CN116069882A - Airspace grid diagram generating method - Google Patents

Abstract

The invention provides a airspace grid diagram generating method, which comprises the following steps: based on the geospatial three-dimensional subdivision grids and time codes, gridding modeling is carried out on the airspace environment of the target object to obtain a plurality of airspace grids, and a airspace grid map is obtained based on the airspace grids; correlating the acquired space-time data with the airspace grids in the airspace grid map to obtain airspace grids of the correlated space-time data; and constructing an airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain a four-dimensional airspace grid map. By generating a four-dimensional airspace grid map of all the whole domain elements, a multi-scale, high-timeliness, scientific, fine, fusion, intelligent and flexible low-altitude airspace management service system is formed, and free switching among two-dimensional, three-dimensional and four-dimensional airspace grid patterns is realized. Thereby achieving the purposes of scientific division, high-efficiency approval and fine utilization of low-altitude airspace resources.

Description

Airspace grid diagram generating method

Technical Field

The invention belongs to the field of geospatial information organization, remote sensing and mapping, and particularly relates to a space domain grid diagram generation method.

Background

Airspace is an important strategic resource of the country, has great economic, national defense and social values, plays an irreplaceable important role in national economic and social development, is a main area of general aviation activities, and reasonably uses low-altitude resources is an indispensable condition for development of general aviation economic industry.

The airspace map which is conventionally constructed based on longitude and latitude equal-point space-time frames and the earth surface map is a first generation airspace map.

The problems in the aspect of low-altitude airspace expression and management at present are as follows:

1) The airspace resource diagram is a plane, no three-dimensional subdivision exists, and the airspace resource utilization is not high.

2) The airspace resource diagram in the current flight service system is planar two-dimensional, and when a flight user applies for airspace resources, all the airspace resources of different high layers are occupied through longitude and latitude; however, in actual use, only a certain height layer is needed to meet the requirement, and most of the space domain resources of the height layer are wasted greatly.

3) The current airspace resource map cannot display the flight situations of different flight types in a stereoscopic way, such as the situation that civil aviation aircrafts, navigation piloted aircrafts, unmanned aircrafts and the like cannot be distinguished, and the space management cannot be stereoscopic and visual and is very inconvenient.

4) Each airspace type is not scientific and fine enough to flexibly release an idle airspace, and a large amount of high-quality airspace resources are idle and extremely wasted.

5) The low-altitude airspace not only relates to a control area, a monitoring area and a reporting area, but also subdivides an airspace which is strictly managed, such as a forbidden area, a restricted area, a dangerous area, a safe interval and the like. At present, no set of online system with relatively perfect functions replaces the traditional manual map operation, and an approver can only analyze and pre-judge data through an original tool; meanwhile, the related data are only stored in some databases, and cannot be comprehensively analyzed with airspace data information in the flight application, so that the flight approval efficiency is extremely low, and the service development requirement of the navigation flight cannot be met.

Disclosure of Invention

Aiming at the problems in the prior art, the invention provides a space domain grid diagram generation method, which at least partially solves the problem of low management efficiency in the prior art.

In a first aspect, an embodiment of the present disclosure provides a method for generating a spatial grid map, including:

based on the geospatial three-dimensional subdivision grids and time codes, gridding modeling is carried out on the airspace environment of the target object to obtain a plurality of airspace grids, and a airspace grid map is obtained based on the airspace grids;

correlating the acquired space-time data with the airspace grids in the airspace grid map to obtain airspace grids of the correlated space-time data;

and constructing an airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain a four-dimensional airspace grid map.

Optionally, based on the geospatial stereo subdivision grid and the time code, gridding modeling is performed on the airspace environment of the target object, including: gridding modeling is performed by using a airspace gridding diagram general calculation model,

the general calculation model of the airspace grid graph is as follows:

wherein s is a subdivision hierarchy; d is the spatial dimension; n is a trellis code; t is E T _s Is a time slice;

assigning a calculation function to the grid data; θ is a function parameter; a, a _n Ti is the ith data participating in operation in a grid with t time slice codes of n, i is more than or equal to 1 and less than or equal to m, and m is an integer; g ^s,d Is a specific grid; t (T) _s Is a time set; />

Calculating a function set for the grid graph; s is more than or equal to 0 and less than or equal to 31, d is more than or equal to {2 },3}。

Optionally, the meshing modeling is performed on the airspace environment of the target object based on the geospatial stereo subdivision grid and the time code to obtain a plurality of airspace grids, and the airspace grid map is obtained based on the airspace grids, which includes:

transforming the airspace grid map into an airspace management grid universal rule earth identification map, a training area grid map, a large area map and a space box earth grid map through combination and conversion, wherein the Beidou grid code earth grid map, a sea map or an empty map;

the deformation into a chart includes:

determining a grid level corresponding to the chart;

and (5) calculating to obtain the grid codes of the target points based on the determined grid level layer-by-layer descent.

Optionally, the deforming into the blank drawing includes:

identifying the map of the current blank map, wherein the first two identified characters represent the current map category;

determining a current map under the map sheet based on the origin coordinate representation, and identifying the current map by using azimuth, longitude values and dimension values;

the selected grid is represented based on the origin coordinates and the current map identification.

Optionally, the associating the obtained spatio-temporal data with the airspace grids in the airspace grid map to obtain airspace grids of the associated spatio-temporal data includes:

correlating the multi-source heterogeneous space-time data with a space grid through space grid coding to obtain a space grid of correlated space-time data; logic abstraction is carried out on the airspace grids related to the spatio-temporal data, and the airspace grid index related to the spatio-temporal data is established by using airspace grid coding.

Optionally, the associating the obtained space-time data with the space grid in the space grid map to obtain the space grid of the associated space-time data includes completing the application data gridding processing and the gridding data management based on the space-time grid data engine;

the space-time grid data engine is used for converging and coding various data, converting the space data and the airspace map into grid data and forming a 4D space-time database based on a unified grid space index table and a time index table.

Optionally, the space-time grid data engine comprises space grid database creation management, space grid data introduction and database logic integrated sharing;

the space grid database creation management is used for managing index data after space data encoding, and the space grid database creation management comprises space grid database creation, data sharing and regional node division; when the airspace database is created, the index database node and the target database type need to be selected; the data sharing pushes index data in an index library to a target data database, wherein in pushing, the data sharing comprises the steps of designating an index table and a data field, and pushing selected data; the space grid database creation management is also used for describing and expressing space-time information, and carrying out self-adaptive multilevel gridding description and data organization and storage according to data resolution and precision, wherein the space-time information comprises multi-element data, route data, multi-temporal vector data, radar field data, meteorological data, elevation data, point cloud data, oblique photography data and/or BIM data acquired by a sensor;

The indexing of the data comprises an object storage function, a data source management function and a data encoding task queue management function, wherein the object storage function is used for providing user data space management and user file management, and the files of the user are stored in the data storage space in the form of objects.

Optionally, the airspace relation calculation model includes:

a airspace grid geographic meaning judgment model, an airspace grid neighborhood position calculation model, an airspace grid distance calculation model and an airspace grid type judgment model;

the airspace grid geographic meaning judgment model is used for judging whether the airspace grid where the target object is located has actual geographic meaning or not;

the airspace grid neighborhood position calculation model is used for calculating neighborhood positions of airspace grids based on airspace grids and airspace grid codes;

the airspace grid distance calculation model is used for calculating the spatial distance of the target object based on airspace grids;

the airspace grid type judging model is used for judging the type of airspace grid where the target object is located.

Optionally, after the step of constructing the airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain the four-dimensional airspace grid map, the method comprises the following steps:

constructing application of a four-dimensional airspace grid map based on a space-time grid calculation engine;

The space-time grid computing engine comprises a gridding space-time slice computing model, a space grid computing general model and space grid computing grid map space-time display.

Optionally, the gridding space-time slice calculation model is a grid space-time knowledge graph constructed based on the grid space-time knowledge graph and the grid space-time knowledge spectrum; the grid space-time knowledge graph is used for assigning a value to each grid based on knowledge rules on the basis of dividing space-time objects; the grid space-time knowledge spectrum is used for constructing space-time or attribute relations between adjacent grid space-time knowledge graphs after discretizing a time axis;

the airspace grid computing general model comprises a GeoSOT2D grid coding algebraic library, a GeoSOT3D grid coding algebraic library, a GEOSOT4D computing model library and a grid knowledge map airspace planning model.

According to the airspace grid pattern generation method, the four-dimensional airspace grid map of the whole domain is generated, so that a multi-scale, high-timeliness, scientific, fine, fusion, intelligent and flexible low-altitude airspace management service system is formed, and free switching among two-dimensional, three-dimensional and four-dimensional airspace grid patterns is realized. Thereby achieving the purposes of scientific division, high-efficiency approval and fine utilization of low-altitude airspace resources.

Drawings

The foregoing and other objects, features and advantages of the disclosure will be apparent from the following more particular descriptions of exemplary embodiments of the disclosure as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the disclosure.

Fig. 1 is a flowchart of a method for generating a space domain mesh map disclosed in this embodiment;

FIG. 2 is a schematic diagram of H-gram trellis encoding disclosed in this embodiment;

FIG. 3 is a schematic view of a water area around a highway port according to the present disclosure;

FIG. 4 is a schematic diagram of a 1 "trellis code near a high bridge port as disclosed in this example;

FIG. 5 is a schematic diagram of an aerial map coding identifier disclosed in 1:200000 of the embodiment;

FIG. 6 is a schematic diagram of a large table of the disclosed coding index according to the present embodiment;

FIG. 7 is a schematic view of a calculation model of a meshed spatiotemporal slice disclosed in this embodiment;

FIG. 8 is a schematic diagram of a general model of airspace grid calculation disclosed in this embodiment;

FIG. 9 is a schematic diagram showing the space-time representation of the space-domain grid computing grid diagram disclosed in this embodiment;

fig. 10 is a schematic diagram of a grid knowledge graph airspace planning model disclosed in this embodiment;

fig. 11 is a schematic diagram of a visualization platform according to the present embodiment.

Detailed Description

Embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

It should be appreciated that the following specific embodiments of the disclosure are described in order to provide a better understanding of the present disclosure, and that other advantages and effects will be apparent to those skilled in the art from the present disclosure. It will be apparent that the described embodiments are merely some, but not all embodiments of the present disclosure. The disclosure may be embodied or practiced in other different specific embodiments, and details within the subject specification may be modified or changed from various points of view and applications without departing from the spirit of the disclosure. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict. All other embodiments, which can be made by one of ordinary skill in the art without inventive effort, based on the embodiments in this disclosure are intended to be within the scope of this disclosure.

It is noted that various aspects of the embodiments are described below within the scope of the following claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the present disclosure, one skilled in the art will appreciate that one aspect described herein may be implemented independently of any other aspect, and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. In addition, such apparatus may be implemented and/or such methods practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.

It should also be noted that the illustrations provided in the following embodiments merely illustrate the basic concepts of the disclosure by way of illustration, and only the components related to the disclosure are shown in the illustrations, rather than being drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complex.

In addition, in the following description, specific details are provided in order to provide a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.

The space grid of the embodiment is based on the standard systems such as GeoSOT earth subdivision coding theory, relevant earth grid standard national military standard, relevant space grid standard, space management grid general identification rule (trial version) and the like, and a space universe full-factor space grid diagram construction system supporting different application fields and different service requirements is built. The airspace grid diagram construction system comprises 1 airspace grid diagram and 3 support engines, namely an airspace grid diagram, a spatiotemporal grid data engine, a spatiotemporal grid calculation engine and a spatiotemporal grid expression engine, provides a unified standard global airspace grid identification and efficient calculation tool for enterprises and departments of airspace digital construction, and also provides standard technical support for the construction of a new spatial airspace grid management system. And the requirements of effective management of airspace meshing and space digital transformation and upgrading are met.

The airspace grid diagram has the integrated expression capability: and (3) organizing different types of data such as 'land, sea, air, space, electricity', underground water and the like into unified codes, constructing a unified two-dimensional, three-dimensional and four-dimensional grid diagram, and comprehensively displaying the grid diagram as shown in the following diagram. The underground and underwater integrated expression capability of 'land, sea, air, space and the like' is realized, and the global expression capability, the regional expression capability, the local capability and the expression capability of underground and underwater space are realized.

The airspace grid diagram has unified coding capability: the ability to aggregate multiple types of data graphs in GeoSOT coding can be provided, including but not limited to the following: vector map data, DEM data, DOM data, control point data, radar field data, meteorological data, ocean data, moving target track data, three-dimensional model data, infrastructure data and other empty information, and multi-element data, route data, multi-time phase vector data, elevation data, point cloud data, oblique photography data, BIM data and other empty information acquired by various sensors.

As shown in fig. 1, a method for generating a space domain mesh map includes:

based on the geospatial three-dimensional subdivision grids and time codes, gridding modeling is carried out on the airspace environment of the target object to obtain a plurality of airspace grids, and a airspace grid map is obtained based on the airspace grids;

Correlating the acquired space-time data with the airspace grids in the airspace grid map to obtain airspace grids of the correlated space-time data;

and constructing an airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain a four-dimensional airspace grid map.

In one example, an airspace grid model is constructed based on airspace environment data of the obtained target object pre-voyage to obtain airspace grids, the obtained spatio-temporal data is associated with the airspace grids to obtain airspace grids of associated spatio-temporal data, and a four-dimensional airspace grid map is obtained based on the airspace grids of associated spatio-temporal data.

The details are as follows:

based on the geospatial three-dimensional subdivision grid and time coding, gridding modeling is carried out on the airspace environment of the target object pre-navigation, and a plurality of airspace grids are obtained. The method comprises the steps of performing seamless and non-overlapping gridding division and coding identification on a target object pre-sailing airspace environment based on a GEOSOT grid coded 32-layer digital earth grid reference line system, and constructing airspace grid diagrams so as to display different levels at different earth view port heights. The spatial grid may be a two-dimensional planar grid or a three-dimensional volumetric grid.

Optionally, based on the geospatial stereo subdivision grid and the time code, gridding modeling is performed on the airspace environment of the target object, including: gridding modeling is performed by using a airspace gridding diagram general calculation model,

The general calculation model of the airspace grid graph is as follows:

wherein s is a subdivision hierarchy; d is the spatial dimension; n is a trellis code; t is E T _s Is a time slice;

assigning a calculation function to the grid data; θ is a function parameter; a, a _n Ti is the ith data participating in operation in a grid with t time slice codes of n, i is more than or equal to 1 and less than or equal to m, and m is an integer; g ^s,d Is a specific grid; t (T) _s Is a time set; />

Calculating a function set for the grid graph; s is more than or equal to 0 and less than or equal to 31, d is {2,3}.

Optionally, the meshing modeling is performed on the airspace environment of the target object based on the geospatial stereo subdivision grid and the time code to obtain a plurality of airspace grids, and the airspace grid map is obtained based on the airspace grids, which includes:

and transforming the airspace grid map into an airspace management grid universal rule earth identification map, a training area grid map, a large area map, a space box earth grid map, a Beidou grid code earth grid map, a sea map or an empty map through combination and conversion.

The H-graph in the embodiment is a chart, and the aerial K-graph in the embodiment is an empty graph.

The deformation is a blank graph, comprising:

identifying the map of the current blank map, wherein the first two identified characters represent the current map category;

determining a current map under the map sheet based on the origin coordinate representation, and identifying the current map by using azimuth, longitude values and dimension values;

The selected grid is represented based on the origin coordinates and the current map identification.

The airspace grid pattern can be deformed into an airspace management grid pattern with general identification rules (trial version), a training area grid pattern, a large area pattern, a space box earth grid pattern, a Beidou grid code earth grid pattern, a sea chart, an empty chart and the like through combination and conversion, and has good ductility.

Airspace grid diagram and chart conversion

(1) Standard basis: GB 12320-1998 Chinese navigation H picture compiling specification and GB 12319-1998 Chinese H picture drawing

(2) Coding base

The H-gram trellis code is ranked as follows:

the design grid is a longitude and latitude grid, and CGCS2000 ellipsoids are adopted as a geometric basis. The dividing origin of the grids is at the intersection point of the equatorial plane and the primary meridian plane, and the two-dimensional grids of the non-bipolar area (88 DEG south latitude to 88 DEG north latitude) of the earth surface are divided into ten stages, which are respectively: 10 total levels of 6 ° ×4 °, 1 ° ×1 °, 30'×30', 15'×15', 5'×5', 1'×1', 30 "×30", 15 "×15", 5 "×5", 1 "×1". The specific dividing method is as follows:

a) First-stage meshing: the first-stage grid is divided according to a 1:100 ten thousand pictures in GB/T13989-2012, and the unit size is 6 degrees multiplied by 4 degrees grid;

b) Second-level meshing: dividing the first-stage grid into 6 multiplied by 4 second-stage grids according to longitude and latitude equally dividing, wherein the second-stage grids correspond to 1 degree multiplied by 1 degree grids;

c) Third-level grid division: dividing the second-level grid into 2 multiplied by 2 third-level grids according to longitude and latitude equally dividing, wherein the third-level grids correspond to 30 'multiplied by 30' grids;

d) Fourth-level meshing: dividing the third-level grid into 2 multiplied by 3 fourth-level grids according to longitude and latitude equally dividing, wherein the fourth-level grids correspond to 15 'multiplied by 10' grids of a 1:5 map, so that the third-level grids can be matched with land topography conveniently;

e) Fifth-level meshing: dividing the fourth-level grid into 3 multiplied by 2 fifth-level grids according to longitude and latitude equally dividing, wherein the fifth-level grids correspond to 5 'multiplied by 5' grids;

f) Sixth-level meshing: dividing the fifth-level grid into 5 multiplied by 5 sixth-level grids according to longitude and latitude equally dividing, wherein the sixth-level grids correspond to 1 'multiplied by 1' grids;

g) Seventh level meshing: dividing the sixth-level grid into 2 multiplied by 2 seventh-level grids according to longitude and latitude equally dividing, wherein the seventh-level grids correspond to 30 multiplied by 30 grids;

h) Eighth level meshing: dividing the seventh-level grid into 2 multiplied by 2 eighth-level grids according to longitude and latitude equally dividing, wherein the eighth-level grids correspond to 15 multiplied by 15 grids;

i) Ninth level meshing: dividing the eighth-level grid into 3 multiplied by 3 ninth-level grids according to longitude and latitude equally dividing, wherein the grids correspond to 5 multiplied by 5;

J) Tenth-level meshing: dividing the ninth grid into 5×5 tenth grids according to longitude and latitude equally, and corresponding to 1×1 grid.

As shown in fig. 2, is the encoding of the H-picture trellis code. The two-dimensional grid position code coding rule consists of at most 20 code elements, is divided into eleven sections according to the sequence from left to right, and corresponds to the southern and northern hemispheres of the earth surface and the first-stage to tenth-stage grids respectively.

In an H-gram grid coding application, the maximum scale of the H-gram is 1:5 kilo, the minimum longitude and latitude differentiation grid is 1 '. Times.1', and the grid can be just aggregated upwards by using a tenth-stage grid.

(3) H-diagram grid

The paper H diagram is provided with warp and weft grids, and the frame grids of the diagram under different scales are divided differently. The statistics of this example are shown in tables 1 and 2:

table 1, H-plot scale and grid level

Table 2, H-plot scale and GeoSOT grid level

/>

(4) H-graph grid computing example

The deformation into a chart includes: determining a grid level corresponding to the chart; and (5) calculating to obtain the grid codes of the target points based on the determined grid level layer-by-layer descent.

1) Grid computing

The 1 "x 1" grid of the water area near the port of the bridge shown in FIG. 3 is (31 DEG 20'12 "N, 121 DEG 33' 12" E) and the corresponding grid code is N51H 024343338.

The calculation flow is as follows:

step 1. The size of the longitude and latitude grid on the H diagram shown in FIG. 3 is 30 '. Times.30', and the nearest H diagram grid level is level 7 (30 '. Times.30');

step2, finding the corner points (31 DEG 20'N,121 DEG 33' E) on the graph, showing the green range line on the graph, and calculating the grid code N51H 0243743 of the 7 th level H graph;

step3, step-by-Step descent calculation to obtain the grid code of the target point (31 DEG 20 '12' N,121 DEG 33 '12' E).

The text in fig. 3 is merely exemplary and does not affect the completeness and clarity of the solution.

2) Spoken language code

(a) Directly reporting longitude and latitude

The H diagram is provided with orthogonal vertical longitude and latitude networks, is suitable for directly measuring the longitude and latitude of any point by using a ruler, and can directly read the longitude and latitude by using the spoken language code, thereby being convenient for semantic recognition and conversion into GeoSOT codes.

(b) Reporting the figure number + corresponding level code

Because each H diagram has a diagram number, the scale of the H diagram is determined with the longitude and latitude grid directly drawn on the diagram, the information can be input into a computer in advance, and the diagram number is reported firstly and then the H diagram grid code of the corresponding level on the diagram is reported when the code is spoken.

In a certain bridge port, the figure number 44254 is shown in fig. 4, the size of the longitude and latitude grid is 30'×30', the scale is 1:5000, and only 1'×1' level and subsequent codes can be reported, such as 44254-243338. Wherein 243338 is a 1'×1' hierarchical code, a 30×30 "hierarchical code, a 15×15" hierarchical code, a 5×5 "hierarchical code, and a 1×1" hierarchical code, respectively.

The text in fig. 4 is merely exemplary and does not affect the completeness and clarity of the solution.

3) Distance measurement

According to GB/T4099-2005, the offshore distance generally refers to the major arc length between two points of a sphere, the short distance being replaced by the length of a constant line, which is expressed as a straight line segment in the H-plot.

The short distance is directly calculated by a ruler on the H diagram, and the long distance is required to calculate the length of the large arc according to the longitude and latitude of the starting point.

Airspace grid diagram and Liu Tu conversion

Take Beijing somewhere in the 1:5 ten-thousand topography 39℃54'30 "North latitude, 116℃28' 25". 1:5 global topography select 15 layer 1'×1' GeoSOT grid aggregation, denoted "G15"; the map where the place is located in the northeast hemisphere, and the longitude and latitude coordinates of the southwest corner locating corner point are as follows: north latitude 39 degree 50', east longitude 116 degree 15', corresponding 1:5 ten thousand picture numbers are "J-50-5-B"; the aggregate grid where the land is located in column 14 and row 5, corresponding to row number "014-005" in the map sheet. The designed GeoSOT consistency grid aggregation model is encoded as G15-J-50-5-B-014-005.

The deformation is a blank graph, comprising:

identifying the map of the current blank map, wherein the first two identified characters represent the current map category;

determining a current map under the map sheet based on the origin coordinate representation, and identifying the current map by using azimuth, longitude values and dimension values;

The selected grid is represented based on the origin coordinates and the current map identification.

(1) GARS partitioning principle

The Global Area Reference System (GARS) is a standardized geospatial reference system developed by the national geospatial information agency (NGA) for use by the united states department of defense. GARS, which is the "regional centered" counterpart of "MGRS" of "point centered", uses WGS 1984 reference ellipsoids as a coordinate system, split based on longitude and latitude. It aims to provide a comprehensive universal reference frame for the situational awareness of the joint forces to facilitate air-to-ground coordination, conflict elimination, integration and synchronization.

GARS divides the earth's surface into units of 30 minutes by 30 minutes, each minute corresponding to an actual length of about two kilometers. Each cell is identified by a name of five characters. (e.g. 006 AG)

The first three characters represent a 30 minute wide longitudinal band. From the 180 degree meridian to the east, band numbers 001 to 720, so 180E to 17930' w is the 001 band; 17930'w to 17900' w is band 002; etc.

The fourth and fifth characters designate a 30 minute wide latitude band. Starting from south pole and going north, the letters of the band range from AA to QZ (I and O omitted), so 9000's to 8930's are band AA;8930's to 8900's are AB bands; etc.

Each 30-minute cell is divided into four quadrants of 15 minutes by 15 minutes. Quadrants are numbered sequentially, starting from the north-most end, from west to east. Specifically, the northwest quadrant is "1"; the northeast quadrant is "2"; the southwest quadrant is "3"; the southeast quadrant is "4". Each quadrant is identified by the name of six characters. (e.g., 006AG 3) the first five characters make up a 30-point cell name. The sixth character is a quadrant number.

Each 15-minute quadrant is divided into 9 5-minute by 5-minute regions. The regions are numbered sequentially starting from the north most end, from west to east. The graphical representation of the 15 quadrants with the 5-by-5 zone numbers is similar to a telephone keypad.

Each 5 point by 5 point region or keyboard "key" is identified by the name of seven characters. The first six characters constitute a quadrant name of 15 minutes. The seventh character is the keyboard "key" number. (e.g., 006AG 39) Chinese avigraph overall conversion specification, as shown in Table 3.

TABLE 3 navigation K map scale, map frame and airspace grid level

(3) Identification conversion method

With reference to the area marking method of the GARS, a marking frame with a point as a center is selected, and a map under a current drawing is marked first, and then a target grid is marked. The lower left corner of the map is taken as the origin of coordinates, namely the minimum longitude and latitude point, as shown in fig. 5, and the 1:200000 aeronautical map is taken as an example for identification and description.

(a) The map of the current drawing is identified, and first two characters represent the current drawing category, and the drawing in 1:200000 in this example represents the fourth type of common aviation map common scale, so roman numeral IV in the first two characters represents.

(b) The current map under the determined map is represented by the origin coordinates in the lower left corner, and is therefore identified by the means "azimuth + longitude value-latitude value", in this example denoted "EN75-30".

(c) Finally, a specific grid of interest is represented, taking a 1:200000 aeronautical map in the example as an example, the area range of 1 degree×40' represented by each map is divided into 5' ×5' units according to an airspace grid standard, and each unit corresponds to an actual length of about ten kilometers. Each cell is shown in increasing order from bottom to top, from left to right by english letters, with the eighth cell in the longitudinal direction and the fifth cell in the latitudinal direction in the figure, and is therefore shown as HE.

Space grid diagram and gas image diagram conversion:

the figure number inherits the rule of the country basic scale topographic map framing and numbering. The weather map with the scale of 1:25 ten thousand has the latitude and longitude range of 109.5-111 DEG E and the latitude range of 31-32 DEG N, and is coded as H49C 001002 according to the basic scale framing and numbering rule.

(1) Standard basis: GB/T33695-2017 ground meteorological element coding and data format, QX/T158-2012 meteorological satellite data classification, MH/T4016.8-2008 civil aviation meteorological 8 th part, weather map filling and analysis

(2) Gas picture grid

The range and the scale of the weather map base map used by the weather station in China at present are as follows:

northern hemisphere pneumogram scale 1:30,000,000

Sub-euler meteorological graph scale 1:20,000,000

Asian aerogram scale 1:20,000,000

East asia meteorological chart scale 1:10,000,000

Chinese area weather map scale 1:5,000,000 or more (china or a province, city and its surroundings).

The size of the weather map scale is mainly determined according to weather analysis content, forecast aging, seasons, regions and the like. The Fengyun No. three D star is a new generation of high-resolution meteorological satellite in China, and has the spatial resolution of 250 meters and 1000 meters. Unlike topographical maps, the scale of the aerial map is typically smaller. The basic grid levels from which the conversion with the weather map was constructed are shown in table 4.

TABLE 4 weather map scale and airspace grid level

(3) Coding reporting bit

And marking the map under the current picture by adopting the coding form of 'picture number + grid level + positioning code', and then marking the target grid. The origin of coordinates is selected closest to the corner point of the intersection of the primary meridian with the equator, as shown in fig. 6:

The figure number inherits the rule of the country basic scale topographic map framing and numbering. The weather map with the scale of 1:25 ten thousand has the latitude and longitude range of 109.5-111 DEG E and the latitude range of 31-32 DEG N, and is coded as H49C 001002 according to the basic scale framing and numbering rule.

The target grid of interest is represented by taking a 1:25 weather map as an example in the example, and a region range of 1 degree 30' ×1 degree represented by each map is divided into 5' ×5' units according to a airspace grid standard, and each unit corresponds to an actual length of about ten kilometers. According to the increasing direction of longitude and latitude, the warp direction is indicated by numerals and the weft direction is indicated by letters, the 13 th lattice of the target in the longitude direction and the 4 th lattice in the latitude direction are coded as 13D. The final encoding of the target is: "H49C 001002-A5-13D" has a coordinate of about 120℃32.5 'E31℃17.5'. In practical use, under the same drawing, the "level code+location code", i.e., "A5-13D" in this example, is mainly memorized, as shown in FIG. 7.

A simple numerical report of its own location may be used, such as "i am in 13D grid, advancing to 06J grid". The azimuth and distance between two grids can be obtained by simple addition, subtraction, multiplication and division operation of grid coding. Assuming that the target is at a 1:25 ten thousand frame coded as H49C 001002, then only the 13D grid itself within that frame need be reported (5', about 10 km). The grid calculation table shows that the size of the latitude positioning level grid is 10km, and the distance between the 13D grid and the 06J grid in the approximate calculation graph is northbound (J-D) x 10 km=60 km, eastern (06-13) x 10 km= -70km, namely northbound 60km and westbound 70km.

Optionally, the associating the obtained spatio-temporal data with the airspace grids in the airspace grid map to obtain airspace grids of the associated spatio-temporal data includes:

correlating the multi-source heterogeneous space-time data with a space grid through space grid coding to obtain a space grid of correlated space-time data; logic abstraction is carried out on the airspace grids related to the spatio-temporal data, and the airspace grid index related to the spatio-temporal data is established by using airspace grid coding.

Optionally, the associating the obtained space-time data with the space grid in the space grid map to obtain the space grid of the associated space-time data includes completing the application data gridding processing and the gridding data management based on the space-time grid data engine;

and correlating the acquired space-time data with the airspace grids in the airspace grid map to obtain airspace grids of the correlated space-time data. Namely, multi-source heterogeneous space-time data is associated with a space grid through space grid coding, so that a space grid of the associated space-time data is obtained; logic abstraction is carried out on the airspace grids related to the spatio-temporal data, and the airspace grid index related to the spatio-temporal data is established by using airspace grid coding.

The space-time grid data engine is used for converging and coding various data, converting the space data and the airspace map into grid data and forming a 4D space-time database based on a unified grid space index table and a time index table.

Optionally, the space-time grid data engine comprises space grid database creation management, space grid data introduction and database logic integrated sharing;

the space grid database creation management is used for managing index data after space data encoding, and the space grid database creation management comprises space grid database creation, data sharing and regional node division; when the airspace database is created, the index database node and the target database type need to be selected; the data sharing pushes index data in an index library to a target data database, wherein in pushing, the data sharing comprises the steps of designating an index table and a data field, and pushing selected data; the space grid database creation management is also used for describing and expressing space-time information, and carrying out self-adaptive multilevel gridding description and data organization and storage according to data resolution and precision, wherein the space-time information comprises multi-element data, route data, multi-temporal vector data, radar field data, meteorological data, elevation data, point cloud data, oblique photography data and/or BIM data acquired by a sensor;

the indexing of the data comprises an object storage function, a data source management function and a data encoding task queue management function, wherein the object storage function is used for providing user data space management and user file management, and the files of the user are stored in the data storage space in the form of objects.

The space-time grid data engine is responsible for completing the application data gridding processing and the data management after gridding. The core is to aggregate and code various existing data, support the data access of a GIS system (arcinfo, mapinfo, INTERGRAPH, supermapper) and support the data interchange. And converting the traditional BIM and other space data, various airspace maps into grid data. And the unified grid space index table and the time index table form a 4D space-time database. The data engine mainly comprises the functions of data connection, airspace database management and grid data service.

1) Airspace grid database creation management

The airspace database storage creation function mainly aims at indexing data after spatial data encoding of a user, and the management of the airspace database comprises the functions of airspace database creation, data sharing, regional node division and the like. When the airspace database is created, a user needs to select an index database node (index area), target database types, and an index database is created after general information is perfected. The data sharing can push the index data in the index database to the target data database, and can assign the index table and the data field to push specific data. The large table of coding indexes is shown in fig. 8. Row definition in fig. 8: ordering by taking the patch index code as a row main key; attribute clusters: the system consists of a plurality of similar attribute columns, and generally takes an attribute cluster as a unit and an access table; attribute column: the number of attribute columns in one attribute cluster is not limited.

The method comprises the steps of describing and expressing space information such as multi-element data, route data, multi-time phase vector data, radar field data, meteorological data, elevation data, point cloud data, oblique photography data, BIM data and the like acquired by various sensors, and carrying out self-adaptive multi-level gridding description and data organization and storage according to data resolution and precision.

In the aspect of data storage organization, a geographic information data management mode based on the technologies of a distributed file system, an elastic search and the like is supported, and a unified space reference is provided for space management, space planning and space-time calculation expression by taking the national standard of Beidou grid position code as a space grid segmentation and coding principle.

2) Airspace grid data leading-in

The airspace grid data leading-in tool function comprises an object storage function, a data source management function and a data coding task queue management function. Object store management functions, object stores provide user data space management, user file management functions. The files of the user are stored in the data storage space in the form of objects, and the user can upload the files to the storage space of different nodes. The file storage space of the user is logically independent. For files and storage spaces, users have the authority of adding, deleting and checking.

3) Logical integration sharing of various databases

The logical integrated sharing function of various databases is coding and warehousing in different data sources, and is management of original sources of data such as data files, non-spatial databases, spatial databases and the like. The data source logic integration supports multiple types: non-spatial databases (Oracle, mysql), spatial databases (Oracle spatial, postGis, supermap-Mysql, supermap-Oracle, supermap-postgresql), cloud files, local files.

4) Airspace data grid memory

The airspace data grid memory is based on the idea that the data storage in hardware can be pluggable, and the airspace data hardware storage unit is customized and developed. The hardware system is matched with a processing mechanism of GEOSOT grid coding to finish seamless and non-overlapping hardware copy expansion of the space data. And the space TB level GIS data migration and copying are completed rapidly. The memory types include data migration memory and grid computing memory.

Optionally, the airspace relation calculation model includes:

a airspace grid geographic meaning judgment model, an airspace grid neighborhood position calculation model, an airspace grid distance calculation model and an airspace grid type judgment model;

the airspace grid geographic meaning judgment model is used for judging whether the airspace grid where the target object is located has actual geographic meaning or not;

The airspace grid neighborhood position calculation model is used for calculating neighborhood positions of airspace grids based on airspace grids and airspace grid codes;

the airspace grid distance calculation model is used for calculating the spatial distance of the target object based on airspace grids;

the airspace grid type judging model is used for judging the type of airspace grid where the target object is located.

And constructing an airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain a four-dimensional airspace grid map. The airspace relation calculation model comprises: the airspace grid geographic meaning judgment model is used for judging whether the airspace grid where the target object is located has actual geographic meaning or not; a spatial grid neighborhood position calculation model for calculating the neighborhood position of the spatial grid based on the spatial grid and spatial grid coding; a airspace grid distance calculation model for calculating the spatial distance of the target object based on airspace grids; the airspace grid type judging model is used for judging the type of airspace grids where the target object is located, and the grid type comprises: temporary flight areas, no-fly areas, restricted areas, dangerous areas, clear areas, warning areas, countermeasures areas, flight report areas, civil airports, peer airports, military airports, and military and civil airports.

The space-time grid computing engine is responsible for completing user development application based on space-time grid finite element computation. The constructed four-dimensional airspace grid map supports the three-dimensional no-fly zone and route establishment, automatic flight path planning, collision risk detection, early warning and other space calculation.

Optionally, after the step of constructing the airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain the four-dimensional airspace grid map, the method comprises the following steps:

constructing application of a four-dimensional airspace grid map based on a space-time grid calculation engine;

the space-time grid computing engine comprises a gridding space-time slice computing model, a space grid computing general model and space grid computing grid map space-time display.

Optionally, the gridding space-time slice calculation model is a grid space-time knowledge graph constructed based on the grid space-time knowledge graph and the grid space-time knowledge spectrum; as shown in fig. 9, the grid space-time knowledge graph is used for assigning a value to each grid based on a knowledge rule on the basis of dividing space-time objects; the grid space-time knowledge spectrum is used for constructing space-time or attribute relations between adjacent grid space-time knowledge graphs after discretizing a time axis;

the airspace grid computing general model comprises a GeoSOT2D grid coding algebraic library, a GeoSOT3D grid coding algebraic library, a GEOSOT4D computing model library and a grid knowledge map airspace planning model.

1) Gridding space-time slice calculation model:

the gridding space-time slice calculation model is a generating tool of a gridding space-time calculation method, and the gridding space-time slice calculation model is a grid space-time knowledge graph. As shown in fig. 6.

2) Calculating a general model of the airspace grid:

the general model tool for airspace grid calculation is a general element calculation tool which uses a GeoSOT grid to realize the split of a full-length and full-length quadtree through three times of earth expansion, and forms a grid of a complete multi-scale quadtree grid of up to earth (0 level) and down to centimeter level surface elements (32 level). The tool comprises a GeoSOT2D grid coding algebra library, a GeoSOT3D grid coding algebra library GEOSOT4D calculation model library and a grid knowledge map airspace planning model. As shown in fig. 10.

3) Space-domain grid computing grid diagram space-time display:

the grid map space-time presentation tool mainly provides a visual platform for data analysis and data overview processed in a space grid computing system. The platform can realize scientific window display and entity data simulation display. As shown in fig. 11, the text in fig. 11 is merely exemplary text and does not affect the completeness and clarity of the solution.

4) Airspace grid computing super-computing system

The airspace grid computing super computing system is a high-performance acceleration framework, and the system is a spatial data computing system which is formed by combining a General-purpose computing task which is originally processed by a central processing unit and a GEOSOT General-purpose meta-computing algorithm base by utilizing an image processor for processing graphics tasks through using a graphics processor (General-purpose computing on graphics processing units, GPGPU for short). With the system, the operation efficiency of grid computing can be improved by 1000 times.

The spatial grid computing super computing system is provided with 7512 stream processors by taking an example of an eosin domestic server (selling price is 13 ten thousand) and a common server 128 thread (selling price is 8 ten thousand), and can simultaneously implement 7512 computing units to perform grid element computing. Assume that a hemisphere defining a space of longitude 0 to 180 latitude [ -9090] is a calculation unit, and that the grid 1' section geoot 15 level is precision. The total number of grids of 180×180×60= 116640000 is calculated, the number of the grids is 200, and the number of the height coding spaces is 23328000000.

The space-time grid expression engine is responsible for completing the space-time grid based visualization component application.

1) Airspace grid display SIM modeling

The airspace grid display SIM modeling tool is a grid modeling at the urban level. The three-dimensional grid codes are used for building grid worlds of urban buildings, floors, forests, towers and antennas, and the tool can be used for completing the construction of airspace environments of underlying target objects, grid management of high-rise buildings and the like.

2) Airspace grid data duty large screen

The space grid on-duty system uses the space-time characteristics of grids to complete the completion degree monitoring of a space plan, the space conflict monitoring, the route and space conflict monitoring, the task information customization and allocation, and provides data and calculation support for the business activities of space operators.

3) Airspace grid situation display large screen

By utilizing a space-time subdivision grid coding technology, the transformation of situation targets and environment data is performed, coding rules of various data such as entities, scenes, activities, capabilities, countermeasure states, natural environments and the like are provided, integrated grid organization of the data and the entities is realized, the calculation of MB capability range and threat intensity is performed, the timeliness and the accuracy of deduction are ensured, a performance evaluation report is generated according to statistical data, and the report is presented in the form of a chart and the like, so that data support is provided for first-long command decisions.

System application extension: space-time planning in airspace management and control, airspace coordination and situation monitoring.

And the system provides calculation analysis functions such as flight path automatic planning, collision risk detection, early warning and the like, which take grid data and grid space calculation as supports, for a user to realize grid data visualization, grid data superposition analysis, grid vision analysis, grid buffer area analysis, entity data query and the like.

The airspace grid image generating method of the embodiment has the following advantages:

1) By generating a new generation airspace map of all the whole domain elements, a multi-scale (hierarchical), high-aging, scientific, fine, fusion, intelligent and flexible low-altitude airspace management service system is formed, and scientific division, high-efficiency approval and fine utilization of low-altitude airspace resources are realized. The free switching among the two-dimensional, three-dimensional and four-dimensional airspace grid patterns is realized.

2) The traditional floating point calculation is changed into integer calculation, the calculation complexity is reduced, and the calculation efficiency is improved by several times to tens of times. And an open unified space-time big data organization framework is used for organizing and managing the whole domain space data and carrying out unified modeling on all the whole elements of the navigation flight domain. The method can be used for efficiently organizing and managing large-scale navigation aircrafts or airspace data and realizing multidimensional visual display (monitoring).

3) Various airspace grid patterns can be expanded and extended through combination and conversion.

The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the disclosure to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.

Claims (10)

1. A method for generating a spatial grid map, comprising:

based on the geospatial three-dimensional subdivision grids and time codes, gridding modeling is carried out on the airspace environment of the target object to obtain a plurality of airspace grids, and a airspace grid map is obtained based on the airspace grids;

correlating the acquired space-time data with the airspace grids in the airspace grid map to obtain airspace grids of the correlated space-time data;

and constructing an airspace relation calculation model based on the airspace grids of the associated spatio-temporal data to obtain a four-dimensional airspace grid map.

2. The airspace meshing map generation method according to claim 1, wherein meshing modeling the airspace environment of the target object based on the geospatial stereoscopic split mesh and the time code, comprises: gridding modeling is carried out by using a general calculation model of the airspace gridding diagram;

The general calculation model of the airspace grid graph is as follows:

wherein s is a subdivision hierarchy; d is the spatial dimension; n is a trellis code; t is E T _s Is a time slice;

assigning a calculation function to the grid data; θ is a function parameter; a, a _n Ti is the ith data participating in operation in a grid with t time slice codes of n, i is more than or equal to 1 and less than or equal to m, and m is an integer; g ^s,d Is a specific grid; t (T) _s Is a time set; />

Calculating a function set for the grid graph;

0≤s≤31，d∈{2,3}。

3. the method for generating a space grid map according to claim 1, wherein the meshing modeling is performed on a space environment of a target object based on the geospatial stereoscopic meshing and the time encoding to obtain a plurality of space grids, and the space grid map is obtained based on the space grids, comprising:

transforming the airspace grid map into an airspace management grid universal rule earth identification map, a training area grid map, a large area map and a space box earth grid map through combination and conversion, wherein the Beidou grid code earth grid map, a sea map or an empty map;

the deformation into a chart includes:

determining a grid level corresponding to the chart;

and (5) calculating to obtain the grid codes of the target points based on the determined grid level layer-by-layer descent.

4. A space grid pattern generation method according to claim 3, wherein the deforming into a blank pattern comprises:

Identifying the map of the current blank map, wherein the first two identified characters represent the current map category;

determining a current map under the map sheet based on the origin coordinate representation, and identifying the current map by using azimuth, longitude values and dimension values;

the selected grid is represented based on the origin coordinates and the current map identification.

5. The method for generating a space grid map according to claim 1, wherein associating the acquired space-time data with a space grid in a space grid map to obtain a space grid of associated space-time data comprises:

correlating the multi-source heterogeneous space-time data with a space grid through space grid coding to obtain a space grid of correlated space-time data; logic abstraction is carried out on the airspace grids related to the spatio-temporal data, and the airspace grid index related to the spatio-temporal data is established by using airspace grid coding.

6. The method for generating a space grid map according to claim 5, wherein the associating the acquired space-time data with the space grid in the space grid map to obtain the space grid of the associated space-time data includes completing the application data gridding processing and the gridding-after-data management based on the space-time grid data engine;

The space-time grid data engine is used for converging and coding various data, converting the space data and the airspace map into grid data and forming a 4D space-time database based on a unified grid space index table and a time index table.

7. The method of generating a spatial grid map according to claim 6, wherein the space-time grid data engine comprises spatial grid database creation management, spatial grid data referencing and database logic integration sharing;

the space grid database creation management is used for managing index data after space data encoding, and the space grid database creation management comprises space grid database creation, data sharing and regional node division; when the airspace database is created, the index database node and the target database type need to be selected; the data sharing pushes index data in an index library to a target data database, wherein in pushing, the data sharing comprises the steps of designating an index table and a data field, and pushing selected data; the space grid database creation management is also used for describing and expressing space-time information, and carrying out self-adaptive multilevel gridding description and data organization and storage according to data resolution and precision, wherein the space-time information comprises multi-element data, route data, multi-temporal vector data, radar field data, meteorological data, elevation data, point cloud data, oblique photographic data and/or BIM data acquired by a sensor;

The indexing of the data comprises an object storage function, a data source management function and a data encoding task queue management function, wherein the object storage function is used for providing user data space management and user file management, and the files of the user are stored in the data storage space in the form of objects.

8. The airspace meshing map generation method according to claim 1, wherein the airspace relation calculation model includes:

a airspace grid geographic meaning judgment model, an airspace grid neighborhood position calculation model, an airspace grid distance calculation model and an airspace grid type judgment model;

the airspace grid geographic meaning judgment model is used for judging whether the airspace grid where the target object is located has actual geographic meaning or not;

the airspace grid neighborhood position calculation model is used for calculating neighborhood positions of airspace grids based on airspace grids and airspace grid codes;

the airspace grid distance calculation model is used for calculating the spatial distance of the target object based on airspace grids;

the airspace grid type judging model is used for judging the type of airspace grid where the target object is located.

9. The method of generating a space grid map according to claim 1, wherein after the step of constructing a space relation calculation model based on the space grid of the associated space-time data to obtain the four-dimensional space grid map, comprising:

Constructing application of a four-dimensional airspace grid map based on a space-time grid calculation engine;

the space-time grid computing engine comprises a gridding space-time slice computing model, a space grid computing general model and space grid computing grid map space-time display.

10. The airspace meshing method according to claim 9, wherein the meshing spatiotemporal slice calculation model is a meshing spatiotemporal knowledge graph constructed based on a meshing spatiotemporal knowledge graph and a meshing spatiotemporal knowledge spectrum; the grid space-time knowledge graph is used for assigning a value to each grid based on knowledge rules on the basis of dividing space-time objects; the grid space-time knowledge spectrum is used for constructing space-time or attribute relations between adjacent grid space-time knowledge graphs after discretizing a time axis;

the airspace grid computing general model comprises a GeoSOT2D grid coding algebraic library, a GeoSOT3D grid coding algebraic library, a GEOSOT4D computing model library and a grid knowledge map airspace planning model.

Images