Wind measurement laser radar wind field inversion optimization method, system and device based on floating platform and medium

Abstract

The invention relates to a floating platform-based wind measurement laser radar wind field inversion optimization method, system and device, and a medium, and the method comprises the steps: carrying out the PPI scanning through a laser radar, and obtaining the radial wind speed before correction; correcting the radial velocity component caused by the floating platform in the radial wind speed before correction for the first time; acquiring the real wind speed and wind direction at the preset position by using the mobile wind meter, and calculating the first radial wind speed corresponding to the azimuth angle of the mobile wind meter before laser radar correction according to the real wind speed and the real wind direction; performing RHI scanning at a preset position, and processing according to an RHI scanning result to obtain a second radial wind speed; based on the first radial wind speed and the second radial wind speed, carrying out second correction on the radial wind speed after the first correction; and based on the second correction result, performing inversion optimization on the sea surface wind field by adopting a VAP algorithm to obtain wind speed and wind direction data. The method can be widely applied to the technical field of remote sensing marine environment monitoring.

Description

Technical Field

[0001] The invention relates to a floating platform-based wind laser radar wind field inversion optimization method, system, equipment and medium, belonging to the technical field of remote sensing marine environment monitoring. Background Art

[0002] As floating platforms at sea, such as ships and buoys, are affected by surges, the laser beam pointing in the laser radar installed on the floating platform deviates from the set direction during measurement, causing deviations in the measured wind speed and wind direction. It is necessary to correct the spatial light output angle of the laser radar relative to the earth. The pitch angle deviation of the corrected radial beam causes the beam to be unevenly distributed in space, and there is a deviation between the pitch angle of the radial beam at each azimuth and the pitch angle of the target wind field. A 1-degree pitch angle deviation of the radial beam can result in a height difference of 90 meters at a radial distance of 5 km and a height difference of about 180 meters at a radial distance of 10 km, which ultimately leads to a large error in the inversion of the horizontal wind field. The larger the pitch angle deviation, the farther away from the laser radar, the greater the fluctuation height, and the greater the error in the inverted horizontal wind field. Therefore, it is necessary to correct the height difference caused by the corrected beam on the floating platform.

[0003] At present, the attitude correction algorithm is relatively mature. It mainly corrects the spatial angle of the radar beam relative to the floating platform coordinate system to the spatial angle relative to the earth coordinate system through the conversion of the spatial coordinate system. The swing angle of the floating platform coordinate system can be measured by installing an inertial navigation system.

[0004] Furthermore, if you want to correct the height difference, you need a reference to the real wind speed. There is no reference data available at present. You can measure it through an in-situ wind speed sensor installed on a floating platform near the lidar. Generally, an anemometer and a wind vane or an ultrasonic anemometer are used. Since the in-situ wind measuring instrument measures a single point, it is impossible to invert the horizontal wind field, but the correction method is simple and less affected by the attitude. By measuring the real wind speed of a single point, the radial speed of the real wind speed at each beam azimuth is calculated, and the difference with the measured wind speed can be used as a preliminary height wind speed fluctuation coefficient.

[0005] Since there are no in-situ instruments at other heights and distances, there will be certain errors when directly using the height wind speed fluctuation coefficient to correct the entire wind field, and the height wind speed fluctuation coefficient needs to be corrected. Therefore, an RHI scan is superimposed on the PPI scan. Since the RHI scan is a scan on the vertical plane, when the floating platform is swaying, as long as the swaying angle is within the pitch angle scanning range of this RHI, the measured radial direction of the pitch angle of the target wind field can be obtained. This measured radial direction is used to correct the fluctuation coefficient. After iteration, a more accurate radial velocity can be obtained, and the horizontal wind field can be further inverted. Summary of the invention

[0006] In view of the above problems, the purpose of the present invention is to provide a wind field inversion optimization method, system, equipment and medium based on a floating platform wind measurement lidar. The method is based on a Doppler wind measurement lidar on a floating platform. In the PPI scanning mode, the first distance library is calibrated by an in-situ wind measurement sensor, and the fluctuation coefficient that can be used to correct the height deviation is calculated. At the same time, in combination with the RHI scanning mode, the fluctuation coefficient is further iteratively corrected to obtain a more accurate radial velocity of the entire wind field, and then the overall wind field inversion is performed.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a method for inversion optimization of wind field using a wind laser radar based on a floating platform, comprising the following steps:

[0009] Use laser radar to perform PPI scanning and obtain radial wind speed before correction;

[0010] Perform the first correction on the radial velocity component caused by the floating platform in the radial wind velocity before correction;

[0011] Using a mobile anemometer to obtain the true wind speed and wind direction at a preset position, and obtaining a first radial wind speed according to the true wind speed and the true wind direction;

[0012] Performing an RHI scan at a preset position, and obtaining a second radial wind speed according to the RHI scan result;

[0013] Performing a second correction on the radial wind speed after the first correction based on the first radial wind speed and the second radial wind speed;

[0014] Based on the second correction results, the VAP algorithm is used to invert and optimize the sea surface wind field to obtain wind speed and direction data.

[0015] Further, the PPI scanning is performed using a laser radar, and the radial wind speed before correction is obtained, including:

[0016] A scanning laser radar installed on a floating platform is used to perform PPI scanning with a fixed pitch angle and a changed azimuth angle, and the azimuth and pitch angles of the laser beam relative to the floating platform are recorded;

[0017] The inertial navigation system is used to record the attitude angle of the floating platform relative to the geographic coordinate system, and the azimuth and pitch angles of the laser beam relative to the geographic coordinate system are obtained by transforming the geographic coordinate system and the floating platform coordinate system, and the radial wind speed is calculated.

[0018] Furthermore, the first correction of the radial velocity component caused by the floating platform in the radial wind velocity before correction includes:

[0019] Based on the pitch angle and azimuth angle of the laser beam relative to the geographic coordinate system and the three-axis motion speed of the floating platform recorded by GPS, a calculated value of the radial velocity component caused by the motion of the floating platform is obtained;

[0020] Based on the laser radar echo data, the measured values ​​of the radial velocity component of the floating platform and the wind speed are extracted, and the calculated values ​​are subjected to attitude correction.

[0021] Further, the method of using a mobile anemometer to obtain a true wind speed and a wind direction at a preset position, and obtaining a first radial wind speed according to the true wind speed and the true wind direction, includes:

[0022] In the first laser radar distance library R 1 The corrected front angle corresponding to the nth laser beam Install GPS-based mobile anemometers to measure the real wind speed and direction data;

[0023] According to the obtained true wind speed and true wind direction, the radial wind speed corresponding to the azimuth angle of the mobile anemometer in front of the laser radar correction is calculated as V los_mast,i , as the first radial wind speed.

[0024] Further, performing RHI scanning at a preset position and obtaining a second radial wind speed according to the RHI scanning result includes:

[0025] In the first laser radar distance library R 1 The corrected front angle corresponding to the nth laser beam Perform RHI scan at the location to obtain the radial wind speed corresponding to the RHI scan;

[0026] The radial wind speed corresponding to the RHI scan is attitude corrected to obtain the azimuth and pitch angles of the RHI after attitude correction, which are expressed as and θ g_rhi,k , and calculate the second radial wind speed.

[0027] Further, the second correction of the radial wind speed after the first correction based on the first radial wind speed and the second radial wind speed includes:

[0028] The pitch angle θ before correction 0,i The corresponding PPI scanning surface is used as the target scanning surface to calculate the initial value of the fluctuation coefficient of different laser beams in the first distance library due to the swaying posture of the floating platform;

[0029] The fluctuation coefficient of the first distance library is iterated to the second distance library, and the radial wind speed V of the second distance library is preliminarily corrected. los_ref,i,2 ';

[0030] Radial wind speed V based on the second distance library after preliminary correction los_ref,i,2 ', calculate the main wind direction and main wind speed of the second distance library;

[0031] The radial wind speed of the second distance library is corrected for the second time using the RHI scanning data to obtain the final corrected radial wind speed of the second distance library and its fluctuation coefficient;

[0032] Repeat the above steps to invert the radial wind speed deviation ΔV of the jth distance bin los,i,j , the fluctuation coefficient of the j-th distance library due to the swing posture of the floating platform is β i,j , iteratively correct the radial velocity V of the j-th distance bin los_ref,i,j .

[0033] Furthermore, based on the second correction result, the VAP algorithm is used to perform inversion optimization on the sea surface wind field to obtain wind speed and wind direction data, including:

[0034] Take the average of adjacent azimuth intervals;

[0035] Based on the average azimuth angle, the radial wind speed on the same altitude circle is taken, and the horizontal wind field of the altitude circle is inferred from the radial wind speed at the center point of the area through trigonometric relationship, and the horizontal wind fields on other altitude circles are calculated in turn.

[0036] In a second aspect, the present invention provides a wind field inversion optimization system based on a floating platform using a wind laser radar, comprising:

[0037] A radial wind speed acquisition module before correction is used to perform PPI scanning using a laser radar and obtain the radial wind speed before correction;

[0038] A first correction module, used for performing a first correction on a radial velocity component of the radial wind velocity before correction caused by the floating platform;

[0039] A first radial wind speed acquisition module is used to acquire the true wind speed and wind direction at a preset position using a mobile anemometer, and obtain a first radial wind speed according to the true wind speed and the true wind direction;

[0040] A second radial wind speed acquisition module, used for performing RHI scanning at a preset position and obtaining a second radial wind speed according to the RHI scanning result;

[0041] A second correction module, configured to perform a second correction on the radial wind speed after the first correction based on the first radial wind speed and the second radial wind speed;

[0042] The inversion module is used to invert and optimize the sea surface wind field based on the second correction result using the VAP algorithm to obtain wind speed and wind direction data.

[0043] In a third aspect, the present invention provides a computer-readable storage medium storing one or more programs, wherein the one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform any method.

[0044] In a fourth aspect, the present invention provides a computing device, comprising: one or more processors and a memory, wherein the memory stores one or more programs and is configured to be executed by the one or more processors, and the one or more programs include instructions for executing any method.

[0045] Since the present invention adopts the above technical scheme, it has the following advantages: due to the swaying posture of the floating platform, the radial beam corrected by the wind measuring laser radar has a spatial height deviation relative to the target wind field, and the laser radar PPI and RHI multiple modes are combined, and the in-situ wind measuring sensor is used to provide the real wind speed to correct the radial velocity deviation caused. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Throughout the accompanying drawings, the same reference numerals are used to represent the same components. In the accompanying drawings:

[0047] Figure 1 It is a flow chart of a wind field inversion optimization method of a wind laser radar based on a floating platform provided in an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of RHI scanning provided by an embodiment of the present invention;

[0049] Figure 3 is a schematic diagram of wind field spatial correction provided by an embodiment of the present invention;

[0050] Figure 4 It is a schematic diagram of wind field inversion provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0052] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0053] First, the relevant terms involved in the present invention are explained:

[0054] LiDAR: The working principle of LiDAR is based on the Doppler effect, that is, when the wave source and the observer are in relative motion, the frequency of the wave received by the observer will change. In LiDAR, this effect is used to measure wind speed and direction in the atmosphere. Specifically, the laser emitted by the LiDAR interacts with moving particles in the atmosphere (such as aerosol particles) to produce scattered light. By measuring the frequency change of the scattered light (i.e., the Doppler shift), the movement speed of the particles can be calculated, thereby obtaining wind speed and direction information. The LiDAR beam is emitted through an optical probe.

[0055] Scanning wind measurement lidar: The scanning wind measurement lidar is equipped with a servo scanning system. The host computer servo scanning controller sends commands to control the servo to drive the optical probe to rotate, thereby realizing spatial stereoscopic scanning measurement.

[0056] PPI scanning: Plan Position Indicator, PPI scanning mode with fixed elevation and changing azimuth (also called conical scanning) displays data in the form of polar coordinates centered on the radar. Its advantages are real-time, intuitive and obvious target features. Conical scanning uses the VAD method to invert the main wind speed and wind direction by fitting the radial wind speed (and then decompose it into u and v components), and can clearly identify and extract the atmosphere from the inversion results.

[0057] RHI scanning: Range Height Indicator, RHI scanning is a vertical pitch scan of the laser radar beam at a fixed azimuth angle, and the results are displayed in polar coordinates centered on the radar. Since the RHI scanning method is a vertical scan, it can obtain the distribution of radial wind speed and other data information with height, thereby analyzing the vertical structure of the wind field.

[0058] Floating platform: A platform used to install a laser wind radar for offshore or offshore wind testing, such as a ship or buoy. Due to the movement of waves, the floating platform will have a swaying posture and movement speed.

[0059] Radial velocity: The velocity component of aerosol particles moving in the radial (line of sight) beam direction of the wind measuring lidar, that is, the projection of the wind speed vector on the radial beam.

[0060] Wind speed and direction: the speed and direction of air movement. Wind measuring lidar measures the velocity components at different positions in a small area (it is assumed that the atmosphere in this small area is uniform and the wind speed is consistent) by emitting multiple laser beams at different azimuths and elevations. These velocity components are synthesized to obtain the wind speed and direction of this small area.

[0061] Distance library: The laser radar emits lasers, and through the data acquisition system, the entire measurement distance is divided into multiple distance regions, called distance libraries. The radial velocity of all beams in the same distance library (in one plane) on the fixed platform is used to invert the wind speed and direction at this distance.

[0062] Laser beam azimuth and elevation: When the laser radar is installed on the ground, the laser beam is g Y g Z g Middle, Y g The axis points north, Y g The axis points east, Z g The axis is vertical to the sky, with the laser radar as the origin, and the 0 degree beam and Y g The positive axis direction is consistent, and the azimuth angle is defined as the laser beam in the X g -Y g Projection in the plane and Y g The pitch angle is defined as the angle between the laser beam and the X axis. g -Y g The angle of the plane; in the floating platform coordinate system X where the laser radar is installed 0 Y 0 Z 0 In the process, the motion attitude and velocity of the platform coordinate system are recorded by the inertial navigation system installed on the radar. 0 Axis points to the nose, X 0 The axis points to the right of the aircraft, Z 0 The axis points to the top of the platform, with the laser radar as the origin, and the laser radar 0 degree beam is aligned with the Y 0 The positive axis direction is consistent, and the azimuth angle φ0 is defined as the laser beam at X 0 -Y 0 Projection in the plane and X 0 The pitch angle θ0 is defined as the angle between the laser beam and the X axis. 0 -Y 0 The angle between the planes.

[0063] Attitude angle: including aircraft pitch angle, roll angle and heading angle, in geographic coordinate system X g Y g Z gMiddle, Y g The axis points north, X g The axis points east, Z g The axis points to the sky, and the pitch angle, roll angle and heading angle of the floating platform are defined as the angle around the X axis. g , Y g and Z g The angle of rotation.

[0064] Coordinate system conversion: The azimuth and elevation angles of the laser beam recorded inside the laser radar are based on the spatial coordinate system with the laser radar as the origin. When the laser radar is installed on the ground, it is based on the geographic coordinate system. If the laser radar is installed on a floating platform, it is based on the floating platform coordinate system. However, the movement of wind speed is based on the geographic coordinate system, so the offshore floating wind laser radar needs to convert the azimuth and elevation angles of the outgoing beam from the floating platform coordinate system to the geographic coordinate system.

[0065] Attitude correction: The correction of the radial beam outgoing azimuth and pitch angle of the airborne wind measuring lidar when it is converted from the floating platform coordinate system to the geographic coordinate system is called attitude correction.

[0066] Velocity correction: The radial velocity measured by the radial beam of the airborne wind-measuring lidar is also based on the floating platform coordinate system. In addition to the wind speed component, the ground speed component of the floating platform is also superimposed. The ground speed component needs to be removed, which is the velocity correction.

[0067] Altitude correction: The change in the flying altitude of the floating platform causes the radial beam distance library of the wind measuring lidar to shift in height, that is, the beams of the same distance library are not at the same altitude level. Because the distribution of wind speed in altitude does not meet the uniform assumption, it needs to be processed and the wind speed is inverted using the radial velocity at the same altitude level.

[0068] Inertial Navigation System IMU: Inertial Measurement Unit, the main components are gyroscopes and accelerometers, and are used to measure the three-axis attitude angle and acceleration of an object. The inertial navigation system obtains the velocity and position based on the measured acceleration of the object through integration operations. For this purpose, the initial velocity and initial position must be known. In addition, in the inertial navigation system that uses the geographic coordinate system as the navigation coordinate system, the object platform must accurately align and track the geographic coordinate system. The three-axis pointing of the inertial navigation system is arbitrary and has no definite orientation. Especially when the inertial navigation system is used on a floating platform. Therefore, it is necessary to introduce a dual GPS / GNSS antenna positioning and direction finding system, which consists of two front and rear antennas. The installation distance between the front and rear GPS / GNSS antennas is more than 1m, and the direction of the floating platform axis is measured. The antenna connection line is parallel to the Y axis of the floating platform longitudinal axis.

[0069] In some embodiments of the present invention, a wind field inversion optimization method based on a floating platform wind measurement lidar is provided. The method corrects the spatial distribution error of the radial light beam by combining scanning modes with an in-situ instrument device installed on the floating platform, thereby inverting a more accurate horizontal wind field.

[0070] Correspondingly, in other embodiments of the present invention, a wind field inversion optimization system, equipment and medium based on a floating platform for wind measurement laser radar are provided.

[0071] Example 1

[0072] like Figure 1 As shown, the present invention provides a wind field inversion optimization method based on a floating platform wind laser radar, comprising the following steps:

[0073] 1) Use the laser radar to perform PPI scanning and obtain the radial wind speed measured by the laser radar as the radial wind speed before correction;

[0074] 2) Perform the first correction on the radial velocity component caused by the floating platform in the radial wind speed measured by the lidar;

[0075] 3) Use the mobile anemometer to obtain the first distance library R of the laser radar 1 The corrected front angle corresponding to the nth laser beam The actual wind speed and direction at the location are calculated, and the mobile anemometer is used to calculate the front angle of the laser radar correction based on the actual wind speed and direction. The corresponding first radial wind speed;

[0076] 4) In the first distance library R of the laser radar 1 The corrected front angle corresponding to the nth laser beam Perform RHI scanning at the location, and obtain the second radial wind speed according to the RHI scanning result;

[0077] 5) performing a second correction on the radial wind speed after the first correction in step 2) based on the first radial wind speed and the second radial wind speed;

[0078] 6) Based on the second correction result obtained in step 5), the VAP algorithm is used to inverse optimize the sea surface wind field to obtain wind speed and wind direction data.

[0079] Furthermore, in the above step 1), if Figure 1 As shown, the following steps are included:

[0080] 1.1) Use a scanning laser radar installed on a floating platform to perform PPI scanning with a fixed pitch angle and a changed azimuth angle, and record the azimuth and pitch angles of the laser beam relative to the floating platform;

[0081] 1.2) The inertial navigation system is used to record the attitude angle of the floating platform relative to the geographic coordinate system, and the azimuth and pitch angles of the laser beam relative to the geographic coordinate system are obtained by transforming the geographic coordinate system and the floating platform coordinate system, and the radial wind speed is calculated.

[0082] In this embodiment, the attitude angle of the floating platform is composed of three axes, including the pitch axis, the roll axis and the heading axis, which are represented by φ, θ and ψ respectively. For the coordinate system of the inertial navigation system, its Y 0 The X axis is consistent with the pitch axis 0°, 0 The axis is consistent with the roll axis 0°, Z 0 The axis is consistent with the heading axis 0°, and the coordinates of any point are (y 0 ,x 0 ,z 0 ). The 0° azimuth of the laser radar and the Y coordinate system of the inertial navigation system 0 The axis is consistent, the 90° pitch angle of the laser radar is consistent with the Z 0 The laser radar controls the servo system to emit laser and records the azimuth and pitch angles of the laser beam relative to the floating platform, which are expressed as φ 0 and θ 0 express.

[0083] Azimuth φ 0 Defined as the laser beam at Y 0 -X 0 Projection in the plane and Y 0 The angle of the positive axis, looking from top to bottom, φ 0 Varies in the range of 0° to 360°; pitch angle θ 0 It refers to the laser beam and Y 0 -X 0 The angle between the two planes. Therefore, the laser beam can be represented by a vector in the floating platform coordinate system:

[0084]

[0085] The geographic coordinate system and the floating platform coordinate system correct the pitch angle and azimuth of the laser beam through coordinate transformation. The laser beam can be represented by another vector in the geographic coordinate system:

[0086]

[0087] Among them, H 1 , H 2 and H 3 Represents the transformation matrices of roll angle, pitch angle and heading angle respectively; (y g , x g , z g ) represents the coordinates of the laser beam.

[0088] Therefore, the azimuth of the laser beam in the geographic coordinate system after attitude correction is and the pitch angle θ g Respectively expressed as:

[0089]

[0090] θ g =arcsinz g

[0091] Furthermore, the above step 2) includes the following steps:

[0092] 2.1) Based on the pitch angle and azimuth angle of the laser beam relative to the geographic coordinate system and the three-axis motion speed of the floating platform recorded by GPS, the calculated value of the radial velocity component caused by the motion of the floating platform is obtained.

[0093] Specifically, the radial velocity component caused by the motion of the floating platform is calculated as:

[0094]

[0095] Among them, V los_platform,i V is the radial velocity component of each beam superimposed by the floating platform velocity; xg,i , V yg,i , V zg,i are the three-axis motion speeds of the floating platform recorded in GPS, and i = 1, 2, ..., n, ..., 2n-1, 2n-1 represents the number of beams of a complete PPI scan of the laser radar; θ g,i is the pitch angle corresponding to different laser beams after attitude correction, is the azimuth angle corresponding to different laser beams after attitude correction.

[0096] 2.2) Based on the laser radar echo data, the measured values ​​of the radial velocity component of the floating platform and the wind speed are extracted, and the calculated value in step 2.1) is subjected to attitude correction.

[0097] Specifically, the radial component caused by the floating platform in the measured radial wind speed is corrected to obtain the corrected radial wind speed V los_lidar_c,i,j , and its calculation formula is expressed as:

[0098] V los_lidar_c,i,j =V los_lidar,i,j +V los_platform,i

[0099] Among them, V los_lidar,i,j is the radial velocity component before correction measured by the lidar, where i = 1, 2, …, n, …, 2n-1; j = 1, 2, …, m, where m represents the number of range bins of a radial beam of the lidar.

[0100] Furthermore, the above step 3) includes the following steps:

[0101] 3.1) In the first range library R of the laser radar 1 The corrected front angle corresponding to the nth laser beam GPS-based mobile anemometers are installed at various locations to measure the actual wind speed and direction data.

[0102] In this embodiment, the azimuth sensor is used to measure the azimuth change of the floating platform where the mobile anemometer is located, and the total wind direction D is synthesized with the wind direction actually measured by the wind direction sensor. mast ', the wind speed measured by the wind speed sensor is the total wind speed V mast ', GPS measures the three-axis velocity V of the floating platform xm , V ym , V zm , and the wind speed vector generated by the movement of the floating platform is converted, and the true wind speed V can be obtained by using the total wind speed and total wind direction mast True wind direction D mast , and its calculation formula is:

[0103]

[0104]

[0105] 3.2) According to the obtained true wind speed and true wind direction, calculate the radial wind speed V corresponding to the position angle of the mobile anemometer in front of the laser radar correction. los_mast,i , as the first radial wind speed.

[0106] The calculation formula can be expressed as:

[0107]

[0108] Among them, θ 0,i is the pitch angle corresponding to different laser beams before correction, and θ 0,i =θ 0,1 =θ 0,2n+1 ; is the azimuth angle corresponding to different laser beams before correction.

[0109] Furthermore, the above step 4) includes the following steps:

[0110] 4.1) In the first range library R of the laser radar 1 The corrected front angle corresponding to the nth laser beam Perform RHI scan at the location to obtain the radial wind speed corresponding to the RHI scan.

[0111] like Figure 2As shown, the corrected forward azimuth angle corresponding to the nth laser beam of the laser radar is Perform RHI scan at the position to obtain the pitch angle θ 0_rhi,k (k=1,2,…p) laser beams collect data, p represents the number of beams of a complete RHI scan of the laser radar, and the corresponding radial wind speed is V los_rhi,k,j .

[0112] 4.2) Perform attitude correction on the radial wind speed corresponding to the RHI scan, and obtain the azimuth and pitch angles of the RHI after attitude correction, which are expressed as and θ g_rhi,k , and calculate the second radial wind speed.

[0113] In this embodiment, the method for performing posture correction on the RHI scan data is the same as step 1.1) to step 1.3), and the present invention will not elaborate on this.

[0114] Furthermore, the above step 5) includes the following steps:

[0115] 5.1) The pitch angle θ before correction 0,i The corresponding PPI scanning surface is used as the target scanning surface, and the initial values ​​of the fluctuation coefficients of different laser beams in the first distance library caused by the swaying posture of the floating platform are calculated.

[0116] like Figure 3 As shown, V los_mast,i The reference radial velocity V is used as the first range library for all laser beams of the lidar. los_ref,i,1 , then the calculation formulas for the height deviation and radial velocity deviation caused by the pitch angle change are:

[0117] ΔH i,j =R j sinθ g,i -R j sinθ 0,i

[0118] ΔV los,i,j =V los_lidar_c,i,j -V los_ref,i,j

[0119] In the formula, ΔH i,j is the height deviation caused by the corrected pitch angle change, ΔV los,i,j is the radial velocity deviation caused by the corrected pitch angle change.

[0120] Then the radial velocity deviation ΔV of the first range library is los,i,1 The calculation formula can be expressed as:

[0121] ΔV los,i,1 =V los_lidar_c,i,1 -Vlos_ref,i,1

[0122] Where V los_lidar_c,i,1 V represents the corrected lidar radial wind speed at the ith azimuth of the first range bin; los_ref,i,1 Represents the radial wind speed of the mobile anemometer at the i-th azimuth of the first range bin.

[0123] The initial value of the fluctuation coefficient β of different laser beams in the first distance library due to the swing posture of the floating platform i,1 for:

[0124] β i,1 =ΔV los,i,1 / ΔH i,1

[0125] 5.2) Iterate the fluctuation coefficient of the first distance library to the second distance library, and preliminarily correct the radial wind speed V of the second distance library. los_ref,i,2 '.

[0126] Among them, the calculation formula of the radial wind speed of the second distance bin is expressed as:

[0127] V los_ref,i,2 '=V los_lidar_c,i,2 +β i,1 ΔH i,2

[0128] Where V los_lidar_c,i,2 represents the corrected lidar radial wind speed at the ith azimuth of the second range bin; ΔH i,2 It represents the i-th azimuth of the second range library, which is the height deviation of the laser beam pointing position caused by the attitude change.

[0129] 5.3) Radial wind speed V based on the second distance library after preliminary correction los_ref,i,2 ', the nonlinear wind field VAD (Velocity Azimuth Display) inversion method is used to calculate the main wind direction and main wind speed of the second distance library.

[0130] Specifically, the steps include:

[0131] ①According to the sinusoidal function The scan data were fitted and the error between the fitted curve and the scan data was calculated using the least squares method.

[0132] Since V los_ref,i,2 'and Construct a sinusoidal function This embodiment is based on the sine curve function The scanned data is fitted; the fitting process uses the least squares method to calculate the error between the fitting curve and the scanned data. The error calculation method is:

[0133]

[0134] In the formula, q b and q e Respectively represent the start and end of the beam involved in the sine fit, is the azimuth angle corresponding to the qth beam, V los_ref,q,2 ' is the radial velocity corresponding to the second range gate of the qth beam participating in the sine fitting.

[0135] ② Since 2n-1 beams are involved in the calculation in the first fitting calculation, that is, qb~qe represent all beams between 1 and 2n-1 at this time, it is necessary to determine whether the error e is less than the preset error threshold Te. If it is greater than the error threshold Te, it means that the difference is too large, which will reduce the wind speed inversion accuracy. It is necessary to remove the beam data with too large a difference and repeat step ①. If it is less than the error threshold, then The minimum value corresponds to The main wind direction D of the second distance library ref,2 , the maximum value is the main wind speed V ref,1 .

[0136] 5.4) The RHI scanning data in step 4) is used to perform a second correction on the radial wind speed of the second distance library to obtain the final corrected radial wind speed of the second distance library and its fluctuation coefficient.

[0137] Due to the error of the fluctuation coefficient caused by the height in the iteration process, the radial wind speed of the second distance library that was initially corrected needs to be further corrected using the measured RHI data in step 4). Find the RHI scanning pitch angle closest to θ 0,i The radial wind speed V corresponding to the beam los_rhi,s,2 , 1≥s≥p, decompose the fitted main wind speed and direction into the azimuth after RHI correction The second distance library can be used to obtain the initial correction of radial wind speed and horizontal wind speed and direction at the azimuth The pitch angle is θ 0,i The radial component of is expressed as:

[0138]

[0139] V los_rhi,s,2 ' and RHI in the direction The pitch angle is θ 0,i The measured radial component V los_rhi,s,2By subtracting and correcting all the preliminary radial wind speeds of the second distance bin calculated in step 5.2), the final corrected radial wind speed of the second distance bin can be calculated, which is expressed as:

[0140] V los_ref,i,2 =V los_ref,i,2 '+(V los_rhi,s,2 -V los_rhi,s,2 ')

[0141] The calculation formula of the radial wind speed deviation of the second distance library is expressed as:

[0142] ΔV los,i,2 =V los_lidar_c,i,2 -V los_ref,i,2

[0143] The fluctuation coefficient of different beams in the second range library due to the platform swing attitude is:

[0144] β i,2 =ΔV los,i,2 / ΔH i,2

[0145] 5.5) Repeat steps 5.1) to 5.4) to invert the radial wind speed deviation ΔV of the jth distance bin los,i,j , the fluctuation coefficient of the j-th distance library due to the swing posture of the floating platform is β i,j , iteratively correct the radial velocity V of the j-th distance bin los_ref,i,j .

[0146] Further, in the above step 6), if Figure 4 As shown in the figure, the VAP algorithm is used to invert the sea surface wind field. It is assumed that the wind vectors of adjacent azimuths with an interval of Δφ are equal. Since the intervals of adjacent azimuths are not the same after attitude correction, the intervals of adjacent azimuths are averaged. The calculation formula is:

[0147]

[0148] Take the radial wind speed on the same height circle, and use the trigonometric relationship to infer the horizontal wind field of this distance circle from the radial wind speed at the center of the area, and then calculate the horizontal wind field on other distance circles in turn. ii,j Indicates the angle between the laser beam direction and the wind direction, ii = i-1 (i = 2, 3…2n-1), D lidar,ii,j Indicates the horizontal wind direction at each measuring point, V lidar,ii,j Represents the horizontal wind speed at each measuring point, and the calculation formula is as follows:

[0149]

[0150]

[0151]

[0152] Example 2

[0153] The above-mentioned embodiment 1 provides a wind field inversion optimization method based on a floating platform using a wind laser radar. Correspondingly, this embodiment provides a wind field inversion optimization system based on a floating platform using a wind laser radar. The system provided in this embodiment can implement the wind field inversion optimization method based on a floating platform using a wind laser radar of embodiment 1. The system can be implemented by software, hardware, or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to execute the corresponding steps in each method of embodiment 1. Since the system of this embodiment is basically similar to the method embodiment, the process described in this embodiment is relatively simple. For relevant details, please refer to the partial description of embodiment 1. The embodiment of the system provided in this embodiment is merely illustrative.

[0154] The wind field inversion optimization system of the wind laser radar based on the floating platform provided in this embodiment includes:

[0155] The radial wind speed acquisition module before correction is used to perform PPI scanning using a laser radar to obtain the radial wind speed measured by the laser radar as the radial wind speed before correction;

[0156] A first correction module, used for performing a first correction on a radial velocity component caused by a floating platform in a first radial wind velocity measured by a laser radar;

[0157] The first radial wind speed acquisition module is used to obtain the first distance library R of the laser radar using a mobile anemometer 1 The corrected front angle corresponding to the nth laser beam The actual wind speed and direction at the location are calculated, and the mobile anemometer is used to calculate the front angle of the laser radar correction based on the actual wind speed and direction. The corresponding first radial wind speed;

[0158] The second radial wind speed acquisition module is used to obtain the first distance library R of the laser radar. 1 The corrected front angle corresponding to the nth laser beam Perform RHI scanning at the location, and obtain the second radial wind speed according to the RHI scanning result;

[0159] A second correction module, configured to perform a second correction on the radial wind speed corrected for the first time in step 2) based on the first radial wind speed and the second radial wind speed;

[0160] The inversion module is used to invert and optimize the sea surface wind field based on the second correction result obtained by using the VAP algorithm to obtain wind speed and wind direction data.

[0161] Example 3

[0162] This embodiment provides a processing device corresponding to the floating platform-based wind measurement laser radar wind field inversion optimization method provided in this embodiment 1. The processing device can be a processing device for a client, such as a mobile phone, a laptop computer, a tablet computer, a desktop computer, etc., to execute the method of embodiment 1.

[0163] The processing device includes a processor, a memory, a communication interface and a bus, and the processor, the memory and the communication interface are connected through the bus to complete mutual communication. The memory stores a computer program that can be run on the processor, and the processor executes the wind field inversion optimization method based on the floating platform wind laser radar provided in this embodiment 1 when running the computer program.

[0164] Preferably, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0165] Preferably, the processor may be a central processing unit (CPU), a digital signal processor (DSP) or other general-purpose processors of various types, which are not limited here.

[0166] Example 4

[0167] The wind field inversion optimization method based on a floating platform wind measurement lidar of this embodiment 1 can be specifically implemented as a computer program product, which may include a computer-readable storage medium carrying computer-readable program instructions for executing the wind field inversion optimization method based on a floating platform wind measurement lidar described in this embodiment 1.

[0168] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0169] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0170] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0171] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A wind field inversion optimization method based on a floating platform wind laser radar, characterized in that: The following steps are involved: Use laser radar to perform PPI scanning and obtain radial wind speed before correction; Perform the first correction on the radial velocity component caused by the floating platform in the radial wind velocity before correction; Using a mobile anemometer to obtain the true wind speed and wind direction at a preset position, and obtaining a first radial wind speed according to the true wind speed and the true wind direction; Performing an RHI scan at a preset position, and obtaining a second radial wind speed according to the RHI scan result; Performing a second correction on the radial wind speed after the first correction based on the first radial wind speed and the second radial wind speed; Based on the second correction results, the VAP algorithm is used to invert and optimize the sea surface wind field to obtain wind speed and direction data.

2. The method for wind field inversion optimization based on a floating platform wind laser radar according to claim 1, characterized in that: The method of performing PPI scanning by using a laser radar and obtaining radial wind speed before correction includes: A scanning laser radar installed on a floating platform is used to perform PPI scanning with a fixed pitch angle and a changed azimuth angle, and the azimuth and pitch angles of the laser beam relative to the floating platform are recorded; The inertial navigation system is used to record the attitude angle of the floating platform relative to the geographic coordinate system, and the azimuth and pitch angles of the laser beam relative to the geographic coordinate system are obtained by transforming the geographic coordinate system and the floating platform coordinate system, and the radial wind speed is calculated.

3. The method for wind field inversion optimization based on a floating platform wind laser radar according to claim 1, characterized in that: The first correction of the radial velocity component caused by the floating platform in the radial wind velocity before correction comprises: Based on the pitch angle and azimuth angle of the laser beam relative to the geographic coordinate system and the three-axis motion speed of the floating platform recorded by GPS, a calculated value of the radial velocity component caused by the motion of the floating platform is obtained; Based on the laser radar echo data, the measured values ​​of the radial velocity component of the floating platform and the wind speed are extracted, and the calculated values ​​are subjected to attitude correction.

4. The method for wind field inversion optimization based on a floating platform wind laser radar according to claim 1, characterized in that: The method of using a mobile anemometer to obtain the true wind speed and wind direction at a preset position, and obtaining a first radial wind speed according to the true wind speed and the true wind direction, includes: The corrected forward angle corresponding to the nth laser beam in the first range library R1 of the laser radar Install GPS-based mobile anemometers to measure the real wind speed and direction data; According to the obtained true wind speed and true wind direction, the radial wind speed corresponding to the azimuth angle of the mobile anemometer in front of the laser radar correction is calculated as V los_mast,i , as the first radial wind speed.

5. The method for wind field inversion optimization based on a floating platform wind laser radar according to claim 1, characterized in that: The performing RHI scanning at the preset position and obtaining the second radial wind speed according to the RHI scanning result includes: The corrected forward angle corresponding to the nth laser beam in the first range library R1 of the laser radar Perform RHI scan at the location to obtain the radial wind speed corresponding to the RHI scan; The radial wind speed corresponding to the RHI scan is attitude corrected to obtain the azimuth and pitch angles of the RHI after attitude correction, which are expressed as and θ g_rhi,k , and calculate the second radial wind speed.

6. The method for wind field inversion optimization based on a floating platform wind laser radar according to claim 1, characterized in that: The second correction of the radial wind speed after the first correction based on the first radial wind speed and the second radial wind speed comprises: The pitch angle θ before correction 0,i The corresponding PPI scanning surface is used as the target scanning surface to calculate the initial value of the fluctuation coefficient of different laser beams in the first distance library due to the swaying posture of the floating platform; The fluctuation coefficient of the first distance library is iterated to the second distance library, and the radial wind speed V of the second distance library is preliminarily corrected. los_ref,i,2 '; Radial wind speed V based on the second distance library after preliminary correction los_ref,i,2 ', calculate the main wind direction and main wind speed of the second distance library; The radial wind speed of the second distance library is corrected for the second time using the RHI scanning data to obtain the final corrected radial wind speed of the second distance library and its fluctuation coefficient; Repeat the above steps to invert the radial wind speed deviation ΔV of the jth distance bin los,i,j , the fluctuation coefficient of the j-th distance library due to the swing posture of the floating platform is β i,j , iteratively correct the radial velocity V of the j-th distance bin los_ref,i,j .

7. The method for wind field inversion optimization based on a floating platform wind laser radar according to claim 1, characterized in that: Based on the second correction result, the VAP algorithm is used to inverse optimize the sea surface wind field to obtain wind speed and wind direction data, including: Take the average of adjacent azimuth intervals; Based on the average azimuth angle, the radial wind speed on the same altitude circle is taken, and the horizontal wind field of the altitude circle is inferred from the radial wind speed at the center point of the area through trigonometric relationship, and the horizontal wind fields on other altitude circles are calculated in turn.

8. A wind field inversion optimization system based on a floating platform wind laser radar, characterized in that: include: A radial wind speed acquisition module before correction is used to perform PPI scanning using a laser radar and obtain the radial wind speed before correction; A first correction module, used for performing a first correction on a radial velocity component of the radial wind velocity before correction caused by the floating platform; A first radial wind speed acquisition module is used to acquire the true wind speed and wind direction at a preset position using a mobile anemometer, and obtain a first radial wind speed according to the true wind speed and the true wind direction; A second radial wind speed acquisition module, used for performing RHI scanning at a preset position and obtaining a second radial wind speed according to the RHI scanning result; A second correction module, configured to perform a second correction on the radial wind speed after the first correction based on the first radial wind speed and the second radial wind speed; The inversion module is used to invert and optimize the sea surface wind field based on the second correction result using the VAP algorithm to obtain wind speed and wind direction data.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform any one of the methods of claims 1 to 7.

10. A computing device, characterized in that include: One or more processors and a memory, wherein the memory stores one or more programs and is configured to be executed by the one or more processors, wherein the one or more programs include instructions for executing any one of the methods described in claims 1 to 7.

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