An intelligent airspace management system based on grid code

Abstract

The present invention relates to an intelligent airspace management system based on a grid code, belonging to the field of aviation control technology. A grid code conversion and management module is added to the airspace management system. The application of the grid code not only greatly reduces the computational complexity and amount of massive airspace data processing, significantly improves the processing capability and response speed of the airspace management system, but also realizes the optimized utilization of airspace resources through dynamic management of the grid code. The present invention also realizes conflict detection and route planning based on the grid code, constitutes a full life cycle control system support for airspace management, and solves the problems of poor airspace management capability, slow processing speed of large data volumes, low efficiency, and lack of full life cycle management capability of existing airspace management systems.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic control, and in particular to an intelligent airspace management system based on grid codes. Background Art

[0002] With the widespread application of drone systems in various fields, including industry, agriculture, and the military, it has become a trend for drones to fly beyond "isolated airspace" and share national airspace with manned aircraft to perform diverse missions. The UAV Intelligent Airspace Management System is an extension of the "UAV Cloud Platform" and "Flight Service Station" systems defined by civil aviation standards. Its goal is to integrate manned and cargo drones into the overall national airspace management system through three phases: isolation, transition, and integration. Through technological advancements and innovative concepts in drone airspace management, a system solution will be developed that exponentially improves airspace utilization efficiency and surpasses civil aviation safety standards. Ultimately, comprehensive airspace management encompasses drones, general aviation, and civil aviation. Currently, the key technology restricting the full lifecycle control of all routes within the airspace is the ability to rapidly detect static conflicts, plan routes effectively, and efficiently support routes with large amounts of data.

[0003] Judging from the current state of research both domestically and internationally, there are currently few mature intelligent airspace management systems. Route generation is mostly achieved through simple manual editing, resulting in poor processing speed for large volumes of data. This, combined with poor airspace resource management capabilities and outdated technology, leads to low airspace resource utilization. Research on airspace route control technology has largely focused on localized drone dynamic obstacle avoidance, lacking systematic research on the entire lifecycle of airspace routes. Summary of the Invention

[0004] In view of the above analysis, an embodiment of the present invention aims to provide an intelligent airspace management system based on grid codes to solve the problems of the existing airspace management system lacking full life cycle management and control capabilities, poor airspace resource management capabilities, slow processing speed of large data volumes, and low computing efficiency.

[0005] On the one hand, an embodiment of the present invention provides an intelligent airspace management system based on a grid code, the intelligent airspace management system comprising a data storage module, a display control and editing module, a grid code conversion and management module, and an aircraft position acquisition module;

[0006] When the intelligent airspace management system is started, the display control and editing module reads the aviation data stored in the data storage module and displays it, and the grid code conversion and management module reads the aviation data stored in the data storage module and converts it into grid codes for temporary storage, wherein the aviation data includes planned routes and no-fly zones;

[0007] The aircraft position acquisition module is used to obtain the real-time position of the aircraft and send it to the data storage module for storage;

[0008] The display control and editing module is also used to edit routes and no-fly zones and temporarily store and display them in real time;

[0009] The grid code conversion and management module is further used to read the real-time position of the aircraft and dynamically update the corresponding grid code according to the real-time position of the aircraft; and read the edited routes and no-fly zones in the display control and editing module and convert them into grid codes for temporary storage.

[0010] The beneficial effects of the above technical solution are as follows: a technical solution for an airspace management system based on a grid code is provided, wherein the grid code conversion and management module not only provides a grid code conversion function, which can convert route and no-fly zone data into grid codes, but also the grid code conversion and management module also supports dynamic grid code management, which can dynamically manage the grid code status based on the aircraft position returned by the aircraft position acquisition module, and utilize the speed and efficiency advantages of grid code operations to improve the processing of aviation data such as routes and no-fly zones and the full life cycle management capabilities of airspace.

[0011] A further improvement to the above system, wherein the corresponding grid code is dynamically updated according to the real-time position of the aircraft, includes: the grid code conversion and management module sets a flight safety area for the aircraft with the aircraft as the center; when the aircraft is about to take off, the flight safety area is set to a safety circle with a radius of a preset threshold; and the grid codes covered by the safety circle are set to an exclusive state.

[0012] The beneficial effect of the above-mentioned further improvement scheme is: setting a safety circle for the aircraft about to take off through the grid code conversion and management module, and setting the grid code covered by the safety circle to an exclusive state, is one of the functions of realizing dynamic management of grid codes, ensuring efficient control of the safe flight area based on the dynamic state management of grid codes.

[0013] Based on a further improvement of the above system, the method of dynamically updating the corresponding grid code according to the real-time position of the aircraft further includes: when the aircraft flies along a planned route, the grid code conversion and management module dynamically updates the flight safety area and the corresponding grid code based on the real-time position grid code of the aircraft by the following method:

[0014] Reading the planned route grid code and dynamically updating the center of the safety circle based on the aircraft's location grid code;

[0015] The safe distance length in the aircraft's forward direction is calculated in real time based on the following formula:

[0016] R front =D+(V1 / V max)*(D max -D), where R front is the safe distance length in the forward direction of the aircraft, D is the preset threshold, and D max The maximum safety threshold of the aircraft is designed, V1 is the actual speed of the aircraft, V max Designing a maximum speed for the aircraft;

[0017] The arc corresponding to the safety circle is divided into four equal parts, wherein the arc includes a front arc, a rear arc, an upper arc, and a lower arc according to its orientation;

[0018] When an aircraft flies along a planned route, the radius of the front arc is updated in real time, using the safety distance in the aircraft's forward direction as the radius. The radii of the other arcs remain unchanged. A first straight line is drawn through the upper vertex of the safety circle parallel to the route, and a second straight line is drawn through the lower vertex of the safety circle parallel to the route. The area enclosed by the front arc, the first straight line, the second straight line, the upper arc, the lower arc, and the rear arc serves as the real-time flight safety area.

[0019] The grid code covered by the flight safety area is set to an exclusive state.

[0020] The beneficial effect of the above-mentioned further improvement scheme is that the safe area of ​​the aircraft's forward direction is dynamically adjusted during the flight process, which not only ensures the safety of the aircraft's flight, but also realizes the optimal utilization of airspace resources during the flight based on the grid code based on the above-mentioned technical solution through the grid code conversion and management module.

[0021] Based on a further improvement of the above system, the preset threshold is an aircraft safety threshold, and a grid code width equal to the aircraft safety threshold or any one of the two closest adjacent level grid code widths is selected as the lowest level grid in the distance constraint grid set.

[0022] The beneficial effects of the above-mentioned further improvement scheme are as follows: the method of setting the preset threshold in the present invention is consistent with the minimum precision selected by the grid map, that is, the lowest level, and is an appropriate and reasonable choice for route grid code processing, which neither greatly increases the computational burden nor too little affects the distance constraint; on the other hand, selecting the minimum precision as the minimum value of the preset threshold can make the route segments approximate straight lines when dividing the route, thereby reducing the computational complexity.

[0023] Based on further improvements to the above system, the grid code conversion and management module further includes a route grid code conversion submodule and a regional grid code conversion submodule. The route grid code conversion submodule converts the route into a grid code by the following method:

[0024] Reading a route from the data storage module or the display control and editing module, and dividing the route into segments starting from the starting point of the route with a preset threshold as a step size;

[0025] A distance constraint grid set is calculated for each route segment one by one, and the route grid code is generated through grid deduplication calculation and aggregation calculation.

[0026] The beneficial effects of the above-mentioned further improvement scheme are as follows: the grid code conversion module in the technical solution of the present invention corresponds to the typical route data in the airspace data, and the regional data provides processing sub-modules respectively, and the route data is segmented by setting the safety threshold, so as to efficiently calculate the grid set within a threshold range for each route segment without having to calculate all intersecting grids, which greatly reduces the amount of calculation and algorithm complexity; and the calculation result of the previous route segment can effectively reduce the amount of calculation of the next segment, further improving the efficiency of grid code calculation.

[0027] Based on further improvements to the above system, the following steps are performed to calculate each route segment one by one and establish a distance constraint grid set, the steps including:

[0028] If the two endpoints of the route segment are in the same grid, the grid is selected as the selected grid. If the selected grid does not exist in the distance constraint grid set, the selected grid is added to the distance constraint grid set.

[0029] If the two endpoints of the route segment are in different grids, the two different grids are added to the distance-constrained grid set, and a first selected area is obtained based on the longitude and latitude of the two different grids. Redundant grids are removed from the first selected area, and grids that meet preset conditions are selected from the remaining grids in the first selected area and added to the distance-constrained grid set.

[0030] The selected grid or the first selected area is expanded based on the preset threshold to obtain a second selected area, redundant grids are removed from the second selected area, and grids that meet preset conditions are selected from the remaining grids in the second selected area to be added to the distance constrained grid set.

[0031] The beneficial effect of the above-mentioned further improvement scheme is: on the basis of calculating the grid codes for each route segment based on the safety threshold, the added grid code de-redundancy operation between segments is added, so that the calculation result of the previous route segment can effectively reduce the amount of calculation for the next segment, further improving the efficiency of route grid code calculation.

[0032] Based on further improvements to the above system, the regional grid code conversion submodule converts the no-fly zone into a grid code by the following method:

[0033] Reading a no-fly zone from the data storage module or the display control and editing module, decomposing the zone based on a grid code hierarchy rule to obtain a lowest-level grid code containing the zone, and using the lowest-level grid code as the grid code to be processed;

[0034] Calculating and obtaining a boundary line grid code set that satisfies a distance constraint with the boundary line of the region;

[0035] The regional grid code set is obtained through the following process:

[0036] S11: converting each grid code in the boundary line grid code set into a grid code of a corresponding level of the grid to be processed, and removing duplicates to obtain the grid codes as each grid code in the updated boundary line grid code set;

[0037] S12: If the level corresponding to the grid code to be processed is higher than the set minimum level, decompose the grid code to be processed into grid codes of the next level; otherwise, end;

[0038] If the next level grid code exists in the area boundary grid set, the next level grid code is used as the grid code to be processed in the next iteration;

[0039] Otherwise, if the grid corresponding to the next-level grid code is located within the regional boundary line, the next-level grid code is added to the regional grid code set; and the process returns to step S11;

[0040] The regional grid code set and the regional boundary line grid code set are merged, and then deduplication and aggregation are performed to obtain the regional grid code.

[0041] The beneficial effects of the above-mentioned further improvement scheme are: compared with the algorithm optimized by the existing technology, the calculation complexity and amount of calculation are greatly reduced, and the regional grid code set can be obtained by fast calculation, and the calculation performance and speed are greatly improved.

[0042] Based on a further improvement of the above system, the intelligent airspace management system further includes a conflict detection module, which is used to read the aviation data edited in the display control and editing module and detect conflict risks by the following method, which includes:

[0043] sorting all grid codes temporarily stored in the grid code conversion and management module by size;

[0044] Determine whether adjacent grid codes in the grid code have a repetitive or inclusive relationship. If so, determine whether the adjacent grid codes with a repetitive or inclusive relationship are all no-fly zones. If so, return a detection result of no risk to the display control and editing module.

[0045] Otherwise, there is a risk of conflict in returning the detection results to the display control and editing module.

[0046] The beneficial effect of the above-mentioned further improvement scheme is that based on the grid code, only a very small amount of calculation is required to quickly find out whether there is a conflict between the existing aviation data and the newly added aviation data, which greatly improves the data processing speed, system response speed and operating efficiency of the intelligent airspace management system.

[0047] Based on the further improvement of the above system, the intelligent airspace management system further includes a route planning module, which is used to read the edited route in the display control and editing module, plan a valid route through the following method and send it to the data storage module for storage. The method is:

[0048] Read the waypoints of the edited route;

[0049] Find the grid codes of all waypoints from the grid code conversion and management module;

[0050] Convert the grid codes of all waypoints to raster;

[0051] Establishing the topological relationship between the waypoints based on grid eight-directional connectivity modeling;

[0052] Based on the topological relationship and the principle of minimum cost, an effective route between the waypoints is planned, and the lines between all the waypoints form the planned route.

[0053] The beneficial effect of the above-mentioned further improvement scheme is that the spatial characteristics of the grid code can be used to achieve more efficient conversion grids and marking of no-fly zone grids than coordinates, which significantly improves the efficiency and response speed of new route planning.

[0054] Based on the further improvement of the above system, when editing the no-fly zone in the display control and editing module, the following method is used to detect conflicts and automatically replan:

[0055] The grid code conversion and management module reads the edited no-fly zone coordinate area, converts the edited no-fly zone into a grid code, and temporarily stores the grid code;

[0056] The conflict detection module reads the planned route grid codes temporarily stored in the grid code conversion and management module and the grid codes corresponding to the edited no-fly zone, sorts all the read grid codes by size, and determines whether adjacent grid codes in the grid codes are repeated or included. If so, the adjacent grid codes with repeated or included relationships are regarded as existing route grid codes that conflict with the edited no-fly zone, and sends a detection result indicating a conflict risk to the display control and editing module for display.

[0057] The route planning module reads the conflicting existing route grid code and calculates the shortest segment of the conflicting existing route grid code, wherein both endpoints of the shortest segment are waypoints of the conflicting existing route, and the waypoints of the conflicting existing route do not conflict with any route or no-fly zone;

[0058] The route planning module automatically replans a valid route based on the two waypoints of the conflicting existing route.

[0059] The beneficial effect of the above-mentioned further improvement scheme is that the spatial characteristics of the grid code can achieve more efficient conflict detection and grid conversion than coordinates, which can significantly improve the efficiency and response speed of route replanning.

[0060] In the present invention, the above-mentioned technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of the present invention will be described in the following description, and some advantages will become apparent from the description or be learned through practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The accompanying drawings are only used for the purpose of illustrating specific embodiments and are not to be considered as limiting the present invention. Throughout the drawings, the same reference symbols denote the same components.

[0062] Figure 1 This is a diagram showing the module structure of the intelligent airspace management system of the present invention;

[0063] Figure 2 A schematic diagram of a grid code set covered by waypoint distance constraints according to an embodiment of the present invention;

[0064] Figure 3 This is a schematic diagram of route segmentation according to an embodiment of the present invention;

[0065] Figure 4 This is a schematic diagram of a first selected area according to an embodiment of the present invention;

[0066] Figure 5 This is a schematic diagram of a second selected area according to an embodiment of the present invention;

[0067] Figure 6 This is a schematic diagram of the segmentation of the regional boundary line according to an embodiment of the present invention;

[0068] Figure 7 A schematic diagram of a regional boundary grid code generated by an embodiment of the present invention;

[0069] Figure 8 A schematic diagram of a regional grid code algorithm generated by an embodiment of the present invention;

[0070] Figure 9 This is a schematic diagram of grid code aggregation operation according to an embodiment of the present invention;

[0071] Figure 10 This is a schematic diagram of the dynamic management of security circles and grid codes according to an embodiment of the present invention;

[0072] Figure 11 This is a schematic diagram of a repeated grid code for conflicting routes according to an embodiment of the present invention;

[0073] Figure 12 A schematic diagram of a grid code conversion grid according to an embodiment of the present invention;

[0074] Figure 13 Schematic diagram of arc fitting according to an embodiment of the present invention;

[0075] Figure 14 A schematic diagram of the topological relationship of the terrain within the no-fly zone according to an embodiment of the present invention;

[0076] Figure 15 This is a schematic diagram of automatic route replanning according to an embodiment of the present invention. DETAILED DESCRIPTION

[0077] To facilitate understanding of the technical solution of the present invention, the following lists specific explanations of the professional terms that appear or are involved:

[0078] Smart airspace refers to the use of technology within drone airspace to achieve intelligent airspace information, platform-based management data, and refined flight control, enabling efficient, safe, and controllable drone flight within controlled airspace. This primarily involves two components: data collection and processing. Data collection utilizes various sensor technologies, enabling the collection of multi-dimensional data such as drone position, speed, and heading. Data processing utilizes technologies such as artificial intelligence to make drone flight more intelligent and safer.

[0079] Grid Code: A multi-scale, discrete, global geographic grid coding model developed based on a global grid, suitable for navigation and positioning services. This grid coding model proposes a unified identification and expression method for global spatial regional location information, capable of identifying both locations and regions. It features non-overlapping boundaries, orthogonal grids, consistent longitude and latitude, and good compatibility with traditional data formats, as well as the ability to represent points and surfaces in an integrated manner. Through the use of integer coding, the complexity of identifying, expressing, and calculating location information can be greatly simplified. This effectively addresses the organization of massive, multi-source, and heterogeneous spatial information in terms of information computation speed, information indexing efficiency, and information exchange and integration.

[0080] Route conflict detection: Drone route conflict detection is divided into two types: static and dynamic. Static detection primarily involves checking the safe distance between a drone's route and other drone routes in the same airspace or within no-fly zones during the planning and generation phase to ensure safe flight. Dynamic detection primarily involves receiving real-time status data from surrounding aircraft during flight to dynamically detect potential collision risks with other aircraft. This also includes checking whether the drone itself is at risk of deviating from its preset route. These scenarios are collectively referred to as drone route conflict detection.

[0081] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, and are not used to limit the scope of the present invention.

[0082] A specific embodiment of the present invention discloses an intelligent airspace management system based on grid code, such as Figure 1 shown.

[0083] The intelligent airspace management system includes a data storage module, a display control and editing module, a grid code conversion and management module, and an aircraft position acquisition module;

[0084] When the intelligent airspace management system is started, the display control and editing module reads the aviation data stored in the data storage module and displays it, and the grid code conversion and management module reads the aviation data stored in the data storage module and converts it into grid codes for temporary storage, wherein the aviation data includes planned routes and no-fly zones;

[0085] The aircraft position acquisition module is used to obtain the real-time position of the aircraft and send it to the data storage module for storage;

[0086] The display control and editing module is also used to edit routes and no-fly zones and temporarily store and display them in real time;

[0087] The grid code conversion and management module is further used to read the real-time position of the aircraft and dynamically update the corresponding grid code according to the real-time position of the aircraft; and read the edited routes and no-fly zones in the display control and editing module and convert them into grid codes for temporary storage.

[0088] Specifically, the intelligent airspace management system disclosed in this embodiment discloses the system functional module structure for airspace management throughout its lifecycle, including a grid code conversion and management module, a display control and editing module, a data storage module, a conflict detection module, a route planning module, and an aircraft position acquisition module. The grid code conversion and management module has an advantage over existing airspace management systems in that it converts fine-grained coordinate data into a highly flexible grid code. By managing the grid code, the computational complexity and amount of aviation data are greatly reduced. The intelligent airspace management system can obtain the real-time position of an aircraft in real time through the aircraft position acquisition module and convert it into a grid code. The grid code conversion and management module dynamically updates the corresponding grid code status and stored parameters based on the aircraft's real-time position grid code. Preferably, the stored parameters of the grid code can be the aircraft's route time. In this way, occupied airspace is dynamically released, achieving optimal use of airspace resources.

[0089] Specifically, in this embodiment, the grid code is converted into the grid code of the corresponding level based on the specified improved GeoSOT level and the longitude and latitude coordinates of the point, and the corresponding grid is quickly located. A complete grid information includes: grid code, grid coordinates, grid level and other information.

[0090] For example, Figure 2 Taking the coordinates of point A (39°54′20″N, 116°25′29″E) as an example, the 16-level grid code (the grid scale is about 1km) is calculated using the following algorithm:

[0091] ① First, encode the longitude and latitude coordinates of point A according to the grid size comparison table below. The encoding process is to divide the coordinate value by the grid size of each level continuously. The quotient is the grid code value of that level until the specified encoding level is reached.

[0092] The longitude value 116°25′29″ is encoded at level 16 as follows:

[0093]

[0094] The 16th level code for latitude 39°54′20″ is as follows:

[0095]

[0096] The final 16th-level binary grid code of point A obtained by cross-coding latitude and longitude is: 00000111010011101010110110100100;

[0098] If converted into quaternary, it is: 0013103222312210.

[0099] Table 1: Grid size comparison table

[0100]

[0101] ② The grid rectangle coordinates are calculated as follows:

[0102] Rect.Left=116°25′29″-29″=116°25′;

[0103] Rect.Bottom=39°54′20″-20″=39°54′;

[0104] Rect.Right=Rect.Left+32″=116°25′32″;

[0105] Rect.Top=Rect.Bottom+32″=39°54′32″;

[0106] ③ Grid code set calculation considering distance constraints:

[0107] like Figure 2 As shown in the figure, the calculation requirement is not only to obtain the grid information of point A, but also to obtain the information of all grids within a certain range from point A. The distance constraint range is expressed by a dotted box in the figure. The actual calculation result is the set of all grids with diagonal lines. There are a total of 9 grids here, each of which includes the grid code of the corresponding level and the corresponding grid coordinates and other information.

[0108] Furthermore, the grid code conversion and management module further includes a route grid code conversion submodule and a regional grid code conversion submodule, wherein the route grid code conversion submodule converts the route into a grid code by the following method:

[0109] Reading a route from the data storage module or the display control and editing module, and dividing the route into segments starting from the starting point of the route with a preset threshold as a step size;

[0110] A distance constraint grid set is calculated for each route segment one by one, and the route grid code is generated through grid deduplication calculation and aggregation calculation.

[0111] Furthermore, the calculation of each route segment one by one and the establishment of a distance constraint grid set are completed by the following steps, which include:

[0112] If the two endpoints of the route segment are in the same grid, the grid is selected as the selected grid. If the selected grid does not exist in the distance constraint grid set, the selected grid is added to the distance constraint grid set.

[0113] If the two endpoints of the route segment are in different grids, the two different grids are added to the distance-constrained grid set, and a first selected area is obtained based on the longitude and latitude of the two different grids. Redundant grids are removed from the first selected area, and grids that meet preset conditions are selected from the remaining grids in the first selected area and added to the distance-constrained grid set.

[0114] The selected grid or the first selected area is expanded based on the preset threshold to obtain a second selected area, redundant grids are removed from the second selected area, and grids that meet preset conditions are selected from the remaining grids in the second selected area to be added to the distance constrained grid set.

[0115] For example, assuming that the lowest level grid is level 16, according to Table 1, the size of the level 16 grid is 1 km, and the size is 32″, so the minimum value of the safety threshold is the width of the level 16 grid.

[0116] Specifically, starting from the starting point A, a temporary intermediate node is inserted between AB with a threshold as the step length to segment the route. The threshold is preferably set to the width of the lowest level grid. If the route AB is less than one step length, no point insertion is required. When the distance between the last inserted node and B is less than one step length, point insertion is also stopped, such as Figure 3 Seven intermediate nodes are inserted to form route segments AA1, A1A2, ..., A7B.

[0117] Then, as Figure 4 As shown, each segment is processed, starting with segment AA1, and the grid codes of point A and point A1 are calculated as G A ,G A1 , if G A =G A1 , indicating that A and A1 are in the same grid. At this time, the grid where points A and A1 are located is saved in the distance constraint grid set G.

[0118] It should be noted that the distance constraint grid set is initially set to an empty set. After traversing all route segments AA1, A1A2, ..., A7B, the grid code corresponding to each route segment is stored in the set.

[0119] like Figure 4 As shown, if the grid code G where point A is located is A The grid code G where point A1 is located A1 Different, they are merged into a large grid G Inner, specifically, according to G A , G A1 The range of the grids where point A and point A1 are located is sorted respectively by their longitude and latitude, and the range of the grids where point A and point A1 are located with the largest difference in longitude and latitude is taken as the first selected area, namely G Inner .

[0120] For example, assume that the grid longitude and latitude of point A is:

[0121] ARect.Left = 116°25′;

[0122] ARect.Bottom=39°54′32″;

[0123] ARect.Right=116°25′32″;

[0124] ARect.Top=39°54′;

[0125] The grid longitude and latitude of point A1 are:

[0126] A1Rect.Left=116°25′32″;

[0127] A1Rect.Bottom=39°55′4″;

[0128] A1Rect.Right=116°26′4″;

[0129] A1Rect.Top=39°54′32″;

[0130] Sort the longitudes of points A and A1, and we get: ARect.Left, ARect.Right, A1Rect.Left, A1Rect.Right. It can be seen that the difference between the longitudes of ARect.Left and A1Rect.Right is the largest, so keep these two longitudes as G Inner Similarly, obtain the two latitudes with the largest difference between point A and point A1, ARect.Top and A1Rect.Bottom, as G Inner The latitude of G Inner The grid code contained in the rectangular area.

[0131] Get G Inner Remove G from A , G A1 The remaining two grid codes are marked as G LT , G RB .

[0132] Furthermore, the preset threshold is an aircraft safety threshold, and a grid code width equal to the aircraft safety threshold or any one of the two closest adjacent grid code widths is selected as the lowest level grid in the distance constraint grid set.

[0133] Specifically, the lowest-level grid code width depends on the aircraft's own safety threshold, which is a factory parameter based on the aircraft's maneuverability properties. Preferably, a grid code width that is equal to or closest to the aircraft's own safety threshold is selected as the lowest-level grid code width. The advantage of this approach is that it not only ensures the aircraft's safety threshold range, but also prevents the selection of a grid code width that is too large to cause coarse-grained errors, or too small to cause low grid code accuracy, resulting in an increase in invalid calculations.

[0134] Judge AA1 and G respectively LT ,G RB The distance relationship, if G LT ,G RB If the distance between the farthest point of the mid-distance route segment AA1 and the perpendicular line of the route segment AA1 is less than the safety threshold, then G LT and G RB Save to the distance constraint grid set G.

[0135] Then, continue to expand G according to the safety threshold Inner Cheng G Outer , specifically, from G Inner The top, bottom, left, and right sides extend outward by a threshold width, such as Figure 5 As shown, in the embodiment G Inner The original rectangular area containing 2*2, that is, 4 grids, is expanded to G Outer After that, it becomes a 4*4 rectangular area, making G Outer Just cover all grids within the AA1 segment threshold range.

[0136] Specifically, from G Outer Remove G from Inner The remaining grids are strictly compared with AA1, and the grids with distances less than the threshold are saved in the distance constraint grid set G.

[0137] After processing the AA1 segment, continue processing the A1A2 segment. When processing the A1A2 segment, it is also processed in a similar way to the previous AA1 segment. However, due to the adjacent relationship between AA1 and A1A2, there will be repeated grid areas at the connection. Many grids have been marked and retained when processing the AA1 segment. Therefore, after removing the redundant grids, the repeated verification of the overlapping grids of AA1 and A1A2 can be skipped directly. No secondary processing is required. Only the newly added grids with a distance greater than the safety threshold from the previous processing are processed to reduce the number of comparisons. This process is repeated until the last route segment is processed, and finally a grid like Figure 6 The total route grid code set shown.

[0138] Furthermore, the regional grid code conversion submodule converts the no-fly zone into a grid code by the following method:

[0139] Reading a no-fly zone from the data storage module or the display control and editing module, decomposing the zone based on a grid code hierarchy rule to obtain a lowest-level grid code containing the zone, and using the lowest-level grid code as the grid code to be processed;

[0140] Calculating and obtaining a boundary line grid code set that satisfies a distance constraint with the boundary line of the region;

[0141] The regional grid code set is obtained through the following process:

[0142] S11: converting each grid code in the boundary line grid code set into a grid code of a corresponding level of the grid to be processed, and removing duplicates to obtain the grid codes as each grid code in the updated boundary line grid code set;

[0143] S12: If the level corresponding to the grid code to be processed is higher than the set minimum level, decompose the grid code to be processed into grid codes of the next level; otherwise, end;

[0144] If the next level grid code exists in the area boundary grid set, the next level grid code is used as the grid code to be processed in the next iteration;

[0145] Otherwise, if the grid corresponding to the next-level grid code is located within the regional boundary line, the next-level grid code is added to the regional grid code set; and the process returns to step S11;

[0146] The regional grid code set and the regional boundary line grid code set are merged, and then deduplication and aggregation are performed to obtain the regional grid code.

[0147] Specifically, to calculate the minimum level grid containing the area, the maximum grid (256*256) can be decomposed level by level. Each time the current grid is decomposed down one level, it is converted into four sub-grids. Suppose the current grid is G A , the four subgrids are GA1 , G A2 , G A3 , G A4 , if G A1 , G A2 , G A3 , G A4 If a grid in G completely contains the region, then this subgrid replaces G A , and the process is repeated until the next level of sub-grid no longer meets the requirements. The current level grid is the minimum level grid that contains the area, and the calculation ends. Figure 7 As shown, the dotted large grid G O It is the smallest level grid that contains the area, with point O as the center point of the grid.

[0148] Calculating and obtaining a boundary line grid code set that satisfies a distance constraint with the boundary line of the region;

[0149] like Figure 8 As shown, the regional grid code set is obtained through the following process:

[0150] For example, for ease of explanation, the region boundary line grid code set is denoted as G Line , the set of grid codes to be processed is recorded as G Intersect First, the minimum level grid code G of the area included in step S1 is O Join G Intersect middle.

[0151] S11: converting each grid code in the boundary line grid code set into a grid code of a corresponding level of the grid to be processed, and removing duplicates to obtain the grid codes as each grid code in the updated boundary line grid code set;

[0152] The low-level bits and codes of each grid code in the boundary line grid code set are removed, and only codes of the same level and bits as those of the grid to be processed are retained.

[0153] For example, for ease of explanation, the current G Intersect The level of the grid code is denoted as L C , G Line All grid codes in the Lth C The grid code of the level is converted and duplicates are removed. The grid code set after conversion is recorded as: G C .

[0154] S12: If the level corresponding to the grid code to be processed is higher than the set minimum level, decompose the grid code to be processed into grid codes of the next level; otherwise, end;

[0155] If the next level grid code exists in the area boundary grid set, the next level grid code is used as the grid code to be processed in the next iteration;

[0156] Otherwise, if the grid corresponding to the next-level grid code is located within the regional boundary line, the next-level grid code is added to the regional grid code set; and the process returns to step S11;

[0157] For example, G Intersect Any grid code in is represented by the variable symbol G i , judge G one by one Intersect Each G i Is it consistent with the grid code set G C A grid code in is equal,

[0158] If yes, it means the current G i Included in the boundary grid code set G Line , then the current one is included in G Line G i Decompose into the next level grid code: G i0 , G i1 , G i2 , G i3 , and put G i0 , G i1 , G i2 , G i3 Add to the spare grid code set and record it as G Bak In the meantime, from G Intersect Delete the file contained in G Line G i ;

[0159] Otherwise, it means the current G i There are two situations: either G i is completely inside the region, or completely outside the region. Next, get G i The center point of the grid is used to determine the spatial relationship with the region. Specifically, the rectangular area formed by the maximum longitude, minimum longitude, highest latitude, and lowest latitude of the region obtained by sorting the longitude and latitude of the region boundary line is used as the minimum circumscribed rectangle of the region. i The center point coordinates are compared with the minimum bounding rectangle. If the current G i If the center point coordinates are inside the minimum bounding rectangle, the current G i As a result, the grid code is retained in the spare grid code set denoted as G Surin In G Intersect Delete the current G from the collection i If the center point is outside the region, then it is also in G Intersect Delete the current G from the collection i , thus ending the current G i judgment.

[0160] To GIntersect After all grid codes are processed, clear the set G Intersect , the set G Bak All grid codes in G are assigned to Intersect , and loop through step S3 until G Intersect The grid code level and G Line If the lowest grid code level is the same, the loop ends.

[0161] After the above steps, the obtained set includes G Line , G Surin .

[0162] The regional grid code set and the regional boundary line grid code set are merged, and then deduplication and aggregation are performed to obtain the regional grid code and store it.

[0163] For example, merge G Line and G Surin Denoted as set G ALL , for G ALL Perform grid code deduplication and aggregation processing.

[0164] Specifically, according to the principle of minimum grid codes, it is necessary to aggregate the grid codes of some areas upwards to reduce the number of grid codes to a minimum.

[0165] Since the grid coding principle follows the equal longitude and latitude quadtree grid system, through sorting, if four adjacent grid codes simultaneously meet the following requirements: Same level, The upper level grid codes are all the same; then the four grid codes can be aggregated into one upper level grid code.

[0166] For example, Figure 9 As shown:

[0167] The large grid where point C is located is actually composed of 4 small grids G C1 ,G C2 ,G C3 ,G C4 ,The level of the small grid is level 16, and the grid codes are:

[0168] G C1 =00000111010011101010110110100100;

[0169] G C2 =00000111010011101010110110100101;

[0170] G C3 =00000111010011101010110110100110;

[0171] G C4 =00000111010011101010110110100111;

[0172] Because G C1 ,G C2 ,G C3 ,G C4 The upper level grid code is 000001110100111010101101101001, recorded as G C ,

[0173] Meet the merging requirements, the merged grid G C Become the 15th level grid.

[0174] Theoretically, after a grid code is aggregated once, it can continue to aggregate upwards until all adjacent grid codes no longer meet the conditions, and then the aggregation process is stopped.

[0175] For example, the grid code G O Decomposed into 4 sub-grid codes G O0 , G O1 , G O2 , G O3 , let L O =15, then L O0 =L O1 =L O2 =L O3 =16, and the boundary line grid code set G Line The minimum level is level 19. O0 , G O1 , G O2 , G O3 Included in G at level 16 Line , need to keep G O0 , G O1 , G O2 , G O3 And continue to judge. O2 For example, G O2 Continue to decompose into: G O20 , G O21 , G O22 , G O23 , after comparing G O20 , G O22 , G O23 Not included in G at level 17 Line , it can be deleted directly after further judgment. O21 Included in G at level 17 Line , continue to retain and further judge. This cycle continues until GIntersect and G Line After the 18th level grid code inclusion relationship judgment is completed, all grid codes included in the region are temporarily stored in the grid code set G Surin In, such as Figure 8 In, G 012 Can be added directly to G Surin Then G Surin and G Line Merge into G ALL , and then call step S4 to G ALL The grid code is deduplicated and aggregated, and the regional grid code algorithm is completed.

[0176] like Figure 10 As shown, further, the dynamic updating of the corresponding grid code according to the real-time position of the aircraft includes: the grid code conversion and management module sets a flight safety area for the aircraft with the aircraft as the center, when the aircraft is about to take off, the flight safety area is set to a safety circle with a radius of a preset threshold, and the grid codes covered by the safety circle are set to an exclusive state.

[0177] Furthermore, the dynamically updating the corresponding grid code according to the real-time position of the aircraft further includes: when the aircraft flies along the planned route, the grid code conversion and management module dynamically updates the flight safety area and the corresponding grid code based on the real-time position grid code of the aircraft by the following method:

[0178] Reading the planned route grid code and dynamically updating the center of the safety circle based on the aircraft's location grid code;

[0179] The safe distance length in the aircraft's forward direction is calculated in real time based on the following formula:

[0180] R front =D+(V1 / V max )*(D max -D), where R front is the safe distance length in the forward direction of the aircraft, D is the preset threshold, and D max The maximum safety threshold of the aircraft is designed, V1 is the actual speed of the aircraft, V max Designing a maximum speed for the aircraft;

[0181] The arc corresponding to the safety circle is divided into four equal parts, wherein the arc includes a front arc, a rear arc, an upper arc, and a lower arc according to its orientation;

[0182] When an aircraft flies along a planned route, the radius of the front arc is updated in real time, using the safety distance in the aircraft's forward direction as the radius. The radii of the other arcs remain unchanged. A first straight line is drawn through the upper vertex of the safety circle parallel to the route, and a second straight line is drawn through the lower vertex of the safety circle parallel to the route. The area enclosed by the front arc, the first straight line, the second straight line, the upper arc, the lower arc, and the rear arc serves as the real-time flight safety area.

[0183] The grid code covered by the flight safety area is set to an exclusive state.

[0184] Specifically, the grid code conversion and management module starts to set a safety circle for an aircraft that is about to execute a planned route AEFG before taking off, such as Figure 10 The dotted circle at point A is shown in the figure. The safety circle is a safe area for an aircraft during flight. Different safety circle ranges are set according to different aircraft types and characteristics. Once the safety circle is set, the grid code conversion and management module sets the grid codes covered by the safety circle to an exclusive state.

[0185] After the aircraft takes off, based on safety considerations, as the speed changes, it is necessary to gradually adjust the distance to the safe area in the direction of flight, such as Figure 10 As shown in the irregular solid line area at point E, the radius of the front arc of the safety circle is gradually adjusted along with the speed of the aircraft in the forward direction, as shown in FIG. Figure 10 As shown in the big circle with point E as the center, the solid line part of the big circle belongs to the safety circle arc in the forward direction of the aircraft after the radius of the safety circle is adjusted, that is, the front arc; Figure 10 Point E is the center of the small circle. The arc radius of the solid line part of the small circle is the same as the radius of the safety circle set when the aircraft is about to take off. Figure 10 The dotted safety circle shown at point A has the same radius and remains unchanged; the safety areas on the left and right sides are as follows: Figure 10 As shown in the figure, two straight lines located on both sides of the route and parallel to the route are shown, the two straight lines are the first straight line and the second straight line respectively. When the aircraft flies along the route, the two sides of the safety area do not exceed the range of the first straight line and the second straight line; the area enclosed by the first straight line, the second straight line, the solid large circle arc, and the solid small circle arc is the safety area. Preferably, as the speed changes, the solid large circle arc (i.e., the front arc) is changed by adjusting the forward direction radius of the safety circle, thereby changing the coverage range of the safety area. The grid code conversion and management module sets the forward direction grid codes to the exclusive state in sequence based on the change in the safety area coverage range.

[0186] Preferably, the maximum radius of the safety circle in the forward direction does not exceed twice the preset threshold.

[0187] As the rear end of the aircraft safety circle leaves the grid code of the coverage area, Figure 10 As shown in the dotted grid, the grid code conversion and management module immediately releases the exclusive state of the corresponding grid code, so that the route BCH can pass safely.

[0188] The advantage of this embodiment is that not only can the grid code conversion and management module realize dynamic monitoring of the real-time flight status of the aircraft and optimized use of airspace resources, but also based on the advantages of grid codes in computing efficiency and speed, the intelligent airspace management system can manage the real-time status of a large number of aircraft and airspace resources very quickly and efficiently.

[0189] Furthermore, the intelligent airspace management system further includes a conflict detection module, which is configured to read the aviation data edited in the display control and editing module and detect conflict risks by the following method, the method comprising:

[0190] sorting all grid codes temporarily stored in the grid code conversion and management module by size;

[0191] Determine whether adjacent grid codes in the grid code have a repetitive or inclusive relationship. If so, determine whether the adjacent grid codes with a repetitive or inclusive relationship are all no-fly zones. If so, return a detection result of no risk to the display control and editing module.

[0192] Otherwise, there is a risk of conflict in returning the detection results to the display control and editing module.

[0193] Specifically, the intelligent airspace management system disclosed in this embodiment also includes a conflict detection module, which is also another core functional module in the airspace full life cycle management.

[0194] For example, Figure 11 As shown, the following algorithm process is explained using the conflict between the new route and the existing route.

[0195] First, generate a grid code set for the new route, denoted as G New ; The existing grid code set in the airspace manager is denoted as G Left ,If there is no task object in the airspace, then G Left At this point, the question of whether the new route can be added to the airspace manager is transformed into: just judge whether G New and G Left It only matters whether there is an intersection. If there is an intersection, it means that the new route conflicts with the existing route. If there is no intersection, it means that the new route does not conflict with the existing route.

[0196] Figure 11 The specific algorithm process is: first temporarily merge G New and G Left G All , for G All Do a quick sort of the grid code, then traverse G once All , check whether the grid codes of the previous and next elements have repeated values ​​or containment relationships. If so, it means that the new route conflicts with existing objects in the airspace; if not, the route is safely added to the airspace manager, and then the G is updated. Left G All The cost of this process is basically the time it takes to do a quick sort, and it is very efficient.

[0197] Furthermore, the intelligent airspace management system further includes a route planning module, which is used to read the edited route in the display control and editing module, plan a valid route by the following method and send it to the data storage module for storage, the method being:

[0198] Read the waypoints of the edited route;

[0199] Find the grid codes of all waypoints from the grid code conversion and management module;

[0200] Convert the grid codes of all waypoints to raster;

[0201] Establishing the topological relationship between the waypoints based on grid eight-directional connectivity modeling;

[0202] Based on the topological relationship and the principle of minimum cost, an effective route between the waypoints is planned, and the lines between all the waypoints form the planned route.

[0203] Furthermore, when editing a no-fly zone in the display control and editing module, the following methods are used to detect conflicts and automatically replan the zone:

[0204] The grid code conversion and management module reads the edited no-fly zone coordinate area, converts the edited no-fly zone into a grid code, and temporarily stores the grid code;

[0205] The conflict detection module reads the planned route grid codes temporarily stored in the grid code conversion and management module and the grid codes corresponding to the edited no-fly zone, sorts all the read grid codes by size, and determines whether adjacent grid codes in the grid codes are repeated or included. If so, the adjacent grid codes with repeated or included relationships are regarded as existing route grid codes that conflict with the edited no-fly zone, and sends a detection result indicating a conflict risk to the display control and editing module for display.

[0206] The route planning module reads the conflicting existing route grid code and calculates the shortest segment of the conflicting existing route grid code, wherein both endpoints of the shortest segment are waypoints of the conflicting existing route, and the waypoints of the conflicting existing route do not conflict with any route or no-fly zone;

[0207] The route planning module automatically replans a valid route based on the two waypoints of the conflicting existing route.

[0208] Specifically, the intelligent airspace management system also includes a route planning module, which is another important functional module in the full life cycle management of airspace. The grid code conversion and management module included in the intelligent airspace management system reads the newly added routes or no-fly zones in the display control and editing module, converts the routes and no-fly zones into grid codes, and the route planning module converts the grid codes converted by the grid code conversion and management module into grids. Among them, the grid is another method of marking routes and no-fly zones, which uses grid marking areas of the same size and each marking consumption weight information for automatic route planning. The eight-way connectivity modeling based on the grid will calculate the import range of consumption weight data according to the positions between the currently planned waypoints, and then import the consumption weight data at one time, and build a topological relationship connecting the eight directions of the nodes, and store it in the corresponding memory data structure, and keep it in memory until one planning is completed.

[0209] It should be noted that the cost weight is an important parameter for calculating eight-directional connectivity and topological relationships using grids. Those skilled in the art can select the specific type of cost weight according to different situations. For example, slope data can be used as the cost weight, and the cost weight of each grid can be determined according to the location of the grid.

[0210] Generally, the eight-way grid connectivity modeling is to convert the very fine-grained data such as the latitude, longitude, and elevation information of the flight route or no-fly zone into a grid. In this embodiment, the grid is converted into a grid code, which can greatly reduce the amount of calculation and complexity of the conversion. For example, Figure 12 As shown, the method of converting the grid code into a grid is:

[0211] Calculate the index positions of the four corner points of the grid code rectangle in the raster data. The dotted grids in the figure are the grids corresponding to the grid code, which are respectively denoted as: L T (X L ,Y T ), R T (X R ,Y T ), R B (X R ,Y B ), L B (X L,Y B );

[0212] If the grid code is in exclusive state during the planned route period, the row and column numbers are in (X L ,X R )、(Y B ,Y T ) is set to a null value, that is, it is marked as an invalid area for route planning and does not participate in automatic route planning; otherwise, the grids within the coverage of the grid code are set to corresponding valid consumption values.

[0213] Then, the route planning algorithm is executed based on the grid, which can complete the grid conversion with a very small amount of calculation. Then, the route planning is completed based on the grid and related algorithms. After the planned route is obtained, it is converted and saved as a grid code.

[0214] Specifically, after the grid code is converted, the DJ algorithm or the A* algorithm is used to search for the minimum cost path, and the starting point and the subsequently searched nodes are iteratively processed in sequence according to the following steps: the node is pushed into the heap manager, and then the heap manager is looped and each time the node grid with the smallest cost in the eight-directional connectivity neighborhood node grid of the node grid is popped out, the 8 neighboring node grids of the node grid with the smallest cost are pushed into the heap manager, if the cost value of the neighboring node grid has been assigned, the assigned cost value is compared with the existing cost value, the cost value of the neighboring node grid is dynamically modified, and the smaller value is retained; this cycle is repeated until the end point is found.

[0215] Select two adjacent waypoints, one as the starting point and the other as the end point, with the starting point as the initial node, and find the valid route grid from the starting point to the end point based on the following steps:

[0216] S1: Push the node into the heap manager;

[0217] S2: The heap manager finds a non-null neighborhood grid in the eight-directional connectivity neighborhood grid of the node, pushes the non-null neighborhood grid into the heap manager, and finds a neighborhood grid with the minimum cost from the non-null neighborhood grids as the updated node;

[0218] S3: summing the cost value of the current node and the existing cost value of the eight-directional connectivity neighborhood grid of the current node to obtain the cost value assigned by the neighborhood grid; for the eight-directional connectivity neighborhood grid of the current node already in the heap manager, determining whether the cost value assigned by the neighborhood grid is greater than the existing cost value of the neighborhood grid; if so, updating the existing cost value of the neighborhood grid to the cost value assigned by the neighborhood grid; otherwise, not updating the existing cost value of the neighborhood grid; for the eight-directional connectivity neighborhood grid of the current node that is pushed into the heap manager for the first time, updating the existing cost value of the neighborhood grid to the cost value assigned by the neighborhood grid;

[0219] S4: Repeat steps S2-S3 until the eight-directional connectivity neighborhood grid of the node includes the end point;

[0220] S5: Connecting the grids corresponding to all nodes in sequence as the valid route grids of the starting point and the end point.

[0221] For example, Figure 13 As shown in the figure, the route is planned to start from waypoint A, pass through waypoint B, and arrive at waypoint C.

[0222] First, split the planning process into two steps: first, plan the route from waypoint A to waypoint B, and then plan the route from waypoint B to waypoint C. The following describes the planning process between A and B. The planning process between B and C is similar and will not be described in detail.

[0223] like Figure 14 As shown, in this embodiment, the grid size of the terrain of the analysis area is 10*10, the value in the grid is the exemplary assigned consumption value, and the grid index value is calculated according to the row and column number calculation method Index=i×10+j, where i and j represent the row number and column number of the grid respectively. Figure 14 The triangles ABC, EFG and HPK are expressed as three no-fly zones, and the grids they cover are as follows: Figure 15 The crossed-out part is shown.

[0224] Taking the DJ algorithm as an example, the process of planning from waypoint A to the next waypoint B is as follows:

[0225] First, based on the eight-way connectivity of the grid, taking waypoint A as the starting point, the grid of the neighborhood nodes of waypoint A based on the eight-way connectivity is:

[0226] Grid 1 (cost 2.0), Grid 2 (cost 2.5), Grid 3 (cost 2.0), Grid 11 (cost 1.7), Grid 13 (cost 2.0), push waypoint A, Grids 1, 2, 3, 11, 13 into the heap manager, and find the neighboring node Grid 11 with the smallest cost.

[0227] Based on the eight-way connectivity of grid 11, the neighboring node grids are found to be grid 0 (cost value 1.0), grid 1 (cost value 2.0), grid 2 (cost value 2.5), grid 10 (cost value 1.5), and grid 20 (cost value 2.0). The newly added grids 0, 10, and 20 are pushed into the heap manager, and the neighboring grid with the minimum cost value is found to be grid 0. Based on the connectivity from grid 11 to grids 0, 10, and 20, the cost values ​​are updated respectively. The grids are: grid 0 (cost 2.7), grid 10 (cost 3.2), grid 20 (cost 3.7). The heap manager already has node grids 1 and 2. Since the sum of the cost of grid 11 and the current cost of the neighboring node grids is greater than the current cost, the cost of grids 1 and 2 remains unchanged. At this time, the node grids in the heap manager include: starting point A, grids 0, 1, 2, 3, 10, 11, 13, and 20.

[0228] Based on the eight-directional connectivity of grid 0, the neighboring nodes grid 1, grid 10, and grid 11 are found. Since grid 11 is the previous search node, grid 11 is excluded, and the neighboring node with the lowest cost is grid 1. There is no new grid node. Since the sum of the cost value of grid 0 and the current cost value of the neighboring node grid is greater than the current cost value, the cost values ​​of grids 1, 10, and 11 remain unchanged.

[0229] ...Continue to iterate the algorithm downward, and finally find the minimum cost path from waypoint A to waypoint B: waypoint A grid - grid 11 - grid 20 - waypoint B grid.

[0230] Repeating the above algorithm to find the minimum cost path for each waypoint, each waypoint is then connected to the grid center point along the minimum cost path derived from the algorithm. Subsequent processing yields the planned route. It should be noted that the technical process of converting the corresponding grids between waypoints into a planned route is well known to those skilled in the art and will not be detailed here.

[0231] For example, Figure 15 In this example, a drone's initial route is a direct flight from point A to point G. En route, at point A1, it receives notification of a temporary no-fly zone ahead, necessitating a detour. The airspace manager quickly invokes the route planner to replan the drone from point A1 to point G, generating a new route A1EFG. The new route also updates information such as the grid code set, successfully avoiding the temporary no-fly zone. The algorithm described above automatically replans the route, maintaining a safe distance from the no-fly zone and the existing route.

[0232] Those skilled in the art will appreciate that all or part of the process steps of the above-described embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a magnetic disk, an optical disk, a read-only memory, or a random access memory.

[0233] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with this technical field within the technical scope disclosed by the present invention should be covered by the scope of protection of the present invention.

Claims

1. An intelligent airspace management system based on grid code, characterized in that: The intelligent airspace management system includes a data storage module, a display control and editing module, a grid code conversion and management module, and an aircraft position acquisition module; When the intelligent airspace management system is started, the display control and editing module reads the aviation data stored in the data storage module and displays it, and the grid code conversion and management module reads the aviation data stored in the data storage module and converts it into grid codes for temporary storage, wherein the aviation data includes planned routes and no-fly zones; The aircraft position acquisition module is used to obtain the real-time position of the aircraft and send it to the data storage module for storage; The display control and editing module is also used to edit routes and no-fly zones and temporarily store and display them in real time; The grid code conversion and management module is further configured to read the real-time position of the aircraft and dynamically update the corresponding grid code based on the real-time position of the aircraft. The dynamic updating of the corresponding grid code based on the real-time position of the aircraft includes: the grid code conversion and management module setting a flight safety area for the aircraft with the aircraft as the center; when the aircraft is about to take off, setting the flight safety area to a safety circle with a radius of a preset threshold, and setting the grid code covered by the safety circle to an exclusive state; The invention also includes: when the aircraft flies along the planned route, the grid code conversion and management module dynamically updates the flight safety area and the corresponding grid code based on the real-time position grid code of the aircraft by the following method: Reading the planned route grid code and dynamically updating the center of the safety circle based on the aircraft's real-time position grid code; The safe distance length in the aircraft's forward direction is calculated in real time based on the following formula: R front =D+(V1 / V max )*(D max -D), where R front is the safe distance length in the forward direction of the aircraft, D is the preset threshold, and D max The maximum safety threshold of the aircraft is designed, V1 is the actual speed of the aircraft, V max Designing a maximum speed for the aircraft; The arc corresponding to the safety circle is divided into four equal parts, wherein the arc includes a front arc, a rear arc, an upper arc, and a lower arc according to its orientation; When an aircraft flies along a planned route, the radius of the front arc is updated in real time, using the safety distance in the aircraft's forward direction as the radius. The radii of the other arcs remain unchanged. A first straight line is drawn through the upper vertex of the safety circle parallel to the route, and a second straight line is drawn through the lower vertex of the safety circle parallel to the route. The area enclosed by the front arc, the first straight line, the second straight line, the upper arc, the lower arc, and the rear arc serves as the real-time flight safety area. Setting the grid code covered by the flight safety area to an exclusive state; And read the edited routes and no-fly zones in the display control and editing module and convert them into grid codes for temporary storage.

2. The intelligent airspace management system based on grid code according to claim 1, characterized in that: The preset threshold is an aircraft safety threshold, and a grid code width equal to the aircraft safety threshold or any one of the two closest adjacent grid code widths is selected as the lowest level grid in the distance constraint grid set.

3. The intelligent airspace management system based on grid code according to claim 2, characterized in that: The grid code conversion and management module further includes a route grid code conversion submodule and a regional grid code conversion submodule, wherein the route grid code conversion submodule converts the route into a grid code by the following method: Reading a route from the data storage module or the display control and editing module, and dividing the route into segments starting from the starting point of the route with a preset threshold as a step size; A distance constraint grid set is calculated for each route segment one by one, and the route grid code is generated through grid deduplication calculation and aggregation calculation.

4. The intelligent airspace management system based on grid code according to claim 3, characterized in that: The calculation of each route segment one by one and the establishment of a distance constraint grid set are completed by the following steps, which include: If the two endpoints of the route segment are in the same grid, the grid is selected as the selected grid. If the selected grid does not exist in the distance constraint grid set, the selected grid is added to the distance constraint grid set. If the two endpoints of the route segment are in different grids, the two different grids are added to the distance-constrained grid set, and a first selected area is obtained based on the longitude and latitude of the two different grids. Redundant grids are removed from the first selected area, and grids that meet preset conditions are selected from the remaining grids in the first selected area and added to the distance-constrained grid set. The selected grid or the first selected area is expanded based on the preset threshold to obtain a second selected area, redundant grids are removed from the second selected area, and grids that meet preset conditions are selected from the remaining grids in the second selected area to be added to the distance constrained grid set.

5. The intelligent airspace management system based on grid code according to claim 4, characterized in that: The regional grid code conversion submodule converts the no-fly zone into a grid code by the following method: Reading a no-fly zone from the data storage module or the display control and editing module, decomposing the zone based on a grid code hierarchy rule to obtain a lowest-level grid code containing the zone, and using the lowest-level grid code as the grid code to be processed; Calculating and obtaining a boundary line grid code set that satisfies a distance constraint with the boundary line of the region; The regional grid code set is obtained through the following process: S11: converting each grid code in the boundary line grid code set into a grid code of a corresponding level of the grid to be processed, and performing deduplication to obtain the grid codes as each grid code in the updated boundary line grid code set; S12: If the level corresponding to the grid code to be processed is higher than the set minimum level, decompose the grid code to be processed into grid codes of the next level; otherwise, end; If the next level grid code exists in the area boundary grid set, the next level grid code is used as the grid code to be processed in the next iteration; Otherwise, if the grid corresponding to the next-level grid code is located within the regional boundary line, the next-level grid code is added to the regional grid code set; Return to step S11; The regional grid code set and the regional boundary line grid code set are merged, and then deduplication and aggregation are performed to obtain the regional grid code.

6. The intelligent airspace management system based on grid code according to claim 2, characterized in that: The intelligent airspace management system further includes a conflict detection module, which is configured to read the aviation data edited in the display control and editing module and detect conflict risks by the following method, the method comprising: sorting all grid codes temporarily stored in the grid code conversion and management module by size; Determine whether there is a duplication or inclusion relationship between adjacent grid codes in the grid code. If so, determine whether the adjacent grid codes with duplication or inclusion relationship are all no-fly zones. If so, return a detection result of no risk to the display control and editing module. Otherwise, there is a risk of conflict in returning the detection results to the display control and editing module.

7. The intelligent airspace management system based on grid code according to claim 6, characterized in that: The intelligent airspace management system further includes a route planning module, which is used to read the edited route in the display control and editing module, plan a valid route by the following method and send it to the data storage module for storage: Read the waypoints of the edited route; Find the grid codes of all waypoints from the grid code conversion and management module; Convert the grid codes of all waypoints to raster; Establishing the topological relationship between the waypoints based on grid eight-directional connectivity modeling; Based on the topological relationship and the principle of minimum cost, an effective route between the waypoints is planned, and the lines between all the waypoints form the planned route.

8. The intelligent airspace management system based on grid code according to claim 7, characterized in that: When editing a no-fly zone in the display control and editing module, conflicts are detected and automatically replanned using the following methods: The grid code conversion and management module reads the edited no-fly zone coordinate area, converts the edited no-fly zone into a grid code, and temporarily stores the grid code; The conflict detection module reads the planned route grid codes temporarily stored in the grid code conversion and management module and the grid codes corresponding to the edited no-fly zone, sorts all the read grid codes by size, and determines whether adjacent grid codes in the grid codes are repeated or included. If so, the adjacent grid codes with repeated or included relationships are regarded as existing route grid codes that conflict with the edited no-fly zone, and sends a detection result indicating a conflict risk to the display control and editing module for display. The route planning module reads the conflicting existing route grid code and calculates the shortest segment of the conflicting existing route grid code, wherein both endpoints of the shortest segment are waypoints of the conflicting existing route, and the waypoints of the conflicting existing route do not conflict with any route or no-fly zone; The route planning module automatically replans a valid route based on the two waypoints of the conflicting existing route.

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