CN106291756B - The construction method of near space air virtual environment resource - Google Patents
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Abstract
The construction method of near space air virtual environment resource is related to a kind of construction method of air virtual environment resource.The problem of present invention is in order to fill up the air virtual environment resource vacancy of near space in domestic dummy experiment system.The present invention obtains the historical data of near space Atmosphere environment resource, and abnormal data is handled；Then the altitude information that each event obtains is normalized；Then coordinate is converted and obtains the spatial dimension of each event；The two-dimensional array of each height layer is built for each resource data and carries out two-dimentional smoothing processing；The three-dimensional array of each resource data is finally built, obtains the cube grid of the three-dimensional array of temperature, density and pressure, finally carries out Data Format Transform, completes the structure for meeting the near space air virtual environment resource of SEDRIS specifications.The structure field of present invention near space Atmosphere environment resource suitable for virtual test.
Description
Technical Field
The invention relates to a construction method of atmospheric virtual environment resources.
Background
The virtual natural environment resource is used as an important component for supporting the virtual test, and the integrity and credibility of the virtual test directly influence the fidelity of the virtual test. The atmospheric environment is used as an important component of a comprehensive natural environment, and the construction of an atmospheric virtual environment resource in an adjacent space has important significance for the improvement of a virtual test system.
The adjacent space is an airspace 20-100 kilometers away from the ground and comprises a stratosphere, an intermediate layer and a low-heat layer. The generation and the perfection of atmospheric environmental resources are very important as important components of comprehensive natural environment data and the basis of the development of a comprehensive natural environment database. At present, the development and utilization of the adjacent space are still in the early stage, the influence factors and the influence degree of the flight of the aircraft in the space are not clear, and if the physical aircraft is directly used for testing in the atmospheric space, many unknown results can be generated, and even immeasurable loss can be brought. Since 'twelve five', the atmospheric virtual environment resources below 20km in China are gradually improved, and the construction method of the atmospheric virtual environment resources in the adjacent space is only in a starting stage.
Disclosure of Invention
The invention aims to solve the problem of resource vacancy of the atmospheric virtual environment of the adjacent space in the domestic virtual test system.
The construction method of the near space atmosphere virtual environment resource comprises the following steps:
step 1, acquiring historical data of atmospheric environment resources in an adjacent space, wherein the historical data comprises longitude data, latitude data, altitude data and corresponding temperature data;
step 2, processing abnormal data in the longitude, latitude, altitude and temperature data;
step 3, normalizing the height data acquired by each event: for the height corresponding to each event, rounding the height data in each event; then, layering is carried out at intervals of k kilometers, the same height value is regarded as the height layer of the same layer, and if a plurality of temperature data exist in one height layer, the average value of the plurality of temperature data is taken as the temperature value of the height layer in the final event;
step 4, coordinate conversion: converting the longitude and latitude coordinates into rectangular coordinates;
step 5, obtaining the spatial range of each event: taking the minimum value of the starting point and the maximum value of the ending point of the latitude in each event after coordinate conversion, and drawing the area range of a single event and the area range represented by all events of each height layer, thereby facilitating the subsequent analysis and data processing;
step 6, constructing a two-dimensional array of each height layer: taking longitude and latitude as dimensions, normalizing the dimensions into k' kilometer intervals, and constructing a temperature two-dimensional array of each height layer; the area range represented by each event has an overlapping part, when a two-dimensional array is constructed, the temperature value of the overlapping part is used as the temperature value of the area by solving the mean value of the two event temperatures, and if the two event temperatures are not overlapped, the temperature value is stored into the original temperature value;
and 7, two-dimensional smoothing: 2D smoothing is carried out on each two-dimensional array;
step 8, constructing a three-dimensional array of the temperature in this month of the year: starting from 20km and ending at 100km, writing the smoothed two-dimensional temperature array layer by layer aiming at an altitude layer with kappa kilometers as incremental intervals, and finally obtaining a three-dimensional array with longitude, latitude and altitude as dimensions;
step 9, constructing temperature data of the same period in a plurality of years according to the steps 1 to 8, averaging the temperature data, and establishing a reliable cubic grid of a three-dimensional array as a temperature data resource of an adjacent space of the month in a virtual test;
step 10, performing the same processing on the density and the pressure according to the steps 1 to 9 to obtain a cubic grid of a three-dimensional array of the density and the pressure;
step 11, writing the constructed data including temperature, density and pressure into a text file T;
step 12D, reading the atmospheric Environment Data from the text file T written with the Data, representing the Data according to three specifications of DRM (Data Representation Model), SRM (Spatial Reference Model) and EDCS (environmental Data coding Specification) of the drive (Synthetic Environment Data Representation and exchange Specification), and storing the atmospheric Environment Data in the drive standard format.
Preferably, the method for constructing the virtual environment resource in the atmosphere of the adjacent space further comprises a construction process of an atmospheric horizontal wind field, and the specific process is as follows:
step 12A, determining a corresponding atmospheric horizontal wind field calculation formula according to the latitude range:
firstly, calculating the wind-turning according to the formula (1) in a latitude range of 15-80 degrees:
wherein, P is air pressure, and rho is atmospheric density;referred to as the turn parameter, omega is the turn angular velocity,is the geographic latitude; x is the eastward distance and y is the northward distance; u. ofg、vgWind is respectively blown in the horizontal latitudinal direction and the longitudinal direction within the range of 15-80 degrees;
and then calculating gradient wind according to the formula (2):
wherein,a is the earth radius; u. ofgr、vgrRespectively horizontal latitudinal direction gradient wind and longitudinal direction gradient wind;
(II) calculating gradient wind according to a formula (3) within a latitude range of 15 degrees S-15 degrees N:
wherein u ise、veThe wind is respectively gradient wind in the horizontal latitudinal direction and the longitudinal direction at an angle of 15 degrees S-15 degrees N;
step 12B, constructing a uniform cubic grid of a three-dimensional array of the atmospheric horizontal wind field: substituting the previously constructed density and pressure three-dimensional array of the area range into a wind field calculation formula to obtain a uniform cubic grid of the three-dimensional array of the wind-turning and gradient wind at the corresponding position, thereby generating atmospheric horizontal wind field resources of the space adjacent to the area;
and 12C, writing the constructed wind field data into the text file T.
Preferably, the specific process of processing abnormal data in the longitude, latitude, altitude and temperature data in step 2 is as follows:
and acquiring the original average resolution of the data aiming at longitude, latitude, altitude and temperature data in each event, then eliminating abnormal data, taking the previous data of the abnormal data as a basis, and adding recursion data which is obtained by recursion by utilizing the resolution on the basis and has the same quantity with the eliminated abnormal data.
Preferably, the specific process of the coordinate transformation in step 4 is as follows:
the grid of the finally established coordinate system is in distance units, so the longitude and latitude data acquired in each event are converted into distance data in rectangular coordinates according to the coordinate projection system in Matlab2014a, and are rounded up nearby.
Preferably, said κ is equal to said κ'.
Preferably, κ ═ κ' ═ 1.
Preferably, the specific process of acquiring the historical data of the atmospheric environment resources in the adjacent space in step 1 is as follows:
selecting an NC file of the atmospheric environment data of the adjacent space corresponding to the specific spatial range and the time range of the SABER; and reading the NC file, and acquiring historical data of the atmospheric environment resources in the adjacent space.
Has the advantages that:
(1) the empirical atmosphere mode adopted by the invention can enable the construction result of the atmospheric environment resource to be more accurate along with the improvement of the accuracy of the detection data without considering the complexity of the atmosphere in the adjacent space, the selection of a parameterization scheme of a plurality of processes and the like.
(2) The construction of the atmospheric environment resource in the near space is carried out based on the satellite detection data, the data source is real and reliable, and the constructed result has higher reliability.
(3) The method for constructing the resources of the atmospheric environment of the near space has universal applicability, the resource construction process is basically unchanged for any region with any size around the world, and the requirements on the atmospheric environment of the near space in a virtual test can be met under most conditions.
Drawings
FIG. 1 is a schematic illustration of a region of an event;
FIG. 2 is a schematic diagram of the area coverage of 10 events at a certain height level;
FIG. 3 is a graph of a temperature profile after an event has been processed;
FIG. 4 is a schematic illustration of a temperature distribution after smoothing the events represented in FIG. 3;
FIG. 5 is a schematic flow chart of the first embodiment;
fig. 6 is a schematic flow chart of the second embodiment.
Detailed Description
The first embodiment is as follows: this embodiment is described with reference to fig. 5;
the construction method of the near space atmosphere virtual environment resource comprises the following steps:
step 1, acquiring historical data of atmospheric environment resources in an adjacent space, wherein the historical data comprises longitude data, latitude data, altitude data and corresponding temperature data;
step 2, processing abnormal data in the longitude, latitude, altitude and temperature data; thereby obtaining a two-dimensional matrix of the abnormal-free data, and facilitating the subsequent data processing operations such as normalization, averaging and the like;
step 3, normalizing the height data acquired by each event: for the height corresponding to each event, rounding the height data in each event; then, layering is carried out at intervals of k kilometers, the same height value is regarded as the height layer of the same layer, and if a plurality of temperature data exist in one height layer, the average value of the plurality of temperature data is taken as the temperature value of the height layer in the final event;
example (c): for height data (km)99.98444366, 99.61489105, 99.24510956, 98.87528229, 98.50534821, 98.13528442, 97.76511383, 97.39484406, 97.0244751 and 96.65398407 in a certain event, temperature values corresponding to each height of the event are 225.5196838, 225.0498047, 224.7708435, 224.5986786, 224.3938904, 224.054245, 223.5292511, 222.8206482, 221.9805908 and 221.1124725, layering is carried out at intervals of 1km, the height data are integrated to obtain 100, 99, 98, 97 and 97, therefore, two temperature values corresponding to 225.5196838 and 225.0498047 in the height layer of 100km are obtained, the average value 225.28474425 of the two temperature values is required to be obtained to serve as the temperature of the height layer of 100km of the event, and the processing methods of other height layers are similar.
Step 4, coordinate conversion: converting the longitude and latitude coordinates into rectangular coordinates;
step 5, obtaining the spatial range of each event: taking the minimum value of the starting point and the maximum value of the ending point of the latitude in each event after coordinate conversion, and drawing the area range of a single event and the area range represented by all events of each height layer, thereby facilitating the subsequent analysis and data processing;
taking a certain height level of 1km as an example, a spatial range of the height level temperature is obtained, as shown in fig. 1 and 2. As can be seen from the figure, the area ranges represented by the events are overlapped.
Step 6, constructing a two-dimensional array of each height layer: taking longitude and latitude as dimensions, normalizing the dimensions into k' kilometer intervals, and constructing a temperature two-dimensional array of each height layer; the area range represented by each event has an overlapping part, so that when a two-dimensional array is constructed, the temperature value of the overlapping part is used as the temperature value of the area by solving the mean value of the two event temperatures, and the original temperature value is stored if the two event temperatures are not overlapped;
as shown in fig. 3, a temperature profile after processing for an event;
and 7, two-dimensional smoothing: 2D smoothing is carried out on each two-dimensional array, so that transition of the overlapped part and other parts is more uniform;
as shown in fig. 4, fig. 4 is a temperature distribution after smoothing the event shown in fig. 3;
step 8, constructing a three-dimensional array of the temperature in this month of the year: because the downloaded NC file takes a month as a time range, the time resolution of the constructed three-dimensional array is the average of the month, and a certain space range can be intercepted according to specific requirements; starting from 20km and ending at 100km, writing the smoothed two-dimensional temperature array layer by layer aiming at an altitude layer with kappa kilometers as incremental intervals, and finally obtaining a three-dimensional array with longitude, latitude and altitude as dimensions;
step 9, constructing temperature data in the same period of several years (for example, the previous 4 years) according to the steps 1 to 8, averaging the temperature data, and establishing a more reliable cubic grid of a three-dimensional array as a near space temperature data resource of the month with universal applicability in a virtual test;
step 10, performing the same processing on the density and the pressure according to the steps 1 to 9 to obtain a cubic grid of a three-dimensional array of the density and the pressure;
step 11, writing the constructed data including temperature, density and pressure into a text file T;
step 12D, reading the atmospheric Environment Data from the text file T written with the Data, representing the Data according to three specifications of DRM (Data Representation Model), SRM (Spatial Reference Model) and EDCS (environmental Data coding Specification) of the drive (Synthetic Environment Data Representation and exchange Specification), and storing the atmospheric Environment Data in the drive standard format.
The second embodiment is as follows: this embodiment is described with reference to fig. 6;
the construction method of the near space atmosphere virtual environment resource comprises the following steps:
step 1, acquiring historical data of atmospheric environment resources in an adjacent space, wherein the historical data comprises longitude data, latitude data, altitude data and corresponding temperature data;
step 2, processing abnormal data in the longitude, latitude, altitude and temperature data; thereby obtaining a two-dimensional matrix of the abnormal-free data, and facilitating the subsequent data processing operations such as normalization, averaging and the like;
step 3, normalizing the height data acquired by each event: for the height corresponding to each event, rounding the height data in each event; then, layering is carried out at intervals of k kilometers, the same height value is regarded as the height layer of the same layer, and if a plurality of temperature data exist in one height layer, the average value of the plurality of temperature data is taken as the temperature value of the height layer in the final event;
example (c): for height data (km)99.98444366, 99.61489105, 99.24510956, 98.87528229, 98.50534821, 98.13528442, 97.76511383, 97.39484406, 97.0244751 and 96.65398407 in a certain event, temperature values corresponding to each height of the event are 225.5196838, 225.0498047, 224.7708435, 224.5986786, 224.3938904, 224.054245, 223.5292511, 222.8206482, 221.9805908 and 221.1124725, layering is carried out at intervals of 1km, the height data are integrated to obtain 100, 99, 98, 97 and 97, therefore, two temperature values corresponding to 225.5196838 and 225.0498047 in the height layer of 100km are obtained, the average value 225.28474425 of the two temperature values is required to be obtained to serve as the temperature of the height layer of 100km of the event, and the processing methods of other height layers are similar.
Step 4, coordinate conversion: converting the longitude and latitude coordinates into rectangular coordinates;
step 5, obtaining the spatial range of each event: taking the minimum value of the starting point and the maximum value of the ending point of the latitude in each event after coordinate conversion, and drawing the area range of a single event and the area range represented by all events of each height layer, thereby facilitating the subsequent analysis and data processing;
taking a certain height level of 1km as an example, a spatial range of the height level temperature is obtained, as shown in fig. 1 and 2. As can be seen from the figure, the area ranges represented by the events are overlapped.
Step 6, constructing a two-dimensional array of each height layer: taking longitude and latitude as dimensions, normalizing the dimensions into k' kilometer intervals, and constructing a temperature two-dimensional array of each height layer; the area range represented by each event has an overlapping part, so that when a two-dimensional array is constructed, the temperature value of the overlapping part is used as the temperature value of the area by solving the mean value of the two event temperatures, and the original temperature value is stored if the two event temperatures are not overlapped;
as shown in fig. 3, a temperature profile after processing for an event;
and 7, two-dimensional smoothing: 2D smoothing is carried out on each two-dimensional array, so that transition of the overlapped part and other parts is more uniform;
as shown in fig. 4, fig. 4 is a temperature distribution after smoothing the event shown in fig. 3;
step 8, constructing a three-dimensional array of the temperature in this month of the year: because the downloaded NC file takes a month as a time range, the time resolution of the constructed three-dimensional array is the average of the month, and a certain space range can be intercepted according to specific requirements; starting from 20km and ending at 100km, writing the smoothed two-dimensional temperature array layer by layer aiming at an altitude layer with kappa kilometers as incremental intervals, and finally obtaining a three-dimensional array with longitude, latitude and altitude as dimensions;
step 9, constructing temperature data in the same period of several years (for example, the previous 4 years) according to the steps 1 to 8, averaging the temperature data, and establishing a more reliable cubic grid of a three-dimensional array as a near space temperature data resource of the month with universal applicability in a virtual test;
step 10, performing the same processing on the density and the pressure according to the steps 1 to 9 to obtain a cubic grid of a three-dimensional array of the density and the pressure;
step 11, writing the constructed data including temperature, density and pressure into a text file T;
step 12A, determining a calculation formula of an atmospheric horizontal wind field: the atmospheric horizontal wind field refers to a horizontal gradient wind field and comprises a latitudinal wind and a longitudinal wind; because the characteristics of different latitude wind fields are different, the calculation method needs to calculate the gradient wind according to different formulas in the latitude range of 15-80 degrees and above the equator; the wind field between 15 degrees S and 15 degrees N can be obtained by a linear interpolation method;
according to the latitude range, determining a corresponding wind field calculation formula:
firstly, calculating the wind-turning according to the formula (1) in a latitude range of 15-80 degrees:
wherein, P is air pressure, and rho is atmospheric density;referred to as the turn parameter, omega is the turn angular velocity,is the geographic latitude; x is the eastward distance and y is the northward distance; u. ofg、vgWind is respectively blown in the horizontal latitudinal direction and the longitudinal direction within the range of 15-80 degrees;
and then calculating gradient wind according to the formula (2):
wherein,a is the earth radius; u. ofgr、vgrRespectively horizontal latitudinal direction gradient wind and longitudinal direction gradient wind;
(II) special solution is needed above the equator, and gradient wind is calculated according to a formula (3) within a latitude range of 15 degrees S-15 degrees N:
wherein u ise、veThe wind is respectively gradient wind in the horizontal latitudinal direction and the longitudinal direction at an angle of 15 degrees S-15 degrees N;
step 12B, constructing a uniform cubic grid of a three-dimensional array of the atmospheric horizontal wind field: the atmospheric horizontal wind field is mainly obtained by calculation by utilizing atmospheric density and pressure, earth orbit radius, corner velocity and the like, so that the previously constructed density and pressure three-dimensional array of the area range is substituted into a wind field calculation formula to obtain a uniform cubic grid of the three-dimensional array of the wind-turning and gradient wind at the corresponding position, and accordingly, the atmospheric horizontal wind field resource of the adjacent space of the area is generated;
step 12C, writing the constructed wind field data into the text file T;
and step 12D, reading the atmospheric environment data from the text file T written with the data, expressing the data according to three specifications of the DRM, the SRM and the EDCS of the SEDRIS, and storing the atmospheric environment data into a SEDRIS standard format.
And at this moment, the construction of the atmospheric environment data resource of the adjacent space is completed, and a database comprising temperature, density, pressure and a wind field is constructed. The data of each atmospheric element is stored in the form of a three-dimensional uniform grid, which is written into a txt file for the purpose of facilitating the subsequent data conversion.
The third concrete implementation mode:
the specific process of processing abnormal data in the longitude, latitude, altitude and temperature data in step 2 of the present embodiment is as follows:
and acquiring the original average resolution of the data aiming at longitude, latitude, altitude and temperature data in each event, then eliminating abnormal data, taking the previous data of the abnormal data as a basis, and adding recursion data which is obtained by recursion by utilizing the resolution on the basis and has the same quantity with the eliminated abnormal data.
Taking abnormal value processing of temperature data as an example: the abnormal maximum values are generally distributed in the last two data of the temperature data in each event, taking the last 10 temperature data of the temperature data as an example, the original average resolution is obtained in advance according to the temperature data, and the last 10 temperature data of the temperature data are as follows: 225.5196838, 225.0498047, 224.7708435, 224.5986786, 224.3938904, 224.054245, 223.5292511, 222.8206482, 221.9805908, 221.1124725, 220.2646179, 219.3830872, 218.3756866, 217.1251678, 215.4690247, 213.3180847, 210.8113708, 208.0403748, 9.96921E +36, 9.96921E +36, it can be seen that the last two data are anomalous data. The method comprises the steps of firstly obtaining original average resolution according to temperature data, taking adjacent temperature differences of all temperature data before an abnormal value, then averaging the differences, and taking the average as the original resolution of the temperature of the event. And adding original resolution recursion on the basis of the third last data to obtain the last two data.
Other steps and parameters are the same as those in the first or second embodiment.
The fourth concrete implementation mode:
the specific process of coordinate transformation described in step 4 of this embodiment is as follows:
since the grid of the finally established coordinate system is in units of distance, the latitude and longitude data acquired in each event is converted into distance data in rectangular coordinates according to the coordinate projection system in Matlab2014a, and rounded up nearby.
Other steps and parameters are the same as those in one of the first to third embodiments.
The fifth concrete implementation mode:
in this embodiment, κ is equal to κ'. When κ ═ κ', the squares constituted by the longitude, latitude, and altitude are squares.
Other steps and parameters are the same as in one of the first to fourth embodiments.
The sixth specific implementation mode:
in the present embodiment, κ ═ κ' ═ 1.
Other steps and parameters are the same as those in one of the first to fifth embodiments.
The seventh embodiment:
in this embodiment, the specific process of acquiring the historical data of the atmospheric environment resource in the near space in step 1 is as follows:
selecting an NC file of the atmospheric environment data of the adjacent space corresponding to the specific spatial range and the time range of the SABER; and reading the NC file, and acquiring historical data of the atmospheric environment resources in the adjacent space.
Taking the data of four years in a certain area as an example, 48 NC files of 48 months in 2012-2015 four years each file contains the information of the NC file, the stored longitude, latitude, altitude, temperature and other data, and the NC files are read by using a NetCDF4Excel plug-in and matlab to obtain the historical data of the atmospheric environment resources of the adjacent space.
Other steps and parameters are the same as those in one of the first to sixth embodiments.
Claims (8)
1. The method for constructing the near space atmosphere virtual environment resource is characterized by comprising the following steps of:
step 1, acquiring historical data of atmospheric environment resources in an adjacent space, wherein the historical data comprises longitude data, latitude data, altitude data and corresponding temperature data;
step 2, processing abnormal data in the longitude, latitude, altitude and temperature data;
step 3, normalizing the height data acquired by each event: for the height corresponding to each event, rounding the height data in each event; then, layering is carried out at intervals of k kilometers, the same height value is regarded as the height layer of the same layer, and if a plurality of temperature data exist in one height layer, the average value of the plurality of temperature data is taken as the temperature value of the height layer in the final event;
step 4, coordinate conversion: converting the longitude and latitude coordinates into rectangular coordinates;
step 5, obtaining the spatial range of each event: taking the minimum value of the starting point and the maximum value of the ending point of the latitude in each event after coordinate conversion, and drawing the area range of a single event and the area range represented by all events in each height layer;
step 6, constructing a two-dimensional array of each height layer: taking longitude and latitude as dimensions, normalizing the dimensions into k' kilometer intervals, and constructing a temperature two-dimensional array of each height layer; the area range represented by each event has an overlapping part, when a two-dimensional array is constructed, the temperature value of the overlapping part is used as the temperature value of the area by solving the mean value of the two event temperatures, and if the two event temperatures are not overlapped, the temperature value is stored into the original temperature value;
and 7, two-dimensional smoothing: 2D smoothing is carried out on each two-dimensional array;
step 8, constructing a three-dimensional array of the temperature in this month of the year: starting from 20km and ending at 100km, writing the smoothed two-dimensional temperature array layer by layer aiming at an altitude layer with kappa kilometers as incremental intervals, and finally obtaining a three-dimensional array with longitude, latitude and altitude as dimensions;
step 9, constructing temperature data of the same period in a plurality of years according to the steps 1 to 8, averaging the temperature data, and establishing a reliable cubic grid of a three-dimensional array as a temperature data resource of an adjacent space of the month in a virtual test;
step 10, performing the same processing on the density and the pressure according to the steps 1 to 9 to obtain a cubic grid of a three-dimensional array of the density and the pressure;
step 11, writing the constructed data including temperature, density and pressure into a text file T;
step 12D, reading the atmospheric environment data from the text file T written with the data, expressing the data according to three specifications of DRM, SRM and EDCS of the SEDRIS, and storing the atmospheric environment data into a SEDRIS standard format; the SEDRIS is a comprehensive environment data representation and exchange specification; DRM is a data representation model; SRM is a space reference model; the EDCS is an environmental data coding specification.
2. The method for constructing the virtual environment resource in the atmosphere near the space according to claim 1, further comprising a construction process of an atmospheric horizontal wind field, which comprises the following specific processes:
step 12A, determining a corresponding atmospheric horizontal wind field calculation formula according to the latitude range:
firstly, calculating the wind-turning according to the formula (1) in a latitude range of 15-80 degrees:
wherein, P is air pressure, and rho is atmospheric density;referred to as the turn parameter, omega is the turn angular velocity,is the geographic latitude; x is the eastward distance and y is the northward distance; u. ofg、vgWind is respectively blown in the horizontal latitudinal direction and the longitudinal direction within the range of 15-80 degrees;
and then calculating gradient wind according to the formula (2):
wherein,a is the earth radius; u. ofgr、vgrRespectively horizontal latitudinal direction gradient wind and longitudinal direction gradient wind;
(II) calculating gradient wind according to a formula (3) within a latitude range of 15 degrees S-15 degrees N:
wherein u ise、veThe wind is respectively gradient wind in the horizontal latitudinal direction and the longitudinal direction at an angle of 15 degrees S-15 degrees N;
step 12B, constructing a uniform cubic grid of a three-dimensional array of the atmospheric horizontal wind field: substituting the previously constructed density and pressure three-dimensional array of the area range into a wind field calculation formula to obtain a uniform cubic grid of the three-dimensional array of the wind-turning and gradient wind at the corresponding position, thereby generating atmospheric horizontal wind field resources of the space adjacent to the area;
and 12C, writing the constructed wind field data into the text file T.
3. The method for constructing the virtual environment resource in the near space atmosphere according to claim 1 or 2, wherein the specific process of processing the abnormal data in the longitude, latitude, altitude and temperature data in the step 2 is as follows:
and acquiring the original average resolution of the data aiming at longitude, latitude, altitude and temperature data in each event, then eliminating abnormal data, taking the previous data of the abnormal data as a basis, and adding recursion data which is obtained by recursion by utilizing the resolution on the basis and has the same quantity with the eliminated abnormal data.
4. The method for constructing the virtual environment resource in the atmosphere near the space according to claim 3, wherein the specific process of the coordinate transformation in the step 4 is as follows:
the grid of the finally established coordinate system is in distance units, so the longitude and latitude data acquired in each event are converted into distance data in rectangular coordinates according to the coordinate projection system in Matlab2014a, and are rounded up nearby.
5. The method as claimed in claim 4, wherein k is equal to k'.
6. The method for constructing the virtual environment resource in the near space atmosphere according to claim 5, wherein the specific process of acquiring the historical data of the atmospheric environment resource in the near space in the step 1 is as follows:
selecting an NC file of the atmospheric environment data of the adjacent space corresponding to the specific spatial range and the time range of the SABER; and reading the NC file, and acquiring historical data of the atmospheric environment resources in the adjacent space.
7. The method for constructing the virtual environment resource in the near space atmosphere as claimed in claim 5, wherein k ═ k' ═ 1.
8. The method for constructing the virtual environment resource in the near space atmosphere according to claim 7, wherein the specific process of acquiring the historical data of the atmospheric environment resource in the near space in the step 1 is as follows:
selecting an NC file of the atmospheric environment data of the adjacent space corresponding to the specific spatial range and the time range of the SABER; and reading the NC file, and acquiring historical data of the atmospheric environment resources in the adjacent space.
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| CN103093410A (en) * | 2013-01-06 | 2013-05-08 | 国家海洋局第二海洋研究所 | Surveying and mapping method of submarine topography six-dimension mesh |
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| CN103093410A (en) * | 2013-01-06 | 2013-05-08 | 国家海洋局第二海洋研究所 | Surveying and mapping method of submarine topography six-dimension mesh |
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| "电子海图云服务关键技术研究与实践";刘灿由;《中国博士学位论文全文数据库（电子期刊）》;20140115;全文 * |
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