Method and apparatus for determining optimal dissection hierarchy of airspace movement trajectory grid

Abstract

Method and device for determining optimal hierarchical level of grid for airspace movement trajectory of the present disclosure. The method discretizes the airspace movement trajectory under different hierarchical grids to obtain discretized grid data of the airspace movement trajectory under different hierarchical grids; calculates the discrete continuity index of the airspace movement trajectory under different hierarchical grids based on the discretized grid data of the airspace movement trajectory under different hierarchical grids; and determines the grid level corresponding to the smallest discrete continuity index of the airspace movement trajectory as the optimal hierarchical level of the grid for the airspace movement trajectory. It can determine the optimal hierarchical level of the discretized representation of the airspace movement trajectory and solve the problem of poor refinement degree in the current discretization of the airspace movement trajectory.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of airspace management based on the earth space information subdivision organization, and particularly relates to a method and device for determining the optimal subdivision level of an airspace movement trajectory grid. Background Art

[0002] Based on the three-dimensional airspace grid and combined with time-discrete coding, a spatio-temporal data expression model of flight tracks based on the airspace grid is studied, a new type of motion description method is established, and an airspace conflict detection algorithm is designed based on the spatial grid.

[0003] The discretization of three-dimensional airspace movement trajectory grid data refers to segmenting continuous three-dimensional airspace movement trajectory data into discrete intervals. The principles of segmentation include equal distance, equal frequency or optimized methods. The reasons for the discretization of three-dimensional airspace movement trajectory grid data are mainly as follows: algorithms such as decision trees and naive Bayes are all based on discrete grid data. Effective discretization of three-dimensional airspace movement trajectory grid data can reduce the time and space overhead of algorithms such as decision trees and naive Bayes, and improve the classification and clustering ability and anti-noise ability of three-dimensional airspace movement trajectory grid data samples. Secondly, the characteristics of the discretization of three-dimensional airspace movement trajectory grid data are easier to understand than continuous features, closer to the expression at the knowledge level, can effectively overcome the hidden defects in the three-dimensional airspace movement trajectory grid data, and make the results of the motion model more stable. Finally, the characteristics and methods of discretization can convert the originally non-existent analytical solution into a numerical solution, and convert complex three-dimensional space calculations into algebraic set operations such as one-dimensional integer intersection, greatly improving the calculation speed.

[0004] From the perspective of data storage, management and indexing, there are generally two principles for the discretization of airspace movement trajectories or air flight trajectories: (1) the minimum grid criterion: the grid coding amount required for airspace movement trajectories directly determines the amount of stored data, so as few subdivision grids as possible should be used to represent the airspace; (2) the accuracy correspondence principle: grids at different levels correspond to different representation accuracies. In the discretization representation of airspace movement trajectories, different elements require different discretization representation accuracies, and representations beyond the required accuracy will lead to a sharp increase in workload and have no practical significance. Summary of the Invention

[0005] The present disclosure overcomes one of the deficiencies of the prior art and provides a method and device for determining the optimal subdivision level of an airspace movement trajectory grid, which can determine the optimal subdivision level of the discretization representation of an airspace movement trajectory and solve the problem of poor refinement during the current discretization of airspace movement trajectories.

[0006] According to one aspect of the present disclosure, a method for determining the optimal subdivision level of an airspace movement trajectory grid is proposed, and the method includes:

[0007] Discretize the airspace motion trajectories under different hierarchical grids to obtain discretized grid data of the airspace motion trajectories under different hierarchical grids;

[0008] Based on the discretized grid data of the airspace motion trajectories under different hierarchical grids, calculate the discrete continuity index of the airspace motion trajectories under different hierarchical grids;

[0009] Determine the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectories as the optimal dissection level of the airspace motion trajectory grid.

[0010] In a possible implementation, the discretized grid data of the airspace motion trajectories has one or more quantities of the first type of discontinuous grid data and the second type of discontinuous grid data.

[0011] In a possible implementation, the calculating the discrete continuity index of the airspace motion trajectories under different hierarchical grids based on the discretized grid data of the airspace motion trajectories under different hierarchical grids includes:

[0012] For each level of grid, calculate the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data of the discretized grid data of the airspace motion trajectories;

[0013] Based on the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data, calculate the discrete continuity index of the airspace motion trajectories.

[0014] In a possible implementation, the cost value of the first type of discontinuous grid data is a constant; the cost value of the second type of discontinuous grid data is the logarithm value of the discrete grid of the airspace motion trajectory under each level of grid.

[0015] In a possible implementation, for each level of grid, the discrete continuity index G(x) of the airspace motion trajectories is

[0016]

[0017] where f(x)1 is the cost function of the first type of discontinuous grid data, f(x)2 is the cost function of the second type of discontinuous grid data, a and b are the weights of the cost function of the first type of discontinuous grid data and the cost function of the second type of discontinuous grid data respectively, and x is the number of discontinuous grids of the airspace motion trajectories.

[0018] In a possible implementation, the first type of discontinuous grid data is the discontinuity of the discretized grid of the airspace motion trajectories; the second type of discontinuous grid data is the discretized grid of the airspace motion trajectories with two or more grid point data.

[0019] According to another aspect of the present disclosure, a device for determining the optimal hierarchical level of an airspace motion trajectory grid is proposed. The device includes:

[0020] A discretization module, configured to discretize the airspace motion trajectory under different hierarchical grids to obtain discretized grid data of the airspace motion trajectory under different hierarchical grids;

[0021] A calculation module, configured to calculate the discrete continuity index of the airspace motion trajectory under different hierarchical grids based on the discretized grid data of the airspace motion trajectory under different hierarchical grids;

[0022] A determination module, configured to determine the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectory as the optimal hierarchical level of the airspace motion trajectory grid.

[0023] According to another aspect of the present disclosure, an electronic device is proposed. The device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the above-mentioned method is implemented.

[0024] According to another aspect of the present disclosure, a computer-readable storage medium is proposed. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned method is implemented.

[0025] The method for determining the optimal hierarchical level of the airspace motion trajectory grid in the present disclosure discretizes the airspace motion trajectory under different hierarchical grids to obtain discretized grid data of the airspace motion trajectory under different hierarchical grids; calculates the discrete continuity index of the airspace motion trajectory under different hierarchical grids based on the discretized grid data of the airspace motion trajectory under different hierarchical grids; and determines the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectory as the optimal hierarchical level of the airspace motion trajectory grid. It can solve the problem of poor refinement of the current airspace motion trajectory.

[0026] Some other optional features and technical effects of the embodiments of the present disclosure are described below, and some can be understood by reading this article. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The elements shown are not limited by the scale shown in the drawings. The same or similar reference numerals in the drawings represent the same or similar elements, where:

[0028] Figure 1 The flowchart of the method for determining the optimal hierarchical level of the airspace motion trajectory grid according to an embodiment of the present disclosure is shown;

[0029] Figure 2 Shows a schematic diagram of the first type of discontinuous grid data according to an embodiment of the present disclosure;

[0030] Figure 3 Shows a schematic diagram of the second type of discontinuous grid data according to an embodiment of the present disclosure;

[0031] Figure 4 Shows a schematic diagram of the trend of the cost value of the first type of discontinuous grid data according to an embodiment of the present disclosure;

[0032] Figure 5 Shows a schematic diagram of the trend of the cost value of the second type of discontinuous grid data according to an embodiment of the present disclosure;

[0033] Figure 6 Shows a schematic diagram of the trend of the discrete continuity index of the airspace motion trajectory obtained by weighting the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data according to an embodiment of the present disclosure;

[0034] Figure 7 Shows an example diagram of the structure of a device for determining the optimal hierarchical level of the grid of the airspace motion trajectory according to an embodiment of the present disclosure;

[0035] Figure 8 Shows an electronic device according to an embodiment of the present disclosure. Detailed implementation manners

[0036] To make the objectives, technical solutions, and advantages of the present disclosure more clear and understandable, the present disclosure will be further described in detail below in combination with the detailed implementation manners and the accompanying drawings. Herein, the illustrative implementation manners of the present disclosure and their descriptions are used to explain the present disclosure, but do not limit the present disclosure.

[0037] The term "including" and its variants used herein represent open inclusion, that is, "including but not limited to". Unless otherwise stated, the term "or" represents "and / or". The term "based on" represents "at least partially based on". The term "an example embodiment" and "an embodiment" represent "at least one example embodiment". The term "another embodiment" represents "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. There may also be other explicit and implicit definitions below.

[0038] In addition, the steps shown in the flowchart of the accompanying drawings can be executed in a computer such as a set of computer-executable instructions. And, although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in a different order.

[0039] Figure 1The flowchart of the method for determining the optimal grid partitioning level of the spatial motion trajectory according to an embodiment of the present disclosure is shown. The method is a dimensionality reduction calculation method, which does not increase the complexity of spatiotemporal calculation with the increase of object dimension, and can be applied to two-dimensional, three-dimensional, four-dimensional or even higher-dimensional spatiotemporal calculation scenarios.

[0040] like Figure 1 As shown, the method may include:

[0041] Step S1: discretizing the airspace motion trajectories under different levels of grids to obtain discretized grid data of the airspace motion trajectories under different levels of grids.

[0042] Any motion trajectory can be composed of several grids and their corresponding attributes. The motion trajectory is modeled using a triplet (C, T, A), where C is a spatial grid set, which represents the spatial information of the spatial motion trajectory and is represented by a spatial grid code; T is the moment in the corresponding time dimension, which represents the time information of the spatial motion trajectory; and A is the attribute set of the motion trajectory, which consists of several attributes.

[0043] The multi-scale time segmentation coding consists of up to 64 levels. Based on the above idea, the actual airspace motion trajectory can be discretized under different levels of grids to obtain the discretized grid data of the airspace motion trajectory under different levels of grids.

[0044] Figure 2 and Figure 3 Schematic diagrams of the first type of discontinuous grid data and the second type of discontinuous grid data according to an embodiment of the present disclosure are respectively shown.

[0045] In one example, the discretized grid data of the spatial motion trajectory has one or more first-type discontinuous grid data and second-type discontinuous grid data. The first-type discontinuous grid data is the discontinuity of the discretized grid of the spatial motion trajectory; the second-type discontinuous grid data is the discretized grid of the spatial motion trajectory with two or more grid point data.

[0046] The discretized spatial motion trajectory data is defined as the function f(x). For the discretized grid data of the discretized spatial motion trajectory, data discontinuity is likely to occur. Figure 2 As shown, a spatial motion trajectory has multiple discontinuities during discretization, and the discretized grid data of the spatial motion trajectory with multiple discontinuities is defined as the first type of discontinuous grid data. The first type of discontinuous grid data f(x)1 is expressed as: f(x)1=φwhile x=x0, that is, the first type of discontinuous grid data f(x)1 does not have a corresponding value at a certain x=x0, that is, there is no corresponding discretized grid data.

[0047] In addition, ifFigure 3 As shown, for a single discretized grid B, there are two or more trajectory point data, and such data is defined as the second type of discontinuous grid data. The second type of discontinuous grid data f(x)2 is expressed as: f(x)2 = {x k , x k+1 , …} while x = x0, that is, the second type of discontinuous grid data f(x)2 has two or more corresponding values at a certain x = x0.

[0048] Such as Figure 3 the position of the discontinuous point of the discretized grid data of the airspace movement trajectory shown, that is, there is no embedding of trajectory point data or track point data corresponding to grid A, while grid B contains multiple trajectory point data or track point data. These two types of discontinuous points are regarded as the grid expressions of the discontinuous airspace movement trajectory.

[0049] Through the statistical analysis of the continuity and smoothness of the discretized data of the airspace movement trajectory under different hierarchical grids (i.e., different scale grids), it can provide a basis for determining the optimal level of the grid subdivision of the airspace movement trajectory based on the research of grid data resolution.

[0050] Step S2: Based on the discretized grid data of the airspace movement trajectory under different hierarchical grids, calculate the discrete continuity index of the airspace movement trajectory under different hierarchical grids.

[0051] The magnitude of the discrete continuity index can be used to judge the continuity degree value in the process of discretizing air traffic trajectory data, that is, the airspace movement trajectory.

[0052] In an example, based on the discretized grid data of the airspace movement trajectory under different hierarchical grids, calculate the discrete continuity index of the airspace movement trajectory under different hierarchical grids. The airspace includes:

[0053] For each hierarchical grid, calculate the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data of the discretized grid data of the airspace movement trajectory; based on the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data, calculate the discrete continuity index of the airspace movement trajectory.

[0054] In an instance, the cost value of the first type of discontinuous grid data is a constant, for example, it can be set to 1, or set to other constant values according to other requirements. The cost value of the second type of discontinuous grid data is the logarithm of the discrete grid of the airspace movement trajectory under each hierarchical grid, that is, the second type of discontinuous grid data f(x)2 = log2(count).

[0055] Multiply the cost values of the first - type discontinuous grid data and the second - type discontinuous grid data of all the discrete points of the airspace movement trajectory grid under each hierarchical grid by their corresponding weights and then sum them up. Then, divide by the number of discrete points of the airspace movement trajectory of this hierarchical grid to obtain the discrete continuity index \(G(x)\) of the airspace movement trajectory.

[0056] The discrete continuity index \(G(x)\) of the airspace movement trajectory can be:

[0057]

[0058] Among them, \(f(x)_1\) is the cost function of the first - type discontinuous grid data, \(f(x)_2\) is the cost function of the second - type discontinuous grid data, \(a\) and \(b\) are the weights of the cost function of the first - type discontinuous grid data and the cost function of the second - type discontinuous grid data respectively, and \(x\) is the number of discontinuous grids (discrete points) of the airspace movement trajectory.

[0059] Through the above - mentioned method, the discrete continuity index value of the airspace movement trajectory under each hierarchical grid can be calculated.

[0060] Step S3: Determine the grid level corresponding to the minimum discrete continuity index of the airspace movement trajectory as the optimal hierarchical level of the airspace movement trajectory grid.

[0061] Based on the time resolution of different grid data of the airspace movement trajectory, to determine the optimal level of the airspace movement trajectory grid dissection, achieving an adaptive effect. The time resolution mainly refers to the time interval of different types of data. When repeatedly detecting the same target, the time interval between two adjacent detections can provide information on the dynamic changes of the ground objects, which can be used to monitor the changes of the ground objects and can also provide additional information for the accurate classification of certain thematic elements. Taking the air traffic trajectory data (airspace movement trajectory data) to be processed in this disclosure as an example, the time resolution of this data track is the time interval of different types of track point data, with an average interval in the order of 3 - 10 s. For example, the radar time resolution is 3 - 5 s, the ADS - B time resolution is 4 - 7 s, and the time resolution of others is 6 - 10 s, etc. Based on the time resolution of different types of aircraft or equipment data, the level of the airspace movement trajectory grid dissection can be determined to achieve an adaptive effect.

[0062] Under different hierarchical grids, the discrete continuity index function \(G(x)\) of the airspace movement trajectory data n is:

[0063] Among them, \(n\) is a positive integer, ranging from 1 to 64.

[0064] Extract the minimum value among the discrete continuity index values of the airspace motion trajectory data calculated under different hierarchical grids, and use the grid level corresponding to the discrete continuity index value of the airspace motion trajectory data as the optimal grid level (grid scale) for the three-dimensional dissection of the airspace motion trajectory.

[0065] For example, when the grid level n is the optimal grid level (scale grid) for the three-dimensional dissection of the airspace motion trajectory, the condition is satisfied: G(x) n = min(......G(x) n-1 , G(x) n , G(x) n+1 ......}. By this method, the optimal dissection level of the airspace motion trajectory grid is determined in the airspace, thereby improving the refinement degree of the airspace motion trajectory.

[0066] Application example:

[0067] Figures 4 - 6 Respectively show the value of the first type of discontinuous grid data, the value of the second type of discontinuous grid data, and the schematic diagram of the trend of the discrete continuity index of the airspace motion trajectory according to an embodiment of the present disclosure.

[0068] Based on the grid-based modeling database, the 4th to 8th level grids of GeoSOT are respectively used to count the first type of discontinuous grid data and the second type of discontinuous grid data defined above, and the specific results of the statistics on the discretized database of the airspace motion trajectory at each level are as Figures 4 - 6 shown.

[0069] As Figures 4 - 6 shown, from the vertical comparison, the value of the first type of discontinuous grid data increases continuously with the increase of the grid level. The finer the grid granularity, the more grids without airspace motion trajectory (flight track data) points will increase. Similarly, for the statistics of the value of the second type of discontinuous grid data, the coarser the grid granularity, the more airspace motion trajectory (flight track data) points are included in the same grid, that is, the value of the second type of discontinuous grid data has a decreasing trend with the increase of the grid scale. By taking the weighted average of the value of the first type of discontinuous grid data and the value of the second type of discontinuous grid data, the optimal three-dimensional dissection grid level of the airspace motion trajectory can be obtained. As Figure 6 can be seen, the 7th grid level is the optimal dissection level of the airspace motion trajectory. By this method, the optimal grid dissection level of any airspace motion trajectory is obtained, providing a more refined grid dissection in other route planning and the solution of route conflict problems, and improving the accuracy of the current airspace motion trajectory management and conflict resolution.

[0070] The method for determining the optimal hierarchical level of the airspace movement trajectory grid in the present disclosure discretizes the airspace movement trajectory under grids of different levels to obtain discretized grid data of the airspace movement trajectory under grids of different levels; calculates the discrete continuity index of the airspace movement trajectory under grids of different levels based on the discretized grid data of the airspace movement trajectory under grids of different levels; and determines the grid level corresponding to the smallest discrete continuity index of the airspace movement trajectory as the optimal hierarchical level of the airspace movement trajectory grid. It can determine the optimal hierarchical level of the discretized representation of the airspace movement trajectory and solve the problem of poor refinement during the current discretization of the airspace movement trajectory.

[0071] The following is an apparatus embodiment of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the apparatus embodiment of the present application, please refer to the method embodiment of the present application.

[0072] Figure 7 Fig. shows a structural example diagram of an apparatus for determining the optimal hierarchical level of the airspace movement trajectory grid according to an embodiment of the present disclosure; as Figure 7 shown, the construction apparatus may include:

[0073] A discretization module 701, configured to discretize the airspace movement trajectory under grids of different levels to obtain discretized grid data of the airspace movement trajectory under grids of different levels;

[0074] A calculation module 702, configured to calculate the discrete continuity index of the airspace movement trajectory under grids of different levels based on the discretized grid data of the airspace movement trajectory under grids of different levels;

[0075] A determination module 703, configured to determine the grid level corresponding to the smallest discrete continuity index of the airspace movement trajectory as the optimal hierarchical level of the airspace movement trajectory grid.

[0076] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0077] Figure 8 Fig. is a structural schematic diagram of an electronic device 3 provided by an embodiment of the present application. As Figure 8 shown, the electronic device 3 in this embodiment includes: a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, the steps in the above method embodiments are implemented. Alternatively, when the processor 301 executes the computer program 303, the functions of each module / unit in the above apparatus embodiments are implemented.

[0078] Exemplarily, the computer program 303 can be divided into one or more modules / units. One or more modules / units are stored in the memory 302 and executed by the processor 301 to complete this application. One or more modules / units can be a series of computer program instruction segments capable of completing specific functions, and these instruction segments are used to describe the execution process of the computer program 303 in the electronic device 3.

[0079] The electronic device 3 can be a desktop computer, a notebook, a palm computer, a cloud server and other electronic devices. The electronic device 3 can include but is not limited to the processor 301 and the memory 302. Those skilled in the art can understand that Figure 8 merely examples of the electronic device 3, which do not constitute a limitation on the electronic device 3. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0080] The processor 301 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0081] The memory 302 can be an internal storage unit of the electronic device 3. For example, the hard disk or memory of the electronic device 3. The memory 302 can also be an external storage device of the electronic device 3. For example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 3. Further, the memory 302 can also include both the internal storage unit and the external storage device of the electronic device 3. The memory 302 is used to store computer programs and other programs and data required by the electronic device. The memory 302 can also be used to temporarily store data that has been output or will be output.

[0082] The embodiment of the present application also relates to a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for determining the optimal hierarchical division of the airspace motion trajectory grid in the foregoing embodiment are implemented.

[0083] For the introduction of the computer-readable storage medium provided by the embodiment of the present application, please refer to the embodiment of the method for determining the optimal hierarchical division of the airspace motion trajectory grid described above. The embodiments of the present disclosure will not be described in detail herein.

[0084] For the introduction of the computer-readable storage medium provided by the embodiment of the present application, please refer to the embodiment of the method for determining the optimal hierarchical division of the airspace motion trajectory grid described above. The embodiments of the present disclosure will not be described in detail herein.

[0085] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be described in detail herein.

[0086] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not described or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0087] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this application can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0088] In the embodiments provided in the present application, it should be understood that the disclosed apparatus / computer device and method can be implemented in other ways. For example, the apparatus / computer device embodiments described above are merely illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. Multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the apparatus or unit can be in electrical, mechanical or other forms.

[0089] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0090] In addition, each functional unit in the various embodiments of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0091] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above method embodiments of the present application, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be implemented. The computer program can include computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0092] Unless otherwise specified, the acts or steps of the methods and procedures described according to the embodiments of the present disclosure do not have to be executed in a specific order and can still achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0093] In this document, multiple embodiments of the present disclosure have been described. For the sake of brevity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the various embodiments may be omitted. In this document, "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean applicable to at least one embodiment or example according to the present disclosure, rather than all embodiments. The above terms do not necessarily refer to the same embodiment or example. Without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0094] The exemplary systems and methods of the present disclosure have been specifically shown and described with reference to the above embodiments, which are only examples of the best mode for implementing the systems and methods. Those skilled in the art can understand that various changes can be made to the embodiments of the systems and methods described herein when implementing the systems and / or methods without departing from the spirit and scope of the present disclosure defined in the appended claims.

Claims

1. A method for determining the optimal hierarchical level of an airspace movement trajectory grid, characterized in that, The method includes: Discretizing the airspace motion trajectories under different hierarchical grids to obtain discretized grid data of the airspace motion trajectories under different hierarchical grids; the discretized grid data of the airspace motion trajectories has one or more quantities of first - type discontinuous grid data and second - type discontinuous grid data. The first - type discontinuous grid data is the discretized grid data of the airspace motion trajectory with discontinuities, and the second - type discontinuous grid data is the discretized grid data of the airspace motion trajectory with two or more grid - point data; Calculating the discrete continuity index of the airspace motion trajectories under different hierarchical grids based on the discretized grid data of the airspace motion trajectories under different hierarchical grids; Determining the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectories as the optimal hierarchical level of the airspace motion trajectory grid; Wherein, calculating the discrete continuity index of the airspace motion trajectories under different hierarchical grids based on the discretized grid data of the airspace motion trajectories under different hierarchical grids includes: For each level of grid, calculating the cost value of the first - type discontinuous grid data and the cost value of the second - type discontinuous grid data of the discretized grid data of the airspace motion trajectories; Calculating the discrete continuity index of the airspace motion trajectories based on the cost value of the first - type discontinuous grid data and the cost value of the second - type discontinuous grid data.

2. The determination method according to claim 1, wherein The cost value of the first - type discontinuous grid data is a constant; the cost value of the second - type discontinuous grid data is the logarithm of the discrete grid of the airspace motion trajectory under each level of grid.

3. The determination method according to claim 2, wherein For each level of grid, the discrete continuity index G(x) of the airspace motion trajectories is ， Where f(x)1 is the cost function of the first - type discontinuous grid data, f(x)2 is the cost function of the second - type discontinuous grid data, a and b are the weights of the cost function of the first - type discontinuous grid data and the cost function of the second - type discontinuous grid data respectively, and x is the number of discontinuous grids of the airspace motion trajectory.

4. An apparatus for determining an optimal hierarchical layer of an airspace movement trajectory grid, characterized in that, The device includes: A discretization module, configured to discretize the airspace motion trajectories under different hierarchical grids to obtain discretized grid data of the airspace motion trajectories under different hierarchical grids; the discretized grid data of the airspace motion trajectories has one or more quantities of first - type discontinuous grid data and second - type discontinuous grid data. The first - type discontinuous grid data is the discretized grid data of the airspace motion trajectory with discontinuities, and the second - type discontinuous grid data is the discretized grid data of the airspace motion trajectory with two or more grid - point data; A calculation module, configured to calculate the discrete continuity index of the airspace motion trajectories under different hierarchical grids based on the discretized grid data of the airspace motion trajectories under different hierarchical grids; A determination module, configured to determine the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectories as the optimal hierarchical level of the airspace motion trajectory grid; Wherein, calculating the discrete continuity index of the airspace motion trajectories under different hierarchical grids based on the discretized grid data of the airspace motion trajectories under different hierarchical grids includes: For each level of grid, calculate the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data for the discretized grid data of the airspace motion trajectory; Based on the cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data, calculate the discrete continuity index of the airspace motion trajectory.

5. An electronic device, characterized in that, The device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the method described in any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the method described in any one of claims 1 to 3 is implemented.

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