A cooperative scanning scheduling method based on strong convective movement direction and radar layout

Abstract

This invention relates to a collaborative scanning and scheduling method based on the direction of movement of strong convection and radar layout, belonging to the field of radar detection. The method includes: collecting radar data to form mosaic data to obtain the direction of movement of the strong convection center; calculating the distances between all schedulable radars and the strong convection target, calculating the azimuths of all schedulable radars relative to the strong convection target, and calculating the angles between the azimuths of all schedulable radars and the strong convection target; selecting the optimal vertical profile radar, and calculating the azimuth of the strong convection target relative to the last vertical profile radar; based on all selected optimal vertical profile radars, if two radars are selected simultaneously, the scheduling radars are scheduled to perform the vertical profile task in two rounds; otherwise, the scheduling radars continue to perform the vertical profile task until the next radar scheduling cycle. This invention enables continuous tracking of multiple strong convection targets during strong convective weather processes, obtaining the internal structure and intensity changes of the strong convective weather system.

Description

Technical Field

[0001] This invention relates to the field of meteorological observation, and in particular to a collaborative scanning scheduling method based on the direction of strong convection movement and radar layout. Background Technology

[0002] In the field of meteorological monitoring and early warning, severe convective weather, due to its suddenness, wide range of impact, and great destructive power, has always been a focus of attention for meteorologists and meteorological service agencies. Traditional weather radar systems, such as S-band and C-band radars, can detect the existence of severe convective weather to a certain extent, but in complex terrain or areas with sparse radar station networks, there are often blind spots, which restricts the monitoring and early warning capabilities for hazardous weather in low-altitude areas.

[0003] Weather radar plays an irreplaceable and crucial role in severe weather monitoring and early warning, playing a key role in reducing loss of life and property caused by meteorological disasters. However, current radar echo data related to severe weather are mostly collected based on observation data from existing operational radars, with a single scanning strategy. Furthermore, weather radar is limited by factors such as the Earth's curvature, electromagnetic wave refraction, terrain, and observation modes, resulting in blind spots in the observation of near-surface weather processes. This restricts the monitoring and early warning capabilities for hazardous weather in low-altitude areas, especially in complex terrain or areas with sparse radar networks. Conducting networked collaborative observations with multiple weather radars, using different scanning strategies, and utilizing a limited-scale observation network to obtain high-resolution data on the vertical structure of precipitation systems is particularly important for analyzing the formation mechanism of severe weather. The main purpose is to identify and track severe convective weather processes that easily trigger natural disasters and obtain high spatiotemporal resolution meteorological structures on the vertical profile of severe convective weather, i.e., to invert particle phase states on the vertical profile of severe convective weather, thereby enabling better analysis of the information of this weather process.

[0004] In recent years, with the accelerated advancement of meteorological modernization, the limited scanning strategies of existing operational radars and the ability of X-band radars to freely control scanning and coordinate observations have made networked collaborative observations between S-band and C-band radars and X-band weather radars an important approach. Coordinated control and scheduling of X-band radars for vertical profile scanning (RHI) to detect severe convective targets and obtain high-resolution data on the vertical structure of precipitation systems using a limited observation network is particularly important for analyzing the formation mechanisms of severe weather. However, during collaborative observation, the rapid movement and changes of severe convective weather targets, coupled with the time required for weather radars to complete full-space detection, mean that the location of the severe convective weather center may have changed within the time interval from detection to identification, decision-making, and scheduling. Therefore, how to rationally schedule radars for collaborative scanning based on the movement direction of severe convective weather and the radar layout to obtain high spatiotemporal resolution meteorological structures on the vertical profile of severe convective weather has become an urgent problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a cooperative scanning scheduling method based on the direction of strong convection movement and radar layout, thus solving the deficiencies of the prior art.

[0006] The objective of this invention is achieved through the following technical solution: a cooperative scanning scheduling method based on strong convection movement direction and radar layout, the method comprising:

[0007] S1. After collecting radar data to form mosaic data, determine whether a strong convective target has been identified. If a strong convective target has been identified, obtain the direction of movement of the strong convection center.

[0008] S2. Calculate the distance between all schedulable radars and the strong convective target, calculate the azimuth of all schedulable radars relative to the strong convective target, and calculate the angle between the azimuth of all schedulable radars and the strong convective target.

[0009] S3. Select the optimal vertical profile radar and calculate the azimuth of the strong convective target relative to the last vertical profile radar. Based on all the selected optimal vertical profile radars, if there are identical radars selected, schedule the radars to perform the vertical profile task in two rounds. Otherwise, schedule the radars to perform the vertical profile task until the next radar scheduling cycle.

[0010] S1 specifically includes the following:

[0011] Data from the S-band and X-band networked radars is collected through a central server, and the data is preprocessed after its integrity and format are checked.

[0012] The coordinate transformation of different radar data is performed, the nearest neighbor interpolation method is used to interpolate the data with inconsistent resolution, and the weighted method is used to fuse the data in the overlapping area.

[0013] The system determines whether a strong convective target has been identified. If a strong convective target has been identified, the background wind field direction at the corresponding height of the wind profile radar data closest to the center of the strong convection is used to represent the motion of the center of the strong convection. If no strong convective target has been identified, the data is reacquired.

[0014] The calculation of the distances between all schedulable radars and strong convective targets includes the following:

[0015] Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB).

[0016] Using A as the reference point, and following the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude.

[0017] The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the distance between point B and point A is... ;

[0018] Calculate the distance D between all schedulable radars and the target with strong convection. i , i=1…n, where n is the total number of schedulable radars.

[0019] The calculation of the azimuth of all schedulable radars relative to strong convective targets includes the following:

[0020] Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB).

[0021] Using A as the reference point, and following the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude.

[0022] The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the orientation of point B relative to point A is: ;

[0023] The orientation of point B relative to point A is determined by the sign of dx. If dx is positive, the orientation of point B relative to point A is 90°. If dx is negative, the orientation of point B relative to point A is 270°.

[0024] The corrected value is obtained by judging based on the difference in latitude and longitude between the two points. Finally, the azimuth of the strong convective target relative to all tunable radars was obtained. , i=1…n, where n is the total number of schedulable radars, where, This represents the difference in longitude between point B and point A. This represents the latitude difference between point B and point A.

[0025] The calculation of the angle between the operating azimuth of all schedulable radars and the strong convective target includes the following:

[0026] Based on the target's azimuth (mAz) and the azimuth of all schedulable radars relative to strong convective targets. This yields the angles between the azimuths of all schedulable radars and the operating azimuths of strong convective targets. .

[0027] The selection of the optimal vertical profiling radar includes the following:

[0028] Based on the effective observation range of the X-band, radars whose targets are within the effective observation range are selected;

[0029] Based on the angle between the radar and the target's direction of movement within the effective observation range radar. Let i = 1…n, where n is the total number of schedulable radars. Calculate the absolute value of the angle between the radar within the effective observation range and the target's direction of travel. ;

[0030] The absolute value of the angle between the radar within the effective observation range and the target's direction of movement. The radars are sorted in ascending order, and the radar with the minimum angle is selected as the optimal observation radar.

[0031] The calculation of the strong convective target's position relative to the final vertical profile radar azimuth includes the following:

[0032] Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB).

[0033] Using A as the reference point, and following the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude.

[0034] The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the orientation of point B relative to point A is: ;

[0035] The orientation of point B relative to point A is determined by the sign of dx. If dx is positive, the orientation of point B relative to point A is 90°. If dx is negative, the orientation of point B relative to point A is 270°.

[0036] The corrected value is obtained by judging based on the difference in latitude and longitude between the two points. This refers to the azimuth of a strong convective target relative to the optimal vertical profile radar. .

[0037] The method further includes:

[0038] When performing a vertical profile task, the vertical profile scanning mode is set with a start elevation angle of 0.5°, an end elevation angle of 70°, and an azimuth of the target relative to the optimal vertical profile radar azimuth az. A scanning command is sent to the executing radar until the optimal radar is selected again in the next cycle.

[0039] This invention has the following advantages: a collaborative scanning and scheduling method based on the direction of strong convection movement and radar layout, by selecting radars for vertical profile scanning along the direction of weather system movement through the direction of precipitation system movement and radar layout, can better obtain the internal structure of weather systems from vertical profile scanning, enabling continuous tracking of multiple strong convective targets during strong convective weather processes, and obtaining the internal structure and intensity changes of strong convective weather systems. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the effect;

[0041] Figure 2 This is a schematic diagram of the process of the present invention;

[0042] Figure 3 This is a schematic diagram of the interpolation method;

[0043] Figure 4 This is a schematic diagram illustrating the effect of clustering strong convection echo points. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of this application provided below with reference to the accompanying drawings is not intended to limit the scope of protection of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. The present invention will be further described below with reference to the accompanying drawings.

[0045] This invention specifically relates to a collaborative scanning scheduling method based on the direction of movement of severe convection and radar layout. By selecting radars for vertical profile scanning (RHI) along the direction of weather system movement, the method can better capture the internal structure of the weather system obtained by RHI. During severe convective weather observations, multiple severe convective targets are continuously tracked to obtain the internal structure and intensity changes of the severe convective weather system.

[0046] like Figure 1 As shown, by selecting the vertical profile (RHI) scan of the radar along the direction of the weather system's movement and the radar layout, the internal structure of the weather system obtained by the vertical profile (RHI) scan can be better understood.

[0047] like Figure 2 As shown, it specifically includes the following:

[0048] 1. Collect radar data to form mosaic data:

[0049] (1) Collect data from S-band and X-band networked radars through a central server;

[0050] (2) Check the integrity and data format of the weather radar data;

[0051] (3) Perform data preprocessing and quality control, including noise and interference removal, to ensure the accuracy and reliability of the data;

[0052] (4) Perform coordinate transformation on different radar data, use the nearest neighbor interpolation method to interpolate the data with inconsistent resolution, and use the weighting method to fuse the data in the overlapping area.

[0053] Furthermore, the S-band and X-band radar network mosaic data fusion technology includes two steps: coordinate transformation and difference processing.

[0054] A1. Calculate spherical coordinates (radar polar coordinates) from Cartesian coordinates (3D grid);

[0055] A three-dimensional grid coordinate system can be constructed based on the size of the puzzle grid points (algorithm input parameters) and the puzzle area. Each grid point is described by latitude, longitude, and altitude. Let the coordinates of any grid cell in the three-dimensional grid be ( , , ),in Latitude Longitude The altitude is given. The coordinates of the radar antenna location are ( ). , , ),in Latitude Longitude The altitude is given. Using radar beam propagation and great circle geometry, the polar coordinate position (r, a, e) of the grid cell relative to the radar point can be determined, where r is the slant range, a is the azimuth angle, and e is the elevation angle. This can be derived from spherical trigonometry formulas.

[0056] ,

[0057] Where R is the Earth's radius and s is the great circle distance, its expression is:

[0058] ,

[0059] Let C = sin a, then we have:

[0060] ,

[0061] The expression for the elevation angle e is:

[0062] ,

[0063] Among them, R m =4 / 3R is the equivalent Earth radius, where R is the Earth radius.

[0064] The expression for the slope distance r is:

[0065] .

[0066] A2, 8-point interpolation method;

[0067] like Figure 3 As shown, the value of the radar falling on the three-dimensional grid point is obtained by using the 8-point interpolation method.

[0068] The polar coordinate position (r, a, e) of a certain grid point relative to a radar point falls on , , , , , , , Within the enclosed cone, the analytical value of that grid point It can be obtained by bilinear interpolation from the observations of these 8 points.

[0069] ,

[0070] Among them, w a1 w a2 For azimuth interpolation weights:

[0071] ,

[0072] w r1 w r2 Slope distance interpolation weights:

[0073] ,

[0074] ,

[0075] we1 w e2 Interpolation weights for elevation angle:

[0076] ,

[0077] A3. Puzzle method;

[0078] In the puzzle area, when a 3D grid cell contains multiple radar data, the reflectivity value of the current cell is obtained using an exponential weighting function.

[0079] ,

[0080] Where f is the composite reflectance value of the three-dimensional cell, f j w is the analysis value of the j-th radar that falls in the current cell. j For the analysis value f j The weights, N rad This represents the total number of radars with analysis values ​​at the current grid cell.

[0081] The exponential weighting function is:

[0082] ,

[0083] Where R1 is an appropriate length ratio, and r1 is the distance from the grid point to the radar center. Through historical experience accumulation and comparative analysis of mosaic effects, R=100km for S-band radar and R=50km for X-band radar can effectively improve the structural discontinuity caused by differences in observation time and sampling volume of different radars, and ensure the integrity and smoothness of the echo structure in the layered cloud area.

[0084] 2. Identification of targets in strong convection:

[0085] Severe convective weather is characterized by small spatial and temporal scale, rapid development, intense intensity, great destructiveness, and easy to cause disasters. The identification of severe convective targets is achieved through mosaic data, which includes information such as boundaries, center, and area.

[0086] (1) Randomly select a strong center point As a starting point, if the point satisfies the following principle:

[0087] ,

[0088] Where Z represents the combined reflectance. Represents coordinate points The corresponding combined reflectance, max(.) is used to maximize the value. This represents the Euclidean distance between two points. The threshold represents the radius sought near the strong center point, which is set to 6 in this invention.

[0089] (2) Generate a set containing only the starting point. .

[0090] The remaining strong convection echo points are traversed, and if a point satisfies the following condition, it is assigned to [the relevant category / category]. Continue until no point satisfies the condition.

[0091] ,

[0092] Where dist(.) represents the computation of point p and set The minimum Euclidean distance between all points.

[0093] (3) From the total sample, Yi Xu has already been assigned to the set. The point in the middle.

[0094] (4) Select a new strong center starting point and repeat steps (1)-(4) until all strong center points have been processed.

[0095] (5) If in a certain set If the total number of points is less than 40, the set is considered noise and removed.

[0096] As can be seen from the above steps, this clustering algorithm mainly uses spatial distance as the core observation point and clusters the points based on their spatial density distribution characteristics. The effect of clustering strong convection echo points is as follows. Figure 4 As shown. It can be seen that, regardless of the convective unit ( Figure 4 The two examples on the top side are still relatively complex multi-monomer structures. Figure 4 (In the two examples below), clustering algorithms can accurately locate the strong convection echo region.

[0097] After clustering, potentially strong convection regions in the radar echoes were identified. Further analysis was performed to extract parameters for each region, including area, maximum reflectivity, average reflectivity, vertical integral liquid water content, and echo top height.

[0098] 3. Obtain the direction of movement of the strong convection center: Based on the information of the strong convection center, find the nearest wind profile radar data and obtain the background wind field direction at the corresponding height. Use it to represent the direction of movement of the strong convection center, which can better reflect the changes in the position of the strong convection center.

[0099] 4. Calculate the distances between all schedulable radars and targets with strong convection:

[0100] Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB).

[0101] Using A as the reference point, and following the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude.

[0102] The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the distance between point B and point A is... .

[0103] Calculate the distance D between each schedulable radar and the target. i (i=1…n), where n is the total number of schedulable radars.

[0104] 5. Calculate the azimuth of all schedulable radars relative to the target:

[0105] Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB).

[0106] Using A as the reference point, and following the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude.

[0107] The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the orientation of point B relative to point A is: ;

[0108] Since the output azimuth here needs to be relative to true north, the az value output by the formula needs to be evaluated and converted. First, if dy is 0, it means that the two points are on the same latitude circle, and no conversion will be performed. The calculation determines the orientation of point B relative to point A based on the sign of dx. If dx is positive, the orientation of point B relative to point A is 90°; if dx is negative, the orientation of point B relative to point A is 270°.

[0109] The corrected value is obtained by judging based on the difference in latitude and longitude between the two points. Finally, the target's azimuth relative to all schedulable radars is obtained. , i=1…n, where n is the total number of schedulable radars, where, This represents the difference in longitude between point B and point A. This represents the latitude difference between point B and point A.

[0110] 6. Calculate the angle between the azimuth of all schedulable radars and the azimuth of strong convective targets:

[0111] Based on the target's azimuth (mAz) and the azimuth of all steerable radars relative to the target. (i=1…n), where n is the total number of schedulable radars. Find the angles between the azimuth of all schedulable radars and the target's operating position. .

[0112] 7. Select the optimal vertical profile radar:

[0113] X-band radar, in conjunction with vertical profiling, has an effective target observation range of 10km-60km. Based on the effective observation range, radars within the effective observation range of the target are selected, i.e., Distance > 10 and Distance < 60, where Distance is the effective observation range.

[0114] Then, based on the angle between the radar within the effective observation range and the target's direction of travel... (i=1…n), calculate the absolute value of the angle between the radar and the target's direction of travel within the effective observation range radar. .

[0115] The absolute value of the angle between the radar within the effective observation range and the target's direction of movement. The radars are sorted in ascending order, and the radar with the minimum angle is selected as the optimal observation radar.

[0116] 8. Calculate the azimuth of a strong convective target relative to the optimal vertical profile radar:

[0117] Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB).

[0118] Using A as the reference point, and following the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude.

[0119] The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the orientation of point B relative to point A is: ;

[0120] The orientation of point B relative to point A is determined by the sign of dx. If dx is positive, the orientation of point B relative to point A is 90°. If dx is negative, the orientation of point B relative to point A is 270°.

[0121] The corrected value is obtained by judging based on the difference in latitude and longitude between the two points. That is, the target's azimuth relative to the optimal vertical profile radar. .

[0122] 9. Radar scheduling and scanning strategy:

[0123] Based on all the selected optimal vertical profile radars, if there are identical radars selected, the radars are scheduled to perform vertical profile tasks in two rounds; otherwise, the radars are scheduled to perform vertical profile tasks continuously until the next radar scheduling cycle.

[0124] 10. Dispatch radar to perform tasks:

[0125] When performing vertical profile analysis, setting the RHI scan mode to a start elevation angle of 0.5°, an end elevation angle of 70°, and an azimuth of the target relative to the optimal vertical profile analysis radar (az) allows for better observation of the vertical structure of weather targets. A scan command is sent to the executing radar until the optimal radar is reselected in the next cycle.

[0126] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and improvements, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A cooperative scanning scheduling method based on strong convective movement direction and radar layout, characterized in that: The method includes: S1. After collecting radar data to form mosaic data, determine whether a strong convective target has been identified. If a strong convective target has been identified, obtain the direction of movement of the strong convection center. S2. Calculate the distance between all schedulable radars and the strong convective target, calculate the azimuth of all schedulable radars relative to the strong convective target, and calculate the angle between the azimuth of all schedulable radars and the strong convective target. S3. Select the optimal vertical profile radar and calculate the azimuth of the strong convective target relative to the last vertical profile radar. Based on all the selected optimal vertical profile radars, if there are two radars selected in the same way, the radars are scheduled to perform the vertical profile task in two rounds. Otherwise, the radars are scheduled to perform the vertical profile task until the next radar scheduling cycle. The calculation of the azimuth of all schedulable radars relative to strong convective targets includes the following: Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB). Using A as the reference point, according to the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude. The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the orientation of point B relative to point A is: ; The orientation of point B relative to point A is determined by the sign of dx. If dx is positive, the orientation of point B relative to point A is 90°. If dx is negative, the orientation of point B relative to point A is 270°. The corrected value is obtained by judging based on the difference in latitude and longitude between the two points. Finally, the azimuth of the strong convective target relative to all tunable radars was obtained. , i=1…n, where n is the total number of schedulable radars, where, This represents the difference in longitude between point B and point A. This represents the latitude difference between point B and point A; The calculation of the angle between the operating azimuth of all schedulable radars and the strong convective target includes the following: Based on the azimuth of the strong convective target (mAz) and the azimuth of all schedulable radars relative to the strong convective target. This yields the angles between the azimuths of all schedulable radars and the operating azimuths of strong convective targets. ; The selection of the optimal vertical profiling radar includes the following: Based on the effective observation range of the X-band, radars whose targets are within the effective observation range are selected; Based on the angle between the radar and the target's direction of movement within the effective observation range radar. Let i = 1…n, where n is the total number of schedulable radars. Calculate the absolute value of the angle between the radar within the effective observation range and the target's direction of travel. ; The absolute value of the angle between the radar within the effective observation range and the target's direction of movement. The radars are sorted in ascending order, and the radar with the minimum angle is selected as the optimal observation radar.

2. The cooperative scanning scheduling method based on strong convection movement direction and radar layout according to claim 1, characterized in that: S1 specifically includes the following: Data from the S-band and X-band networked radars is collected through a central server, and the data is preprocessed after its integrity and format are checked. The coordinate transformation of different radar data is performed, the nearest neighbor interpolation method is used to interpolate the data with inconsistent resolution, and the weighted method is used to fuse the data in the overlapping area. Determine whether a strong convective target has been identified. If a strong convective target has been identified, obtain the background wind field direction at the corresponding height of the wind profile radar data closest to the center of the strong convection to represent the direction of movement of the center of the strong convection. If no strong convective target has been identified, re-acquire the data.

3. The cooperative scanning scheduling method based on strong convection movement direction and radar layout according to claim 1, characterized in that: The calculation of the distances between all schedulable radars and strong convective targets includes the following: Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB). Using A as the reference point, according to the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude. The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the distance between point B and point A is... ; Calculate the distance D between all schedulable radars and the target with strong convection. i , i=1…n, where n is the total number of schedulable radars.

4. The cooperative scanning scheduling method based on strong convection movement direction and radar layout according to claim 1, characterized in that: The calculation of the strong convective target's position relative to the final vertical profile radar azimuth includes the following: Let the latitude and longitude of radar location A be (LonA, LatA), and let the latitude and longitude of active weather target B be (LonB, LatB). Using A as the reference point, according to the formula and We obtain Ed and Ec for point A, where Ea is the equatorial radius, Eb is the polar radius, Ed is the latitude circle radius of point A, and Ec is the sphere radius that is corrected for the constantly changing latitude. The distances of point B relative to point A in the longitude and latitude directions are respectively... and Therefore, the orientation of point B relative to point A is: ; The orientation of point B relative to point A is determined by the sign of dx. If dx is positive, the orientation of point B relative to point A is 90°. If dx is negative, the orientation of point B relative to point A is 270°. The corrected value is obtained by judging based on the difference in latitude and longitude between the two points. That is, the target's azimuth relative to the optimal vertical profile radar. .

5. A cooperative scanning scheduling method based on strong convection movement direction and radar layout according to any one of claims 1-4, characterized in that: The method further includes: When performing a vertical profile task, the vertical profile scanning mode is set with a start elevation angle of 0.5°, an end elevation angle of 70°, and an azimuth of the target relative to the optimal vertical profile radar azimuth az. A scanning command is sent to the executing radar until the optimal radar is selected again in the next cycle.

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