Reflectivity factor weighted comparison method and system based on radar beam volume overlapping ratio

Abstract

The invention discloses a reflectivity factor weighted comparison method and system based on a radar beam volume overlapping ratio, and the method comprises the steps: S1, building an elliptical platform model used for representing a comparison distance library in a space according to the information of the comparison distance library, and comprehensively considering the distance resolution and the pitch angle and azimuth angle of a beam, establishing a beam volume matching model to obtain a beam space sampling volume of the distance library; s2, generating a large number of random points based on Monte Carlo simulation, calculating the volume overlapping ratio of different beams according to a region labeling method, and quantifying the space matching degree of the radar beams; s3, giving a corresponding weight to the reflectivity factor of each matching area through the volume overlapping ratio, carrying out the weighted calculation of a final weighted error, a weighted standard deviation and a weighted correlation coefficient, and evaluating the radar performance difference; according to the method, the matching degree of different radar distance libraries can be accurately calculated, the space matching degree is quantitatively evaluated, weighted calculation is carried out, the radar consistency comparison precision is improved, and more accurate calibration is carried out on the radar.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of weather radar data processing and calibration, and more particularly to a reflectivity factor weighting comparison method and system based on radar beam volume overlap rate. BACKGROUND

[0002] As one of the pillars in the meteorological field, weather radar is widely used in weather prediction, precipitation estimation and disaster monitoring. In order to ensure that the radar detection data has high precision and robustness, the radar must be calibrated regularly. Radar consistency comparison, as an important means to evaluate the performance of weather radar, mainly evaluates the reflectivity factor of the radar, and has been widely used in business.

[0003] At present, the existing radar consistency comparison algorithm mainly matches the space based on the center position of the beam volume of the distance library, and judges the degree of spatial matching through the position difference of different distance library centers. However, this matching method is relatively rough, which may cause different degrees of errors in radar consistency comparison, and cannot intuitively reflect the volume overlap degree of the beams of different radars in space. Especially in the consistency of different wave bands, the errors caused by different beam widths and distance resolutions are greater.

[0004] In addition, in the comparison of different wave band radars, such as satellite-ground verification, although the volume matching method is applied to calculate the weighted reflectivity factor, the weight is calculated according to the size of the distance library sampling volume and the distance, and the actual distance library matching degree is not accurately considered.

[0005] Therefore, how to accurately calculate the matching degree of different radar distance libraries, quantitatively evaluate the spatial matching degree, and improve the accuracy of the radar consistency comparison algorithm and the accuracy of the radar calibration are problems that need to be solved by those skilled in the art. SUMMARY

[0006] Therefore, the present application provides a reflectivity factor weighting comparison method and system based on radar beam volume overlap rate to solve the technical problems mentioned in the background.

[0007] In order to achieve the above purpose, the present application adopts the following technical solutions:

[0008] A reflectivity factor weighting comparison method based on radar beam volume overlap rate, comprising the following steps:

[0009] S1. According to the comparison distance library information stored in the radar base data, an elliptical platform model for representing the comparison distance library is established in space, and the distance resolution, the elevation angle and the azimuth angle of the beam are comprehensively considered to establish a beam volume matching model to obtain the beam space sampling volume of the distance library;

[0010] S2. Based on the Monte Carlo simulation method, the matching degree of the radar beam in space is quantified by generating a large number of random points and calculating the volume overlap rate of different beams according to the regional annotation method;

[0011] S3. By assigning each matching area a reflectivity factor corresponding to the weight of the volume overlap rate, the final weighted error, weighted standard deviation and weighted correlation coefficient are calculated in a weighted manner to accurately evaluate the performance difference of the radar.

[0012] Preferably, the specific content of step S1 includes:

[0013] S11. Extract the information of the target beam from the radar-based data, including the radar latitude and longitude, antenna feed height, radar beam width, distance resolution, and the target beam corresponding to the radar's elevation angle, azimuth angle and distance library;

[0014] S12. Calculate the major and minor axes of the upper and lower ellipses on the elliptical table through the distance resolution, beam width and the distance of the distance library center relative to the radar;

[0015] S13. Establish a station-centered coordinate system based on the antenna feed for each radar, and express the center of the target beam in station-centered coordinates;

[0016] S14. Convert the station-centered coordinates of the center of the target beam B relative to radar B to geocentric coordinates, and then convert the geocentric coordinates to station-centered coordinates relative to radar A, unify the coordinate systems, and calculate the elevation and azimuth angles of the center of the target beam B relative to the antenna feed of radar A, as well as the distance, to obtain the polar coordinates of the beam center of all distance libraries of radar A and radar B relative to radar A;

[0017] S15. According to the endpoints of the major and minor axes of the ellipse and the height of the elliptical table, an elliptical table model is constructed with the antenna feed of radar A as the center, including the eight endpoints of the upper and lower ellipses of the elliptical table;

[0018] S16. Construct a rotation matrix according to the elevation and azimuth angles of the center of the target beam B relative to radar A;

[0019] S17. Transform the eight endpoints representing the elliptical table model by the rotation matrix, and then translate the center to the station-centered coordinates of the corresponding beam relative to radar A, to model the spatial relationship of different beams.

[0020] Preferably, in step S12, the major and minor axes of the upper and lower ellipses of the elliptical table correspond to the larger and smaller values of the horizontal and vertical beam widths, respectively, and specifically:

[0021]

[0022] where Lup L is the length of the major axis of the upper and lower ellipsoids of the elliptical table low R is the length of the minor axis of the upper and lower ellipsoids of the elliptical table cen R is the distance from the distance base to the corresponding radar antenna feed reso γ is the horizontal or vertical beam width

[0023] The rotation matrix constructed in step S16 is:

[0024]

[0025] where θ A is the pitch angle of the beam center relative to the radar A antenna feed A is the azimuth angle of the beam center relative to the radar A antenna feed.

[0026] Preferably, the specific content of step S2 includes:

[0027] S21. Model different radar beams through a beam volume matching model, and based on the maximum and minimum values of the coordinates of different elliptical tables in the global coordinate system, construct a beam bounding box;

[0028] S22. Randomly generate a series of scattered points in the beam bounding box according to the range of the bounding box;

[0029] S23. Subtract the station center coordinates of the beam A center relative to the radar A from the coordinates of all scattered points, and convert the global coordinates of all scattered points into local coordinates relative to the radar A through the corresponding rotation matrix;

[0030] S24. In the local coordinates, calculate the boundary of the elliptical table A, judge whether the scattered points are within the elliptical table, and mark each point;

[0031] S25. Repeat steps S23 and S24 to judge whether the scattered points are within the elliptical table B and mark them;

[0032] S26. Based on all the marks, obtain the number of scattered points contained in each elliptical table and the number of scattered points in the common region;

[0033] S27. Calculate the volume overlap rate of different beams in space to obtain the matching degree in space.

[0034] Preferably, the volume overlap rate is used to represent the spatial matching degree between the distance bases, specifically:

[0035]

[0036] where V overepresents the volume of the two ellipsoidal tables overlapping, V1 and V2 are the volumes of the two ellipsoidal tables in space, respectively;

[0037] The number of scattered points contained in different beams is equivalent to the size of the volume of the beams, and the number of scattered points in the common volume of different beams is equivalent to the volume of the beam overlap.

[0038] Preferably, the specific content of step S3 includes:

[0039] S31. Use the traditional consistency comparison algorithm to obtain the matched area as prior knowledge;

[0040] S32. Calculate the volume overlap rate of the comparison distance library and determine the weighting strategy according to the characteristics of the radar itself;

[0041] S33. Calculate the volume overlap rate of the matched distance library as the weight of the area, and calculate the weighted evaluation parameters in a weighted manner, including weighted average error, weighted standard deviation and weighted Pearson correlation coefficient.

[0042] Preferably, the weighted evaluation parameters are specifically:

[0043]

[0044]

[0045]

[0046]

[0047] Wherein, Z ei is the difference between the two radars Z on the ith matching area, ω i is the volume overlap rate on the ith matching area, Err w is the weighted average error, Std w is the weighted standard deviation, Z Ai is the Z value of radar A on the ith matching area, is the weighted Z mean value of radar A, r w is the weighted Pearson correlation coefficient.

[0048] A reflectivity factor weighted comparison system based on radar beam volume overlap rate, based on the reflectivity factor weighted comparison method based on radar beam volume overlap rate, comprising: a beam volume matching module, a space matching degree calculation module and a weighted reflectivity factor calculation module;

[0049] A beam volume matching module is configured to establish an elliptical platform model for representing the matched range library in space according to the matched range library information stored in the radar-based data, and to establish a beam volume matching model to obtain the beam space sampling volume of the range library by comprehensively considering the range resolution and the elevation angle and azimuth angle of the beam.

[0050] A space matching degree calculation module is configured to calculate the different beam volume overlap rates by generating a large number of random points and according to the region annotation method based on the Monte Carlo simulation method, so as to quantify the matching degree of the radar beam in space.

[0051] A weighted reflectivity factor calculation module is configured to give each matching region a corresponding weight of the reflectivity factor by the volume overlap rate, and to calculate the final weighted error, weighted standard deviation and weighted correlation coefficient in a weighted manner, so as to accurately evaluate the performance difference of the radar.

[0052] A computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to implement the reflectivity factor weighting comparison method based on the radar beam volume overlap rate.

[0053] A processing terminal includes a memory and a processor, and the memory stores a computer program executable on the processor, and the processor executes the computer program to implement the reflectivity factor weighting comparison method based on the radar beam volume overlap rate.

[0054] According to the above technical solution, compared with the prior art, the reflectivity factor weighting comparison method and system based on the radar beam volume overlap rate are provided, which can systematically solve the problem of insufficient spatial matching accuracy in traditional consistency comparison, and can improve the comparison accuracy.

[0055] By establishing the beam volume matching model, the sampling volume of a certain range library of different radars in space under a real scene is restored, the volume overlap rate of the sampling volume of different range libraries is accurately calculated based on the Monte Carlo simulation, and the final consistency comparison result is obtained in a weighted manner based on the volume overlap rate.

[0056] The present application has good business applicability and popularization, and is helpful to improve the traditional radar consistency comparison accuracy, and is suitable for different models and different working frequency range weather radar systems, and can be applied to the star-ground verification technology, and has wide business popularization value and application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute a part of the embodiments of the present application, and all other drawings obtained by those skilled in the art without creative effort based on the provided drawings also belong to the protection scope of the present application.

[0058] Figure 1 The schematic diagram of the reflectivity factor weighted comparison method based on radar beam volume overlap rate provided by the present application;

[0059] Figure 2 The schematic diagram of the consistency comparison of different weather radar distance bases provided by the present application;

[0060] Figure 3 The schematic diagram of the modeling of different weather radar beam irradiation volumes provided by the present application; wherein, (a) is the ellipsoid platform model of the radar A beam irradiation volume; (b) is the ellipsoid platform model of the radar B beam irradiation volume;

[0061] Figure 4 The schematic diagram of the volume overlap rate calculation based on Monte Carlo simulation provided by the present application; wherein, (a) is the schematic diagram of the overlap of the ellipsoid platform, (b) is the schematic diagram of the overlap part of the ellipsoid platform;

[0062] Figure 5 The schematic diagram of the radar consistency comparison result provided by the present application; wherein, (a) is the schematic diagram of the reflectivity factor correlation, (b) is the schematic diagram of the reflectivity factor weighted comparison result. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort belong to the protection scope of the present application.

[0064] The embodiments of the present application disclose a reflectivity factor weighted comparison method based on radar beam volume overlap rate, as shown in Figure 1 , comprising the following steps:

[0065] S1. According to the comparison distance base information stored in the radar-based data, an ellipsoid platform model for representing the comparison distance base is established in space, and the beam volume matching model is established by comprehensively considering the distance resolution and the pitch angle and azimuth angle of the beam to obtain the beam space sampling volume of the distance base;

[0066] S2. Based on the Monte Carlo simulation method, a large number of random points are generated, and the volume overlap rate of different beams is calculated according to the regional labeling method, so as to quantify the matching degree of the radar beam in space;

[0067] S3. By assigning a reflectivity factor corresponding weight to each matching area through the volume overlap rate, the final weighted error, weighted standard deviation and weighted correlation coefficient are calculated in a weighted manner, so as to accurately evaluate the performance difference of the radar.

[0068] In the radar data processing, usually the information within the 3dB beam width is concerned. Assuming that only the 3dB beam width is concerned, the radar beam can be approximated as a pen shape. If the information within a certain range bin of the weather radar is concerned, the shape of the radar beam irradiating a certain range bin in space can be approximated as an elliptical table. The long axis and the short axis of the upper elliptical surface of the elliptical table are determined by the beam width and the distance of the range bin center relative to the radar. The axis line (elliptical table axis line) vertically penetrating the upper and lower elliptical surfaces of the elliptical table is determined by the pitch and azimuth of the transmitted electromagnetic wave signal relative to the radar. The volume of the elliptical table in space is the sampling volume of the range bin in space. In this embodiment, the elliptical table model is established in space to approximate the beam space sampling volume of a certain range bin.

[0069] In order to further implement the above technical solutions, the specific content of step S1 includes:

[0070] S11. Extract the information of the target beam from the radar base data, including the radar latitude and longitude, antenna feed height, radar beam width, distance resolution, and the pitch angle, azimuth angle and range bin corresponding to the target beam of the radar;

[0071] S12. Calculate the long axis and the short axis of the upper and lower ellipses of the elliptical table through the distance resolution, beam width and distance of the range bin center relative to the radar;

[0072] S13. Establish a local coordinate system respectively: establish a station heart coordinate system based on the antenna feed center for each radar, and express the center of the target beam in the station heart coordinate;

[0073] S14. Unify the local coordinate system: convert the station heart coordinate of the center of the target beam B relative to the radar B into the geocentric coordinate, and then convert the geocentric coordinate into the station heart coordinate relative to the radar A, realize the unification of the coordinate system, and calculate the pitch and azimuth of the center of the target beam B relative to the antenna feed of the radar A and the distance, so as to obtain the polar coordinates of the beam center of all range bins of the radar A and the radar B relative to the radar A;

[0074] In this embodiment, the beam A and the beam B are both target beams, the target beam B is transmitted by the radar B, the target beam A is transmitted by the radar A, and the beam polar coordinate information of the radar A is itself, so no conversion is needed.

[0075] S15. Constructing the elliptical table in the local coordinate system: according to the endpoints of the major and minor axes of the ellipse, the height of the elliptical table (distance resolution), an elliptical table model is constructed with the radar A antenna feed as the center, containing eight endpoints of the upper and lower two ellipses of the elliptical table;

[0076] In this embodiment, the elliptical table model in the local coordinate system does not consider the influence of radar pitch and azimuth, therefore, the coordinates of the major axis endpoints of the upper ellipse of the elliptical table can be expressed as (±Lupa / 2, 0, Rreso / 2), Lupa represents the length of the major axis of the upper ellipse of the elliptical table, and the minor axis endpoints can be obtained in the same way;

[0077] S16. Obtaining the representation of the elliptical table model in the global coordinate system: according to the pitch and azimuth of the target beam B center relative to radar A, a rotation matrix is constructed;

[0078] S17. Transforming the eight endpoints representing the elliptical table model in direction through the rotation matrix, and then translating the center to the station center coordinate of the corresponding beam relative to radar A, to realize the modeling of the position relationship of different beams in space;

[0079] This modeling method can be extended to any point in the elliptical table, and is also applicable to beams of any width.

[0080] In order to further implement the above technical solution, step S12, the major and minor axes of the upper and lower two ellipses of the elliptical table correspond to the larger and smaller values in the horizontal and vertical beam widths, specifically;

[0081]

[0082] wherein, L up is the length of the major axis of the upper and lower ellipses of the elliptical table, L low is the length of the minor axis of the upper and lower ellipses of the elliptical table, R cen is the distance from the distance library to the corresponding radar antenna feed, R reso is the distance resolution, and γ is the horizontal or vertical beam width;

[0083] In this embodiment, although the arc length formula is used to approximate the length of the major and minor axes of the ellipse, the error can be ignored;

[0084] Step S16, the constructed rotation matrix is:

[0085]

[0086] wherein, θ A is the pitch angle of the beam center relative to the radar A antenna feed, and φ A is the azimuth angle of the beam center relative to the radar A antenna feed.

[0087] In practical applications, when different weather radars have common illumination areas, the degree of overlap of different distance banks is found by spatial matching, as shown in Figure 2 The light yellow and light blue represent different beams emitted, the yellow and blue represent the matched distance banks, and the green represents the common illumination volume. The traditional method can only match the center of the distance bank and cannot accurately calculate the volume overlap rate of the green part. To accurately calculate the beam overlap volume, the beam shape is modeled in space as an elliptical table, as shown in Figure 3 The spatial sampling volumes of different distance banks of two radars are modeled. First, an upright elliptical table is established at the origin, and then the elliptical table is rotated and translated according to the coordinates of the center of the distance bank and its pitch angle and azimuth angle to obtain the simulated actual situation. Through this method, the illumination volume of the beam in the real space can be restored to a certain extent.

[0088] To further implement the above technical solutions, the specific content of step S2 includes:

[0089] S21. Model different radar beams by a beam volume matching model, and based on the maximum and minimum values of the coordinates of different elliptical tables in the global coordinate system, construct a beam bounding box;

[0090] S22. Randomly generate a series of scattered points in the beam bounding box according to the range of the bounding box;

[0091] S23. Subtract the center coordinates of beam A relative to the station center of radar A from the coordinates of all scattered points, and convert the global coordinates of all scattered points into local coordinates relative to radar A by the corresponding rotation matrix;

[0092] S24. In the local coordinates, calculate the boundary of elliptical table A, judge whether the scattered points are in the elliptical table, and mark each point;

[0093] S25. Repeat steps S23 and S24 to judge whether the scattered points are in elliptical table B and mark them;

[0094] S26. Based on all the marks, obtain the number of scattered points contained in each elliptical table and the number of scattered points in the common area;

[0095] S27. Calculate the volume overlap rate of different beams in space to obtain the matching degree in space.

[0096] To further implement the above technical solution, when two weather radars of the same specifications are very close to each other, if the spatial matching degree of the range database is very high, then the two elliptical frustums representing the sampling volume of the range database should be highly overlapping in space; conversely, if the spatial matching degree is low, then the two elliptical frustums have only a small portion of overlapping volume or even no overlapping volume.

[0097] The spatial matching degree between the comparison distance databases is characterized by the volume overlap rate, specifically:

[0098]

[0099] Among them, V ove V1 and V2 represent the volume of the two overlapping ellipsoids, respectively, where V1 and V2 are the volumes of the two ellipsoids in space.

[0100] In this embodiment, the volume overlap rate is 1 when the two beams completely overlap; the volume overlap rate is 0 when the two beams do not intersect in space.

[0101] The number of scattered points contained in different beams is equivalent to the volume of the beam, and the number of scattered points within the common volume of different beams is equivalent to the beam overlap volume.

[0102] In this embodiment, as Figure 4 As shown, using the Monte Carlo simulation method, a large number of three points are randomly generated within a given area, and the boundary of each elliptic frustum is given through the elliptic frustum model. By determining whether the scattered points are within the boundary, each scattered point is labeled, which can clearly show the overlap of the elliptic frustums and the shape of the overlapping part. The beam volume overlap rate can be calculated by the number of points in each elliptic frustum and the number of points in the common area.

[0103] To further implement the above technical solution, step S3 includes the following:

[0104] S31. Use the traditional consistency comparison algorithm to obtain the well-matched regions as prior knowledge;

[0105] S32. Calculate the volume overlap rate of the comparison range database and determine the weighting strategy based on the characteristics of the radar itself;

[0106] S33. Calculate the volume overlap rate of the matched distance library as the weight of the region, and calculate the weighted evaluation parameters in a weighted manner, including the weighted average error, weighted standard deviation and weighted Pearson correlation coefficient.

[0107] To further implement the above technical solution, the weighted evaluation parameters are as follows:

[0108]

[0109]

[0110]

[0111]

[0112] wherein Z ei is the difference of Z of two radars in the ith matching area, ω i is the volume overlap ratio in the ith matching area, Err w is the weighted average error, Std w is the weighted standard deviation, Z Ai is the Z value of radar A in the ith matching area, is the weighted Z mean value of radar A, r w is the weighted Pearson correlation coefficient.

[0113] In the embodiment, as shown in Figure 5 , after calculating the volume overlap ratio of all matching points, the original matching result is calculated by weighting with the overlap ratio as the weight to obtain the final weighted comparison result;

[0114] Since the weight can reflect the size of the beam overlap area in the real space, reduce the error caused by different sampling spaces, and finally obtain a more accurate comparison result, it can be used not only for ground-based radar comparison, but also for spaceborne radar and ground-based radar comparison.

[0115] A reflectivity factor weighted comparison system based on radar beam volume overlap ratio, based on a reflectivity factor weighted comparison method based on radar beam volume overlap ratio, comprising: a beam volume matching module, a space matching degree calculation module and a weighted reflectivity factor calculation module;

[0116] The beam volume matching module is configured to establish an ellipsoid table model for representing the comparison distance library in space according to the comparison distance library information stored in the radar base data, and to establish a beam volume matching model to obtain the beam space sampling volume of the distance library by comprehensively considering the distance resolution and the elevation angle and azimuth angle of the beam.

[0117] The space matching degree calculation module is configured to calculate different beam volume overlap ratios by generating a large number of random points and according to the region labeling method based on the Monte Carlo simulation method, so as to quantify the matching degree of the radar beam in space.

[0118] The weighted reflectivity factor calculation module is configured to give each matching area a corresponding weight of the reflectivity factor by the volume overlap ratio, and to calculate the final weighted error, weighted standard deviation and weighted correlation coefficient in a weighted manner, so as to accurately evaluate the performance difference of the radars.

[0119] A computer readable storage medium, having stored thereon a computer program, which, when executed by a processor, implements a reflectivity factor weighted alignment method based on radar beam volume overlap ratio.

[0120] A processing terminal, comprising a memory and a processor, the memory storing a computer program capable of running on the processor, and the processor implementing a reflectivity factor weighted alignment method based on radar beam volume overlap ratio when executing the computer program.

[0121] The various embodiments are described in the specification in a progressive manner, each embodiment focusing on the differences from other embodiments, and the same or similar parts between the various embodiments can be mutually referred to. For the apparatus disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part.

[0122] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio, characterized in that, The method comprises the following steps: S1. According to the comparison distance library information stored in the radar-based data, an ellipsoid platform model for representing the comparison distance library is established in space, the distance resolution and the elevation angle and azimuth angle of the beam are comprehensively considered, a beam volume matching model is established to obtain the beam space sampling volume of the distance library; S2. Based on the Monte Carlo simulation method, a large number of random points are generated, and the overlap rate of different beam volumes is calculated according to the region labeling method, so as to quantify the matching degree of the radar beam in space; S3. Through the volume overlap rate, each matching region is given a corresponding weight of the reflectivity factor, and the final weighted error, weighted standard deviation and weighted correlation coefficient are calculated in a weighted manner to accurately evaluate the performance difference of the radar.

2. The reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio according to claim 1, characterized in that, The specific content of step S1 includes: S11. Extract the information of the target beam from the radar-based data, including the radar latitude and longitude, the antenna feed height, the radar beam width, the distance resolution, and the elevation angle, azimuth angle and distance library corresponding to the target beam of the radar; S12. The long axis and short axis of the upper and lower ellipses of the ellipsoid platform are calculated according to the distance resolution, beam width and distance of the distance library center relative to the radar; S13. A station-centered coordinate system is established for each radar based on the antenna feed center, and the center of the target beam is represented in the station-centered coordinate; S14. The station-centered coordinates of the center of the target beam B relative to the radar B are converted into the geocentric coordinates, and then the geocentric coordinates are converted into the station-centered coordinates relative to the radar A, the coordinate systems are unified, and the elevation and azimuth angles of the center of the target beam B relative to the antenna feed of the radar A and the distance are calculated to obtain the polar coordinates of the beam centers of all distance libraries of the radar A and the radar B relative to the radar A; S15. According to the endpoints of the ellipse long axis and short axis and the height of the ellipsoid platform, an ellipsoid platform model is constructed with the radar A antenna feed as the center, including eight endpoints of the upper and lower ellipses of the ellipsoid platform; S16. A rotation matrix is constructed according to the elevation and azimuth angles of the center of the target beam B relative to the radar A; S17. The eight endpoints representing the ellipsoid platform model are transformed in direction by the rotation matrix, and then the center is translated to the station-centered coordinates of the corresponding beam relative to the radar A, to realize the modeling of the position relationship of different beams in space.

3. The reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio according to claim 2, characterized in that, In step S12, the long axis and short axis of the upper and lower ellipses of the ellipsoid platform correspond to the larger value and the smaller value in the horizontal and vertical beam width respectively, which are specifically: ； where L up is the length of the major axis of the upper and lower ellipses of the elliptical table, L low is the length of the minor axis of the upper and lower ellipses of the elliptical table, R cen is the distance from the base to the corresponding radar antenna feed, R reso is the distance resolution, and γ is the horizontal or vertical beam width; In step S16, the constructed rotation matrix is: ； where θ A is the elevation angle of the beam center relative to the radar A antenna feed, and φ A is the azimuth angle of the beam center relative to the radar A antenna feed.

4. The reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio according to claim 1, characterized in that, The specific content of step S2 includes: S21. Model different radar beams through the beam volume matching model, and construct a beam bounding box based on the maximum and minimum values of the coordinates of different ellipsoid platforms in the global coordinate system; S22. A series of scattered points are randomly generated in the beam bounding box according to the range of the bounding box; S23. The coordinates of all scattered points are subtracted from the center of beam A relative to the station-centered coordinates of radar A, and the global coordinates of all scattered points are converted into local coordinates relative to radar A through the corresponding rotation matrix; S24. In the local coordinates, the boundary of the ellipsoid platform A is calculated, it is judged whether the scattered points are in the ellipsoid platform, and each point is marked; S25. Repeat step S23 and step S24 to determine whether the scatter points are within the elliptical table B and mark them; S26. Based on all the marks, obtain the number of scatter points contained in different elliptical tables and the number of scatter points in the common area; S27. Calculate the volume overlap rate of different beams in space to obtain the matching degree in space.

5. The reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio according to claim 4, characterized in that, The volume overlap rate is used to represent the spatial matching degree between the distance library, which is: ； where V ove represents the volume of the overlap of the two elliptical frustums, Vi and V2are the volumes of the two elliptical frustums in space, respectively; The number of scatter points contained in different beams is equivalent to the volume size of the beam, and the number of scatter points in the common volume of different beams is equivalent to the beam overlap volume.

6. The reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio according to claim 1, characterized in that, The specific content of step S3 includes: S31. Use the traditional consistency comparison algorithm to obtain the matched area as prior knowledge; S32. Calculate the volume overlap rate of the distance library and determine the weighting strategy according to the characteristics of the radar itself; S33. Calculate the volume overlap rate of the matched distance library as the weight of the region, and calculate the weighted evaluation parameters in a weighted manner, including weighted mean error, weighted standard deviation and weighted Pearson correlation coefficient.

7. The reflectivity factor weighting ratio comparison method based on radar beam volume overlap ratio according to claim 6, characterized in that, The weighted evaluation parameters are: ； ； ； ； where Z ei is the difference of Z of two radars in the ith matching area, ω i is the volume overlap ratio in the ith matching area, Err w is the weighted average error, Std w is the weighted standard deviation, Z Ai is the Z value of radar A in the ith matching area, is the weighted Z mean of radar A, r w is the weighted Pearson correlation coefficient.

8. A reflectivity factor weighting alignment system based on radar beam volume overlap ratio, characterized in that, A reflectivity factor weighted comparison method based on radar beam volume overlap rate according to any one of claims 1-7, comprising a beam volume matching module, a spatial matching degree calculation module and a weighted reflectivity factor calculation module; The beam volume matching module is used to establish an elliptical table model for representing the distance library in space according to the distance library information stored in the radar base data, and to establish a beam volume matching model to obtain the beam space sampling volume of the distance library by considering the distance resolution and the elevation angle and azimuth angle of the beam; The spatial matching degree calculation module is used to calculate the volume overlap rate of different beams by generating a large number of random points and calculating the volume overlap rate of different beams based on the Monte Carlo simulation method, so as to quantify the matching degree of the radar beam in space; The weighted reflectivity factor calculation module is used to assign a corresponding weight to the reflectivity factor of each matching area by the volume overlap rate, and to calculate the final weighted error, weighted standard deviation and weighted correlation coefficient in a weighted manner to accurately evaluate the performance difference of the radar.

9. A computer-readable storage medium, characterized in that, A computer program is stored thereon, which is executed by a processor to implement a reflectivity factor weighted comparison method based on radar beam volume overlap rate according to any one of claims 1-7.

10. A processing terminal, characterized by, It includes a memory and a processor, and the memory stores a computer program that can be run on the processor, and the processor executes the computer program to implement a reflectivity factor weighted comparison method based on radar beam volume overlap rate according to any one of claims 1-7.

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