A millimeter wave wind finding radar system based on interference self-detection and adaptive suppression

Abstract

The application discloses a millimeter wave wind measurement radar system based on interference self-detection and self-adaptive suppression, and relates to the technical field of wind measurement radars, which comprises a pre-preparation module, a preset formation module, a beam receiving module, a numerical calculation module, an image recognition module and an interference analysis module. The preset formation module forms a preset time and a preset number. The numerical calculation module calculates a wind speed measurement value at a transmission time point. The image recognition module forms a beam action area and identifies a beam interference object in the beam action area. The interference analysis module analyzes a wave speed influence probability of a space image. The interference suppression module obtains a wind speed correction value and an actual wind speed. By arranging the preset formation module, the image recognition module, the interference analysis module and the interference suppression module, the influence of interference objects in airflow is suppressed, and the actual wind speed is more accurately reflected.

Description

Technical Field

[0001] This invention relates to the field of wind measurement radar technology, specifically to a millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression. Background Technology

[0002] Millimeter-wave wind radar is a novel remote sensing device that uses millimeter-wave electromagnetic waves and the scattering effect of electromagnetic waves by atmospheric turbulence and the Doppler principle to detect wind fields. It transmits multiple beams vertically, receives and analyzes the reflected echoes of millimeter waves from aerosols, condensates, etc. in the atmosphere, calculates radial wind speed using Doppler frequency shift, and then synthesizes the horizontal wind speed and direction at different heights. However, during measurement, because airflow itself is fluctuating, wind speed is not a stable value but a fluctuating value. The dominant value representing wind speed can be selected from these fluctuations, and the data measured by wind radar can easily deviate significantly from the dominant wind speed value. Furthermore, various loose particles in the airflow have mass, and their velocity is significantly lower than the wind speed. The radar beams reflected by these particles also participate in the wind speed calculation, affecting the measurement accuracy. Summary of the Invention

[0003] To address the aforementioned technical problems, a millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression is provided. This technical solution solves the problems mentioned in the background section.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression includes: The pre-preparation module uses the direction perpendicular to the ground as the feature direction and obtains the allowable detection error based on historical measurement data. A preset generation module, which generates a preset time and a preset number of data based on the allowable detection error and the fluctuation pattern of wind speed, wherein the preset number of data is the number of detections and the preset time is the detection interval; A beam receiving and transmitting module, which forms at least one transmission time point based on a preset time and a preset number of times. At the transmission time point, the wind measuring radar transmits a radar beam along a characteristic direction, and the wind measuring radar receives at least one reflected beam of the radar beam. The numerical calculation module calculates the wind speed measurement value at the time of transmission based on the frequency of the radar beam and at least one reflected beam. The image recognition module controls the camera to acquire images along the characteristic direction on the left side of the wind measuring radar at the time of transmission, thereby obtaining a spatial image. A beam action area is formed in the spatial image, and at least one beam interference object is identified in the beam action area. The camera lens and the radar beam transmission port of the wind measuring radar are at the same height. The interference analysis module analyzes and obtains the average actual velocity of beam interference objects in the spatial image, and analyzes and obtains the probability of beam velocity influence in the spatial image. The interference suppression module pairs wind speed measurements and spatial images corresponding to the same transmission time point. Based on the average moving speed and wave speed influence probability, it corrects the wind speed measurements corresponding to the spatial images to obtain corrected wind speed values. The average of at least one corrected wind speed value is taken to obtain the actual wind speed.

[0005] Preferably, obtaining the detection allowable error includes the following steps: At least one historical qualified test result is obtained in advance, and the maximum value of the test error in the historical qualified test result is taken as the allowable test error.

[0006] Preferably, the formation of the preset time and preset number includes the following steps: In the wind tunnel, a characteristic airflow with a preset wind speed is formed. The characteristic airflow is continuously measured using a wind-measuring radar. The time point when the wind-measuring radar first measures the maximum wind speed is taken as the first time point, and the time point when the wind-measuring radar first measures the minimum wind speed is taken as the second time point. Using the first time and the second time as endpoints, a sample interval is formed, and at least one set of sample time points is formed in the sample interval, satisfying that the sample time points in the set of sample time points are evenly distributed in the sample interval; The sample time point sets are numbered from smallest to largest according to the number of elements in the sample time point set; The wind speed of the characteristic airflow is measured at the sample time point using a wind-measuring radar to obtain the sample wind speed at the sample time point. The average wind speed of the sample time points in the sample time point set is taken to obtain the main wind speed of the sample time point set; The absolute value of the difference between the main wind speed of the sample time point set numbered i and the main wind speed of the sample time point set numbered i+1 is taken as the fluctuation value of the sample time point set numbered i. If the fluctuation values ​​of the sample time point set with a number not less than j do not exceed the detection allowable error, then j is taken as the feature value, and the minimum value of the feature value is taken as the target value. The number of elements in the sample time point set whose number equals the target value is used as the preset number. The preset number is subtracted by one to get the target number. The length of the sample interval is divided by the target number to get the preset time.

[0007] Preferably, forming at least one launch time point includes the following steps: The future time interval equal to the length of the sample interval from the current time is taken as the boundary time; A detection interval is formed with the current time and the boundary time as the endpoints. At least one transmission time point is uniformly selected in the detection interval, and the number of transmission time points is equal to the preset number.

[0008] Preferably, the calculation of the wind speed measurement value at the launch time point includes the following steps: Using the Doppler velocity measurement formula, the wind speed monitoring value corresponding to the reflected beam is calculated. The average value of the wind speed monitoring value corresponding to at least one reflected beam generated at the time of transmission is taken to obtain the wind speed measurement value at the time of transmission. The Doppler velocity measurement formula is as follows: , Where v is the wind speed monitoring value corresponding to the reflected beam, f is the frequency of the radar beam, F is the frequency of the reflected beam, and c is the speed of light.

[0009] Preferably, forming the beamforming region in the spatial image includes the following steps: A sample steel pipe with the same diameter as the radar beam transmitter of the wind measuring radar is placed in front of the camera lens, and the camera captures the sample image. Obtain the pixel value of the pipe wall in the image of the sample steel pipe as the steel pipe pixel value. Collect the pixels in the sample image that have the same pixel value as the steel pipe pixel value as the steel pipe pixel point. Aggregate the steel pipe pixels to form the steel pipe region. The area enclosed in the middle of the steel pipe area is taken as the beam preparation area, and at least one edge point is uniformly selected at the edge of the beam preparation area. Coordinate modeling is performed on the sample image and at least one spatial image in the same manner, and the maximum distance between edge points is used as the image diameter; The image coefficient is obtained by dividing the diameter of the image tube by the diameter of the sample steel tube. The corrected distance is obtained by multiplying the actual distance between the camera lens and the radar beam transmitter of the wind measuring radar by the image coefficient. The beam preparation area is shifted horizontally to the right in the sample image to correct the distance, thus obtaining the beam sample area. The area in the spatial image that has the same position and shape as the beam sample area is taken as the beam action area.

[0010] Preferably, identifying at least one beam jammer in the beam action area includes the following steps: Use the pixel values ​​of the sky pixels in the image as the first pixel value, and the pixel values ​​of the clouds pixels in the image as the second pixel value; Pixels whose pixel values ​​in the beam action area are not equal to the first pixel value or the second pixel value are taken as target pixels. Adjacent target pixels are aggregated to obtain at least one beam jammer.

[0011] Preferably, the analysis to obtain the average actual velocity of beam interference in the spatial image includes the following steps: At least one identification point is uniformly selected at the edge of the beam jammer, and the average value of the coordinates of the identification points is taken to obtain the center coordinates of the beam jammer. The mean value of the center coordinates of beam interference objects in the spatial image is taken to obtain the characteristic coordinates of the spatial image; The space images are numbered from smallest to largest according to their launch time. The distance between the feature coordinates of the space image numbered k and the feature coordinates of the space image numbered k+1 is taken as the moving distance of the space image numbered k. The average actual velocity of beam interference objects in the spatial image is obtained by dividing the moving distance of the spatial image by the image coefficient and then by the preset time.

[0012] Preferably, the analysis to obtain the probability of wave velocity influence in the spatial image includes the following steps: Pixels located within beam interference objects in the spatial image are used as reference pixels. The number of pixels in the spatial image is counted as the first number, and the number of reference pixels in the spatial image is used as the second number. Dividing the second number by the first number yields the probability of wave velocity influence in the spatial image.

[0013] Preferably, the step of correcting the wind speed measurement value corresponding to the spatial image to obtain the corrected wind speed value includes the following steps: The corrected wind speed value is obtained by solving the corrected equation. The corrected equation is as follows: , Where B is the wind speed measurement value corresponding to the spatial image, p is the wave speed influence probability of the spatial image, M is the average actual velocity of beam interference objects in the spatial image, and N is the wind speed correction value.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By setting preset generation modules, image recognition modules, interference analysis modules, and interference suppression modules, the number of detections and detection intervals can be set according to the pattern of wind speed fluctuations. This allows for the integration of multiple detection results to form a more accurate master value reflecting wind speed fluctuations. In addition, the radar beam emission area can be identified, thereby identifying objects in that area that interfere with wind speed. Based on their movement speed, the wind speed measurement value obtained by radar detection is corrected, thus suppressing the influence of interfering objects in the airflow and more accurately reflecting the actual wind speed. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to the present invention. Figure 2 This is a flowchart illustrating the process of forming a preset time and a preset number of items according to the present invention; Figure 3 This is a schematic diagram of the process for forming at least one launch time point according to the present invention; Figure 4 This is a schematic diagram of the process for forming a beamforming region in a spatial image according to the present invention; Figure 5 This is a schematic diagram of the process of identifying at least one beam interference object in the beam action area according to the present invention; Figure 6 This is a schematic diagram illustrating the process of obtaining the average actual velocity of beam interference objects in a spatial image based on the analysis of this invention. Figure 7 This is a schematic diagram illustrating the process of analyzing and obtaining the probability of wave velocity influence in spatial images according to the present invention. Detailed Implementation

[0016] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0017] Reference Figure 1 As shown, a millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression includes: The pre-preparation module uses the direction perpendicular to the ground as the feature direction and obtains the allowable detection error based on historical measurement data. A preset generation module, which generates a preset time and a preset number of data based on the allowable detection error and the fluctuation pattern of wind speed, wherein the preset number of data is the number of detections and the preset time is the detection interval; A beam receiving and transmitting module, which forms at least one transmission time point based on a preset time and a preset number of times. At the transmission time point, the wind measuring radar transmits a radar beam along a characteristic direction, and the wind measuring radar receives at least one reflected beam of the radar beam. The numerical calculation module calculates the wind speed measurement value at the time of transmission based on the frequency of the radar beam and at least one reflected beam. The image recognition module controls the camera to acquire images along the characteristic direction on the left side of the wind measuring radar at the time of transmission, thereby obtaining a spatial image. A beam action area is formed in the spatial image, and at least one beam interference object is identified in the beam action area. The camera lens and the radar beam transmission port of the wind measuring radar are at the same height. The interference analysis module analyzes and obtains the average actual velocity of beam interference objects in the spatial image, and analyzes and obtains the probability of beam velocity influence on the spatial image. The interference suppression module pairs wind speed measurements and spatial images corresponding to the same transmission time point. Based on the average moving speed and wave speed influence probability, it corrects the wind speed measurements corresponding to the spatial images to obtain corrected wind speed values. The average of at least one corrected wind speed value is taken to obtain the actual wind speed.

[0018] Because airflow is undulating, the actual wind speed is a multi-valued value, not a single value, while wind-measuring radar detects only a single value. Therefore, without limiting the detection method, the obtained data may not accurately reflect the wind speed, resulting in a significant discrepancy with the main components of wind speed. Detection primarily relies on the Doppler principle: when the electromagnetic waves emitted by the radar encounter moving particles in the atmosphere (such as aerosols or water droplets) and are reflected back, the frequency of the reflected wave changes. This frequency change (Doppler shift) is proportional to the particle's velocity along the radar beam direction (radial velocity). Thus, the particle's velocity can be calculated based on the change in the transmitted beam frequency and used as the wind speed. However, it's normal for wind to contain various debris. If the radar beam hits debris during detection, the debris's large mass will cause its velocity to be significantly lower than the wind speed, leading to inaccurate wind speed measurements. Therefore, a series of steps are implemented to address the aforementioned issues. Note: i, j, and k mentioned in this scheme are all counting numbers.

[0019] Obtaining the allowable error for detection includes the following steps: At least one historical qualified test result is obtained in advance, and the maximum value of the test error in the historical qualified test result is taken as the allowable test error.

[0020] Reference Figure 2 As shown, the process of setting a preset time and a preset number of items includes the following steps: In the wind tunnel, a characteristic airflow with a preset wind speed is formed. The characteristic airflow is continuously measured using a wind-measuring radar. The time point when the wind-measuring radar first measures the maximum wind speed is taken as the first time point, and the time point when the wind-measuring radar first measures the minimum wind speed is taken as the second time point. Using the first time and the second time as endpoints, a sample interval is formed, and at least one set of sample time points is formed in the sample interval, satisfying that the sample time points in the set of sample time points are evenly distributed in the sample interval; The sample time point sets are numbered from smallest to largest according to the number of elements in the sample time point set; The wind speed of the characteristic airflow is measured at the sample time point using a wind-measuring radar to obtain the sample wind speed at the sample time point. The average wind speed of the sample time points in the sample time point set is taken to obtain the main wind speed of the sample time point set; The absolute value of the difference between the main wind speed of the sample time point set numbered i and the main wind speed of the sample time point set numbered i+1 is taken as the fluctuation value of the sample time point set numbered i. If the fluctuation values ​​of the sample time point set with a number not less than j do not exceed the detection allowable error, then j is taken as the feature value, and the minimum value of the feature value is taken as the target value. The number of elements in the sample time point set whose number equals the target value is used as the preset number. The preset number is subtracted by one to get the target number. The length of the sample interval is divided by the target number to get the preset time.

[0021] Airflow fluctuations are typically periodic. Therefore, in continuous measurements, i.e., high-density measurements, the time intervals corresponding to two adjacent maximum and minimum wind speeds constitute a complete cycle of the fluctuation. High-density detection can accurately obtain values ​​that reflect the main part of the wind speed, but its excessive use of the wind-measuring radar can reduce its lifespan. Therefore, the number of measurements and the measurement interval of the wind-measuring radar are set. Here, the larger the sample time point set number, the more sample time points it contains, i.e., the more detections are performed. As the number of detections increases, the fluctuation of the main wind speed of the detected sample time point set becomes smaller and smaller. Consequently, there must exist a j such that the fluctuation values ​​of the sample time point set numbered not less than j do not exceed the detection allowable error. As long as the detection is performed according to the sample time points in the sample time point set numbered j, the detection results meet the accuracy requirements and can reflect the main part of the wind speed. Therefore, using the sample time points in the sample time point set numbered equal to the target value for detection minimizes the number of detections and meets the requirements. It should be noted that the sample time points in the sample time point set are evenly distributed in the sample interval, with two sample time points located at the endpoints of the sample interval. Therefore, the interval is equal to the preset number minus one. Thus, the length of the sample interval is divided by the number of targets to obtain the preset time, which is used as the detection interval. Here, the characteristic airflow is generated in the wind tunnel, and there is only the influence of airflow fluctuations, without the influence of drifting debris.

[0022] Reference Figure 3 As shown, forming at least one launch time point includes the following steps: The future time interval equal to the length of the sample interval from the current time is taken as the boundary time; A detection interval is formed with the current time and the boundary time as the endpoints. At least one transmission time point is uniformly selected in the detection interval, and the number of transmission time points is equal to the preset number.

[0023] Here, at least one emission time point is taken sequentially from the left end of the detection interval, and the interval between adjacent emission time points is equal to a preset time.

[0024] The calculation of the wind speed measurement at the launch time includes the following steps: Using the Doppler velocity measurement formula, the wind speed monitoring value corresponding to the reflected beam is calculated. The average value of the wind speed monitoring value corresponding to at least one reflected beam generated at the time of transmission is taken to obtain the wind speed measurement value at the time of transmission. The Doppler velocity measurement formula is as follows: , Where v is the wind speed monitoring value corresponding to the reflected beam, f is the frequency of the radar beam, F is the frequency of the reflected beam, and c is the speed of light.

[0025] The Doppler velocity measurement formula is an existing formula. Its main principle is that the frequency change of the radar beam (i.e., Doppler frequency shift) is proportional to the velocity of the particle along the direction of the radar beam (i.e., radial velocity). Therefore, as long as the radar beam is emitted perpendicular to the ground, the measured value is the wind speed. Airflow exists in multiple layers, and the wind speed is different at different layers. When the radar beam reaches different layers, it will generate reflected beams. Therefore, the average value of the detection results of at least one reflected beam is taken to obtain the wind speed measurement value at the time of transmission.

[0026] Reference Figure 4 As shown, forming a beamforming region in a spatial image includes the following steps: A sample steel pipe with the same diameter as the radar beam transmitter of the wind measuring radar is placed in front of the camera lens, and the camera captures the sample image. Obtain the pixel value of the pipe wall in the image of the sample steel pipe as the steel pipe pixel value. Collect the pixels in the sample image that have the same pixel value as the steel pipe pixel value as the steel pipe pixel point. Aggregate the steel pipe pixels to form the steel pipe region. The area enclosed in the middle of the steel pipe area is taken as the beam preparation area, and at least one edge point is uniformly selected at the edge of the beam preparation area. Coordinate modeling is performed on the sample image and at least one spatial image in the same manner, and the maximum distance between edge points is used as the image diameter; The image coefficient is obtained by dividing the diameter of the image tube by the diameter of the sample steel tube. The corrected distance is obtained by multiplying the actual distance between the camera lens and the radar beam transmitter of the wind measuring radar by the image coefficient. The beam preparation area is shifted horizontally to the right in the sample image to correct the distance, thus obtaining the beam sample area. The area in the spatial image that has the same position and shape as the beam sample area is taken as the beam action area.

[0027] In order to eliminate the interference encountered during radar beam detection, it is necessary to identify the interference objects encountered. Therefore, image recognition is required. However, only a portion of the spatial image contains the radar beam. Therefore, it is necessary to identify the area where the radar beam exists and ignore the interference objects in the remaining area. The camera lens and the radar beam transmitter of the wind measuring radar are both set along the characteristic direction. The part enclosed by the beam preparation area is a hollow part, which is consistent with the shape of the radar beam transmitter. However, according to the setting of the camera lens and the radar beam transmitter of the wind measuring radar, the beam preparation area needs to be moved to obtain the area where the radar beam exists. Here, it is necessary to convert the actual distance between the camera lens and the radar beam transmitter of the wind measuring radar into the image distance, that is, the corrected distance. The principle is that the ratio of the distance in the image to the corresponding actual distance is a fixed value. Since the camera is to the left of the wind-measuring radar, moving it to the right yields the beam sample area, which is the area where the radar beam exists in the image.

[0028] Reference Figure 5 As shown, identifying at least one beam jammer in the beam action area includes the following steps: Use the pixel values ​​of the sky pixels in the image as the first pixel value, and the pixel values ​​of the clouds pixels in the image as the second pixel value; Pixels whose pixel values ​​in the beam action area are not equal to the first pixel value or the second pixel value are taken as target pixels. Adjacent target pixels are aggregated to obtain at least one beam jammer.

[0029] Reference Figure 6As shown, the analysis of the average actual velocity of beam interference in the spatial image includes the following steps: At least one identification point is uniformly selected at the edge of the beam jammer, and the average value of the coordinates of the identification points is taken to obtain the center coordinates of the beam jammer. The mean value of the center coordinates of beam interference objects in the spatial image is taken to obtain the characteristic coordinates of the spatial image; The space images are numbered from smallest to largest according to their launch time. The distance between the feature coordinates of the space image numbered k and the feature coordinates of the space image numbered k+1 is taken as the moving distance of the space image numbered k. The average actual velocity of beam interference objects in the spatial image is obtained by dividing the moving distance of the spatial image by the image coefficient and then by the preset time.

[0030] The average moving speed of beam jammers is mainly estimated by the overall movement of beam jammers in adjacent spatial images. Since the time interval between adjacent spatial images is short, the beam jammers in them are almost the same, only their positions have changed. Therefore, the speed of beam jammers can be calculated based on this. However, the moving distance in the spatial image is the distance in the image, which needs to be divided by the image coefficient to convert it into the actual speed.

[0031] Reference Figure 7 As shown, the analysis of the probability of wave velocity influence in spatial images includes the following steps: Pixels located within beam interference objects in the spatial image are used as reference pixels. The number of pixels in the spatial image is counted as the first number, and the number of reference pixels in the spatial image is used as the second number. Dividing the second number by the first number yields the probability of wave velocity influence in the spatial image.

[0032] Since there are many radar beams being emitted, the probability of them coming into contact with beam jammers is equal to the area of ​​the beam jammers within the beam's effective region.

[0033] Correcting the wind speed measurements corresponding to the spatial image to obtain the corrected wind speed values ​​involves the following steps: The corrected wind speed value is obtained by solving the corrected equation. The corrected equation is as follows: , Where B is the wind speed measurement value corresponding to the spatial image, p is the wave speed influence probability of the spatial image, M is the average actual velocity of beam interference objects in the spatial image, and N is the wind speed correction value.

[0034] B is the wind speed measurement value corresponding to the spatial image, which is a comprehensive result of radar beams that have come into contact with beam interference and those that have not. p is the probability of encountering a beam jammer in the radar beam, p*M is the contribution of the beam jammer's velocity to B, 1-p is the probability of not encountering a beam jammer in the radar beam, then this part is the wind speed without interference, which is the required wind speed correction value, (1-p)*N is the contribution of the wind speed without interference to B, therefore, the wind speed correction value can be calculated through this equation.

[0035] Furthermore, this solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is invoked, it executes the aforementioned millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression.

[0036] It is understandable that the storage medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid-state drive (SSD).

[0037] In summary, the advantages of this invention are as follows: by setting a preset forming module, an image recognition module, an interference analysis module, and an interference suppression module, the number of detections and the detection interval can be set according to the pattern of wind speed fluctuations, thereby integrating the results of multiple detections to form a more accurate master value reflecting wind speed fluctuations. In addition, by identifying the area where the radar beam is emitted, objects that interfere with wind speed in that area can be identified. Thus, the wind speed measurement value obtained by radar detection can be corrected according to their movement speed, thereby suppressing the influence of interfering objects in the airflow and thus reflecting the actual wind speed more accurately.

[0038] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression, characterized in that, include: The pre-preparation module uses the direction perpendicular to the ground as the feature direction and obtains the allowable detection error based on historical measurement data. A preset generation module, which generates a preset time and a preset number of data based on the allowable detection error and the fluctuation pattern of wind speed, wherein the preset number of data is the number of detections and the preset time is the detection interval; A beam receiving and transmitting module, which forms at least one transmission time point based on a preset time and a preset number of times. At the transmission time point, the wind measuring radar transmits a radar beam along a characteristic direction, and the wind measuring radar receives at least one reflected beam of the radar beam. The numerical calculation module calculates the wind speed measurement value at the time of transmission based on the frequency of the radar beam and at least one reflected beam. The image recognition module controls the camera to acquire images along the characteristic direction on the left side of the wind measuring radar at the time of transmission, thereby obtaining a spatial image. A beam action area is formed in the spatial image, and at least one beam interference object is identified in the beam action area. The camera lens and the radar beam transmission port of the wind measuring radar are at the same height. The interference analysis module analyzes and obtains the average actual velocity of beam interference objects in the spatial image, and analyzes and obtains the probability of beam velocity influence in the spatial image. The interference suppression module pairs wind speed measurements and spatial images corresponding to the same transmission time point. Based on the average moving speed and wave speed influence probability, it corrects the wind speed measurements corresponding to the spatial images to obtain corrected wind speed values. The average of at least one corrected wind speed value is taken to obtain the actual wind speed.

2. The millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 1, characterized in that, The process of obtaining the allowable detection error includes the following steps: At least one historical qualified test result is obtained in advance, and the maximum value of the test error in the historical qualified test result is taken as the allowable test error.

3. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 2, characterized in that, The formation of the preset time and preset number includes the following steps: In the wind tunnel, a characteristic airflow with a preset wind speed is formed. The characteristic airflow is continuously measured using a wind-measuring radar. The time point when the wind-measuring radar first measures the maximum wind speed is taken as the first time point, and the time point when the wind-measuring radar first measures the minimum wind speed is taken as the second time point. Using the first time and the second time as endpoints, a sample interval is formed, and at least one set of sample time points is formed in the sample interval, satisfying that the sample time points in the set of sample time points are evenly distributed in the sample interval; The sample time point sets are numbered from smallest to largest according to the number of elements in the sample time point set; The wind speed of the characteristic airflow is measured at the sample time point using a wind-measuring radar to obtain the sample wind speed at the sample time point. The average wind speed of the sample time points in the sample time point set is taken to obtain the main wind speed of the sample time point set; The absolute value of the difference between the main wind speed of the sample time point set numbered i and the main wind speed of the sample time point set numbered i+1 is taken as the fluctuation value of the sample time point set numbered i. If the fluctuation values ​​of the sample time point set with a number not less than j do not exceed the detection allowable error, then j is taken as the feature value, and the minimum value of the feature value is taken as the target value. The number of elements in the sample time point set whose number equals the target value is used as the preset number. The preset number is subtracted by one to get the target number. The length of the sample interval is divided by the target number to get the preset time.

4. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 3, characterized in that, The process of forming at least one launch time point includes the following steps: The future time interval equal to the length of the sample interval from the current time is taken as the boundary time; A detection interval is formed with the current time and the boundary time as the endpoints. At least one transmission time point is uniformly selected in the detection interval, and the number of transmission time points is equal to the preset number.

5. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 4, characterized in that, The calculation of the wind speed measurement value at the launch time point includes the following steps: Using the Doppler velocity measurement formula, the wind speed monitoring value corresponding to the reflected beam is calculated. The average value of the wind speed monitoring value corresponding to at least one reflected beam generated at the time of transmission is taken to obtain the wind speed measurement value at the time of transmission. The Doppler velocity measurement formula is as follows: ， Where v is the wind speed monitoring value corresponding to the reflected beam, f is the frequency of the radar beam, F is the frequency of the reflected beam, and c is the speed of light.

6. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 5, characterized in that, The process of forming a beamforming region in a spatial image includes the following steps: A sample steel pipe with the same diameter as the radar beam transmitter of the wind measuring radar is placed in front of the camera lens, and the camera captures the sample image. Obtain the pixel value of the pipe wall in the image of the sample steel pipe as the steel pipe pixel value. Collect the pixels in the sample image that have the same pixel value as the steel pipe pixel value as the steel pipe pixel point. Aggregate the steel pipe pixels to form the steel pipe region. The area enclosed in the middle of the steel pipe area is taken as the beam preparation area, and at least one edge point is uniformly selected at the edge of the beam preparation area. Coordinate modeling is performed on the sample image and at least one spatial image in the same manner, and the maximum distance between edge points is used as the image diameter; The image coefficient is obtained by dividing the diameter of the image tube by the diameter of the sample steel tube. The corrected distance is obtained by multiplying the actual distance between the camera lens and the radar beam transmitter of the wind measuring radar by the image coefficient. The beam preparation area is shifted horizontally to the right in the sample image to correct the distance, thus obtaining the beam sample area. The area in the spatial image that has the same position and shape as the beam sample area is taken as the beam action area.

7. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 6, characterized in that, The process of identifying at least one beam jammer in the beam action area includes the following steps: Use the pixel values ​​of the sky pixels in the image as the first pixel value, and the pixel values ​​of the clouds pixels in the image as the second pixel value; Pixels whose pixel values ​​in the beam action area are not equal to the first pixel value or the second pixel value are taken as target pixels. Adjacent target pixels are aggregated to obtain at least one beam jammer.

8. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 7, characterized in that, The analysis to obtain the average actual velocity of beam interference in the spatial image includes the following steps: At least one identification point is uniformly selected at the edge of the beam jammer, and the average value of the coordinates of the identification points is taken to obtain the center coordinates of the beam jammer. The mean value of the center coordinates of beam interference objects in the spatial image is taken to obtain the characteristic coordinates of the spatial image; The space images are numbered from smallest to largest according to their launch time. The distance between the feature coordinates of the space image numbered k and the feature coordinates of the space image numbered k+1 is taken as the moving distance of the space image numbered k. The average actual velocity of beam interference objects in the spatial image is obtained by dividing the moving distance of the spatial image by the image coefficient and then by the preset time.

9. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 8, characterized in that, The analysis to obtain the probability of wave velocity influence in the spatial image includes the following steps: Pixels located within beam interference objects in the spatial image are used as reference pixels. The number of pixels in the spatial image is counted as the first number, and the number of reference pixels in the spatial image is used as the second number. Dividing the second number by the first number yields the probability of wave velocity influence in the spatial image.

10. A millimeter-wave wind measurement radar system based on interference self-detection and adaptive suppression according to claim 9, characterized in that, The process of correcting the wind speed measurement value corresponding to the spatial image to obtain the corrected wind speed value includes the following steps: The corrected wind speed value is obtained by solving the corrected equation. The corrected equation is as follows: ， Where B is the wind speed measurement value corresponding to the spatial image, p is the wave speed influence probability of the spatial image, M is the average actual velocity of beam interference objects in the spatial image, and N is the wind speed correction value.

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