Method and system for measuring wind profile by laser wind finding radar and computer device

Abstract

The invention discloses a laser wind-finding radar system, a wind profile measurement method and a computer device, and the method comprises the steps: obtaining the geographic position coordinates of each laser wind-finding radar and the inclination angle between each laser wind-finding radar and the horizontal plane through the configuration of at least three laser wind-finding radars and a data server; configuring a measurement inclination angle, a layered acquisition height and an acquisition period for at least three laser wind measurement radars; synchronizing system clocks of the at least three laser wind finding radars, and collecting and calculating the radial speed of scattering particles at the same coordinate point of each layered collection height; a least square method inversion algorithm is used, a Kalman filtering technology is combined, the radial speed of scattering particles is subjected to cooperative processing to obtain an accurate three-dimensional wind profile, by measuring a plurality of wind profiles and integrating multi-dimensional real-time data, high-precision and dynamic wind field measurement capability is provided, the limitation of a traditional anemometer tower and a single radar in application is solved, and the wind field measurement efficiency is improved. And the requirements of fine management of multiple scenes (wind power generation, local meteorology, low-altitude flight and the like) are met.

Description

Technical Field

[0001] The present disclosure relates to the field of wind measurement, and more particularly to a method, a system and a computer device for measuring wind profiles using a lidar. Background Art

[0002] Existing lidars have some limitations in wind profile measurement. First, when a single lidar obtains wind field data, it usually assumes that the wind field within the scanning area is uniform. However, in reality, the wind field may vary significantly in different regions and at different heights.

[0003] Second, a single lidar can only measure the radial wind speed and cannot identify the wind direction, making it difficult to obtain accurate wind field data, fully reflect the dynamic characteristics of the wind field, and even more difficult to capture the instantaneous changes in the wind field.

[0004] In addition, a single lidar can only measure the radial wind speed along the direction of the laser beam. To obtain wind speeds in other directions such as horizontal and vertical wind speeds, multiple scans and derivations are required, resulting in a lower time resolution for three-dimensional wind field measurement and increased computational complexity and errors. Summary of the Invention

[0005] In view of the above, embodiments of the present disclosure provide a lidar system, a method for measuring wind profiles, and a computer device, which can effectively overcome the problems of low time resolution, low spatial resolution, low data refresh rate, complex calculation, and insufficient accuracy of a single lidar, and meet the requirements of high-precision wind measurement.

[0006] In a first aspect, embodiments of the present disclosure provide a method for measuring wind profiles using a lidar, the system comprising:

[0007] Configuring at least three lidars and a data server;

[0008] Obtaining the geographical location and the inclination angle with respect to the horizontal plane of each of the lidars;

[0009] Configuring a measurement inclination angle, an azimuth angle, a stratified acquisition height, and an acquisition period for the at least three lidars;

[0010] Synchronizing the system clocks of the at least three lidars through GNSS calibration or mobile base station calibration;

[0011] The at least three lidars synchronously emit laser beams to the same coordinate points at each of the stratified acquisition heights according to the azimuth angle and the measurement inclination angle, and receive the backscattered laser at each of the stratified acquisition heights;

[0012] The at least three lidar wind sensors respectively capture the backscattered laser, compare the frequency of the backscattered laser with that of the transmitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles;

[0013] Each of the at least three lidar wind sensors sends the calculated radial velocity of the scattering particles to the data server. The data server uses the least squares inversion algorithm and combines the Kalman filtering technique to perform collaborative processing on the radial velocities of the scattering particles respectively sent by the at least three lidar wind sensors, and obtains an accurate three-dimensional wind profile;

[0014] Each of the at least three lidar wind sensors is configured with different azimuth angles to obtain multiple three-dimensional wind profiles.

[0015] Optionally, obtaining the geographical location and the inclination angle with the horizontal plane of each lidar wind sensor includes: the lidar wind sensor determines the three-dimensional coordinates of the location where the lidar wind sensor is located through a positioning system;

[0016] The lidar wind sensor monitors the inclination state of the lidar wind sensor through an inclinometer and an angle encoder; the inclination state is used for the lidar wind sensor to perform attitude adjustment or to make corresponding corrections to the measurement results during data processing.

[0017] Optionally, the measured inclination angle is used to determine the vertical pointing direction of the beam of the lidar wind sensor;

[0018] The stratified acquisition height is used to set the range and interval for the lidar wind sensor to collect wind profile data at different height layers;

[0019] The acquisition period is used to determine the time interval for the lidar wind sensor to collect wind field data.

[0020] Optionally, the at least three lidar wind sensors synchronously emit laser beams to the same coordinate points at each stratified acquisition height and receive the backscattered laser at each stratified acquisition height, including:

[0021] Before observation, the stratified acquisition heights at the same altitude and the corresponding coordinate points are preset in advance; the corresponding coordinate points are the common measurement target points of the at least three lidar wind sensors; the corresponding coordinate points have the same geographical coordinates in space and are distributed at different stratified acquisition heights;

[0022] The at least three lidar wind sensors can adjust the emission direction according to the common measurement target points at each stratified acquisition height, so that the emitted laser beam accurately points to the common measurement target points;

[0023] After the emitted laser beam reaches the common measurement target point, it interacts with the particles in the atmosphere to generate backscattered laser, and the at least three lidars receive the backscattered laser; each of the at least three lidars is configured with a different azimuth angle to obtain multiple three-dimensional wind profiles.

[0024] Optionally, the at least three lidars respectively receive the backscattered laser, compare the frequency of the backscattered laser with that of the emitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles, including:

[0025] The at least three lidars use the Doppler effect principle to calculate the motion velocity of the particles in the atmosphere by measuring the frequency shift of the backscattered laser relative to the emitted laser beam, and then obtain the radial velocity of the scattering particles. The specific formula is as follows:

[0026] Δf = fr - ft = λ2vcosθ,

[0027] where Δf is the frequency shift of the backscattered laser relative to the emitted laser beam, fr is the frequency of the emitted laser beam, ft is the frequency of the backscattered laser, λ is the wavelength of the emitted laser beam, v is the radial velocity of the scattering particles, and θ is the angle between the emitted laser beam and the wind direction.

[0028] Optionally, each of the at least three lidars sends the calculated radial velocity of the scattering particles to the data server. The data server uses the least squares inversion algorithm and combines the Kalman filtering technology to perform collaborative processing on the radial velocities of the scattering particles sent by the at least three lidars respectively to obtain an accurate three-dimensional wind profile, including:

[0029] The at least three lidars respectively send the calculated radial velocity information of the scattering particles to the data server. The radial velocity information includes the radar identifier, acquisition time, layer height, spatial coordinates of the acquisition point, and the radial velocity of the scattering particles;

[0030] The data server fuses the radial velocities of the scattering particles collected by the at least three lidars at the same layer height and the same time, and forms a wind speed vector through trigonometric relations;

[0031] The data server uses the least squares inversion algorithm to calculate the horizontal wind speed and vertical wind speed of each height layer through the wind speed vector; applies the Kalman filtering technology to smooth the horizontal wind speed and vertical wind speed data of each height layer to obtain the accurate three-dimensional wind profile.

[0032] The described lidar wind measurement system can observe multiple vertical wind profiles through three lidar wind sensors configured at different azimuth angles;

[0033] Each of the at least three lidar wind sensors is configured at a different azimuth angle to obtain multiple three-dimensional wind profiles.

[0034] In a second aspect, an embodiment of the present disclosure also provides a lidar wind sensor system, which includes:

[0035] At least three lidar wind sensors and a data server are configured;

[0036] Each of the lidar wind sensors obtains its geographical location through a positioning system, and obtains the inclination angle of the lidar wind sensor with respect to the horizontal plane through an inclinometer and an encoder;

[0037] Measurement inclination angles, stratified acquisition heights, and acquisition periods are configured for the at least three lidar wind sensors;

[0038] The system clocks of the at least three lidar wind sensors are calibrated through GNSS or a mobile base station to achieve time synchronization;

[0039] The at least three lidar wind sensors simultaneously emit laser beams to the same coordinate points at each of the stratified acquisition heights, and receive the backscattered laser at each of the stratified acquisition heights;

[0040] The at least three lidar wind sensors respectively capture the backscattered laser, compare the frequency of the backscattered laser with that of the emitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles;

[0041] Each of the at least three lidar wind sensors sends the calculated radial velocity of the scattering particles to the data server, and the data server uses a least squares inversion algorithm and combines it with Kalman filtering technology to perform collaborative processing on the radial velocities of the scattering particles respectively sent by the at least three lidar wind sensors to obtain an accurate three-dimensional wind profile.

[0042] In a third aspect, an embodiment of the present disclosure also provides a computer device, which is characterized in that the computer device includes:

[0043] At least one processor; and,

[0044] A memory communicatively connected to the at least one processor; wherein,

[0045] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the lidar wind sensor measurement wind profile method described in any of the above.

[0046] Fourthly, an embodiment of the present disclosure further provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions for causing a computer to execute the method for measuring a wind profile by the lidar for wind measurement as described in any one of the above.

[0047] Fifthly, an embodiment of the present disclosure further provides a computer program product including computer instructions, characterized in that when the computer instructions are executed by a processor, the steps of the method as described in any one of the above are implemented.

[0048] The lidar system for wind measurement, the method for measuring a wind profile, and the computer device disclosed in the present application configure at least three lidars for wind measurement and a data server, and obtain the geographical location and the inclination angle with the horizontal plane of each of the lidar for wind measurement; configure a measurement inclination angle, a stratified acquisition height, and an acquisition period for the at least three lidars for wind measurement; synchronize the system clocks of the at least three lidars for wind measurement, and collect and calculate the radial velocity of the outgoing scattered particles at the same coordinate point of each stratified acquisition height; use the least squares inversion algorithm and combine the Kalman filtering technique to perform collaborative processing on the radial velocities of the scattered particles respectively sent by the at least three lidars for wind measurement to obtain an accurate three-dimensional wind profile, thus realizing a collaborative observation system composed of multiple lidars for wind measurement. The collaborative observation system provides a high-precision and dynamic wind resource measurement capability by integrating multi-dimensional real-time wind field data, solves the limitations in the applications of traditional wind measurement towers and single radars, and meets the requirements of refined management in multiple scenarios (wind power, meteorology, low-altitude flight).

[0049] The collaborative observation system (select more than three lidars for wind measurement according to the on-site terrain and meteorological conditions) consists of a set of lidar wind measurement station systems composed of lidars for wind measurement, and performs refined measurement on the wind field in the same area through collaborative observation. The system uses the intersection of laser beams to generate a vertical wind profile, and realizes high-precision and real-time acquisition of parameters such as wind speed and wind direction. The advantages of the lidar wind measurement station compared with the traditional wind measurement tower are that in addition to being able to accurately measure wind profile data, it can flexibly select the wind measurement position, height, azimuth, and the vertical resolution of wind measurement can be adjusted, which can effectively meet the requirements of dynamic wind measurement.

[0050] The above description is only an overview of the technical solution of the present disclosure. In order to understand the technical means of the present disclosure more clearly, it can be implemented according to the content of the description. And in order to make the above and other purposes, features, and advantages of the present disclosure more obvious and understandable, the following specific preferred embodiments are given and described in detail in conjunction with the accompanying drawings. Description of the Drawings

[0051] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following will briefly introduce the accompanying drawings required for the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0052] Figure 1 It is a schematic structural diagram of a lidar wind measurement radar system provided by an embodiment of the present disclosure.

[0053] Figure 2 It is a schematic flow diagram of a lidar wind measurement radar for measuring a wind profile provided by an embodiment of the present disclosure.

[0054] Figure 3 It is a schematic structural diagram of a lidar wind measurement radar provided by an embodiment of the present disclosure.

[0055] Figure 4 It is a schematic structural diagram of a computer device provided by an embodiment of the present disclosure. Detailed implementation manners

[0056] The following will describe the embodiments of the present disclosure in detail with reference to the accompanying drawings.

[0057] It should be clear that the following uses specific specific examples to illustrate the implementation manners of the present disclosure. Those skilled in the art can easily understand other advantages and effects of the present disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. The present disclosure can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present disclosure without creative efforts belong to the scope of protection of the present disclosure.

[0058] It should be noted that the following describes various aspects of the embodiments within the scope of the appended claims. It should be obvious that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is illustrative only. Based on the present disclosure, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and these aspects can be combined in various ways in two or more of them. For example, any number of aspects described herein can be used to implement a device and / or practice a method. In addition, this device and / or this method can be implemented using other structures and / or functions in addition to one or more of the aspects described herein.

[0059] It should also be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present disclosure in a schematic manner. The diagrams only show the components related to the present disclosure, rather than being drawn according to the number, shape, and size of the components in actual implementation. The types, quantities, and proportions of the components in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0060] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0061] Referring to Figure 1 , the present application discloses a system for measuring wind profiles using a provided lidar wind sensor, including: Multiple lidar wind sensors (31, 32, 33) cover key areas of the wind farm through collaborative observations to collect multi-dimensional wind field parameters such as real-time wind speed, wind direction, and turbulence intensity. The data server (21) uses the least squares inversion algorithm and combines Kalman filtering technology to collaboratively process the data sent by multiple lidar wind sensors (31, 32, 33) to obtain an accurate three-dimensional wind profile. When using this system to measure the wind profile, the wind speed measurement error is less than 0.3 m / s, significantly better than traditional wind measurement towers and single radars. The data acquisition frequency and measurement resolution can be dynamically adjusted to support real-time wind field monitoring. It can be flexibly arranged according to the terrain characteristics, wind speed distribution, and main wind direction of the wind farm. The system adapts to different terrain and climate conditions and performs stably in complex wind fields and extreme weather. It simultaneously obtains horizontal and vertical wind speeds and provides a comprehensive analysis of wind field characteristics.

[0062] Referring to Figure 2 , the present application discloses a method for measuring wind profiles using a provided lidar wind sensor, including:

[0063] S100, Configure at least 3 lidar wind sensors and a data server.

[0064] According to the main wind direction and terrain characteristics of the wind farm, reasonably select the installation positions of the lidar. Avoid installing in the wake interference area of the wind turbines to ensure data quality.

[0065] S200, Obtain the geographical location and inclination angle with the horizontal plane of each of the lidar wind sensors.

[0066] Laser wind lidars are usually equipped with high-precision positioning systems, such as the Global Positioning System (GPS), the BeiDou Navigation Satellite System (BDS), etc., to obtain their accurate geographical location information. These positioning systems calculate the three-dimensional coordinates of the lidar's location, including longitude, latitude, and altitude, by receiving satellite signals and using satellite orbital parameters, time information, and signal propagation time. When the positioning system is working, it will receive signals from multiple satellites simultaneously and calculate the most accurate location information through algorithms. To improve the positioning accuracy, some laser wind lidars may also use differential positioning technology, that is, using a reference station with a known accurate location to correct the satellite signals received by the lidar, thereby reducing the positioning error and making the geographical location positioning accuracy of the lidar reach the centimeter level or even higher.

[0067] During the installation and use of the laser wind lidar, it is necessary to maintain a certain level state to ensure the accuracy and reliability of the measurement data. To obtain the inclination angle of the lidar relative to the horizontal plane, a high-precision level is usually used. The level is generally installed at the bottom of the lidar or on key components and can monitor the tilt state of the lidar in real time. Its working principle is usually based on the measurement of gravitational acceleration. By detecting the components of gravitational acceleration in different directions, the tilt angle of the lidar relative to the horizontal plane is calculated. When the lidar is tilted, the level will transmit the detected inclination angle information to the lidar's control system. The control system adjusts the attitude of the lidar according to this information or makes corresponding corrections to the measurement results during data processing to eliminate the measurement errors caused by the tilt. In addition, to ensure the measurement accuracy of the level, it needs to be strictly calibrated during installation, and during the use of the lidar, it also needs to be regularly inspected and maintained to ensure its normal operation.

[0068] Through the above methods, the laser wind lidar can accurately obtain its geographical location and the inclination angle relative to the horizontal plane, thus providing a reliable basis for its accurate measurement of the atmospheric wind field and ensuring the accuracy and availability of the measurement data.

[0069] S300, configure the measurement inclination angle, stratified acquisition height, and acquisition period for the at least 3 laser wind lidars.

[0070] When configuring the measurement inclination angle for a lidar wind profiler, the main consideration is the pointing angle of the radar antenna to ensure that the radar can transmit and receive laser signals at an appropriate angle. Usually, the pitch angle and azimuth angle of the radar are the key parameters that need to be configured. The pitch angle determines the vertical pointing of the radar beam, while the azimuth angle determines the pointing of the radar beam on the horizontal plane. The configuration of these angles needs to be determined according to specific observation targets and requirements. To achieve precise angle configuration, a lidar wind profiler is usually equipped with a high-precision servo control system that can accurately adjust the position of the radar antenna according to preset angle parameters. At the same time, the radar may also be equipped with angle sensors to monitor and feedback the actual pointing angle of the radar antenna in real time for adjustment and correction when needed. In addition, in the case of collaborative observation by multiple radars, the measurement inclination angles of each radar need to be unifiedly planned and coordinated to ensure that their beams can cover the predetermined spatial area, thereby achieving a comprehensive detection of the atmospheric wind field. In the present invention, the measurement inclination angles of at least 3 lidar wind profilers can be adjusted according to the actual application scenario and measurement requirements. For example, with an adjustment unit of 5 degrees, they can be set to -10°, -5°, 0°, 5°, 10°, 15°, 30°... 90°, etc., and the adjustment accuracy is 0.01°.

[0071] The configuration of the stratified acquisition height refers to setting the range and interval for the lidar wind profiler to collect wind field data at different height layers. This configuration needs to be determined according to the observation target and research requirements. For example, for studying the wind field structure of the near-surface atmospheric boundary layer, the acquisition height may need to be set in a lower range, such as from the ground to 1000 meters, and a smaller height interval, such as collecting data every 10 meters or 20 meters within this range, to obtain high-resolution wind field information. For studying the wind field changes in the middle and upper layers of the atmosphere, the upper limit of the acquisition height can be appropriately increased and the height interval can be appropriately enlarged to cover a wider height range.

[0072] In actual operation, the lidar wind profiler realizes the acquisition of wind field data at different height layers by adjusting its internal signal processing parameters and transmission and reception modes. When the laser pulse emitted by the radar propagates in the atmosphere, it interacts with aerosol particles at different heights and generates backscattered signals. By receiving these backscattered signals with different delay times and combining the Doppler frequency shift information of the signals, the lidar can retrieve the wind speed and wind direction at different height layers. To ensure the height accuracy of stratified acquisition and the reliability of data, when configuring the stratified acquisition height, the radar also needs to consider its own detection performance and resolution limitations, as well as the influence of atmospheric conditions on signal propagation and scattering. In the present invention, the stratified acquisition height divides the wind measurement height range (0 - 600 meters) into 60 layers, that is, each layer has a height of 10 meters.

[0073] The configuration of the acquisition period refers to determining the time interval for the lidar wind profiler to collect wind field data. The setting of this parameter needs to comprehensively consider factors such as the observation purpose, the requirement for data update frequency, and the performance of the radar. For example, in application scenarios for real-time monitoring of atmospheric wind field changes, such as weather forecasting and aviation safety assurance, a shorter acquisition period may be required, such as collecting data once per minute, to obtain wind field information with high time resolution and promptly capture the rapid changes in the atmospheric wind field. For some long-term climate research or atmospheric science experiments, a longer acquisition period may be adopted, such as collecting data once every half hour or every hour, to reduce the data volume and the complexity of data processing.

[0074] When implementing the configuration of the acquisition period, the control system of the lidar wind profiler will automatically control operations such as the radar's transmission, reception, and data processing according to the set period parameters, ensuring that the radar collects wind field data at the predetermined time interval. Meanwhile, to adapt to different observation requirements, the radar may also have a flexible acquisition period adjustment function, allowing users to dynamically adjust the acquisition period according to the actual situation. In addition, considering that the radar may be affected by external environmental factors during long-term continuous operation, such as temperature changes and electromagnetic interference, the configuration of its acquisition period also needs to take into account the stability and reliability of the radar, avoiding equipment overheating or other failure problems caused by frequent data acquisition. In the present invention, the acquisition period is that each lidar wind profiler completes a scan in 10 seconds to obtain the radial wind speed data of this layer, and the setting of the stratified acquisition height ensures high resolution in the vertical direction and can capture the wind speed changes at different height layers. The setting of the acquisition period needs to consider the performance of the radar and the data processing ability, and the 10-second acquisition period can achieve a balance between the data volume and real-time performance.

[0075] S400, the system clocks of the at least 3 lidar wind profilers are calibrated through GNSS or a mobile base station to achieve time synchronization.

[0076] In the case of multiple lidar wind profilers working in coordination, to achieve time synchronization of the entire system, usually a master control unit is required to coordinate the time calibration work of each radar. The master control unit will send synchronization instructions to each radar according to the precise time provided by GNSS or a mobile base station. After each radar receives the instructions, it adjusts its system clock according to the predetermined algorithm and process to make it consistent with the time of the master control unit. In this way, all the radars within the entire system can work in coordination under a unified time reference to ensure the time consistency of the measurement data. The master control unit of the present invention is the data server in the system or one of the radars.

[0077] S500, at least three lidars synchronously emit laser beams towards the same coordinate points at each of the stratified acquisition heights, and receive the backscattered laser at each of the stratified acquisition heights.

[0078] In a multi-lidar collaborative observation system, there will be a main control unit or a central control system responsible for coordinating the operations of each lidar. In the present invention, the data server can serve as the central control system, or one of the lidars can serve as the main control unit. When the predetermined acquisition moment is reached, the main control unit will send a synchronous emission instruction to all the lidars, and each lidar will immediately start the laser emission program after receiving the instruction.

[0079] Each lidar is equipped with a high-precision clock and a timing control circuit inside, which can accurately trigger the laser emission within an extremely short time after receiving the synchronous instruction, and the error is usually at the microsecond level or even smaller, so as to realize the almost simultaneous emission of laser beams by multiple lidars.

[0080] Before the observation, a series of stratified acquisition heights and corresponding coordinate points will be preset according to the research objectives and the observation area. These coordinate points are the common target points of all the lidars, and they have the same geographical coordinates in space and are distributed on different height layers. The lidar is equipped with a high-precision servo control system and an angle measurement device, which can accurately adjust its emission direction according to the preset coordinate points, that is, adjust the pitch angle and azimuth angle of the radar antenna, so that the laser beam accurately points to the target coordinate point. During the adjustment process, the radar will continuously correct the position of the antenna by using the angle feedback mechanism to ensure that the pointing accuracy of the laser beam reaches the milliradian level.

[0081] When the emitted laser beam reaches the target coordinate point, it will interact with particles such as atmospheric aerosol and water droplets at this height layer to generate backscattered laser. Each lidar will collect these scattered laser signals through its receiving system. The receiving system usually includes a high-sensitivity photodetector, a signal amplifier, a filter, etc., which can extract the weak backscattered laser signal from the background noise.

[0082] Since multiple lidars emit lasers and receive scattered signals towards the same coordinate points from different positions and angles, the data received contains wind field information observed from different perspectives. These data will be transmitted to a central data processing center and comprehensively analyzed through data fusion algorithms to improve the accuracy and reliability of wind field measurement and obtain more comprehensive and accurate three-dimensional structure information of the atmospheric wind field. The central data processing center is the data server.

[0083] For the S600, at least three lidar wind sensors respectively capture the backscattered laser, compare the frequency of the backscattered laser with that of the emitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles.

[0084] The backscattered laser signals received by the lidar wind sensor are usually very weak. First, a highly sensitive photodetector is required to convert the backscattered laser signals into electrical signals. After the photodetector converts the optical signals into electrical signals, the signals will be transmitted to a preamplifier. The preamplifier preliminarily amplifies the signals to increase the signal intensity, making it easier for subsequent processing.

[0085] To ensure that the signals are amplified to an appropriate amplitude while avoiding overload or distortion, the lidar wind sensor may adopt a multi-stage amplification circuit. During the amplification process, through an accurate gain control circuit, the amplification factor is dynamically adjusted according to the initial intensity of the signals, ensuring that the signals are amplified within the optimal range and providing high-quality electrical signals for subsequent signal processing.

[0086] The backscattered laser signals may contain interference with various frequency components, such as ambient light noise, noise generated by electronic components, etc. A band-pass filter allows signals within a specific frequency range to pass through while attenuating signals of other frequencies. The lidar wind sensor designs a suitable band-pass filter according to the frequency characteristics of its working laser, only retaining the frequency components related to the laser signals, effectively removing the interference signals of irrelevant frequencies, and improving the signal-to-noise ratio of the signals.

[0087] In practical applications, the characteristics and intensities of the interference signals may change over time, such as atmospheric turbulence, changes in background light intensity, etc. An adaptive filter can monitor the changes in signals and interference in real time and automatically adjust the parameters of the filter, such as the center frequency and bandwidth of the filter, according to a certain algorithm to always maintain the best filtering effect and ensure that the useful information in the backscattered laser signals is retained and extracted to the greatest extent.

[0088] The analog signals after amplification and filtering need to be sampled and digitized through a high-speed analog-to-digital converter (ADC), converting the continuous analog signals into discrete digital signals. The sampling frequency and resolution of the ADC need to be selected according to the measurement requirements and signal characteristics of the radar to ensure that the detailed information in the signals can be accurately captured.

[0089] The lidar wind profiler utilizes the principle of the Doppler effect. By measuring the frequency shift (Doppler shift) of the backscattered laser signal relative to the transmitted laser signal, it calculates the velocity of particles in the atmosphere and thus obtains the wind speed. Specifically, the signal processing unit of the radar performs spectral analysis methods such as fast Fourier transform (FFT) on the digitized signal to determine the frequency components of the signal. According to the Doppler shift formula, combined with parameters such as the wavelength and emission angle of the radar, the Doppler shift is converted into the magnitude and direction of the wind speed.

[0090] For example, when the lidar wind profiler emits a laser beam with a frequency of ft and the angle between the laser beam and the wind direction is When the wind speed is v, there is a frequency shift Δf between the frequency fr of the scattered light and the frequency of the transmitted light:

[0091]

[0092] where λ is the laser wavelength. By measuring the Doppler shift Δf, the radial component of the wind speed

[0093] S700, each of the at least 3 lidar wind profilers sends the calculated radial velocity of the scattered particles to the data server. The data server uses the least squares inversion algorithm and combines it with the Kalman filtering technology to perform collaborative processing on the radial velocities of the scattered particles sent by the at least 3 lidar wind profilers respectively to obtain accurate three-dimensional wind profile data.

[0094] The data server receives the wind measurement data from three lidar wind profilers through the network interface. Each radar sends data at a collection period of 20 seconds. The data packet contains information such as the identification of the radar, the collection time, the stratified height, and the radial wind speed.

[0095] Since the system clocks of the three radars are calibrated by GNSS, ensuring time synchronization at the millisecond level, the server checks the timestamps of each data packet when receiving the data to ensure the temporal consistency of the data. If there are minor time deviations, the server will correct them.

[0096] The server parses the received data packets, extracts the radial wind speed data, stratified height information, three-dimensional spatial coordinates, and collection time of each radar, etc. The parsed data will be organized into a structured format for subsequent processing. The parsed data is stored in the database and classified and stored according to time, height layer, collection point spatial coordinates, and radar identification.

[0097] The server fuses the radial wind speed data collected by the three radars at the same stratified height and the same time. Since the measurement inclination angles of each radar are different, they provide wind speed components in different directions. These components can be combined through trigonometric relationships to form a more comprehensive wind speed vector.

[0098] Using the least squares inversion algorithm and combining the radial wind speed data of three radars, the horizontal and vertical wind speeds at each altitude layer are calculated. The least squares method can minimize the measurement error and improve the accuracy of wind speed inversion. The specific method is as follows:

[0099] Assume that the measurement tilts of the three radars are θ1, θ2, and θ3 respectively, and their radial wind speeds at a certain altitude layer h and a certain time t are Vr1(h,t), Vr2(h,t), and Vr3(h,t).

[0100] The radial wind speed of each radar can be decomposed into components of the horizontal wind speed U and the vertical wind speed W:

[0101] Vr1(h,t) = U1cosθ1 + W1sinθ1

[0102] Vr2(h,t) = U2cosθ2 + W2sinθ2

[0103] Vr3(h,t) = U3cosθ3 + W3sinθ3

[0104] Through these equations, a linear equation system can be established to solve for U and W.

[0105] The least squares inversion algorithm is used to solve the above linear equation system to find the optimal values of U and W, minimizing the measurement error.

[0106] Write the above three equations in matrix form: Ax = b

[0107] Where:

[0108]

[0109] The solution of the least squares method is: x = (A T A) -1 A T b

[0110] The specific steps are as follows:

[0111]

[0112] 3. Solve for x = (A T A) -1 A T b

[0113] Through the above steps, the optimal estimated values of the horizontal wind speed U and the vertical wind speed W at altitude h and time t can be obtained. By measuring with multiple laser beams in different directions, multiple radial wind speed components are obtained. Using vector synthesis and trigonometric function relationships, the horizontal component, vertical component, and wind direction of the wind speed can be calculated.

[0114] Based on the inversion results, the Kalman filtering technique is applied to smooth the wind speed data, further improving the stability and reliability of the data. Kalman filtering can effectively reduce noise interference and provide a more accurate wind speed estimate. The specific steps are as follows:

[0115] The wind speed data obtained by least squares inversion is used as the observed data and input into the Kalman filter.

[0116] According to the above Kalman filtering iteration steps, the wind speed data at each moment is processed to obtain the smoothed wind speed estimate.

[0117] Output the smoothed wind speed data, including horizontal wind speed, vertical wind speed, and crosswind component, etc.

[0118] The data server checks whether the data of each radar is complete, whether there is data loss or outliers. If data loss or anomalies are found, they will be marked and attempts will be made to supplement them through interpolation or other methods. The data server checks whether the data of the three radars at the same altitude and the same time is consistent. If it is inconsistent, the reasons will be analyzed and corresponding adjustments will be made. After the above processing by the data server, the server calculates the accurate wind speed data at each altitude, including horizontal wind speed, vertical wind speed, and wind direction, etc. The data server displays the processed wind speed data in the form of charts, tables, etc. on the user interface for the user to view and analyze. At the same time, a data report can be generated for further research use.

[0119] The lidar wind measurement station realizes high-precision measurement and dynamic optimization of the wind farm's wind field characteristics through the collaborative observation of multiple radars and advanced data processing techniques. This system significantly improves the operation efficiency and management level of the wind farm and provides strong technical support for the construction of an intelligent wind farm.

[0120] Refer to Figure 3 , this application discloses a structural schematic diagram of a lidar wind measurement radar. The main components of the lidar wind measurement radar 30 include a laser 301, an angle encoder 302, a pan-tilt servo motor 303, an antenna 304, a balanced detector 305, a data acquisition card 306, a central control card 307, and a 5G communication card 308.

[0121] The laser 301 is used to generate laser pulses. The laser is one of the core components of the lidar wind profiler, and its main function is to generate high-energy and high-frequency laser pulses. After being processed by the internal optical system, these laser pulses are emitted into the atmosphere. As a light source for wind measurement, the laser pulses emitted into the atmosphere will interact with aerosol particles in the atmosphere and generate scattered echoes. The laser emitted by the laser has a specific wavelength and frequency. By analyzing the received scattered echo signals and using principles such as the Doppler frequency shift effect, information such as the wind speed and wind direction in the atmosphere can be inverted.

[0122] The angle encoder 302 is used to measure the tilt angle of the lidar wind profiler device itself. In actual applications, the device may be tilted due to the installation environment or external factors. The inclination encoder can monitor the tilt state of the device in real time and feedback the angle information to the central control card 307.

[0123] Based on the measured tilt angle, the central control card 307 can make corresponding corrections to the laser emission direction to ensure that the laser is always emitted into the atmosphere at the correct angle, thereby improving the accuracy and reliability of wind measurement.

[0124] The main function of the pan-tilt servo motor 303 is to drive the pan-tilt of the lidar wind profiler to rotate precisely under the control of the central control card 307. The pan-tilt is a platform that carries the laser emission and reception devices. Through the control of the servo motor, the pan-tilt can be flexibly rotated in the horizontal and vertical directions.

[0125] The servo motor can adjust the pan-tilt to the specified angle position according to the instructions of the central control card 307, realizing precise control of the laser emission direction. This can ensure that the laser can accurately irradiate the target area or scan according to the preset scan trajectory, thereby obtaining more comprehensive and accurate wind field data.

[0126] It has a fast response speed and good stability, can complete the angle adjustment in a short time, and maintain a stable state, avoiding affecting the accuracy of wind measurement data due to pan-tilt shaking or untimely adjustment.

[0127] The antenna 304 emits the laser pulse signal generated by the laser into the atmosphere. The laser signal is expanded and collimated through the antenna system to ensure that it can propagate to the target area in a suitable direction and intensity. The emission direction of the antenna can be precisely adjusted through the servo control system to cover different measurement areas and altitude layers.

[0128] When the laser signal propagates in the atmosphere and interacts with aerosol particles, etc., scattered echoes, i.e., backscattering, will be generated. The antenna is responsible for receiving these scattered echo signals and focusing them onto the balanced detector. To improve the receiving efficiency and signal quality, the antenna usually has a high gain and a large receiving aperture to collect as many scattered signals as possible.

[0129] Inside the balanced detector 305, there are two mutually matching photodiodes and a low-noise transimpedance amplifier. When the received backscattered laser signal and the local oscillator optical signal generate photocurrents on the detector, the balanced detector subtracts these two signals, effectively eliminating common-mode noise, such as background light noise, noise generated by electronic components, etc. At the same time, the transimpedance amplifier amplifies the signal to increase the signal intensity, making it easier for subsequent processing and analysis.

[0130] The balanced detector converts the optical signal into an electrical signal and outputs a radio frequency (RF) signal. These RF signals contain the beat frequency information of the backscattered laser signal and the local oscillator optical signal, i.e., Doppler frequency shift information. The subsequent signal processing unit processes these RF signals through sampling, filtering, spectrum analysis, etc., extracts the magnitude and frequency of the Doppler frequency shift, and then calculates the moving speed of the particles in the atmosphere, i.e., the wind speed.

[0131] The acquisition card 306 includes a preamplifier, a multi-stage amplification circuit, a filter, a high-speed analog-to-digital converter, and a signal processing unit, etc. The electrical signal converted from the backscattered signal is initially amplified by the preamplifier of the acquisition card to increase the signal intensity and make it easier for subsequent processing. To ensure that the signal is amplified to an appropriate amplitude while avoiding overload or distortion, the acquisition card may use a multi-stage amplification circuit. During the amplification process, through an accurate gain control circuit, the amplification factor is dynamically adjusted according to the initial intensity of the signal to ensure that the signal is amplified within the optimal range and provide a high-quality electrical signal for subsequent signal processing.

[0132] The backscattered signal may contain various frequency component interferences, such as environmental light noise, noise generated by electronic components, etc. The bandpass filter allows signals within a specific frequency range to pass through while attenuating signals of other frequencies. The acquisition card designs a suitable bandpass filter according to the frequency characteristics of its working laser, only retaining the frequency components related to the laser signal, effectively removing interference signals of irrelevant frequencies, and improving the signal-to-noise ratio of the signal.

[0133] In practical applications, the characteristics and intensity of interference signals may vary with time, such as atmospheric turbulence, changes in background light intensity, etc. The adaptive filter can monitor the changes in signals and interference in real time and automatically adjust the parameters of the filter, such as the center frequency and bandwidth of the filter, according to a certain algorithm to always maintain the best filtering effect and ensure that the useful information in the backscattered laser signal is retained and extracted to the greatest extent.

[0134] The analog signal after amplification and filtering needs to be sampled and digitized by a high-speed analog-to-digital converter (ADC) to convert the continuous analog signal into a discrete digital signal. The sampling frequency and resolution of the ADC need to be selected according to the measurement requirements and signal characteristics of the radar to ensure that the detailed information in the signal can be accurately captured.

[0135] It is used to calculate the movement speed of particles in the atmosphere and then obtain the wind speed by measuring the frequency shift (Doppler frequency shift) of the backscattered signal relative to the transmitted laser signal using the principle of the Doppler effect. Specifically, the signal processing unit of the radar performs spectral analysis methods such as fast Fourier transform (FFT) on the digitized signal to determine the frequency components of the signal. According to the Doppler frequency shift formula, combined with parameters such as the wavelength and emission angle of the radar, the Doppler frequency shift is converted into wind speed and wind direction.

[0136] The central control card 307 is the control and information processing center of the product. At the control level, as the only control instruction issuing unit, it is for the consistency of the actions of each module and to reduce time errors. In terms of information processing, it mainly adds time and space coordinates to the signal, unifies the timekeeping, reads the pitch angle data of the angle encoder to calculate the three-dimensional space coordinates, and keeps the horizontal data stationary after aligning with the wind profile. The central control card 307 is responsible for controlling the laser 301, angle encoder 302, pan-tilt servo motor 303, antenna 304, balance detector 305, acquisition card 306, and 5G communication card 308.

[0137] The 5G communication card 308 is used for data communication with the data server and other lidar wind sensors.

[0138] The computer device according to an embodiment of the present disclosure includes a memory and a processor. The memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0139] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the computer device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory, so that the computer device executes all or part of the steps of the learning outcome prediction method based on learning behavior data mining in the foregoing embodiments of the present disclosure.

[0140] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain good user experience effects, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included in the protection scope of the present disclosure.

[0141] Such as Figure 4 FIG. is a schematic structural diagram of a computer device provided by an embodiment of the present disclosure. It shows a schematic structural diagram of a computer device suitable for implementing the computer device in the embodiments of the present disclosure. Figure 4 The illustrated computer device is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0142] Such as Figure 4 As shown, the computer device may include a processor (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage device into a random access memory (RAM). In the RAM, various programs and data required for the operation of the computer device are also stored. The processor, ROM, and RAM are connected to each other through a bus. An input / output (I / O) interface is also connected to the bus.

[0143] Generally, the following devices may be connected to the I / O interface: an input device including, for example, a sensor or a visual information acquisition device; an output device including, for example, a display screen; a storage device including, for example, a magnetic tape, a hard disk, etc.; and a communication device. The communication device may allow the computer device to communicate with other devices (such as edge computing devices) wirelessly or wiredly to exchange data. Although a computer device with various devices is illustrated, it should be understood that it is not required to implement or include all the illustrated devices. More or fewer devices may be alternatively implemented or included.

[0144] In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present disclosure includes a computer program product that includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processor, all or part of the steps of the learning outcome prediction method based on learning behavior data mining according to the embodiments of the present disclosure are performed.

[0145] For a detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details are not repeated here.

[0146] A computer-readable storage medium according to an embodiment of the present disclosure stores non-temporary computer-readable instructions. When the non-temporary computer-readable instructions are run by a processor, all or part of the steps of the learning outcome prediction method based on learning behavior data mining according to the foregoing embodiments of the present disclosure are performed.

[0147] The above computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROMs and DVDs), magneto-optical storage media (e.g., MOs), magnetic storage media (e.g., magnetic tapes or removable hard disks), media with built-in rewritable non-volatile memories (e.g., memory cards), and media with built-in ROMs (e.g., ROM cartridges).

[0148] For a detailed description of this embodiment, reference may be made to the corresponding descriptions in the foregoing embodiments, and details are not repeated here.

[0149] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present disclosure. In addition, the above-mentioned specific details are only for illustrative purposes and for ease of understanding, and are not limitations. The above details do not limit the present disclosure to necessarily adopt the above specific details for implementation.

[0150] In the present disclosure, 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. The block diagrams of devices, apparatuses, equipment, and systems involved in the present disclosure are only illustrative examples and do not intend to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "comprising", "including", "having", etc. are open-ended words, meaning "including but not limited to", and can be used interchangeably with each other. The word "or" and "and" used herein refer to the word "and / or", and can be used interchangeably with each other, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to", and can be used interchangeably with each other.

[0151] It should also be noted that in the systems and methods of the present disclosure, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present disclosure.

[0152] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0153] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although several example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for measuring wind profiles using a lidar wind profiler, the method comprising: Configuring at least 3 lidar wind profilers and a data server; Obtaining the geographical location coordinates and the inclination angle with respect to the horizontal plane of each of the lidar wind profilers; Configuring the measurement inclination angle, azimuth angle, stratified acquisition height, and acquisition period for the at least 3 lidar wind profilers; The system clocks of the at least 3 lidar wind profilers are calibrated through GNSS or a mobile base station to achieve time synchronization; The at least 3 lidar wind profilers synchronously emit laser beams towards the same coordinate points at each of the stratified acquisition heights according to the azimuth angle and the measurement inclination angle, and receive the backscattered laser at each of the stratified acquisition heights; The at least 3 lidar wind profilers respectively capture the backscattered laser, compare the frequency of the backscattered laser with the emitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles; Each of the at least 3 lidar wind profilers sends the calculated radial velocity of the scattering particles to the data server, and the data server uses a least squares inversion algorithm and combines Kalman filtering technology to perform collaborative processing on the radial velocities of the scattering particles respectively sent by the at least 3 lidar wind profilers to obtain an accurate three-dimensional wind profile.

2. The method for measuring wind profile by the lidar according to claim 1, wherein The obtaining of the geographical location and the inclination angle with respect to the horizontal plane of each of the lidar wind profilers includes: The lidar wind profiler determines the three-dimensional coordinates of the location where the lidar wind profiler is located through a positioning system; The lidar wind profiler monitors the tilt state of the lidar wind profiler through an inclinometer and an angle encoder; the tilt state is used for the lidar wind profiler to perform attitude adjustment or to perform corresponding correction on the measurement results during data processing.

3. The method for measuring wind profiles using a lidar wind profiler according to claim 1 or 2, wherein: The measurement inclination angle is used to determine the inclination angle direction of the beam of the lidar wind profiler with respect to the horizontal plane; The stratified acquisition height is used to set the range and interval for the lidar wind profiler to collect wind profile data at different height layers; The acquisition period is used to determine the time interval for the lidar wind profiler to collect wind field data.

4. The method for measuring the wind profile by the lidar according to claim 3, characterized in that, The at least 3 lidar wind profilers synchronously emit laser beams towards the same coordinate points at each of the stratified acquisition heights and receive the backscattered laser at each of the stratified acquisition heights, including: Before observation, the stratified acquisition heights with the same height and the corresponding coordinate points are preset; the corresponding coordinate points are the common measurement target points of the at least 3 lidar wind profilers; the corresponding coordinate points have the same geographical coordinates in space and are distributed at different stratified acquisition heights; The at least 3 lidar wind profilers can adjust the emission direction according to the common measurement target points at each of the stratified acquisition heights so that the emitted laser beam accurately points to the common measurement target points; When the emitted laser beam reaches the common measurement target points, it will interact with the particles in the atmosphere to generate backscattered laser, and the at least 3 lidar wind profilers collect the backscattered laser.

5. The method for measuring wind profile by the lidar according to claim 1 or 2, characterized in that, The at least three lidar wind profilers respectively capture the backscattered laser, compare the frequency of the backscattered laser with that of the emitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles, including: The at least three lidar wind profilers utilize the Doppler effect principle to calculate the motion velocity of the particles in the atmosphere by measuring the frequency shift of the backscattered laser relative to the emitted laser beam, and then obtain the radial velocity of the scattering particles. The specific formula is as follows: Where, Δf is the frequency shift of the backscattered laser relative to the emitted laser beam, fr is the frequency of the emitted laser beam, ft is the frequency of the backscattered laser, λ is the wavelength of the emitted laser beam, v is the radial velocity of the out-scattering particles, is the angle between the emitted laser beam and the wind direction.

6. The method for measuring wind profile by the lidar according to claim 1, characterized in that Each of the at least three lidar wind profilers sends the calculated radial velocity of the scattering particles to the data server. The data server uses the least squares inversion algorithm and combines the Kalman filtering technique to perform collaborative processing on the radial velocities of the scattering particles respectively sent by the at least three lidar wind profilers to obtain an accurate three-dimensional wind profile, including: The at least three lidar wind profilers respectively send the calculated radial velocity information of the scattering particles to the data server. The radial velocity information includes the radar identification, acquisition time, stratification height, and the radial velocity of the scattering particles; The data server fuses the radial velocities of the scattering particles collected by the at least three lidar wind profilers at the same stratification height and the same time, and forms a wind speed vector through trigonometric relationships; The data server uses the least squares inversion algorithm to calculate the horizontal wind speed and vertical wind speed of each height layer through the wind speed vector; applies the Kalman filtering technique to smooth the horizontal wind speed and vertical wind speed data of each height layer to obtain the accurate three-dimensional wind profile.

7. A laser wind measurement radar system, characterized in that: The system includes: Configuring at least three lidar wind profilers and a data server; Each of the lidar wind profilers obtains its geographical location through a positioning system, and obtains the inclination angle of the lidar wind profiler with respect to the horizontal plane through an inclinometer and an encoder; Configuring the measurement inclination angle, azimuth angle, stratification acquisition height, and acquisition period for the at least three lidar wind profilers; The system clocks of the at least three lidar wind profilers are calibrated through GNSS or a mobile base station to achieve time synchronization; The at least three lidar wind profilers synchronously emit laser beams to the same coordinate points at each stratification acquisition height according to the azimuth angle and the measurement inclination angle, and receive the backscattered laser at each stratification acquisition height; The at least three lidar wind profilers respectively capture the backscattered laser, compare the frequency of the backscattered laser with that of the emitted laser beam, analyze the frequency change, and calculate the radial velocity of the scattering particles; Each of the at least three lidar wind profilers sends the calculated radial velocity of the scattering particles to the data server. The data server uses the least squares inversion algorithm and combines the Kalman filtering technique to perform collaborative processing on the radial velocities of the scattering particles respectively sent by the at least three lidar wind profilers to obtain an accurate three-dimensional wind profile; Each of the at least three lidar wind profilers is configured with different azimuth angles to obtain multiple three-dimensional wind profiles.

8. A computer device, characterized in that, The computer device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method for measuring wind profile by the lidar according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to execute the method for measuring wind profile by the lidar according to any one of claims 1-6.

10. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by a processor, the steps of the method according to any one of claims 1-6 are implemented.

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