1. A airspace multilevel grid characterization and conflict detection method based on a multi-way tree is characterized by comprising the following steps:

step 1: establishing a space domain discrete grid model, and coding the space domain discrete grid model to form three-dimensional coding of the space domain grid model;

step 2: generating a traditional geometric airspace according to the military civil aviation air plan, and performing airspace grid representation on the traditional geometric airspace based on a multi-way tree;

and step 3: and performing conflict detection on the traditional geometric airspace generated by the civil and military aviation air plan to obtain a conflict grid.

2. The method according to claim 1, wherein the establishing of the spatial domain grid model in step 1 comprises:

step 1-1: longitude [70 degrees E,140 degrees E ] and latitude [0 degrees N,70 degrees N ]) of the earth surface space are subjected to positive axis cylinder equidistant projection, and the earth spherical surface is projected to have the length-width ratio of 1: 1, dividing the longitude and latitude projection plane layer by layer according to 8 × 8 sixty-four equal parts to form a longitude and latitude projection plane grid model with each hierarchy mutually containing no gap, and dividing 10 hierarchies at the highest;

step 1-2: dividing the height [0,100km ] by 8 equal parts layer by layer, and when the longitude and latitude plane is subjected to first-level division, not dividing the height direction, namely not dividing the height of the first level; when the longitude and latitude plane is divided into a second level, dividing the longitude and latitude plane into 8 equal parts in the height direction to form a second level height, and dividing the longitude and latitude plane layer by layer in the height direction to form a height grid model, wherein 9 levels are divided at the highest; the height grid model and the longitude and latitude projection plane grid model are combined to form a spatial domain discrete grid model together.

3. The method according to claim 1, wherein the encoding of the spatial domain discrete grid model to form the spatial domain grid model three-dimensional encoding in step 1 comprises:

the longitude and latitude projection plane grid coding is coded by adopting a double-bit octal coding from left to right and from bottom to top, and nested coding is carried out according to the levels from low to high, namely the grid size from large to small, so as to obtain the longitude and latitude codes from the first level to the tenth level; the height grid coding is used for coding the height grids from low to high, the first level is not coded, the height grids are also coded by adopting octal coding from bottom to top, and the height codes from the second level to the tenth level are obtained; and combining the longitude and latitude projection plane grid codes and the height grid codes according to corresponding levels to form the three-dimensional codes of the airspace grid model.

4. The airspace multilevel grid characterization and collision detection method based on the multi-branch tree according to claim 1, wherein the conventional geometric airspace in the step 2 includes a polygonal airspace, a hemispherical airspace, a cylindrical airspace, a cone airspace and a sector airspace, and the corresponding conventional geometric airspace can be generated according to longitude and latitude height information in a military civil aviation air plan.

5. The method according to claim 1, wherein the step 2 of performing the multi-tree-based spatial domain multi-level grid characterization and collision detection on the traditional geometric spatial domain comprises:

step 2-1: calculating a first-level grid of an airspace discrete grid model with intersection with any point of the bottom surface of the traditional geometric airspace according to the longitude and latitude height of the any point of the bottom surface of the traditional geometric airspace, expanding the grid in the longitude and latitude direction to obtain all first-level grids with intersection with the bottom surface of the traditional geometric airspace, recording all first-level longitude and latitude codes with intersection with the traditional geometric airspace, and constructing an airspace grid representation multi-branch tree by taking the airspace ID as a root node and taking the first-level longitude and latitude codes with intersection as leaf nodes;

step 2-2: performing next-level decomposition on the first-level grids obtained in the step 2-1 to obtain grids with intersection between a second level and the bottom of the traditional geometric airspace, recording second-level longitude and latitude codes of the grids, expanding the grids in the height direction, recording second-level height codes of the grids with intersection between each second-level longitude and latitude code in the height direction and the traditional geometric airspace, and performing layer-by-layer decomposition until reaching a target level, wherein the target level refers to the decomposition from a latitude projection plane grid to a tenth level in an airspace discrete grid model, and the decomposition of the height grids to the tenth level; leaf nodes formed by longitude and latitude codes and height codes of the low-to-high levels are inserted into the nodes corresponding to the spatial domain grid representation multi-way tree to form the grid representation multi-way tree of the traditional geometric spatial domain.

6. The spatial domain multi-level grid characterization and collision detection method based on the multi-way tree according to claim 1, wherein step 3 comprises:

step 3-1: performing time exclusion detection on a traditional geometric airspace generated by two civil aviation air plans, wherein if the time does not overlap, the two airspaces do not conflict;

step 3-2: performing spatial exclusion detection on two traditional geometric airspaces, namely comparing longitude and latitude height boundaries of the two airspaces, wherein if one of the three dimensions of the longitude and latitude height does not have an overlapping area, the two airspaces do not have a conflict area;

step 3-3: comparing two grid representation multi-branch trees of the traditional geometric airspace, firstly solving intersection of the longitude and latitude codes of the first level of the two airspaces, obtaining the longitude and latitude codes of the next level of the intersection grid of the first level in the grid representation multi-branch trees of the two airspaces, and continuously solving intersection, and thus obtaining the highest level intersection longitude and latitude codes of leaf nodes of the multi-branch trees; and obtaining height codes corresponding to the highest level intersection longitude and latitude codes in the grid representation multi-branch tree, solving intersection of the height codes, and determining the grid codes jointly by the highest level intersection longitude and latitude codes and the highest level height codes to be the conflict grids of the two airspaces.

Background

The airspace conflict detection technology is an important premise for realizing the orderly operation and air utilization plan of airspace in China, along with the rapid increase of economy, the international situation is increasingly tense, the civil and military aviation plans in China are more frequent, the conflict between civil and military aviation conflicts and conflict among military varieties is continuously upgraded, and how to rapidly and accurately judge the conflict airspace of the airspace utilization plan is a premise for guaranteeing the stable and safe operation of the airspace and is a key problem of the collaborative control of the future airspace.

For the spatial domain discrete grid representation and collision detection technology, relevant researches have appeared in recent years, some relevant models and algorithms appear, namely, the spatial domain is subjected to grid subdivision coding representation, then the traditional spatial domain is mapped into the grid to be subjected to spatial domain representation, and if two mapping spatial domains appear in the grid and are overlapped in time, the grid is judged to be a collision grid. When the method is used for detecting the conflict between two large airspaces, the conflict range of the airspace can be quickly given, but the method has the problems that the time for mapping the airspace into the grid is long, the flexible comparison of different precisions is difficult to carry out on the airspaces, and the like.

Disclosure of Invention

The purpose of the invention is as follows: the invention provides a method for detecting airspace multilevel grid representation and conflict based on a multi-way tree, aiming at the defects of the prior art.

In order to solve the technical problem, the invention discloses a method for detecting airspace multilevel grid characteristics and conflicts based on a multi-way tree, which comprises the following steps:

step 1: establishing a space domain discrete grid model, and coding the space domain discrete grid model to form three-dimensional coding of the space domain grid model;

step 2: generating a traditional geometric airspace according to the military civil aviation air plan, and performing airspace grid representation on the traditional geometric airspace based on a multi-way tree;

and step 3: and performing conflict detection on the traditional geometric airspace generated by the civil and military aviation air plan to obtain a conflict grid.

In one implementation, the establishing the spatial grid model in step 1 includes:

step 1-1: longitude [70 degrees E,140 degrees E ] and latitude [0 degrees N,70 degrees N ]) of the earth surface space are subjected to positive axis cylinder equidistant projection, and the earth spherical surface is projected to have the length-width ratio of 1: 1, dividing the longitude and latitude projection plane layer by layer according to 8 × 8 sixty-four equal parts to form a longitude and latitude projection plane grid model with each hierarchy mutually containing no gap, and dividing 10 hierarchies at the highest;

step 1-2: dividing the height [0,100km ] by 8 equal parts layer by layer, and when the longitude and latitude plane is subjected to first-level division, not dividing the height direction, namely not dividing the height of the first level; when the longitude and latitude plane is divided into a second level, dividing the longitude and latitude plane into 8 equal parts in the height direction to form a second level height, and dividing the longitude and latitude plane layer by layer in the height direction to form a height grid model, wherein 9 levels are divided at the highest; the height grid model and the longitude and latitude projection plane grid model are combined to form a spatial domain discrete grid model together.

In one implementation, the encoding the spatial domain discrete grid model in step 1 to form a spatial domain grid model three-dimensional code includes:

the longitude and latitude projection plane grid coding is coded by adopting a double-bit octal coding from left to right and from bottom to top, and nested coding is carried out according to the levels from low to high, namely the grid size from large to small, so as to obtain the longitude and latitude codes from the first level to the tenth level; the height grid coding is used for coding the height grids from low to high, the first level is not coded, the height grids are also coded by adopting octal coding from bottom to top, and the height codes from the second level to the tenth level are obtained; and combining the longitude and latitude projection plane grid codes and the height grid codes according to corresponding levels to form the three-dimensional codes of the airspace grid model.

In one implementation, in step 2, the traditional geometric airspace includes a polygonal airspace, a hemispherical airspace, a cylindrical airspace, a conical airspace and a sector airspace, and the corresponding traditional geometric airspace can be generated according to longitude and latitude height information in the military civil aviation air plan.

In one implementation, the performing multi-tree-based spatial domain multi-level grid characterization on the traditional geometric spatial domain in step 2 includes:

step 2-1: calculating a first-level grid of an airspace discrete grid model with intersection with any point of the bottom surface of the traditional geometric airspace according to the longitude and latitude height of the any point of the bottom surface of the traditional geometric airspace, expanding the grid in the longitude and latitude direction to obtain all first-level grids with intersection with the bottom surface of the traditional geometric airspace, recording all first-level longitude and latitude codes with intersection with the traditional geometric airspace, and constructing an airspace grid representation multi-branch tree by taking the airspace ID as a root node and taking the first-level longitude and latitude codes with intersection as leaf nodes;

step 2-2: performing next-level decomposition on the first-level grids obtained in the step 2-1, obtaining grids with intersection between a second level and the bottom of the traditional geometric airspace, recording second-level longitude and latitude codes of the grids, expanding the grids in the height direction, recording second-level height codes of the grids with intersection between each second-level longitude and latitude code in the height direction and the traditional geometric airspace, and performing layer-by-layer decomposition until reaching a target level, wherein the target level refers to the decomposition from a latitude projection plane grid to a tenth level in an airspace discrete grid model, and the decomposition of the height grids to the tenth level; leaf nodes formed by longitude and latitude codes and height codes of the low-to-high levels are inserted into the nodes corresponding to the spatial domain grid representation multi-way tree to form the grid representation multi-way tree of the traditional geometric spatial domain.

In one implementation, step 3 includes:

step 3-1: performing time exclusion detection on a traditional geometric airspace generated by two civil aviation air plans, wherein if the time does not overlap, the two airspaces do not conflict;

step 3-2: performing spatial exclusion detection on two traditional geometric airspaces, namely comparing longitude and latitude height boundaries of the two airspaces, wherein if one of the three dimensions of the longitude and latitude height does not have an overlapping area, the two airspaces do not have a conflict area;

step 3-3: comparing two grid representation multi-branch trees of the traditional geometric airspace, firstly solving intersection of the longitude and latitude codes of the first level of the two airspaces, acquiring the longitude and latitude codes of the next level of the intersection grid of the first level in the grid representation multi-branch trees of the two airspaces, and continuously solving intersection until the highest level intersection longitude and latitude codes of leaf nodes of the multi-branch trees are acquired; and acquiring height codes corresponding to the highest level intersection longitude and latitude codes in the grid representation multi-branch tree, solving intersection of the height codes, and determining the grid codes jointly by the highest level intersection longitude and latitude codes and the highest level height codes to be the conflict grids of the two airspaces.

In step 3-3, intersection of the first-level longitude and latitude codes of the two airspaces is firstly solved, next-level longitude and latitude codes of the first-level intersection grid are obtained from the two airspace grid representation multi-branch trees, intersection is continuously solved, and accordingly the highest-level intersection longitude and latitude codes of leaf nodes of the multi-branch trees are obtained, the representation levels of the leaf nodes of the multi-branch trees, namely the contrast depth of the multi-branch trees, can be flexibly selected according to needs, the higher the selected level is, the higher the precision is, and therefore flexible conflict detection with different precisions of the airspaces is achieved.

Has the advantages that:

the airspace is divided into seamless grid models with different sizes and mutually contained size levels from the warp direction, the weft direction and the high direction by adopting an octal subdivision mode, each grid of each size level is uniquely nested and coded, the grid codes and grid airspace entities form a one-to-one correspondence relationship, and a novel airspace discretization representation mode based on grids is formed.

Performing spatial grid representation, namely generating a traditional geometric spatial domain according to an spatial domain use plan, calculating grids which have intersection with the geometric spatial domain from the lowest level, namely the maximum size grid, downwards subdividing the grids which have intersection, calculating whether the grids intersect with the geometric spatial domain or not, and recording all grids which have intersection with the spatial domain at the current level until the grids are decomposed to a target level; and a multi-branch tree structure is adopted to perform rasterization representation on the traditional geometric airspace according to grid codes with intersection between grid size records from large to small and the geometric airspace, the representation mode can realize multi-level grid representation of the airspace, and representation grids at different levels correspondingly represent grids at different depths in the multi-branch tree, so that flexible representation of different precisions of the airspace is realized.

And (3) airspace conflict detection, namely, firstly, excluding detection of time and space is carried out on two airspaces, then, pairwise comparison is carried out on the airspace grid representation multi-way tree obtained in the step (2), namely, the multi-way tree is traversed and compared from top to bottom, grids with the same or containing leaf nodes are used as conflict grids of two geometric airspaces, the conflict detection time is greatly reduced by the detection mode, and the representation levels of a conflict area, namely the contrast depth of the multi-way tree, can be flexibly selected according to requirements, so that the flexible conflict detection with different precisions is carried out on the airspaces.

The multi-tree grid representation method based on the grid model is used for carrying out multi-tree grid representation on each type of airspace, then the conflict range and the conflict time of a large number of airspace use plans can be rapidly and efficiently detected based on the grid, compared with the prior art, the problem that airspace discrete mapping representation is difficult is solved, multi-level flexible representation of the airspace is realized, and different-level representation grids directly correspond to nodes with different depths in the multi-tree; and the rapid conflict detection of different accuracies of conflict airspace can be realized, the contrast depth of the representation multi-branch tree can be flexibly selected aiming at different airspaces, and the conflict detection of different accuracies is realized.

Drawings

The foregoing and/or other advantages of the invention will become further apparent from the following detailed description of the invention when taken in conjunction with the accompanying drawings.

FIG. 1 is a flowchart of grid-based geometric spatial domain characterization according to an embodiment of the present application.

Fig. 2 is a longitude and latitude subdivision diagram of an airspace grid model according to the embodiment of the present application.

FIG. 3 is a high-level subdivision diagram of a spatial grid model according to an embodiment of the present application.

Fig. 4 is a schematic diagram of spatial trellis coding according to an embodiment of the present application.

FIG. 5 is a diagram of a spatial grid multi-way tree representation according to an embodiment of the present application.

FIG. 6 is a flowchart of spatial domain collision detection based on a grid model according to an embodiment of the present application.

Detailed Description

Embodiments of the present invention will be described below with reference to the accompanying drawings.

A airspace multilevel grid characterization and conflict detection method based on a multi-branch tree comprises the following steps:

step 1: establishing a space domain discrete grid model, and coding the space domain discrete grid model to form three-dimensional coding of the space domain grid model;

step 2: generating a traditional geometric airspace according to the military civil aviation air plan, and performing airspace grid representation on the traditional geometric airspace based on a multi-way tree;

and step 3: and performing conflict detection on the traditional geometric airspace generated by the civil and military aviation air plan to obtain a conflict grid.

Referring to fig. 1, step 1 includes the following steps:

firstly, a longitude [70 degrees E,140 degrees E ], a latitude [0 degrees N,70 degrees N ] and a height [0,100km ] airspace is subjected to rasterization modeling, a continuous airspace is divided into 10 layers of plane grids and 9 layers of height grids, as shown in figures 2 and 3, the plane division projects the earth surface space to a square plane by a positive axis cylinder equidistant projection method, then the plane is divided into 8-sixty-four equal divisions step by step as shown in figure 2, the height layers are divided according to eight equal divisions, and the height of a first level is not divided as shown in figure 3. And combining the plane subdivision and the height subdivision to form a three-dimensional grid model framework.

Second, digitally encoding the space domain lattice model

Coding all grids based on a three-dimensional grid model framework established by an airspace grid subdivision method, wherein the coding is divided into a longitude and latitude coding part and a height coding part, the longitude and latitude coding part adopts a zigzag octal dibit coding part, and the coding is sequentially carried out from left to right from 00 to 77 from bottom to top; the height coding adopts linear octal coding, and the coding is carried out from '0' to '7' from bottom to top in sequence, and the height of the first level is not divided. The high-level grids are subjected to nested coding, longitude and latitude coding and height coding are combined to form three-dimensional coding of an airspace grid system, fig. 4 shows first-level grid longitude and latitude coding and second-level longitude and latitude and height coding, and the first-level grids coded to 07_ are subjected to subdivision coding as shown in fig. 4.

And 2, the traditional geometric airspace comprises a polygonal airspace, a hemispherical airspace, a cylindrical airspace, a cone airspace and a sector airspace, and the corresponding traditional geometric airspace can be generated according to longitude and latitude height information in the military civil aviation air plan. The step 2 comprises the following steps:

calculating a first-level grid of an airspace discrete grid model with intersection with any point of the bottom surface of the traditional geometric airspace according to the longitude and latitude height of the any point of the bottom surface of the traditional geometric airspace, expanding the grid in the longitude and latitude direction to obtain all first-level grids with intersection with the bottom surface of the traditional geometric airspace, recording all first-level longitude and latitude codes with intersection with the traditional geometric airspace, and constructing an airspace grid representation multi-branch tree by taking the airspace ID as a root node and taking the first-level longitude and latitude codes with intersection as leaf nodes;

performing next-level decomposition on the obtained first-level grid, obtaining grids with intersection between a second level and the bottom of the traditional geometric airspace, recording second-level longitude and latitude codes of the grids, expanding the grids in the height direction, recording second-level height codes of the grids with intersection between each second-level longitude and latitude code in the height direction and the traditional geometric airspace, and performing layer-by-layer decomposition until a target level is reached, wherein the target level refers to that the grids are decomposed to a tenth level through a latitude projection plane in an airspace discrete grid model, and the height grids are decomposed to the tenth level; leaf nodes formed by longitude and latitude codes and height codes of the low-to-high levels are inserted into the nodes corresponding to the spatial domain grid representation multi-way tree to form the grid representation multi-way tree of the traditional geometric spatial domain, as shown in fig. 5.

Referring to fig. 6, step 3 includes:

the first step is as follows: performing time exclusion detection on a traditional geometric airspace generated by two civil aviation air plans, wherein if the time does not overlap, the two airspaces do not conflict;

the second step is that: performing spatial exclusion detection on a traditional geometric airspace generated by two civil aviation air plans, namely comparing longitude and latitude height boundaries of the two airspaces, wherein if one dimension of the three dimensions of the longitude and latitude height does not have an overlapping area, the two airspaces do not have a conflict area;

the third step: comparing two grid representation multi-branch trees of the traditional geometric airspace, firstly solving intersection of the longitude and latitude codes of the first level of the two airspaces, acquiring the longitude and latitude codes of the next level of the intersection grid of the first level in the grid representation multi-branch trees of the two airspaces, and continuously solving intersection until the highest level intersection longitude and latitude codes of leaf nodes of the multi-branch trees are acquired; and acquiring height codes corresponding to the highest level intersection longitude and latitude codes in the grid representation multi-branch tree, solving intersection of the height codes, and determining the grid codes jointly by the highest level intersection longitude and latitude codes and the highest level height codes to be the conflict grids of the two airspaces.

And thirdly, solving intersection of the first-level longitude and latitude codes of the two airspaces, acquiring the next-level longitude and latitude codes of the first-level intersection grid from the two airspace grid representation multi-branch trees, and continuously solving intersection until the highest-level intersection longitude and latitude codes of the leaf nodes of the multi-branch trees are acquired, wherein the representation levels of the leaf nodes of the multi-branch trees, namely the contrast depth of the multi-branch trees, can be flexibly selected according to requirements, and the higher the selected level is, the higher the precision is, so that the flexible conflict detection with different precisions is performed on the airspaces.

The present invention provides a method for spatial domain multi-level grid representation and collision detection based on a multi-way tree, and a plurality of methods and approaches for implementing the technical solution are provided, and the above description is only a specific embodiment of the present invention, and it should be noted that, for those skilled in the art, a plurality of improvements and modifications may be made without departing from the principle of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention. All the components not specified in the present embodiment can be realized by the prior art.