A method for wind field inversion of a dual-laser wind lidar based on wind observation of valley bridges

Abstract

The present invention relates to a method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation, belonging to the field of radar meteorology. The method includes: obtaining radar radial data through coordinated scanning by two radars and calculating the coordinate information of radar radial data points; calculating the three-dimensional wind field coordinate information of the target and inverting the radar radial data through the IVAP technology to obtain horizontal wind data; screening the original data points for estimating the three-dimensional wind field data of a single target one by one, performing quality control on the screened original data points, and finally estimating the wind speed data of the target wind field data points. The present invention can quickly extract the key data points that are most valuable for estimating the wind speed of unknown points from a large number of radar scan data points, significantly reduce data redundancy, improve the calculation efficiency, and is of great significance for real-time wind field inversion and dynamic monitoring.

Description

Technical Field

[0001] The present invention relates to the field of radar meteorology, and in particular to a method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation. Background Art

[0002] In the fields of meteorological observation and wind engineering, the wind field characteristics in the valley bridge area have an important impact on the safety of bridge structures, traffic operation, and the surrounding environment. Due to the complex terrain, the wind field in the valley bridge area often exhibits a high degree of non-uniformity and dynamic changes. In recent years, laser wind lidar technology has gradually become an important means of wind field observation due to its advantages such as high precision, non-contact measurement, and high spatial resolution. However, when a single laser wind lidar observes complex terrain, there are still certain limitations, such as observation blind spots and limited data coverage. Therefore, traditional single-point wind speed measurement methods are difficult to comprehensively and accurately reflect the spatial distribution and variation characteristics of the wind field. Summary of the Invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art, and provides a method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation, which solves the deficiencies existing in the prior art.

[0004] The purpose of the present invention is achieved through the following technical solutions: A method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation, the method includes:

[0005] S1. Coordinate scanning is performed by two radars to obtain radar radial data, and the coordinate information of the radar radial data points is calculated;

[0006] S2. Calculate the three-dimensional wind field coordinate information of the target, and invert the radar radial data through the IVAP technology to obtain horizontal wind data;

[0007] S3. Screen the original data points for estimating the three-dimensional wind field data of a single target one by one, perform quality control on the selected original data points, and finally estimate the wind speed data of the target wind field data points.

[0008] The calculation of the coordinate information of the radar radial data points specifically includes the following content:

[0009] A1. Let the two radars be radar and radar , where the longitude, latitude, and altitude information of radar A is , radar 's longitude, latitude, and altitude information is , with the due east direction as the positive direction of the axis, the due north direction as the positive direction of the axis, and the vertically upward direction as the In the positive direction of the axis, Cartesian rectangular coordinate systems with the positions of the two radars as the coordinate origins are respectively created;

[0010] A2. From the elevation angle , azimuth angle , number of range bins , and range bin length information in the multi-layer RPI scanning mode, calculate the coordinates of the radial data points relative to the radar in the rectangular coordinate system. Among them, , is the number of radial data points, and RPI represents azimuth sector scan;

[0011] A3. Calculate the longitude, latitude, and altitude information of the radial data points by calculating the coordinate information of the single-radar data points obtained in A2 relative to the radar and the longitude, latitude, and altitude information of the radar itself. .

[0012] The specific calculation of the target three-dimensional wind field coordinate information includes the following:

[0013] B1. Calculate the longitude, latitude, and altitude information of the center of the measured space from the longitude, latitude, and altitude information of the two radars as ;

[0014] B2. Set the distance resolution in the radial, latitudinal, and vertical directions of the target three-dimensional wind field to be . Taking the center of the measured space as the origin and as the step size, expand in the radial, latitudinal, and vertical directions respectively, and calculate the minimum values , , and the maximum values , , in the three directions of the radial, latitudinal, and vertical directions of the three-dimensional wind field;

[0015] B3. Obtain the longitude, latitude, and altitude information of a single data point of the target three-dimensional wind field expressed as , where , , , , , are all positive integers.

[0016] The specific process of inverting the radar radial data to obtain horizontal wind data through the integrated velocity-azimuth processing technique (IVAP) includes the following:

[0017] C1. The IVAP technology observes the radial velocity data and azimuth information through radar. When the elevation angle of the radar scan is less than the set value, the velocity components of the wind field are inverted using the least squares method. , , the radial velocity observed by the radar is expressed as the projection of the velocity components of the wind field , in the radar beam direction, where , is the elevation angle of the radar beam, is the azimuth angle of the radar beam, representing the angle between the radar beam and the due north direction, is the velocity component in the east-west direction, and 𝑣 is the velocity component in the north-south direction;

[0018] C2. It is set that the wind field is uniform within the range of the azimuth angle , then the velocity components of the wind field are calculated by the formula as and , where and are the ranges of the azimuth angle.

[0019] The S3 specifically includes the following contents:

[0020] S31. Taking the due east direction as the positive direction of the axis, the due north direction as the positive direction of the axis, and the vertically upward direction as the positive direction of the axis, a Cartesian rectangular coordinate system with the current radar location as the origin is created. The target data points are traversed, and using the longitude, latitude, and altitude information of the data points and the current radar, the coordinate information of a certain target data point in the rectangular coordinate system is calculated ;

[0021] S32. In the three-dimensional rectangular coordinate system, the sphere with the data point as the center and as the radius is projected onto the plane axis, axis, and the origin constitute, and the sphere is projected onto the plane formed by the axis, the ray , and the origin constitute. Four auxiliary angles are calculated from the two projections respectively , , , to determine whether there is an intersection between the target data point and the scanning range of the radar at the origin;

[0022] S33. Determine the target data point to check if it is within the single scan range of the radar. If both criterion a and criterion b are satisfied, the data point can obtain the estimated value through subsequent steps, and continue with step S34 to screen the elevation angle of the original data point. Otherwise, analyze the next target data point and repeat the judgment in step S33 until a target data point that meets the conditions is obtained;

[0023] S34. Start traversing from the first scan layer of both radars, and determine if each scan layer intersects with a sphere centered at the current target data point with as the radius. If the elevation angle of the scan layer meets criterion c, the original data contained in this scan layer can be used to estimate the target data point . Continue with step S35 to screen the azimuth angle of the original data point. Otherwise, analyze the next scan layer and repeat the judgment in step S34 until a scan layer that meets the conditions is obtained;

[0024] S35. Traverse all the radials on the radar scan layer obtained in step S34, and determine if the azimuth angle of each radial relative to the radar conforms to criterion d. If the azimuth angle of the radial meets criterion d, continue with step S36 to screen the range bins of the radial data points. Otherwise, analyze the next radial and repeat the judgment in step S35 until a radial that meets the conditions is obtained;

[0025] S36. Traverse all the range bins on a single radial obtained in step S35, and screen out the original data points within from the target data point . Determine if each range bin number conforms to criterion e. If the bin number meets criterion e, and the wind speed of the original data point on this range bin is a valid value, continue with step S37 to screen the original data point. Otherwise, analyze the next range bin and repeat the judgment in step S36 until a range bin number that meets the conditions is obtained, indicating the coordinates of the original data in the current coordinate system;

[0026] S37. Calculate for a single target data point and the original data point obtained in step S36 to get the spatial distance between the two points. If the distance If the criterion f is satisfied, record the original data point; otherwise, analyze the next original data point. Repeat the judgment in step S37 until all original data points that meet the conditions are obtained, and then continue with step S38;

[0027] S38. Statistically analyze and calculate all the original data points that meet the conditions obtained in step S37 to obtain the number of original data points used to estimate the target data point , and set a quantity threshold . If , it is considered that the amount of original data is sufficient; otherwise, directly set the wind speed of this data point to an invalid value, and then execute step S32 to process the next target data point. If the amount of original data is sufficient, calculate the mean values of the original data points , and the standard deviations , of the velocity components , . Set the threshold , and remove the data points whose values in the , velocity components exceed the corresponding thresholds. After the processing is completed, record the number of remaining original data points as ;

[0028] S39. Calculate the weight values of each original data point and estimate the target data point. From , obtain the velocity components of the data point , . represents the weight of the original data point . , is the number of original data points for calculating the current data point . represents the velocity component of the original data point or . represents the velocity component of the data point or ;

[0029] S310. Synthesize the horizontal wind at the target data point from the , velocity components.

[0030] The expression of the criterion a includes: , represents the spatial distance between the target data point and the origin, is the maximum number of distance libraries, is the length of the distance library;

[0031] The expression of the criterion b includes: or , and respectively correspond to the elevation angles of the first scan and the last scan of the radar in the multi-layer RPI scan, represents the total number of scans of the radar;

[0032] The expression of the decision c includes: , where is the elevation angle value of the th scan layer data, , is the total number of scan layers;

[0033] The expression of the criterion d includes: , where is the azimuth angle of the th scan layer, the th radial, , is the th total number of radials of the scan layer;

[0034] The expression of the criterion e includes: , roughly screening out the original data points within from the target data point , , represents the th scan layer, the th radial, the th distance library, , is the th scan layer, the th total number of distance libraries of the radial;

[0035] The expression of the criterion f includes: .

[0036] The specific process of obtaining radar radial data through coordinated scanning by two radars includes:

[0037] Place the two radars at both ends of the bridge respectively, and use the multi-layer RPI mode for coordinated scanning at the same time to obtain data near the bridge deck;

[0038] Preprocess and quality control the obtained data to ensure the accuracy and reliability of the data, and obtain radar radial data.

[0039] The present invention has the following advantages: A method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation can quickly extract key data points most valuable for estimating the wind speed at unknown points from a large number of radar scan data points, significantly reducing data redundancy and improving calculation efficiency, which is of great significance for real-time wind field inversion and dynamic monitoring; by calculating the mean and standard deviation of wind field data points and setting dynamic thresholds based on these statistics, quality control of radar scan data points is achieved, effectively eliminating abnormal data points. This not only reduces the interference of redundant data on the wind field inversion results but also improves the automation and reliability of data screening, enabling better adaptation to the non-uniformity and dynamic changes of the wind field, and providing more efficient and accurate data support for real-time wind field inversion and dynamic monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a schematic flow chart of the present invention;

[0041] Figure 2 is a schematic diagram of a three-dimensional rectangular coordinate system;

[0042] Figure 3 is a schematic diagram of the projection coordinates on the plane xOy;

[0043] Figure 4 is a schematic diagram of the projection coordinates on the plane zOm. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Usually, the components of the embodiments of the present application described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the protection scope of the present application claimed, but only represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the protection scope of the present application. The present invention will be further described below with reference to the accompanying drawings.

[0045] As Figure 1 shown, the present invention specifically relates to a method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation. By optimizing the collaborative observation strategy and data processing algorithm of the dual radars, the wind field inversion in the valley bridge area is realized, the wind field environment around the bridge is monitored, and the safety of bridge construction workers and vehicle traffic is ensured; it specifically includes the following content.

[0046] Step 1: The two radars perform coordinated scans to obtain radial data;

[0047] 1.1. Two radars are located at both ends of the bridge respectively, and cooperate to scan simultaneously using the multi-layer RPI (azimuth sector scan) mode to obtain data near the bridge deck.

[0048] 1.2. Preprocess and quality control the data, including removing noise, interference, etc., to ensure the accuracy and reliability of the data, and obtain the radar radial data.

[0049] Step 2. Calculate the coordinate information of the radar radial data points;

[0050] 2.1. Let the two radars be radar and radar respectively. The longitude, latitude, and altitude information of radar A is , and the longitude, latitude, and altitude information of radar is . Taking the due east direction as the positive direction of the axis, the due north direction as the positive direction of the axis, and the vertically upward direction as the positive direction of the axis, create Cartesian rectangular coordinate systems with the positions of the two radars as the coordinate origins respectively.

[0051] 2.2. Calculate the coordinate of the data points of a single radar. From the elevation angle , azimuth angle , number of range bins , and range bin length information in the multi-layer RPI scan mode, calculate the coordinate of the radial data point relative to the radar in the rectangular coordinate system, where , and is the number of radial data points.

[0052] 2.3. Calculate the longitude, latitude, and altitude information of the radial data point by calculating the coordinate information of the single radar data point relative to the radar obtained in 2.2 and the longitude, latitude, and altitude information of the radar itself, where , and is the number of radial data points.

[0053] Step 3. Calculate the three-dimensional wind field coordinate information of the target;

[0054] 3.1. Calculate the longitude, latitude, and altitude information of the center of the measured space from the longitude, latitude, and altitude information of the two radars:

[0055] ,

[0056] 3.2. Based on the topographic information near the bridge, initially calculate the maximum range of the three-dimensional wind field. Set the distance resolution of the target three-dimensional wind field in the radial, latitudinal, and vertical directions to be . Taking the center of the measured space as the origin and as the step size, expand in the radial, latitudinal, and vertical directions respectively, and calculate the minimum values , , and the maximum values , , of the three-dimensional wind field in the radial, latitudinal, and vertical directions.

[0057] 3.3. The longitude, latitude, and altitude information of a single data point in the target three-dimensional wind field can be expressed as:

[0058] ,

[0059] where, , , , are all positive integers.

[0060] Step 4. Invert the horizontal wind data from the radial wind data;

[0061] Based on the assumption of local uniformity of the wind field, use the integral velocity-azimuth processing technique (IVAP) to invert the horizontal wind from the radial wind data. When the radar scan elevation angle is less than 20°, the vertical velocity is not considered. The IVAP technique uses the radial velocity data and azimuth angle information to invert the horizontal components , of the wind field by the least squares method. The radial velocity observed by the radar can be expressed as the projection of the velocity components , of the wind field in the radar beam direction:

[0062] ,

[0063] where, is the elevation angle of the radar beam; is the azimuth angle of the radar beam, representing the angle between the radar beam and the due north direction; is the velocity component in the east-west direction, and 𝑣 is the velocity component in the north-south direction.

[0064] During the calculation process, first perform screening and averaging operations on the radial velocity data observed by the radar to remove invalid values.

[0065] Assume that at the azimuth angle Within the range, the wind field is uniform, and the velocity components of the wind field can be calculated by the following equations:

[0066] ,

[0067] ,

[0068] where, and are the azimuth ranges.

[0069] Step 5: Use the original data points obtained in Step 2 and the longitude, latitude, and altitude coordinate information of the target three-dimensional wind field in Step 3 to calculate the set of original data points for estimating a single data point in the target wind field. When setting interpolation estimation, select the original data points within (including ) in the spatial distance from the estimation point within the detection range of the two radars. To improve the screening efficiency, by projecting onto multiple coordinate planes, quickly obtain the range information of the scan layer number, radial number, and distance bin number where the qualified original data points are located, and then calculate the coordinates of the original data points and the target wind field data points to obtain the set of original data points within from the target data point. The specific method is as follows:

[0070] 5.1. Screen the original data points of the two radars respectively: As shown in Figure 2 , with the due east direction as the positive direction of the axis, the due north direction as the positive direction of the axis, and the vertically upward direction as the positive direction of the axis, create a Cartesian rectangular coordinate system with the position of the current radar as the origin . Traverse the target data points, and use the longitude, latitude, and altitude information of the data points and the radar to calculate the coordinate information of a certain data point in the rectangular coordinate system . Connect the center of the sphere and the origin to make a ray . Project onto the plane axis, axis, and the origin constitutes the plane to obtain the ray .

[0071] 5.2. In the three-dimensional rectangular coordinate system, project the sphere with the data point as the center of the sphere and as the radius onto the plane axis, axis, and the origin constitutes the plane . This projection is as shown inFigure 3 As shown; in a three-dimensional rectangular coordinate system, project the sphere onto the plane axis, ray and the origin constitute the plane projection, and the projection is as Figure 4 shown. Calculate the values of four auxiliary angles from the two projections respectively to determine whether there is an intersection between the target data point and the scanning range of the radar at the origin. The four auxiliary angles , , , are calculated as shown in the following formula:

[0072] ,

[0073] ,

[0074] ,

[0075] ,

[0076] ,

[0077] ,

[0078] where, represents the coordinates of the target data point in the current coordinate system, represents the spatial distance between the target data point and the origin.

[0079] 5.3. Determine whether the target data point is within the single scan range of the radar. If both criterion a and criterion b are satisfied, the target data point can obtain an estimated value through subsequent steps, and continue to screen the elevation angle of the original data point in 5.4. Otherwise, analyze the next target data point and repeat the judgment in 5.3 until a target data point that meets the conditions is obtained. The expressions of criterion a and b are as follows:

[0080] a. ,

[0081] b. or ,

[0082] where, is the maximum number of distance bins, is the length of the distance bin, and correspond to the elevation angles of the first scan and the last scan in the multi-layer RPI scan of the radar respectively, represents the total number of scans of the radar.

[0083] 5.4. Starting from the first scan layer of the two radars respectively, traverse to determine whether each scan layer intersects with the sphere centered at the current target data point and with as the radius. If the elevation angle of the scan layer satisfies criterion c, then the scan layer contains the raw data that can be used to estimate the target data point . Continue with the azimuth angle screening of the raw data points in 5.5. Otherwise, analyze the next scan layer and repeat the judgment in 5.4 until a scan layer that meets the conditions is obtained. The expression of criterion c is as follows:

[0084] c、 ,

[0085] where is the elevation angle value of the scan data of the th layer, , is the total number of scan layers.

[0086] 5.5. Traverse all the radials on the radar scan layer obtained in 5.4 to determine whether the azimuth angle of each radial relative to the radar conforms to criterion d. If the azimuth angle of the radial satisfies criterion d, then continue with the range bin screening of the radial data points in 5.6. Otherwise, analyze the next radial and repeat the judgment in 5.5 until a radial that meets the conditions is obtained. The expression of criterion d is as follows:

[0087] d、 ,

[0088] where is the azimuth angle of the rd scan layer and the th radial, , is the total number of radials of the th scan layer.

[0089] 5.6. Traverse all the range bins on the single radial obtained in 5.5, roughly screen out the raw data points within from the target data point , and judge whether each range bin number conforms to criterion e. If the bin number satisfies criterion e, and the wind speed of the raw data point on this range bin is a valid value, then continue with the screening of the raw data points in 5.7. Otherwise, analyze the next range bin and repeat the judgment in 5.6 until a range bin number that meets the conditions is obtained. The expression of criterion e is as follows:

[0090] e, ,

[0091] wherein, is the spatial distance between the target data point obtained in 5.2 and the origin of the coordinate system, represents the th scanning layer, the th radial direction, and the th distance bin, , is the total number of distance bins in the th scanning layer and the th radial direction.

[0092] 5.7. Calculate the spatial distance between a single target data point and the original data point obtained in 5.6 to obtain the spatial distance between the two points. If the distance satisfies the criterion f, record the original data point; otherwise, analyze the next original data point and repeat the judgment in 5.7 until an original data point that meets the conditions is obtained, and then continue with the content of 5.8. The expression of criterion f is as follows:

[0093] f, ,

[0094] wherein, and respectively represent the coordinates of the target data point and the original data point in the current coordinate system.

[0095] 5.8. Statistically analyze and calculate all the original data points that meet the conditions obtained in 5.7 to obtain the number of original data points used to estimate the target data point . To improve the accuracy of the three-dimensional wind field data and avoid excessive wind field errors caused by too little effective data during estimation, a quantity threshold is set. If , it is considered that the amount of original data is sufficient; otherwise, directly set the wind speed of this data point to an invalid value, and then execute the content of 5.2 to process the next target data point. If the amount of original data is sufficient, calculate the mean values , of the velocity components of the original data points , and the standard deviations , , set the threshold , and use , Eliminate the data points in the velocity components whose values exceed the corresponding thresholds. After the processing is completed, record the number of remaining original data points as . The expression for the threshold is as follows:

[0096] ,

[0097] where represents the z-th original data point 's or , , is the number of original data points for calculating the threshold.

[0098] 5.9. Calculate the weight values of each original data point and estimate the target data point. The 's , velocity components are obtained from the following formula.

[0099] ,

[0100] where represents the weight of the original data point , , is the number of original data points for calculating the current data point , represents the velocity component of the original data point or , represents the velocity component of the data point or .

[0101] 5.10. Synthesize the horizontal wind at the target data point from the , velocity components. The magnitude of the horizontal wind and the direction of the horizontal wind are calculated as shown in the following formulas:

[0102] ,

[0103] ,

[0104] ,

[0105] where it is stipulated that the incoming direction of the horizontal wind is the wind direction of the horizontal wind, taking the due north direction , and the direction of the horizontal wind is .

[0106] The above are only the preferred embodiments of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein, and should not be regarded as excluding other embodiments. Instead, it can be used in various other combinations, modifications, and improvements, and can be changed within the scope of the concept described herein through the above teachings or the techniques or knowledge in related fields. Any changes and variations made by those skilled in the art without departing from the spirit and scope of the present invention shall fall within the protection scope of the appended claims of the present invention.

Claims

1. A method for wind field inversion of a dual-laser wind lidar based on valley bridge wind observation, characterized in that: The method includes: S1. Obtain radar radial data through coordinated scanning by two radars, and calculate the coordinate information of radar radial data points; S2. Calculate the three-dimensional wind field coordinate information of the target, and invert the radar radial data through the IVAP technology to obtain horizontal wind data; S3. Screen the original data points for estimating the three-dimensional wind field data of a single target one by one, perform quality control on the screened original data points, and finally estimate the wind speed data of the target wind field data points; The specific content of S3 includes the following: S31. With the due east direction as the positive direction of the axis, the due north direction as the positive direction of the axis, and the vertically upward direction as the positive direction of the axis, create a Cartesian rectangular coordinate system with the current position of the radar as the origin . Traverse the target data points, and use the longitude, latitude, and altitude information of the data points and the radar to calculate the coordinate information of a certain target data point in the rectangular coordinate system . Set a sphere with the data point as the center of the sphere and as the radius. Connect the center of the sphere and the origin to make a ray . Project onto the plane formed by the axis, the axis, and the origin to obtain the ray ; S32. In a three-dimensional rectangular coordinate system, project a sphere centered at the data point with a radius of onto the plane formed by the axis, the axis, and the origin to form a plane . Project the sphere onto the plane formed by the axis, the ray , and the origin to form a plane . Calculate the values of four auxiliary angles , , , from the two projections to determine whether there is an intersection between the target data point and the scanning range of the radar at the origin; S33. Determine the target data point Whether it is within the single scan range of the radar. If both criterion a and criterion b are satisfied, the target data point will obtain the estimated value through subsequent steps and continue to perform step S34 to screen the elevation angle of the original data point. Otherwise, the next target data point will be analyzed, and the judgment in step S33 will be repeated until a target data point that meets the conditions is obtained; S34. Traverse from the first scan layer of the two radars respectively, and determine whether each scan layer intersects with a sphere centered at the current target data point and with as the radius. If the elevation angle of the scan layer satisfies criterion c, the scan layer contains the raw data that can be used to estimate the target data point . Continue to step S35 to screen the azimuth angle of the raw data point. Otherwise, analyze the next scan layer and repeat the judgment in step S34 until a scan layer that meets the conditions is obtained; S35. Traverse all the radials on the radar scan layer obtained in step S34, and judge the azimuth angle of each radial relative to the radar whether it meets the criterion d. If the azimuth angle of the radial meets the criterion d, continue to perform step S36 to screen the range bins of the radial data points; otherwise, analyze the next radial and repeat the judgment in step S35 until a radial that meets the conditions is obtained. S36. Traverse all the distance libraries on a single radial direction obtained in step S35, and screen out the original data points within a distance of from the target data point . Judge whether each distance library count meets criterion e. If the library count satisfies criterion e and the wind speed of the original data points on this distance library is an effective value, then continue with step S37 to screen the original data points. Otherwise, analyze the next distance library and repeat the judgment in step S36 until a distance library count that meets the conditions is obtained. represents the coordinates of the original data in the current coordinate system; S37. For a single target data point and the original data point obtained in step S36 perform a calculation to obtain the spatial distance between the two points . If the distance satisfies the criterion f, record the original data point; otherwise, analyze the next original data point, repeat the judgment in step S37 until an original data point that meets the conditions is obtained, and then continue with step S38; S38. Statistically calculate all the qualified original data points obtained in step S37 to obtain the number of original data points used to estimate the target data point ; Set a quantity threshold . If , it is considered that the original data volume is sufficient; otherwise, directly set the wind speed of this data point to an invalid value, then execute step S32 to process the next target data point. If the original data volume is sufficient, calculate the mean values and of the velocity components of the original data points and respectively, as well as the standard deviations and . Set the threshold . Remove the data points in and whose values exceed the corresponding thresholds in the velocity components. After the processing is completed, record the number of remaining original data points as .; S39. Calculate the weight values of each original data point and estimate the target data point. From obtain the data point 's and velocity components. represents the weight of the original data point . , is the number of original data points for calculating the current data point . represents the velocity component of the original data point or . represents the velocity component of the data point or . S310. Synthesize the horizontal wind at the target data point from the and speed components.

2. The dual-laser wind measurement radar wind field inversion method based on valley bridge wind observation according to claim 1, wherein: The specific content of calculating the coordinate information of radar radial data points includes the following: A1. Let the two radars be radar and radar . Among them, the longitude, latitude, and altitude information of radar A is , and the longitude, latitude, and altitude information of radar is . Taking the due east direction as the positive direction of the axis, the due north direction as the positive direction of the axis, and the vertically upward direction as the positive direction of the axis, create Cartesian rectangular coordinate systems with the positions of the two radars as the coordinate origins respectively; A2. Elevation angle in the multi-layer RPI scanning mode , azimuth angle , number of range bins , range bin length information, and calculate the coordinates of the radial data points relative to the radar in the Cartesian coordinate system , where , is the number of radial data points, and RPI represents azimuth sector scanning; A3. Calculate the coordinate information of the single radar data points obtained in A2 relative to the radar, along with the longitude, latitude, and altitude information of the radar itself, to obtain the radial data points of the longitude, latitude, and altitude information .

3. A method for wind field inversion of a dual-laser wind measurement radar based on valley bridge wind observation according to claim 2, characterized in that: The specific content of calculating the three-dimensional wind field coordinate information of the target includes the following: B1. The longitude, latitude, and altitude information of the center of the measured space calculated from the longitude, latitude, and altitude information of the two radars are ; B2. Set the distance resolution of the target three-dimensional wind field in the radial, zonal, and vertical directions to be , with the center of the measured space as the origin, and with as the step size, expand in the radial, zonal, and vertical directions respectively. Calculate the minimum values of the three-dimensional wind field in the radial, zonal, and vertical directions to be , , and the maximum values to be , , ; B3. Obtain the longitude, latitude, and altitude information of a single data point in the target three-dimensional wind field, expressed as , where , , , , , are all positive integers.

4. A dual-laser wind measurement radar wind field inversion method based on valley bridge wind observation according to claim 1, characterized in that: The specific content of inverting the radar radial data through the IVAP technology to obtain horizontal wind data includes the following: C1. The IVAP technology observes radial velocity data and azimuth information through radar. When the elevation angle of the radar scan is less than the set value, the velocity components of the wind field are inverted using the least squares method. , , the radial velocity observed by the radar is expressed as the projection of the velocity components of the wind field , in the direction of the radar beam, , where is the elevation angle of the radar beam, is the azimuth angle of the radar beam, representing the angle between the radar beam and the due north direction, is the velocity component in the east-west direction, and 𝑣 is the velocity component in the north-south direction; C2. Set that the wind field is uniform within the azimuth range Then, the velocity components of the wind field are calculated by the formula as and , where and are the ranges of the azimuth angle.

5. A method for wind field inversion of a dual-laser wind measurement radar based on valley bridge wind observation according to claim 1, characterized in that: The expression of the criterion a includes: , represents the spatial distance between the target data point and the origin, is the maximum number of distance bins, is the length of the distance bin; The expression of the criterion b includes: or , and respectively correspond to the elevation angles of the first scan and the last scan of the radar in the multi-layer RPI scan, is the total number of scans of the radar; The expression of the criterion c includes: , where is the elevation angle value of the -th layer of scanning data, , is the total number of scanning layers; The expression of the criterion d includes: , where is the azimuth angle of the th scanning layer and the th radial direction, , is the total number of radial directions of the th scanning layer; The expression of the criterion e includes: , indicating the th scanning layer, the th distance bin in the th radial direction, , being the total number of distance bins in the th scanning layer and the th radial direction; The expression of the criterion f includes: .

6. A method for wind field inversion of a dual-laser wind measurement radar based on valley bridge wind observation according to any one of claims 1-5, characterized in that: The specific content of obtaining radar radial data through coordinated scanning by two radars includes: Set the two radars at both ends of the bridge respectively, and use the multi-layer RPI mode for coordinated scanning simultaneously to obtain the data near the bridge deck; Preprocess and perform quality control on the obtained data to ensure the accuracy and reliability of the data, and obtain the radar radial data.

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