prism space partitioning retrieval and calculation method to suit the needs of various scenarios.

[0008] To achieve the above objectives, this application discloses a hexagonal prism space partitioning method suitable for flight missions, comprising the following steps:

[0009] The space is divided using a spatial hexagonal prism, where the upper hexagon is larger than the lower hexagon. The horizontal direction uses Uber H3 encoding, and the vertical direction uses height rounding encoding. The coordinate system is expanded from (i,j,k) to (i,j,k,h).

[0010] The appropriate number of bits and speed calculation method are selected according to the different missions, including UAV formation flight, strike, civil aviation flight, and missile strike.

[0011] Preferably, the hexagonal prism space partitioning retrieval method adopts a (i,j,k,h) retrieval mode, including:

[0012] The horizontal direction of the hexagonal prism adopts the (i,j,k) retrieval method of Uber H3 hexagonal grid code;

[0013] In the vertical direction, k = h a / L h , where h a For altitude, L h L is the smallest element size in the height direction of a hexagonal prism spatial partition. h The integer method is used, where k is an integer.

[0014] Preferably, the hexagonal prism three-dimensional encoding rule consists of horizontal and vertical encoding of Uber H3, and the number of encodings varies depending on the task:

[0015] If the task scenario is m kilometers and the granularity is n meters, then the number of codes p = Floor(m*1000 / n), where Floor represents the floor operation. q <p<2 q+1 Then the elevation code of H3 two-dimensional encoding is q+1 bits, and the H3 two-dimensional encoding is 64 bits;

[0016] Minimum unit: The radius L of the smallest unit in H3 two-dimensional encoding he The smallest unit size L of elevation coding h Select | L he -L h When it is at its smallest.

[0017] Preferably, depending on the required response speed of the mission, Euclidean distance, Manhattan distance, and Manhattan-like distance are used to calculate the spatial distance between two points, including the distance between any two drones in drone formation flight, the distance between a missile and a target in a strike mission, and the distance from a civil aircraft to the destination in civil aviation flight.

[0018] The coordinate system after the hexagonal prism is partitioned into (i,j,k,h) parts has the following Euclidean distance:

[0019]

[0020] Where L r =cos(60°)L he L he and L h The minimum cell radius for H3 2D encoding and the minimum cell size for elevation encoding;

[0021] The Manhattan distance of the hexagonal prism space partition is: L man =max(i,i,k)+h, where max(i,i,k) is the maximum value of (i,i,k);

[0022] Manhattan-like distance of hexagonal prism space partition:

[0023]

[0024] Preferably, the appropriate distance calculation method is selected according to the different response speeds required by the task. From fast to slow, the distance calculation formulas are Manhattan distance, Manhattan-like distance, and Euclidean distance in that order.

[0025] The beneficial effects of this invention are as follows:

[0026] This invention combines the diversity of tasks with the advantages of hexagonal prism space partitioning to establish a task-based hexagonal prism space partitioning retrieval and calculation method, which can be suitable for the needs of various scenarios. Attached Figure Description

[0027] Figure 1 A flowchart of a hexagonal prism space partitioning method suitable for flight missions.

[0028] Figure 2 This is a schematic diagram of a hexagonal horizontal grid code.

[0029] Figure 3 This is a schematic diagram of the spatial division of a hexagonal prism.

[0030] Figure 4 This is a coding method for spatial partitioning of hexagonal prisms.

[0031] Figure 5 This is a calculation method for spatial partitioning of a hexagonal prism. Detailed Implementation

[0032] The present invention will be further described below with reference to the accompanying drawings, but this is not intended to limit the present invention in any way. Any modifications or substitutions made based on the teachings of the present invention shall fall within the protection scope of the present invention.

[0033] Hexagonal grid codes are developed based on the theory of Earth's surface subdivision. They are a type of spatial indexing based on a grid, but unlike ordinary rectangular grid indices, each grid cell is a regular hexagon. Compared to quadrilateral grid codes, regular hexagonal grid codes have uniform size, equal distances to neighbors, and six directions, making them more suitable for scenarios with stringent precision requirements. A common example of a hexagonal grid code is the Uber H3 grid code.

[0034] refer to Figure 1 A flowchart of a hexagonal prism spatial partitioning method suitable for flight missions is presented. The spatial hexagonal prism partitions space using a hexagonal prism approach, with the upper hexagon being larger than the lower hexagon. The horizontal direction of the hexagon uses Uber H3 encoding, while the vertical direction uses height rounding encoding. The coordinate system is expanded from (i,j,k) to (i,j,k,h). The appropriate number of bits and calculation method for the hexagonal prism are selected based on the specific mission.

[0035] Figure 2 This is a schematic diagram of a hexagonal horizontal grid code. The horizontal coding coordinate system uses the (i,j,k) method. Since the three-dimensional (i,j,k) coding is used to encode the two-dimensional coordinates, there is at least one case where the code (i,j,k) in any region is 0.

[0036] Figure 3 This is a schematic diagram of the spatial partitioning of a hexagonal prism. The spatial partitioning of a hexagonal prism divides the globe into hexagonal prisms of different sizes, with the upper hexagon being larger than the lower hexagon.

[0037] Figure 4 This is a schematic diagram of the hexagonal prism space partitioning encoding method. The hexagonal prism space partitioning retrieval method uses the (i,j,k,h) retrieval method, specifically as follows:

[0038] (1) Horizontal direction of hexagonal prism: The horizontal direction of hexagonal prism adopts the (i,j,k) retrieval method of Uber H3 hexagonal grid code;

[0039] (2) Vertical direction: k = h a / L h , where h a For altitude, L h L is the smallest element size in the height direction of a hexagonal prism spatial partition. h Using the rounding method, the value can be 10 meters or 20 meters.

[0040] The hexagonal prism 3D encoding rule consists of horizontal and vertical encoding for Uber H3, with the number of encoding elements varying depending on the task.

[0041] (1) If the task scenario is m kilometers and the granularity is n meters, then the number of codes p = Floor(m*1000 / n), where Floor represents the rounding operation. q <p<2 q+1 Therefore, the elevation code in the H3 2D encoding is q+1 bits, and the H3 2D encoding is 64 bits. Taking a 3km mission scenario as an example, and combining aviation practices, if a granularity of 10m is selected and the number is 300, then 9 bits can be used for representation. In this case, the H3 2D encoding is 60 bits, and the elevation code is 9 bits.

[0042] (2) Minimum Unit: To facilitate subsequent calculations and data management, the radius L of the minimum unit in H3 two-dimensional encoding is... he The smallest unit size L of elevation coding h Select | L he -L h When it is at its smallest.

[0043] Figure 5 This describes a hexagonal prism spatial partitioning calculation method. In the diagram, ΔH represents the horizontal distance, and Δh represents the vertical distance. In one embodiment, this application uses Euclidean distance, Manhattan distance, and Manhattan-like distance to calculate the spatial distance between two points, depending on the required speed for the mission. This includes the distance between any two drones in drone formation flight, the distance between a missile and its target in a strike mission, and the distance from a civil aircraft to its destination in civil aviation flights.

[0044] (1) Euclidean distance: The coordinate system after the hexagonal prism is partitioned into (i,j,k,h) parts has the following Euclidean distance:

[0045]

[0046] Where L r =cos(60°)L he L he L is the radius of the horizontal hexagon of the hexagonal prism. h The smallest element size in the height direction of the spatial division of a hexagonal prism;

[0047] (2) Manhattan distance: The Manhattan distance of the hexagonal prism space partition is: L man =max(i,i,k)+h, where max(i,i,k) is the maximum value of (i,i,k);

[0048] (3) Manhattan-like distance:

[0049] (4) Distance selection criteria: Select the appropriate distance calculation method according to the different response speeds required by the task. From fast to slow, the distance calculation formulas are Manhattan distance, Manhattan-like distance, and Euclidean distance in turn.

[0050] The beneficial effects of this invention are as follows:

[0051] This invention combines the diversity of tasks with the advantages of hexagonal prism space partitioning to establish a task-based hexagonal prism space partitioning retrieval and calculation method, which can be suitable for the needs of various scenarios.

[0052] As used herein, the term "preferred" is meant as an example, illustration, or illustration. Any aspect or design described herein as "preferred" need not be construed as being more advantageous than other aspects or designs. Rather, the use of the term "preferred" is intended to present the concept in a specific manner. As used in this application, the term "or" is intended to mean an inclusive "or" rather than an exclusionary "or." That is, unless otherwise specified or clear from the context, "X uses A or B" naturally includes either of the permutations. That is, if X uses A; X uses B; or X uses both A and B, then "X uses A or B" is satisfied in any of the foregoing examples.

[0053] Furthermore, although this disclosure has been shown and described with respect to one or more implementations, equivalent variations and modifications will occur to those skilled in the art based on a reading and understanding of this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the appended claims. In particular, with respect to the various functions performed by the aforementioned components (e.g., elements, etc.), the terminology used to describe such components is intended to correspond to any component (unless otherwise indicated) that performs the specified function of said component (e.g., is functionally equivalent to it), even if structurally not equivalent to the disclosed structure performing the functions in the exemplary implementations of this disclosure shown herein. Moreover, although specific features of this disclosure have been disclosed with respect to only one of several implementations, such features may be combined with one or more features of other implementations that may be desirable and advantageous for a given or particular application. Furthermore, with regard to the use of the terms “comprising,” “having,” “containing,” or variations thereof in the Detailed Description or claims, such terms are intended to be included in a manner similar to the term “including.”

[0054] The functional units in this invention embodiment can be integrated into a processing module, or each unit can exist physically separately, or multiple units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. The aforementioned devices or systems can execute the storage methods in the corresponding method embodiments.

[0055] In summary, the above embodiments are one implementation of the present invention, but the implementation of the present invention is not limited to the embodiments described above. Any changes, modifications, substitutions, combinations, or simplifications made that deviate from the spirit and principle of the present invention should be considered equivalent substitutions and are included within the protection scope of the present invention.

Claims

1. A method for spatial partitioning of hexagonal prisms suitable for flight missions, characterized in that, Includes the following steps: The space is divided using a spatial hexagonal prism, where the upper hexagon is larger than the lower hexagon. The horizontal direction uses Uber H3 encoding, and the vertical direction uses height rounding encoding. The coordinate system is expanded from (i,j,k) to (i,j,k,h). The appropriate number of bits and speed calculation method are selected according to the different tasks. Flight tasks include UAV formation flight, strike, civil aviation flight, and missile strike. The hexagonal prism space partitioning retrieval method uses a (i,j,k,h) retrieval pattern, including: The horizontal direction of the hexagonal prism adopts the (i,j,k) retrieval method of Uber H3 hexagonal grid code; Vertical direction ,in Altitude This represents the smallest element size in the height direction of a hexagonal prism spatially partitioned space. Using the integer method, It is an integer; The hexagonal prism 3D encoding rule consists of horizontal and vertical encoding for Uber H3, with the number of encoding elements varying depending on the task. If the task scenario is m kilometers and the granularity is n meters, then the number of codes p = Floor(m*1000 / n), where Floor represents the floor operation. q <p<2 q+1 Then the elevation code of H3 two-dimensional encoding is q+1 bits, and the H3 two-dimensional encoding is 64 bits; Minimum unit: Radius of the smallest unit in H3 two-dimensional encoding and the smallest unit size of elevation coding choose At its smallest; Depending on the required response speed for the mission, Euclidean distance, Manhattan distance, and Manhattan-like distance are used to calculate the spatial distance between two points, including the distance between any two drones in drone swarm flight, the distance between a missile and its target in an attack mission, and the distance from a civil aircraft to its destination in civil aviation flights. The coordinate system after the hexagonal prism is partitioned into (i,j,k,h) parts has the following Euclidean distance: in , and The minimum cell radius for H3 2D encoding and the minimum cell size for elevation encoding; The Manhattan distance of the hexagonal prism space partition is: ,in for The maximum value; Manhattan-like distance of hexagonal prism space partition: 。 2. The hexagonal prism space partitioning method suitable for flight missions according to claim 1, characterized in that, Choose the appropriate distance calculation method based on the different response speeds required by the task. From fastest to slowest response speed, the distance calculation formulas are Manhattan distance, Manhattan-like distance, and Euclidean distance, respectively.

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