A method, device, equipment and storage medium for wind field measurement

Abstract

The present invention discloses a wind field measurement method, device, equipment and storage medium, which are applied to the field of wind field measurement. Based on a drone equipped with a wind field measurement sensor, wind field measurement is carried out in a target area to obtain first wind field data, and the first wind field data is corrected based on the three-dimensional velocity of the drone; based on a vertical wind lidar, wind field measurement is carried out in the target area to obtain second wind field data, and the drone wake interference data in the second wind field data is deleted; the second wind field data is merged with the first wind field data in the non-radar blind area to obtain non-radar blind area wind field data; the first wind field data in the radar blind area is determined as the radar blind area wind field data, and the target wind field of the target area is determined based on the non-radar blind area wind field data and the radar blind area wind field data. The present invention uses a vertical wind lidar and a drone system equipped with a wind field measurement sensor for joint observation, and jointly analyzes and calculates the data of both to improve the measurement accuracy.

Description

Technical Field

[0001] The present invention relates to the field of wind field measurement, and particularly relates to a wind field measurement method, a wind field measurement device, an electronic device, and a computer-readable storage medium. Background Art

[0002] Currently, the measurement of the vertical wind field by lidar is based on the assumption of wind field uniformity, assuming that the wind field within a small cone angle directly above is uniform. Using the triangular projection relationship, the radial wind speed results in each direction are jointly calculated to obtain an equivalent wind field data directly above. In conventional scenarios, the measurement results of the lidar for the wind field directly above are relatively accurate. However, in complex terrain and high-rise building scenarios, the error of the wind field uniformity assumption will increase significantly, and the wind profile information measured by the lidar cannot accurately represent the overall wind field results.

[0003] Due to the increased non-uniformity of the wind field under complex terrain, the measurement result deviation of conventional vertical wind measurement radars will also increase significantly, unable to meet the requirements for accurate wind field measurement in corresponding sites, such as wind power exploration in mountainous scenarios, scientific research on building wind engineering, etc. Summary of the Invention

[0004] The purpose of the present invention is to provide a wind field measurement method, device, equipment, and storage medium, which are applied to the field of wind field measurement. This method uses a vertical wind measurement lidar and an unmanned aerial vehicle system equipped with a wind speed and direction sensor for joint observation, and jointly analyzes and calculates the data of both to improve measurement accuracy.

[0005] To solve the above technical problems, the present invention provides a wind field measurement method, including:

[0006] Performing wind field measurement in a target area based on an unmanned aerial vehicle equipped with a wind field measurement sensor to obtain first wind field data, and correcting the first wind field data based on the three-dimensional speed of the unmanned aerial vehicle;

[0007] Performing wind field measurement in the target area based on a vertical wind measurement lidar to obtain second wind field data, and deleting the unmanned aerial vehicle wake interference data in the second wind field data;

[0008] Merging the second wind field data with the first wind field data in the non-radar blind area to obtain non-radar blind area wind field data;

[0009] Determining the first wind field data in the radar blind area as radar blind area wind field data, and determining the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data.

[0010] Optionally, deleting the unmanned aerial vehicle wake interference data in the second wind field data includes:

[0011] Determine the target time when the UAV reaches the target altitude during ascent;

[0012] Determine the spatial distance between the UAV and the radar beam at the same altitude when the UAV is at the target altitude;

[0013] Determine the horizontal wind speed collected by the UAV when the UAV is at the target altitude;

[0014] Determine the value obtained by dividing the spatial distance by the horizontal wind speed as the spoiler transfer time, and determine the sum of the spoiler transfer time and the target time as the target interference time;

[0015] Determine the second wind field data collected at the target interference time as the wind field data to be corrected;

[0016] Delete the data collected at the target altitude from the wind field data to be corrected.

[0017] Optionally, the first wind field data obtained by measuring the wind field in the target area based on a UAV equipped with a wind field measurement sensor includes:

[0018] Control the UAV equipped with the wind field measurement sensor to fly directly above the vertical wind lidar and ascend uniformly in the target area at a preset speed to obtain the first initial wind field data;

[0019] Perform distance sliding averaging on the first initial wind field data according to a preset scale to obtain the first wind field data.

[0020] Optionally, the preset scale is one-half of the lidar pulse width.

[0021] Optionally, the process of merging the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data includes:

[0022] Average the wind speed values in the second wind field data collected at the same altitude to obtain the average wind speed value;

[0023] Vectorially sum the wind directions in the second wind field data collected at the same altitude to obtain the average wind direction;

[0024] Determine the second average wind field data based on the average wind speed value and the average wind direction at each altitude;

[0025] Merge the second average wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data.

[0026] Optionally, merging the second wind field data with the first wind field data in the non-radar blind area to obtain non-radar blind area wind field data includes:

[0027] Averaging the wind speed values of the second wind field data and the first wind field data at the same altitude to obtain an average wind speed value;

[0028] Performing vector summation on the wind directions of the second wind field data and the first wind field data at the same altitude to obtain an average wind direction;

[0029] Constructing the non-radar blind area wind field data based on the average wind speed values and the average wind directions at each altitude.

[0030] Optionally, the measurement mode of the vertical wind lidar is a four-beam measurement mode.

[0031] To solve the above technical problems, the present invention provides a wind field measurement device, including:

[0032] A first module, configured to perform wind field measurement in a target area based on a drone carrying a wind field measurement sensor to obtain first wind field data, and correct the first wind field data based on the three-dimensional speed of the drone;

[0033] A second module, configured to perform wind field measurement in the target area based on a vertical wind lidar to obtain second wind field data, and delete the drone wake interference data in the second wind field data;

[0034] A third module, configured to merge the second wind field data with the first wind field data in the non-radar blind area to obtain non-radar blind area wind field data;

[0035] A fourth module, configured to determine the first wind field data in the radar blind area as radar blind area wind field data, and determine the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data.

[0036] To solve the above technical problems, the present invention provides an electronic device, including:

[0037] A memory, configured to store a computer program;

[0038] A processor, configured to implement the above-mentioned wind field measurement method when executing the computer program.

[0039] To solve the above technical problems, the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the wind field measurement method is implemented.

[0040] It can be seen that the method of the present invention measures the wind field in the target area by using a drone equipped with a wind field measurement sensor to obtain the first wind field data, and corrects the first wind field data based on the three-dimensional velocity of the drone; measures the wind field in the target area by using a vertical wind lidar to obtain the second wind field data, and deletes the drone wake interference data in the second wind field data; merges the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data; determines the first wind field data in the radar blind area as the radar blind area wind field data, and determines the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data. The method of the present invention uses a vertical wind lidar and a drone system equipped with a wind field measurement sensor for joint observation, and jointly analyzes and calculates the data of both to improve the measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0042] Figure 1 It is a flowchart of a wind field measurement method provided by an embodiment of the present invention;

[0043] Figure 2 It is a schematic diagram of the influence of drone wake provided by an embodiment of the present invention;

[0044] Figure 3 It is a structural block diagram of a wind field measurement device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0046] The measurement of the vertical wind field by lidar is generally based on the assumption of wind field uniformity, assuming that the wind field within a small cone angle directly above is uniform, and using the triangular projection relationship to jointly calculate an equivalent wind field data directly above from the radial wind speed results in each direction.

[0047] In a conventional scenario, the measurement results of lidar for the wind field directly above are relatively accurate. However, in complex terrain and high-rise building scenarios, the error of the wind field uniformity assumption will increase significantly, and the wind profile information measured by lidar cannot accurately represent the overall wind field results.

[0048] Due to the increased non-uniformity of the wind field under complex terrain, the measurement error of conventional vertical wind lidar will also increase significantly, unable to meet the requirements of accurate wind field measurement for corresponding sites, such as wind power exploration in mountainous areas, research on building wind engineering, etc.

[0049] The present invention can more accurately measure the wind field in complex terrain through a vertical wind lidar and a drone equipped with a wind field measurement sensor, especially in the fields of wind power and building structure wind, and can more accurately obtain the results representing typical wind fields.

[0050] The following combines Figure 1 , Figure 1 is a flowchart of a wind field measurement method provided by an embodiment of the present invention. The method may include:

[0051] S101: Perform wind field measurement in a target area based on a drone equipped with a wind field measurement sensor to obtain first wind field data, and correct the first wind field data based on the three-dimensional velocity of the drone.

[0052] In this embodiment, first wind field data can be obtained by performing wind field measurement in a target area based on a drone equipped with a wind field measurement sensor. This embodiment does not limit the specific type of the drone or the model of the wind field measurement sensor.

[0053] In this embodiment, a drone takeoff and landing platform can be set in the vicinity of the vertical wind lidar for functions such as charging and fixing the drone.

[0054] In this embodiment, to avoid the interference of the drone's own disturbance on the wind field results, the wind field measurement sensor can be fixed at a preset height above the drone, and the drone flies upward at a constant speed during the measurement process to ensure that the wind field measurement results are only superimposed on the influence of the drone's vertical upward movement and avoid the interference of the drone's own disturbance on the wind field results.

[0055] In this embodiment, the drone can be controlled to fly directly above the radar at preset intervals and collect the first wind field data in the form of rising at a constant speed.

[0056] A wireless network module can be integrated inside the vertical wind lidar to establish a data transmission channel with the drone. The first wind field data measured by the drone can be transmitted to the vertical wind lidar, and the wind field joint calculation can be realized through a unified data processing computer to obtain the target wind field.

[0057] Since there may be differences in the sampling intervals of the unmanned aerial vehicle (UAV) and the vertical wind lidar, for the convenience of merging the first wind field data and the second wind field data, in this embodiment, the resolutions of the first wind field data and the second wind field data can be unified.

[0058] Specifically, in this embodiment, distance sliding averaging can be performed on the wind field data collected by the UAV. For example, the UAV carrying the wind field measurement sensor is controlled to fly directly above the vertical wind lidar and rise uniformly in the target area at a preset speed to obtain the first initial wind field data; the first initial wind field data is processed by distance sliding averaging according to a preset scale to obtain the first wind field data.

[0059] In this embodiment, the size of the preset scale Δh is not limited. The specific preset scale can be appropriately adjusted according to the actual performance of the actual cumulative measurement. To align the first wind field data and the second wind field data, the preset scale can be half of the lidar pulse width, and the sampling points of the first wind field data and the second wind field data need to be aligned. That is, for any sampling point of the first wind field data, the first initial wind field data within Δh / 2 from the sampling point is averaged, the wind speed values within the interval are arithmetically averaged, and the wind directions within the interval are vectorially summed to obtain the first wind field data of each sampling point.

[0060] Furthermore, in this embodiment, distance sliding averaging (or time sliding averaging) can also be performed on the first wind field data and the second wind field data simultaneously to unify the data output distance intervals (or time intervals) of the first wind field data and the second wind field data.

[0061] Since the first wind field data measured by the UAV is interfered by the UAV's own speed, in this embodiment, the three-dimensional speed of the UAV during the ascending process can be obtained, and the first wind field data can be corrected based on the UAV's three-dimensional speed.

[0062] S102: Based on the vertical wind lidar, wind field measurement is performed in the target area to obtain the second wind field data, and the UAV wake interference data in the second wind field data is deleted.

[0063] In this embodiment, the second wind field data can be obtained based on the vertical wind lidar in the target area. The model and measurement mode of the vertical wind lidar are not limited in this embodiment. Generally, a four-beam measurement mode can be set for collecting wind field data.

[0064] Since the wake generated by the UAV during the ascending process will affect the measurement results of the vertical wind lidar, causing the measured second wind field data to deviate from the actual value, in this embodiment, the second wind field data can be corrected, and the UAV wake interference data in the second wind field data is deleted.

[0065] This embodiment does not limit the specific method of deleting the UAV wake interference data in the second wind field data. Generally, the target time when the UAV is at the target altitude during the ascending process can be determined; the spatial distance between the UAV and the radar beam at the same altitude when the UAV is at the target altitude can be determined; the horizontal wind speed collected when the UAV is at the target altitude can be determined; the value obtained by dividing the spatial distance by the horizontal wind speed is determined as the wake transfer time, and the sum of the wake transfer time and the target time is determined as the target interference time; the second wind field data collected at the target interference time is determined as the wind field data to be corrected; the data collected at the target altitude in the wind field data to be corrected is deleted.

[0066] As Figure 2 shown, the UAV can fly by rotating the rotor clockwise. When it flies to the target altitude H, the target time at this time is T. The four arrows in the figure are the beams of the vertical wind lidar respectively, the middle vertical dotted line is the ascending route of the UAV, and the horizontal dotted line can be regarded as the horizontal distance between the UAV and the radar beam at the same altitude.

[0067] Since the beam inclination angle of the vertical wind lidar is a preset value θ, when the UAV is at the target altitude H, the spatial distance from any radar beam at the same altitude is L = H·tanθ.

[0068] Furthermore, if the horizontal wind speed value of the horizontal wind field when the UAV is at the target altitude H is determined as v, then the wake transfer time of the UAV can be determined as t = (H·tanθ) / v, and the sum of the wake transfer time and the target time is determined as the target interference time (T + t).

[0069] The second wind field data collected by the vertical wind lidar at (T + t) is determined as the wind field data to be corrected, and the wind field data collected at the target altitude H in the wind field data to be corrected is deleted to correct the second wind field data.

[0070] In this embodiment, the altitude during the ascending process of the UAV can be sequentially determined as the target altitude until the correction of all the second wind field data is completed.

[0071] S103: Combine the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data.

[0072] Due to the measurement blind area of the vertical wind lidar, the first wind field data and the second wind field data can be measured in the non-radar blind area, while only the first wind field data can be measured in the radar blind area.

[0073] In this embodiment, the first wind field data collected within the non-radar blind area can be used to correct the second wind field data. Specifically, the second wind field data and the first wind field data within the non-radar blind area can be combined to obtain the non-radar blind area wind field data.

[0074] Since within one measurement period of an unmanned aerial vehicle, the vertical wind lidar can output multiple sets of second wind field data, in this embodiment, the wind speed values in the second wind field data collected at the same altitude can be averaged to obtain the average wind speed value; the wind directions in the second wind field data collected at the same altitude can be vectorially summed to obtain the average wind direction; the second average wind field data is determined based on the average wind speed value and the average wind direction at each altitude; and the second average wind field data and the first wind field data within the non-radar blind area are combined to obtain the non-radar blind area wind field data.

[0075] This embodiment does not limit the specific combination method. Generally, the wind speed values of the second wind field data and the first wind field data at the same altitude can be averaged to obtain the average wind speed value; the wind directions of the second wind field data and the first wind field data at the same altitude can be vectorially summed to obtain the average wind direction; and the non-radar blind area wind field data is constructed based on the average wind speed value and the average wind direction at each altitude.

[0076] S104: Determine the first wind field data within the radar blind area as the radar blind area wind field data, and determine the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data.

[0077] For the blind area that cannot be detected by the vertical wind lidar, this embodiment can fill it with the first wind field data measured by the unmanned aerial vehicle, that is, determine the first wind field data within the radar blind area as the radar blind area wind field data. The target wind field of the entire target area can be constructed through the non-radar blind area wind field data and the radar blind area wind field data.

[0078] Based on the above embodiments, the present invention uses a vertical wind lidar and an unmanned aerial vehicle system equipped with a wind speed and direction sensor for joint observation, and jointly analyzes and calculates the data of both to improve the measurement accuracy.

[0079] The following combines Figure 3 , Figure 3 which is the structural block diagram of a wind field measurement device provided by an embodiment of the present invention. The device may include:

[0080] The first module 100 is configured to measure the wind field in the target area based on an unmanned aerial vehicle equipped with a wind field measurement sensor to obtain the first wind field data, and correct the first wind field data based on the three-dimensional velocity of the unmanned aerial vehicle;

[0081] The second module 200 is used to measure the wind field in the target area based on the vertical wind lidar to obtain second wind field data, and delete the UAV wake interference data in the second wind field data;

[0082] The third module 300 is used to merge the second wind field data with the first wind field data in the non-radar blind area to obtain non-radar blind area wind field data;

[0083] The fourth module 400 is used to determine the first wind field data in the radar blind area as the radar blind area wind field data, and determine the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data.

[0084] Based on the above embodiments, the present invention uses a vertical wind lidar and a UAV system equipped with a wind speed and direction sensor for joint observation, and jointly analyzes and calculates the data of both to improve the measurement accuracy.

[0085] Based on the above embodiments, the second module 200 may include:

[0086] The first unit is used to determine the target time when the UAV is at the target height during the ascending process;

[0087] The second unit is used to determine the spatial distance between the UAV and the radar beam at the same height when the UAV is at the target height;

[0088] The third unit is used to determine the horizontal wind speed collected by the UAV when the UAV is at the target height;

[0089] The fourth unit is used to determine the wake transfer time by dividing the spatial distance by the horizontal wind speed, and determine the target interference time by adding the wake transfer time and the target time;

[0090] The fifth unit is used to determine the second wind field data collected at the target interference time as the wind field data to be corrected;

[0091] The sixth unit is used to delete the data collected at the target height in the wind field data to be corrected.

[0092] Based on the above embodiments, the first module 100 may include:

[0093] The seventh unit is used to control the UAV equipped with the wind field measurement sensor to fly directly above the vertical wind lidar and ascend uniformly in the target area at a preset speed to obtain the first initial wind field data;

[0094] The eighth unit is configured to perform distance sliding averaging on the first initial wind field data according to a preset scale to obtain the first wind field data.

[0095] Based on the above embodiments, the preset scale is one half of the lidar pulse width.

[0096] Based on the above embodiments, the third module 300 may include:

[0097] The ninth unit is configured to average the wind speed values in the second wind field data collected at the same height to obtain an average wind speed value;

[0098] The tenth unit is configured to perform vector summation on the wind directions in the second wind field data collected at the same height to obtain an average wind direction;

[0099] The eleventh unit is configured to determine second average wind field data based on the average wind speed values and the average wind directions at each height;

[0100] The twelfth unit is configured to merge the second average wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data.

[0101] Based on the above embodiments, the third module 300 may include:

[0102] The thirteenth unit is configured to average the wind speed values of the second wind field data and the first wind field data at the same height to obtain an average wind speed value;

[0103] The fourteenth unit is configured to perform vector summation on the wind directions of the second wind field data and the first wind field data at the same height to obtain an average wind direction;

[0104] The fifteenth unit is configured to construct the non-radar blind area wind field data based on the average wind speed values and the average wind directions at each height.

[0105] Based on the above embodiments, the measurement mode of the vertical wind lidar is a four-beam measurement mode.

[0106] Based on the above embodiments, the present invention further provides an electronic device, which may include a memory and a processor. Among them, the memory stores a computer program, and when the processor calls the computer program in the memory, the steps provided in the above embodiments can be implemented. Of course, the device may further include various necessary network interfaces, power supplies, and other components.

[0107] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by an execution terminal or a processor, the method provided by the embodiments of the present invention can be implemented; the storage medium may include: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0108] In this text, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the element.

Claims

1. A wind field measurement method, characterized in that: include: A UAV equipped with a wind field measurement sensor performs wind field measurement in a target area to obtain first wind field data, and corrects the first wind field data based on a three-dimensional speed of the UAV; The wind field measurement sensor is fixed at a preset height above the drone, and the drone flies upward at a constant speed during the measurement process; Performing wind field measurement in the target area based on a vertical wind measurement laser radar to obtain second wind field data, and deleting the UAV turbulence interference data in the second wind field data; Combining the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data; Determine the first wind field data in the radar blind area as the radar blind area wind field data, and determine the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data; The method of deleting the UAV turbulence interference data in the second wind field data includes: determining a target time when the drone is at a target altitude during the ascent; Determine the spatial distance between the UAV and the radar beam at the same altitude when the UAV is at the target altitude; Determine the horizontal wind speed collected by the UAV at the target height; The value obtained by dividing the spatial distance by the horizontal wind speed is determined as the disturbance transfer time, and the sum of the disturbance transfer time and the target time is determined as the target interference time; Determining the second wind field data acquired during the target interference time as the wind field data to be corrected; Deleting the data collected at the target height in the wind field data to be corrected; The height of the UAV during its ascent is sequentially determined as the target height until the correction of the second wind field data is completely completed.

2. The wind field measurement method according to claim 1, characterized in that: The first wind field data is obtained by measuring the wind field in the target area using a UAV equipped with a wind field measurement sensor, including: Controlling the UAV equipped with the wind field measurement sensor to fly to directly above the vertical wind measurement laser radar, and ascending uniformly in the target area at a preset speed to obtain first initial wind field data; The first initial wind field data is processed by distance sliding average according to a preset scale to obtain the first wind field data.

3. The wind field measurement method according to claim 2, characterized in that: The preset scale is half of the laser radar pulse width.

4. The wind field measurement method according to claim 1, characterized in that: Combining the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data, including: Averaging the wind speed values ​​in the second wind field data collected at the same height to obtain an average wind speed value; Performing vector summation on the wind directions in the second wind field data collected at the same height to obtain an average wind direction; Determine second average wind field data based on the average wind speed value and the average wind direction at each height; The second average wind field data is combined with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data.

5. The wind field measurement method according to claim 1, characterized in that: Combining the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data, including: Averaging the wind speed values ​​of the second wind field data and the first wind field data at the same height to obtain an average wind speed value; Performing vector summation on the wind directions of the second wind field data and the first wind field data at the same height to obtain an average wind direction; The non-radar blind area wind field data is constructed based on the average wind speed value and the average wind direction at each height.

6. The wind field measurement method according to claim 1, characterized in that: The measurement mode of the vertical wind measurement laser radar is a four-beam measurement mode.

7. A wind field measurement device, characterized in that: include: The first module is used to obtain first wind field data by measuring the wind field in a target area using a drone equipped with a wind field measurement sensor, and to correct the first wind field data based on the three-dimensional speed of the drone; the wind field measurement sensor is fixed at a preset height above the drone, and the drone rises at a constant speed during the measurement process; The second module is used to obtain second wind field data by measuring the wind field in the target area based on the vertical wind measurement laser radar, and delete the UAV turbulence interference data in the second wind field data; A third module is used to combine the second wind field data with the first wind field data in the non-radar blind area to obtain the non-radar blind area wind field data; A fourth module is used to determine the first wind field data in the radar blind area as the radar blind area wind field data, and determine the target wind field of the target area based on the non-radar blind area wind field data and the radar blind area wind field data; The method of deleting the UAV turbulence interference data in the second wind field data includes: determining a target time when the drone is at a target altitude during the ascent; Determine the spatial distance between the UAV and the radar beam at the same altitude when the UAV is at the target altitude; Determine the horizontal wind speed collected by the UAV at the target height; The value obtained by dividing the spatial distance by the horizontal wind speed is determined as the disturbance transfer time, and the sum of the disturbance transfer time and the target time is determined as the target interference time; Determining the second wind field data acquired during the target interference time as the wind field data to be corrected; Deleting the data collected at the target height in the wind field data to be corrected; The height of the UAV during its ascent is sequentially determined as the target height until the correction of the second wind field data is completely completed.

8. An electronic device, characterized in that: include: Memory, for storing computer programs; A processor, configured to implement the wind field measurement method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the wind field measurement method according to any one of claims 1 to 6 is implemented.

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