UAV conflict detection method, device and storage medium based on airspace digital grid

Abstract

The present invention provides a method, device and storage medium for detecting unmanned aerial vehicle conflicts based on airspace digital grids, including: establishing an airspace discrete subdivision grid model; constructing grid coding rules and the conversion relationship between longitude and latitude coordinates and grid coding; establishing an unmanned aerial vehicle safety protection zone to grid-express unmanned aerial vehicles in the airspace; establishing a coordinate system to convert the grid coding of unmanned aerial vehicles into coordinates; using the GJK algorithm to calculate the Minkowski difference of two blocks; and judging whether unmanned aerial vehicles conflict based on the Minkowski difference. By combining airspace grid coding with the GJK algorithm, the complexity of conflict detection can be effectively reduced compared with traditional paired coordinate operations, a large amount of computing time can be saved, and the efficiency of unmanned aerial vehicle conflict detection can be effectively improved to meet the needs of fast and real-time conflict detection of unmanned aerial vehicles in the airspace.

Description

Technical Field

[0001] The present invention relates to the field of aviation, and in particular to a method, a device and a storage medium for detecting unmanned aerial vehicle conflicts in an airspace digital grid. Background Art

[0002] In recent years, with the rapid increase in the number of drones, research in the field of drones has achieved unprecedented development. Compared with traditional manned aircraft, drones have the advantages of low cost, high cost performance, easy use and high maneuverability due to the separation of man and machine. With the rapid increase in the number of drones, low-altitude airspace is becoming increasingly congested. How to efficiently detect drone conflicts in low-altitude airspace is a key issue restricting the safe flight of drones.

[0003] Traditional conflict detection methods can be used for UAV conflict detection in low-altitude airspace, and the distance between the positions of each track point is calculated to determine whether there is a conflict. As the number of UAVs increases and the airspace involved is larger, if traditional conflict detection methods are used, the calculation under longitude and latitude coordinates cannot achieve high accuracy according to the operating characteristics and volume of the UAV, and the calculation complexity is very high, which will reduce the efficiency of conflict detection, resulting in the algorithm operation time being too long or even unable to effectively detect the conflict, making it difficult to meet the requirements of UAV conflict detection.

[0004] Airspace gridding refers to a method of discretizing airspace by establishing an airspace grid unit division method through rasterization, constructing airspace system data analysis based on network index, and conducting research related to airspace performance. Current research has shown that grid-based conflict detection algorithms can greatly improve conflict detection efficiency. However, most of the research does not integrate the data information space of gridded airspace, but only adopts gridding methods at the application level, and the proposed grid division methods are not modeled for specific operating environments.

[0005] Therefore, how to construct a low-altitude airspace environment and design grid coding to improve the efficiency of UAV conflict detection is a problem that needs to be solved urgently. Summary of the invention

[0006] Purpose of the invention: The technical problem to be solved by the present invention is to provide a method for detecting UAV conflicts in an airspace digital grid in view of the deficiencies of the prior art, including:

[0007] Establish a spatial discrete grid model;

[0008] Construct raster coding rules and the conversion relationship between longitude and latitude coordinates and codes;

[0009] Establish a drone safety protection zone to grid the drones in the airspace;

[0010] Establish a coordinate system to convert the drone's grid code into coordinates;

[0011] The Minkowski difference of two blocks is calculated using the GJK (Gilbert-Johnson-Keerthi) distance algorithm;

[0012] Determine whether the drones are in conflict based on the Minkowski difference set.

[0013] Furthermore, the establishment of the spatial discrete grid model includes the following steps:

[0014] Step 1: Expand the longitude and latitude space of the earth three times, expand the geographic space to 512° east-west and 512° north-south, expand 1° to 64′, and expand 1′ to 64″;

[0015] Step 2: Perform spherical recursive grid division based on geographic spatial longitude and latitude, divide the plane into three levels of degree, minute, and second, and divide the earth's spherical surface into 8 levels of recursive grids, divided into blocks with a minimum side length of 1″;

[0016] Step 3: The altitude is independent of the spherical surface. According to the different altitude reference surfaces, it can be divided into true altitude, surface pressure altitude, corrected sea level pressure altitude, and standard atmospheric pressure altitude. The altitude is expressed and expanded upward with X1 (generally 30m) as the granularity.

[0017] Furthermore, the construction of the grid coding rules and the conversion relationship between the latitude and longitude coordinates and the coding includes:

[0018] The coding includes plane coding and altitude coding. Both plane coding and altitude coding adopt "Z" shaped coding. The "degree" level block coding is represented by d; the "minute" level block coding is represented by m; the "second" level block coding is represented by s. The plane coding and altitude coding are combined to form a three-dimensional coding of the airspace grid system.

[0019] Furthermore, the establishment of a drone safety protection zone includes:

[0020] A drone safety protection zone is established based on the drone’s operating performance. The horizontal and vertical intervals of the protection zone are D hor , the vertical spacing is D ver , select the appropriate grid size according to the size of the protected area. According to the classification standard of drones, general civilian consumer drones belong to micro drones, corresponding to the 8th level grid granularity, and the 6th and 7th level grids correspond to the size of medium-sized drones and small drones, respectively. Therefore, the 6th, 7th, and 8th level grids can represent most drones. If some drones are of special size and cannot be directly represented by one grid, multiple grids can be used for combined expression.

[0021] Furthermore, the gridding expression method for UAVs in the airspace includes:

[0022] Mesh expression can express the target object through mesh combination or independently. First, use only one cube to represent the drone, and Point represents a cube information. The following point object expression model is established:

[0023]

[0024] In the formula, Represents the latitude, longitude, and altitude of the point object's location. Indicates that at this latitude and longitude, the volume is divided into n blocks. In the process of computer storage and calculation, use Represents a point object;

[0025] Then use some continuous cubes to represent the path of the drone, Line represents the flight trajectory of the drone, and establish the following line object expression model:

[0026]

[0027] When the drone or obstacle cannot be represented by a cube, two or more small grids are stacked to represent irregular shaped objects. Space represents objects formed by stacking two or more cubes. The following volume object expression model is established:

[0028]

[0029] For the current drone detection object, the flight latitude, longitude and altitude information obtained from the airborne ADS-B (ADS-B is the abbreviation of the Automatic Dependent Surveillance-Broadcast system) equipment or ground station is encoded and converted. The formula is as follows:

[0030]

[0031]

[0032] Code Alt =Alt / x1

[0033] Among them, longitude coding, latitude coding and altitude coding are respectively represented by Code Lon 、Code Lat and Code Alt Indicates, n indicates the encoding level, gridsize n Indicates the size of the grid granularity at the nth level, Lon d , Lon m and Lon sThey represent degrees, minutes, and seconds in longitude coordinates respectively, and the altitude level is expanded upward with the granularity of x1 and encoded separately.

[0034] Further, the establishment of a coordinate system to convert the grid code of the drone into coordinates includes:

[0035] After gridding the drones in the airspace, the drones and their track points are placed in the grid coordinate system, and the longitude and latitude coordinates are converted into rectangular coordinate integer operations.

[0036] Furthermore, the method of calculating the Minkowski difference of two blocks using the GJK algorithm includes:

[0037] The GJK algorithm is used to calculate the distance between two convex bodies. The distance between object A and object B is represented by d(A, B), which is defined by the following formula:

[0038] d(A,B)=min{||xy||:x∈A,y∈B};

[0039] Where x and y represent points in object A and object B respectively; objects A and B are both cubes;

[0040] The two points a∈A and b∈B that are closest to objects A and B satisfy ||ab||=d(A,B);

[0041] The Minkowski difference is a set of points consisting of the differences between all points of object A and all points of object B, as shown below:

[0042] M(A,B)={xy:x∈A,y∈B};

[0043] M(A,B) represents the Minkowski difference of cubes A and B;

[0044] The distance between objects A and B is represented by the Minkowski difference set, which can be described as follows:

[0045] d(A,B)=min||M(A,B)||=min{||xy||:x∈A,y∈B}.

[0046] Furthermore, judging whether the drones collide based on the Minkowski difference set includes: converting the distance between the drones into the Minkowski difference between the drones, and determining whether the two objects collide by judging whether the difference set contains the origin, the greater the distance between the two drones, the farther the center position of the difference set is from the origin, and vice versa, the closer it is to the origin. If the drone blocks collide, the difference set polygon will contain the origin.

[0047] The present invention also provides a UAV conflict detection device for an airspace digital grid, comprising:

[0048] A spatial domain discrete subdivision grid model building module is used to build a spatial domain discrete subdivision grid model;

[0049] A conversion relationship building module is used to build raster coding rules and the conversion relationship between longitude and latitude coordinates and codes;

[0050] The grid expression module is used to establish a drone safety protection zone and to perform grid expression on drones in the airspace;

[0051] The coordinate conversion module is used to establish a coordinate system to convert the grid code of the drone into coordinates;

[0052] The Minkowski difference calculation module is used to calculate the Minkowski difference of two blocks using the GJK distance algorithm;

[0053] The UAV conflict determination module is used to determine whether the UAVs conflict based on the Minkowski difference set.

[0054] The present invention also provides a storage medium storing a computer program or instruction. When the computer program or instruction is executed, the UAV conflict detection method of the airspace digitized grid is implemented.

[0055] The beneficial effect of the present invention is that the present invention provides a UAV conflict detection method based on airspace digitized grids. The UAV conflict detection method based on airspace digitized grids includes: establishing an airspace discrete subdivision grid model; constructing grid coding rules and the conversion relationship between longitude and latitude coordinates and grid codes; establishing a UAV safety protection zone to grid-express UAVs in the airspace; establishing a coordinate system to convert the grid code of the UAV into coordinates; using the GJK algorithm to calculate the Minkowski difference of two blocks; judging whether the UAVs are in conflict based on the Minkowski difference. By combining airspace grid coding with the GJK algorithm, compared with traditional paired coordinate operations, the complexity of conflict detection can be effectively reduced, a large amount of computing time can be saved, and the efficiency of UAV conflict detection can be effectively improved to meet the needs of fast and real-time conflict detection of UAVs in the airspace. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, and the above and / or other advantages of the present invention will become more clear.

[0057] Figure 1 It is a flow chart of a UAV conflict detection method based on airspace digitized grid provided by the present invention.

[0058] Figure 2 This is a schematic diagram of grid expansion.

[0059] Figure 3 It is a schematic diagram of the subdivision level division.

[0060] Figure 4 This is a schematic diagram of the Minkowski difference distance transformation.

[0061] Figure 5 It is a schematic diagram showing three drones of the same type, A, B, and C, represented as three cubes of the size of the level 8 grid.

[0062] Figure 6 This is a schematic diagram of the Minkowski difference result between A and B.

[0063] Figure 7 This is a schematic diagram of the Minkowski difference result between A and C.

[0064] Figure 8 Conflict Detection Time Comparison DETAILED DESCRIPTION

[0065] Example

[0066] like Figure 1 As shown, the present invention provides a method for detecting UAV conflicts based on airspace digital grid. The air traffic area division method based on fuzzy C-means clustering includes the following steps:

[0067] S110: Establishing a spatial discrete grid model;

[0068] S120: constructing raster coding rules and the conversion relationship between longitude and latitude coordinates and codes;

[0069] S130: Establish a drone safety protection zone to grid the drones in the airspace;

[0070] S140: Establish a coordinate system to convert the grid code of the drone into coordinates;

[0071] S150: Calculate the Minkowski difference of two blocks using the GJK algorithm;

[0072] S160: Determine whether the drones are in conflict based on the Minkowski difference set.

[0073] In this embodiment, step S110 includes: spherical division and height division of the earth, recursive grid division, analyzing the requirements of airspace gridding methods according to the operating characteristics of low-altitude airspace, constructing a discretized gridded airspace and establishing a grid division of the digital model.

[0074] S111: Expand the longitude and latitude space of the earth three times, expand the geographic space to 512° east-west and 512° north-south, expand 1° to 64′, and expand 1′ to 64″, such as Figure 2 As shown;

[0075] S112: Perform spherical recursive grid division based on geographic spatial longitude and latitude, divide the plane into three levels of "degree-minute-second" step by step, and divide the earth's spherical surface into 8 levels of recursive grids, divided into blocks with a minimum side length of 1", as shown in Table 1;

[0076] S113: Altitude is independent of spherical divisions. According to the different altitude reference surfaces, it can be divided into true altitude, surface pressure altitude, corrected sea level pressure altitude, and standard atmospheric pressure altitude. It is expanded upward with a granularity of 30m.

[0077] In this embodiment, step S120 includes the following steps: the coding is divided into two parts, plane coding and height coding. Both plane coding and height coding adopt "Z"-shaped coding. The "degree" level block coding is represented by d; the "minute" level block coding is represented by m; the "second" level block coding is represented by s. The plane coding and height coding are combined to form a three-dimensional coding of the spatial grid system.

[0078] Table 1

[0079] Decomposition level Grid Size Approximate size near the equator First level 15°×15° 1669km Level 2 1°×1° 111km Level 3 30'×30' 56km Level 4 10'×10' 9km Level 5 1'×1' 1km Level 6 6"×6" 0.2km Level 7 3"×3" 0.1km Level 8 1"×1" 0.03km

[0080] In this embodiment, step S130 includes the following steps:

[0081] S131: Establish a drone safety protection zone based on the drone’s operating performance, with a horizontal and vertical spacing of D hor , the vertical spacing is D ver , select a grid of appropriate granularity according to the size of the protected area.

[0082] S132: Establish point object expression model:

[0083]

[0084] In the formula, Represents the latitude, longitude, and altitude of the point object's location. It means that at this latitude and longitude, the volume with level n is divided, such as Figure 3 As shown in the figure, according to the classification standard of drones, general civilian consumer drones belong to micro drones, corresponding to the 8th level grid granularity, and the 6th and 7th level grids correspond to the sizes of medium-sized drones and small drones, respectively. Therefore, the 6th, 7th, and 8th level grids can represent most drones. If some drones are of special size and cannot be directly represented by one grid, multiple grids can be used to combine and express them.

[0085] In the process of computer storage and calculation, Represents a point object;

[0086] S133: Establish line object expression model:

[0087]

[0088] S134: Establishing a volume object expression model:

[0089]

[0090] For the current drone detection object, the flight latitude, longitude and altitude information obtained from the airborne ADS-B equipment or ground station is encoded and converted. The formula is as follows:

[0091]

[0092]

[0093] Code Alt =Alt / x1

[0094] Among them, longitude coding, latitude coding and altitude coding are respectively represented by Code Lon 、Code Lat and Code Alt Indicates, n indicates the encoding level, gridsize n Indicates the size of the grid granularity at the nth level, Lon d , Lon m and Lon s They represent degrees, minutes, and seconds in longitude coordinates respectively, and the altitude level is expanded upward with the granularity of x1 and encoded separately.

[0095] In this embodiment, step S140 includes: after the airspace is expressed in grid form, the UAV and its track points are placed in a grid coordinate system, and the longitude and latitude coordinates are converted into rectangular coordinate integer operations.

[0096] In this embodiment, step S150 includes:

[0097] S151: The GJK algorithm calculates the distance between two convex bodies. The distance between objects A and B is represented by d(A, B), which is defined by the following formula:

[0098] d(A,B)=min{||xy||:x∈A,y∈B}

[0099] The two points a∈A and b∈B that are closest to objects A and B satisfy ||ab||=d(A,B);

[0100] S152: The Minkowski difference set is a point set consisting of the difference between all points of object A and all points of object B, which can be expressed as follows:

[0101] M(A,B)={xy:x∈A,y∈B};

[0102] S153: The distance between objects A and B can be expressed by Minkowski difference sets, such as Figure 4 As shown, the description is as follows:

[0103] d(A,B)=min||M(A,B)||=min{||xy||:x∈A,y∈B}.

[0104] In this embodiment, step S160 includes: converting the distance between the drones into the Minkowski difference between the two, and determining whether the two objects collide by judging whether the difference set contains the origin. The greater the distance between the two drones, the farther the center position of the difference set is from the origin, and vice versa. If the drone blocks collide, the difference set polygon will contain the origin. Drones A and B collide if and only if the Minkowski difference set M(A, B) of the two cubes contains the origin. Three drones of the same type A, B, and C are represented as three cubes of the 8th level grid size, such as Figure 5 As shown, A and B are in contact, C is far away from A and B, and the number of algorithm iterations is set to 5000. Therefore, the obtained Minkowski difference set contains 5000 points. These element points are placed in the coordinates to show that the Minkowski difference results of A and B, A and C are as follows: Figure 6 and Figure 7 As shown in , the relationship between the Minkowski difference set and the origin is intuitively shown. Figure 6 As shown, the origin is inside the Minkowski difference set generated by cubes A and B. If the origin is inside the difference set, it means that there is a conflict between the two. If there is no conflict between cubes A and C, then the origin is outside the Minkowski difference set of the two. Figure 7 The conflict detection time of the proposed method is analyzed by using three different sizes of drones, with the 6th, 7th and 8th level grid granularity as the cube representation of three different types of drones. The experiment selected 3 medium-sized drones, 3 small drones and 14 micro drones, a total of 20 drones. The 8th level coding was also used to generate a 1km×1km×0.6km gridded airspace environment for the experiment, and the average conflict detection time of the two algorithms over a period of time was recorded. The results are shown in Figure 8 As the number of drones increases, the conflict detection time of the traditional three-dimensional coordinate system based on the Euclidean distance conflict detection method between drones grows nearly exponentially, while the conflict detection method based on GJK grows linearly, with a relatively slow growth trend, which shows the high efficiency of the method of the present invention.

[0105] This embodiment also provides a UAV conflict detection device for an airspace digital grid, including:

[0106] A spatial domain discrete subdivision grid model building module is used to build a spatial domain discrete subdivision grid model;

[0107] A conversion relationship building module is used to build raster coding rules and the conversion relationship between longitude and latitude coordinates and codes;

[0108] The grid expression module is used to establish a drone safety protection zone and to perform grid expression on drones in the airspace;

[0109] The coordinate conversion module is used to establish a coordinate system to convert the grid code of the drone into coordinates;

[0110] The Minkowski difference calculation module is used to calculate the Minkowski difference of two blocks using the GJK distance algorithm;

[0111] The UAV conflict determination module is used to determine whether the UAVs conflict based on the Minkowski difference set.

[0112] This embodiment also provides a storage medium storing a computer program or instruction. When the computer program or instruction is executed, the method for detecting UAV conflicts in a digital airspace grid is implemented.

[0113] As described above, the apparatus according to the embodiment of the present application can be implemented in various terminal devices, such as a server of a distributed computing system. In one example, the apparatus according to the embodiment of the present application can be integrated into the terminal device as a software module and / or a hardware module. For example, the apparatus can be a software module in the operating system of the terminal device, or can be an application developed for the terminal device; of course, the apparatus can also be one of the many hardware modules of the terminal device.

[0114] Alternatively, in another example, the apparatus and the terminal device may also be separate terminal devices, and the apparatus may be connected to the terminal device via a wired and / or wireless network, and transmit the interactive information in accordance with an agreed data format.

[0115] In summary, the present invention provides a method for detecting UAV conflicts based on airspace digital grids, including: establishing an airspace discrete grid model; constructing grid coding rules and the conversion relationship between longitude and latitude coordinates and grid coding; establishing a UAV safety protection zone to grid-express UAVs in the airspace; establishing a coordinate system to convert the grid coding of the UAV into coordinates; using the GJK algorithm to calculate the Minkowski difference of two blocks; and judging whether the UAVs conflict based on the Minkowski difference. By combining airspace grid coding with the GJK algorithm, compared with traditional paired coordinate operations, the complexity of conflict detection can be effectively reduced, a large amount of computing time can be saved, and the efficiency of UAV conflict detection can be effectively improved to meet the needs of fast and real-time conflict detection of UAVs in the airspace.

[0116] The present invention provides a method, device and storage medium for detecting UAV conflicts in an airspace digital grid. There are many methods and ways to implement the technical solution. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention. All components not specified in this embodiment can be implemented using existing technologies.

Claims

1. A UAV conflict detection method based on airspace digital grid, characterized in that: include: Establish a spatial discrete grid model; Construct raster coding rules and the conversion relationship between longitude and latitude coordinates and codes; Establish drone safety protection zones and grid the drones in the airspace; Establish a coordinate system to convert the drone's grid code into coordinates; The Minkowski difference of two blocks is calculated using the GJK distance algorithm; Determine whether the drones are in conflict based on the Minkowski difference set; The step of establishing a spatial discrete grid model comprises the following steps: Step 1: Expand the longitude and latitude space of the earth three times, expand the geographic space to 512° east-west and 512° north-south, expand 1° to 64′, and expand 1′ to 64″; Step 2: Perform spherical recursive grid division based on geographic spatial longitude and latitude, divide the plane into three levels of degree, minute, and second, and divide the earth's spherical surface into 8 levels of recursive grids, divided into blocks with a minimum side length of 1″; Step 3: The height is independent of the spherical surface division. The height is expressed according to the different height reference surfaces and expanded upward with X1 as the granularity. The construction of the grid coding rules and the conversion relationship between the latitude and longitude coordinates and the coding include: The coding includes plane coding and height coding. Both plane coding and height coding adopt Z-shaped coding. Degree block coding is represented by d; graded block coding is represented by m; second block coding is represented by s. The plane coding and height coding are combined to form a three-dimensional coding of the airspace grid system. The establishment of a drone safety protection zone includes: A drone safety protection zone is established based on the drone’s operating performance. The horizontal and vertical intervals of the protection zone are D hor , the vertical spacing is D ver , select the grid with appropriate granularity according to the size of the protected area; The gridding expression of the UAV in the airspace includes: First, use only a cube to represent the drone. Point represents a cube information. The following point object expression model is established: In the formula, θ, h represents the latitude, longitude and altitude of the point object respectively; Indicates that at θ, At the latitude and longitude height h, the volume is divided into n levels; Represents a point object; Then use continuous cubes to represent the path of the drone, Line to represent the flight trajectory of the drone, and establish the following line object expression model: When the drone or obstacle cannot be represented by a cube, two or more small grids are stacked to represent irregular shaped objects. Space represents objects formed by stacking two or more cubes. The following volume object expression model is established: For the current drone detection object, the flight latitude, longitude and altitude information obtained from the airborne ADS-B equipment or ground station is encoded and converted. The formula is as follows: Code Alt =All / x1 Among them, longitude coding, latitude coding and altitude coding are respectively represented by Code Lon 、Code Lat and Code Alt Indicates, n indicates the encoding level, gridsize n Indicates the size of the grid granularity at the nth level, Lon d , Lon m and Lon s They represent degrees, minutes, and seconds in longitude coordinates respectively, and the altitude level is independently coded with the granularity of x1 extending upwards; The establishment of a coordinate system to convert the grid code of the drone into coordinates includes: after gridding the drone in the airspace, placing the drone and its track points in the grid coordinate system, and converting the longitude and latitude coordinates into rectangular coordinate integer operations; The method of calculating the Minkowski difference of two blocks using the GJK algorithm includes: The GJK algorithm is used to calculate the distance between two convex bodies. The distance between object A and object B is represented by d(A, B), which is defined by the following formula: d(A,B)=min{||xy||:x∈A,y∈B}; Where x and y represent points in object A and object B respectively; The two points a∈A and b∈B that are closest to object A and object B satisfy ||ab||=d(A,B); The Minkowski difference is a set of points consisting of the differences between all points of object A and all points of object B, as shown below: M(A,B)={xy:x∈A,y∈B}; M(A,B) represents the Minkowski difference of cubes A and B; The distance between objects A and B is represented by the Minkowski difference set, which can be described as follows: d(A,B)=min||M(A,B)||=min{||xy||:x∈A,y∈B} The method of judging whether the UAVs collide with each other based on the Minkowski difference set includes: converting the distance between the UAVs into the Minkowski difference between the UAVs, and determining whether the two objects collide with each other by judging whether the difference set contains the origin.

2. The UAV conflict detection device based on the airspace digital grid implemented by the method according to claim 1 is characterized in that: include: A spatial domain discrete subdivision grid model building module is used to build a spatial domain discrete subdivision grid model; A conversion relationship building module is used to build raster coding rules and the conversion relationship between longitude and latitude coordinates and codes; The grid expression module is used to establish a drone safety protection zone and to perform grid expression on drones in the airspace; The coordinate conversion module is used to establish a coordinate system to convert the grid code of the drone into coordinates; The Minkowski difference calculation module is used to calculate the Minkowski difference of two blocks using the GJK distance algorithm; The UAV conflict determination module is used to determine whether the UAVs conflict based on the Minkowski difference set.

3. A storage medium, characterized in that: A computer program or instruction is stored, and when the computer program or instruction is executed, the method according to claim 1 is implemented.

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