Method and device for determining optimal subdivision hierarchy of airspace motion trail grid

Abstract

According to the method and the device for determining the optimal subdivision hierarchy of the airspace motion trail grid, the method comprises the following steps: discretizing airspace motion trails under grids of different hierarchies to obtain discretized grid data of the airspace motion trails under the grids of different hierarchies; calculating discrete continuity indexes of the airspace motion trails under the different levels of grids based on the discrete grid data of the airspace motion trails under the different levels of grids; and determining the grid hierarchy corresponding to the minimum discrete continuity index of the airspace motion trail as the optimal subdivision hierarchy of the airspace motion trail grid. The optimal subdivision hierarchy represented by the discretization of the airspace movement track can be determined, and the problem that the refinement degree is poor during the discretization of the current airspace movement track is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of airspace management based on earth space information segmentation and organization, and in particular, relates to a method and device for determining an optimal segmentation level of an airspace motion trajectory grid. Background Art

[0002] On the basis of three-dimensional airspace grid and combined with time discrete coding, the track spatiotemporal data expression model based on airspace grid is studied, a new motion description method is established, and an airspace conflict detection algorithm is designed based on spatial grid.

[0003] The discretization of three-dimensional airspace motion trajectory grid data refers to segmenting the continuous three-dimensional airspace motion trajectory data into discrete intervals. The principles of segmentation include equal distance, equal frequency or optimization methods. The main reasons for the discretization of three-dimensional airspace motion trajectory grid data are as follows: For example, algorithms such as decision trees and naive Bayes are all based on discrete grid data. The effective discretization of three-dimensional airspace motion 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 motion trajectory grid data samples. Secondly, the discretization characteristics of three-dimensional airspace motion trajectory grid data are easier to understand than continuous features, and are closer to the expression of knowledge level. It can effectively overcome the hidden defects in three-dimensional airspace motion trajectory grid data and make the motion model results more stable. Finally, the discretization characteristics and methods can convert the non-existent analytical solutions into numerical solutions, and convert complex three-dimensional space calculations into algebraic set operations such as one-dimensional integer intersection, which greatly improves the calculation speed.

[0004] From the perspective of data storage, management, and indexing, there are generally two principles for discretizing airspace motion trajectories or aerial flight trajectories: (1) Minimum grid principle: The amount of grid code required for the airspace motion trajectory directly determines the amount of storage data required, so as few grids as possible should be used to represent the airspace; (2) Accuracy correspondence principle: Grids at different levels correspond to different representation accuracies. In the discretization representation of airspace motion trajectories, different elements require different discretization representation accuracies. Representation that exceeds the required accuracy will lead to a surge in workload and has 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 partitioning level of the spatial motion trajectory grid, which can determine the optimal partitioning level of the discretized representation of the spatial motion trajectory and solve the problem of poor refinement in the current discretization of the spatial motion trajectory.

[0006] According to one aspect of the present disclosure, a method for determining the optimal partitioning level of a spatial motion trajectory grid is proposed, the method comprising:

[0007] 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;

[0008] Based on the discretized grid data of the airspace motion trajectory under different levels of grids, the discrete continuity index of the airspace motion trajectory under different levels of grids is calculated;

[0009] The grid level corresponding to the smallest discrete continuity index of the spatial motion trajectory is determined as the optimal grid subdivision level of the spatial motion trajectory.

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

[0011] In a possible implementation, the discrete grid data of the airspace motion trajectory under different levels of grids are used to calculate the discrete continuity index of the airspace motion trajectory under different levels of grids, including:

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

[0013] Based on the first-type discontinuous grid data cost value and the second-type discontinuous grid data cost value, a discrete continuity index of the spatial motion trajectory is calculated.

[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 logarithmic value of the discrete grid of the spatial 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 spatial motion trajectory is

[0016]

[0017] Among them, 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 in the spatial motion trajectory.

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

[0019] According to another aspect of the present disclosure, a device for determining an optimal grid partitioning level of a spatial motion trajectory is proposed, the device comprising:

[0020] A discretization module is used to discretize the airspace motion trajectory under different levels of grids to obtain discretized grid data of the airspace motion trajectory under different levels of grids;

[0021] A calculation module, used for calculating the discrete continuity index of the airspace motion trajectory under different levels of grids based on the discretized grid data of the airspace motion trajectory under different levels of grids;

[0022] The determination module is used to determine the grid level corresponding to the smallest discrete continuity index of the spatial motion trajectory as the optimal grid subdivision level of the spatial motion trajectory.

[0023] According to another aspect of the present disclosure, an electronic device is provided, the device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described above when executing the program.

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

[0025] The disclosed method for determining the optimal grid partitioning level of the airspace motion trajectory obtains the discretized grid data of the airspace motion trajectory under the grids of different levels by discretizing the airspace motion trajectory under the grids of different levels; based on the discretized grid data of the airspace motion trajectory under the grids of different levels, the discrete continuity index of the airspace motion trajectory under the grids of different levels is calculated; and the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectory is determined as the optimal grid partitioning level of the airspace motion trajectory. The problem of poor refinement of the current airspace motion trajectory can be solved.

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

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

[0028] Figure 1 A flow chart of a method for determining the optimal grid segmentation level of airspace motion trajectory according to an embodiment of the present disclosure is shown;

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

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

[0031] Figure 4 A schematic diagram showing a trend of cost values ​​of a first type of discontinuous grid data according to an embodiment of the present disclosure is shown;

[0032] Figure 5 A schematic diagram showing a trend of cost values ​​of the second type of discontinuous grid data according to an embodiment of the present disclosure is shown;

[0033] Figure 6 A schematic diagram showing a trend of discrete continuity indicators of a spatial motion trajectory obtained by weighting the first type of discontinuous grid data cost value and the second type of discontinuous grid data cost value according to an embodiment of the present disclosure is shown;

[0034] Figure 7 An example diagram of the structure of a device for determining the optimal grid partitioning level of a spatial motion trajectory according to an embodiment of the present disclosure is shown;

[0035] Figure 8 An electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the present disclosure more clear, the present disclosure is further described in detail below in conjunction with specific implementation methods and drawings. Here, the illustrative implementation methods and descriptions of the present disclosure are used to explain the present disclosure, but are not intended to limit the present disclosure.

[0037] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included 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. Also, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described can be performed in a sequence different from that here.

[0039] Figure 1 The 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 2As shown in FIG. 1 , 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 It is expressed as: f(x) 1 =φwhile x=x 0 , that is, the first type of discontinuous grid data f(x) 1 At some x=x 0 There is no corresponding value at , that is, there is no corresponding discretized grid data.

[0047] In addition, if Figure 3 As shown, for a single discretized grid B, there are two or more motion 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 It is expressed as: f(x) 2 ={x k , x k+1 , …} while x=x 0 , that is, the second type of discontinuous grid data f(x) 2 At some x=x 0 There are two or more corresponding values.

[0048] like Figure 3 The discontinuous point positions of the discretized grid data of the airspace motion trajectory shown in the figure, that is, there is no embedded motion trajectory point data or track point data corresponding to the A grid, while the B grid contains multiple motion trajectory point data or track point data. These two types of discontinuous points are regarded as discontinuous grid expressions of the aerial motion trajectory.

[0049] Through the statistical analysis of the continuity and smoothness of the discretized data of airspace motion trajectories under different levels of grids (i.e. grids of different scales), it can provide a basis for determining the optimal level of grid division of airspace motion trajectories based on grid data resolution.

[0050] Step S2: Based on the discretized grid data of the airspace motion trajectory under different levels of grids, the discrete continuity index of the airspace motion trajectory under different levels of grids is calculated.

[0051] The size of the discrete continuity index can be used to determine the degree of continuity in the discretization process of air traffic trajectory data, i.e., airspace motion trajectory.

[0052] In one example, based on the discretized grid data of the airspace motion trajectory under different levels of grids, the discrete continuity index of the airspace motion trajectory under different levels of grids is calculated, and the airspace includes:

[0053] For each level of grid, the first type of discontinuous grid data cost value and the second type of discontinuous grid data cost value of the discretized grid data of the airspace motion trajectory are calculated; based on the first type of discontinuous grid data cost value and the second type of discontinuous grid data cost value, the discrete continuity index of the airspace motion trajectory is calculated.

[0054] In one example, the cost value of the first type of discontinuous grid data is a constant, such as 1, or 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 spatial motion trajectory under each level of grid, that is, the second type of discontinuous grid data f(x) 2 =log 2 (count).

[0055] The first-class discontinuous grid data cost value and the second-class discontinuous grid data cost value of the discrete points of the entire airspace motion trajectory grid under each level of grid are multiplied by the corresponding weights and added, and then the discrete continuity index G(x) of the airspace motion trajectory is obtained by averaging the number of discrete points of the airspace motion trajectory of the grid at this level.

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

[0057]

[0058] Among them, 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 (discrete points) of the spatial motion trajectory.

[0059] Through the above method, the discrete continuity index value of the airspace motion trajectory at each level of grid can be calculated.

[0060] Step S3: Determine the grid level corresponding to the smallest discrete continuity index of the spatial motion trajectory as the optimal grid subdivision level of the spatial motion trajectory.

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

[0062] Discrete continuity index function G(x) of spatial motion trajectory data under different levels of grids n for:

[0063] Where n is a positive integer ranging from 1 to 64.

[0064] The minimum value of the discrete continuity index value of the spatial motion trajectory data calculated under different levels of grids is extracted, and the grid level corresponding to the discrete continuity index value of the spatial motion trajectory data is used as the optimal grid level (grid scale) for three-dimensional segmentation of the spatial motion trajectory.

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

[0066] Application examples:

[0067] Figure 4-6 A schematic diagram of the trend of discrete continuity indicators of the first type of discontinuous grid data cost value, the second type of discontinuous grid data cost value, and the spatial motion trajectory according to an embodiment of the present disclosure is respectively shown.

[0068] Based on the grid modeling database, the 4th to 8th level grids of GeoSOT are used to count the first type of discontinuous grid data and the second type of discontinuous grid data defined above, and the statistics of the spatial motion trajectory discretization database of each level are calculated. The specific results are as follows Figure 4-6 shown.

[0069] like Figure 4-6 As shown in the figure, from a vertical comparison, the cost value of the first type of discontinuous grid data increases with the increase of grid level. The finer the grid granularity, the more grids there are without airspace motion trajectory (track data) points. Similarly, for the cost value statistics of the second type of discontinuous grid data, the coarser the grid granularity, the more airspace motion trajectory (track data) points are contained in the same grid, that is, the cost value of the second type of discontinuous grid data tends to decrease with the increase of grid scale. The cost value of the first type of discontinuous grid data and the cost value of the second type of discontinuous grid data are weighted averaged to obtain the optimal three-dimensional subdivision grid level for airspace motion trajectory, which is obtained by Figure 6 It can be seen that the 7th grid level is the optimal division level of the airspace motion trajectory. The optimal grid division level of any airspace motion trajectory can be obtained through this method, which can provide more refined grid division in other route planning and resolution of route conflicts, and improve the accuracy of current airspace motion trajectory management and conflict resolution.

[0070] The disclosed method for determining the optimal grid partitioning level of the airspace motion trajectory obtains the discretized grid data of the airspace motion trajectory under the grids of different levels by discretizing the airspace motion trajectory under the grids of different levels; based on the discretized grid data of the airspace motion trajectory under the grids of different levels, the discrete continuity index of the airspace motion trajectory under the grids of different levels is calculated; and the grid level corresponding to the smallest discrete continuity index of the airspace motion trajectory is determined as the optimal grid partitioning level of the airspace motion trajectory. The optimal partitioning level of the discretized representation of the airspace motion trajectory can be determined, solving the problem of poor refinement when discretizing the current airspace motion trajectory.

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

[0072] Figure 7 FIG. 4 shows an example structure diagram of a device for determining the optimal grid partitioning level of a spatial motion trajectory according to an embodiment of the present disclosure; Figure 7 As shown, the construction device may include:

[0073] Discretization module 701, used for discretizing the airspace motion trajectory under different levels of grids to obtain discretized grid data of the airspace motion trajectory under different levels of grids;

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

[0075] The determination module 703 is used to determine the grid level corresponding to the smallest discrete continuity index of the spatial motion trajectory as the optimal grid subdivision level of the spatial motion trajectory.

[0076] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0077] Figure 8 Schematic diagram of the structure of the electronic device 3 provided in the embodiment of the present application. Figure 8 As shown, the electronic device 3 of 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-mentioned method embodiments are implemented. Alternatively, when the processor 301 executes the computer program 303, the functions of the modules / units in the above-mentioned device embodiments are implemented.

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

[0079] The electronic device 3 may be a desktop computer, a notebook, a PDA, a cloud server, or other electronic device. The electronic device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that Figure 8 It is only an example of the electronic device 3 and does not constitute a limitation of the electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

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

[0081] The memory 302 may be an internal storage unit of the electronic device 3, for example, a hard disk or memory of the electronic device 3. The memory 302 may 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 may also include both an internal storage unit and an 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 may also be used to temporarily store data that has been output or is to be output.

[0082] An 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 segmentation level of the spatial motion trajectory grid in the aforementioned embodiment are implemented.

[0083] For an introduction to the computer-readable storage medium provided in the embodiments of the present application, please refer to the aforementioned embodiment of the method for determining the optimal segmentation level of the spatial motion trajectory grid, and the embodiments of the present disclosure will not be repeated here.

[0084] For an introduction to the computer-readable storage medium provided in the embodiments of the present application, please refer to the aforementioned embodiment of the method for determining the optimal segmentation level of the spatial motion trajectory grid, and the embodiments of the present disclosure will not be repeated here.

[0085] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0086] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0087] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments applied for herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0088] In the embodiments provided in the present application, it should be understood that the disclosed devices / computer equipment and methods can be implemented in other ways. For example, the device / computer equipment embodiments described above are only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

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

[0090] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may 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 this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. The computer program may include computer program code, and the computer program code may be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained 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 electric carrier signals and telecommunication signals.

[0092] Unless explicitly stated, the actions or steps of the methods, programs, and embodiments of the present disclosure do not have to be performed in a specific order and can still achieve the desired results. In some implementations, multitasking and parallel processing are also possible or may be advantageous.

[0093] In this article, multiple embodiments of the present disclosure are described, but for the sake of brevity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the embodiments may be omitted. In this article, "one embodiment", "some embodiments", "example", "specific example", or "some examples" are meant to be applicable to at least one embodiment or example according to the present disclosure, rather than all embodiments. The above terms do not necessarily mean to refer to the same embodiment or example. In the absence of contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the 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 merely examples of the best modes for implementing the present systems and methods. It will be appreciated by those skilled in the art that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present disclosure as defined in the appended claims.

Claims

1. A method for determining the optimal grid partitioning level of airspace motion trajectory, characterized in that: The method comprises: 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; Based on the discretized grid data of the airspace motion trajectory under different levels of grids, the discrete continuity index of the airspace motion trajectory under different levels of grids is calculated; The grid level corresponding to the smallest discrete continuity index of the spatial motion trajectory is determined as the optimal grid subdivision level of the spatial motion trajectory.

2. The determination method according to claim 1, characterized in that: The discretized grid data of the spatial motion trajectory has one or more quantities of first-type discontinuous grid data and second-type discontinuous grid data.

3. The determination method according to claim 2, characterized in that: The discrete grid data of the airspace motion trajectory under different levels of grids are used to calculate the discrete continuity index of the airspace motion trajectory under different levels of grids, including: For each level of grid, calculating the first type of discontinuous grid data cost value and the second type of discontinuous grid data cost value of the discretized grid data of the airspace motion trajectory; Based on the first-type discontinuous grid data cost value and the second-type discontinuous grid data cost value, a discrete continuity index of the spatial motion trajectory is calculated.

4. The determination method according to claim 3, characterized in that: 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 logarithmic value of the discrete grid of the spatial motion trajectory under each level of grid.

5. The determination method according to claim 3, characterized in that: For each level of grid, the discrete continuity index G(x) of the spatial motion trajectory is Among them, 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 in the spatial motion trajectory.

6. The determination method according to claim 2, characterized in that: The first type of discontinuous grid data is the discontinuity of the discretized grid of the spatial motion trajectory; the second type of discontinuous grid data is the discretized grid of the spatial motion trajectory having two or more grid point data.

7. A device for determining the optimal grid partitioning level of airspace motion trajectory, characterized in that: The device comprises: A discretization module is used to discretize the airspace motion trajectory under different levels of grids to obtain discretized grid data of the airspace motion trajectory under different levels of grids; A calculation module, used for calculating the discrete continuity index of the airspace motion trajectory under different levels of grids based on the discretized grid data of the airspace motion trajectory under different levels of grids; The determination module is used to determine the grid level corresponding to the smallest discrete continuity index of the spatial motion trajectory as the optimal grid subdivision level of the spatial motion trajectory.

8. An electronic device, characterized in that: The device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the method according to any one of claims 1 to 6 when executing the program.

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

Images