A method for correcting the plane of underwater PIV flow field measurement based on buoy platform

Abstract

The present application belongs to the technical field of ocean current field measurement, and particularly relates to a kind of underwater PIV flow field measurement plane correction method based on buoy platform.The underwater PIV flow field measurement plane correction method based on buoy platform provided by the present application realizes the standardization processing of dynamic instantaneous measurement plane through multi-level coordinate system simultaneous calibration, pose data adaptive noise reduction, plane offset amount accurate solution, particle coordinate reverse remapping, flow velocity vector global compensation and space interpolation reconstruction, and finally outputs the continuous, high-precision time series two-dimensional flow field data of fixed observation plane in geodetic coordinate system.The method of the present application effectively eliminates the measurement error caused by buoy disturbance, and effectively improves the measurement accuracy and data stability.

Description

Technical Field

[0001] This invention belongs to the field of marine flow field measurement technology, specifically relating to a planar correction method for underwater PIV flow field measurement based on a buoy platform. Background Technology

[0002] Particle image velocimetry (PIV) is an optical visualization flow field measurement technique that enables quantitative measurement of flow fields and acquisition of fine flow characteristics such as turbulent structure and vortex evolution. Underwater PIV flow field measurement technology based on a buoy platform employs an underwater vertical down-firing PIV architecture. It achieves unmanned continuous observation of the underwater near-wall flow field by vertically emitting sheet light from a laser and orthogonally imaging it with an underwater camera. Unlike traditional laboratory fixed-tank PIVs, marine buoys lack a fixed base and are subject to the coupling effects of wind, waves, and currents, continuously generating multi-degree-of-freedom coupled random motion. This results in the laser measurement plane corresponding to each frame of PIV imaging being in a dynamic state of offset, tilt, and rise / fall, making it impossible to uniformly superimpose the measurement planes from different time series and thus difficult to form continuous flow field data for a fixed region.

[0003] Most existing PIV correction algorithms are designed for fixed observation platforms and uniformly moving carriers. They can only correct local optical errors such as lens distortion and imaging deviation. They are not adapted to the multi-degree-of-freedom complex disturbance characteristics of buoys, cannot quantify the angular offset and vertical deviation of the dynamic measurement plane relative to the geodetic reference plane, and lack targeted spatial coordinate mapping and global flow velocity vector compensation logic. Consequently, they cannot unify the scattered dynamic instantaneous measurement planes from multiple frames to the fixed geodetic observation plane. This results in the flow field data acquired by buoy-based PIV systems having disordered timing and large errors, making it impossible to carry out scientific research analysis such as turbulence statistics and eddy evolution. This seriously limits the engineering application and data value of buoy-type underwater PIV equipment. Summary of the Invention

[0004] To address the problems of existing technologies, this invention proposes a planar correction method for underwater PIV flow field measurement based on a buoy platform. By simultaneously calibrating multi-level coordinate systems, adaptive noise reduction of pose data, accurate solution of planar offset, reverse remapping of particle coordinates, global compensation of flow velocity vector, and spatial interpolation reconstruction, the method achieves standardized processing of dynamically scattered measurement planes and ultimately outputs continuous, high-precision time-series two-dimensional flow field data with a preset fixed observation plane in the geodetic coordinate system.

[0005] This invention proposes a planar correction method for underwater PIV flow field measurement based on a buoy platform, comprising the following steps: Step S1: Construct a four-level coordinate system mapping system adapted to vertically down-illuminated sheet light. Complete offline joint calibration under the condition of buoy being stationary and without wind and waves, and solidify the coordinate mapping parameters of the pixel coordinate system, underwater camera coordinate system, buoy carrier coordinate system, and geodetic coordinate system. The calibration obtains the reference sheet light plane equation of the vertically down-illuminated laser sheet light in the buoy carrier coordinate system, and at the same time, the preset fixed observation plane parameters in the geodetic coordinate system are entered. Step S2: Synchronously acquire single-frame particle images and corresponding instantaneous six-degree-of-freedom motion data of the buoy during image exposure, including geodetic coordinates, roll, pitch, bow roll, horizontal translation, and vertical heave; Step S3: Based on the noise-reduced six-degree-of-freedom motion data, calculate the rotation matrix and translation matrix of the buoy relative to the geodetic coordinate system frame by frame, merge them to generate a real-time homogeneous positive transformation matrix, and use the fixed observation plane in the geodetic coordinate system as the reference plane to solve the spatial offset parameters of the instantaneous measurement plane in the current frame relative to the reference plane; the spatial offset parameters include angular offset, horizontal offset, and vertical rise and fall offset. Step S4: Solve the inverse transformation compensation matrix based on the homogeneous forward transformation matrix, and use the inverse transformation compensation matrix to progressively reverse map the pixel coordinates of all effective tracer particles in a single frame image, converting the particle coordinates in the dynamic instantaneous measurement plane into the standard particle coordinates in the fixed observation plane. Step S5: Perform cross-correlation calculation on the original particle image to obtain the original two-dimensional velocity vector. Combine the real-time heave displacement of the buoy to complete the sheet light separation error compensation. Combine the spatial offset parameters to complete the velocity vector angle and translation coupling compensation, and obtain the standard velocity vector of the fixed observation plane in the geodetic coordinate system.

[0006] Preferably, the offline joint calibration in step S1 includes: underwater refractive distortion calibration of the camera, optical distortion calibration of the lens, laser-guided optical plane calibration, and relative position calibration between the camera and the buoy carrier.

[0007] Preferably, step S2 uses an adaptive gain Kalman filter to reduce noise. The greater the sea state and wave height, the greater the adaptive gain value of the filter, thus filtering out the high-frequency micro-vibration attitude noise of the buoy.

[0008] Preferably, in step S2, the time difference between particle image exposure, laser stroboscopic imaging, and six-degree-of-freedom data sampling is ≤1μs.

[0009] Preferably, the light separation error compensation logic in step S5 is as follows: the effective velocity measuring plate thickness is dynamically corrected based on the real-time heave value of the buoy, so as to offset the velocity error caused by the buoy's rise and fall causing the tracer particles to deviate from the standard velocity measuring plane.

[0010] Preferably, the preset fixed observation plane parameters support remote custom modification, including depth, horizontal tilt angle, and observation length and width boundaries.

[0011] Compared with existing technologies, this invention effectively eliminates measurement errors caused by buoy disturbances through four-level coordinate system joint correction, multi-dimensional offset compensation, particle remapping and adaptive interpolation reconstruction, thereby effectively improving measurement accuracy and data stability. Attached Figure Description

[0012] Figure 1 A schematic diagram of the overall deployment relationship of the buoy-type underwater downward-firing PIV to adapt to the method of the present invention; Figure 2 This is a schematic diagram of the internal layout of the buoy; Figure 3 A schematic diagram showing the spatial comparison between the dynamic instantaneous measurement plane and the fixed observation plane after the buoy moves; Figure 4 The figures show a comparison of the planar correction effects of the method of the present invention on the underwater PIV flow field measurement; where (a) is the uncorrected flow field vector distribution; (b) is the corrected flow field vector distribution; (c) is the uncorrected flow field velocity distribution; and (d) is the corrected flow field velocity distribution. Detailed Implementation

[0013] To facilitate understanding of the present invention, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and specific examples. The following examples or drawings are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0014] This embodiment provides a planar correction method for underwater PIV flow field measurement based on a buoy platform, including the following steps: S1: System multi-coordinate system joint calibration First, according to Figure 1 and Figure 2 The structure shown provides a hardware foundation adapted to the method of this invention. The upper part of the buoy body 101 is equipped with a Beidou antenna 201 and a GPS antenna 202, and the interior houses a sealed chamber 102 containing a high-precision IMU inertial measurement module 203, a control module 204, and a laser light source 105. An underwater camera 104 is mounted below the buoy body 101 via a fixed bracket 103. The Beidou antenna 201, GPS antenna 202, high-precision IMU inertial measurement module 203, underwater camera 104, and laser light source 105 are all electrically connected to the control module 204 within the sealed chamber. The laser light source 105 emits a sheet light beam 106, which illuminates and forms the camera imaging area 107. The underwater camera's optical axis is strictly orthogonal to the laser sheet light beam, and optical acquisition is completed by aligning with this imaging area.

[0015] The BeiDou / GPS dual-mode positioning system provides the geodetic coordinate system reference anchor point and absolute geodetic coordinates, as well as the buoy's longitudinal drift, lateral drift, and vertical rise and fall relative to the initial calibration origin. The high-precision IMU inertial measurement module outputs real-time data on the buoy's roll, pitch, and yaw. The control module 204 receives positioning and attitude data, triggers timing signals in a unified manner, and achieves microsecond-level time alignment between laser sheet light exposure, camera frame acquisition, and pose data sampling. This ensures that each particle image corresponds to the buoy's precise six-DOF pose parameters at the instant of imaging, eliminating correction errors caused by timing misalignment.

[0016] A calm, waveless water area was selected for buoy placement. Three types of calibrations were completed to establish a four-level coordinate fixed mapping relationship: calibration of underwater camera optical distortion and water refraction distortion to obtain mapping parameters from the pixel coordinate system to the camera coordinate system; calibration of the vertically downward-firing laser sheet plane carrier coordinates to determine the reference plane equation of the sheet plane within the buoy carrier coordinate system; and calibration of the relative position of the camera and the buoy rigid body to solidify the transformation parameters between the camera coordinate system and the buoy carrier coordinate system. Simultaneously, fixed observation plane parameters in the geodetic coordinate system were entered, including system preset parameters such as depth (underwater burial depth of the plane), plane inclination angle, and plane observation boundary range. A spatial comparison between the dynamic instantaneous measurement plane and the fixed observation plane after buoy movement was performed. Figure 3 As shown in the figure: Represents pixel coordinates, Indicates the camera coordinate system; Indicates the coordinate system of the buoy carrier; This represents the geodetic coordinate system.

[0017] 1. Coordinate transformation from pixel to camera Using an underwater calibration board, the conversion formula from pixel coordinates to camera coordinates is obtained: ; In the formula, , These represent the horizontal and vertical coordinates of the particle pixel. This is the camera intrinsic parameter matrix, describing the optical projection mapping from the camera's 3D coordinate system to the 2D pixel coordinate system. It is determined solely by the camera lens and image sensor hardware, and is independent of the buoy's movement and shooting position. The calculation formula is: ; In the formula, and for , Equivalent focal length in direction, and These are the pixel coordinates of the optical center of the image.

[0018] 2. Coordinate transformation from camera to buoy Solve the rigid body transformation matrix The position of the camera relative to the rigid buoy is fixed. The solution method is as follows: (1) Fix the underwater high-precision checkerboard calibration plate to the reference position of the buoy support, and pre-align the coordinates of the calibration plate with the coordinate system of the buoy carrier. The three-dimensional coordinates of the corner points of the calibration plate are known constants in the buoy carrier coordinate system. The underwater camera captures multiple sets of checkerboard images from different angles and distances using vertical / lateral views, acquiring no fewer than 15 sets of valid calibration images.

[0019] (2) Using the already calibrated camera intrinsic parameter matrix The pixel coordinates of the corner points of each chessboard square Restored to 3D coordinates in the camera coordinate system Solve the formula: .

[0020] (3) Through perspective Point PnP algorithm to establish reference points for buoy carrier coordinate system to camera coordinate system measurement point The mapping relationship is used to solve for the fundamental rigid body transformation: ; In the formula, The true three-dimensional coordinates of the corner points of the calibration plate are given in the buoy carrier coordinate system. Restore the coordinates of the corresponding corner points in the camera coordinate system. Iterate through the algorithm to find the optimal solution and output the rotation matrix. Translation vector .

[0021] (4) Solve for PnP , Substituting into the standard 4×4 homogeneous structure, we obtain the rigid body transformation matrix: .

[0022] 3. Calibration of the lower beam reference plane Solve the equation of the reference plate light plane in the buoy carrier coordinate system. : ; In the formula, Let be the normal vector of the reference plane in the buoy carrier coordinate system. This is the plane offset constant, used to determine the coordinate origin of the sheet light plane relative to the buoy carrier. The normal distance is used to obtain the underwater reference height of the flat surface, which is then combined with the buoy's attitude.

[0023] 4. Input fixed observation plane parameters Enter the preset fixed observation plane equation in the geodetic coordinate system : ; In the formula, This is the normal vector of the fixed observation plane in the geodetic coordinate system. The plane offset constant defines the absolute water depth / spatial position of the fixed observation plane in the geodetic coordinate system.

[0024] S2: Synchronous acquisition of particle images and buoy pose parameters Synchronous acquisition Particle image at time and The buoy's six-DOF pose parameters at time t, where the original six-DOF parameters include: geodetic coordinates. Horizontal rocking , swaying , bow rocking Horizontal translation Vertical rise and fall During the data acquisition process, an adaptive Kalman filter is used to process the data. The iterative formula is as follows: ; In the formula, Here is the system state transition matrix. For adaptive Kalman gain, yes The observation vector at time t.

[0025] S3: Solving for plane offset measurement Based on filtered six-degree-of-freedom data, the real-time rotation and translation matrices of the buoy carrier relative to the geodetic coordinate system are solved, and combined to generate a real-time homogeneous positive transformation matrix; combined with the reference plane equation ( ), calculate the spatial offset parameters (angular offset, horizontal offset, vertical rise and fall offset) of the instantaneous measurement plane relative to the fixed observation plane in the current frame.

[0026] 1. Construction Momentary buoy attitude rotation matrix: ; In the formula, the roll rotation matrix (around the X-axis) for: ; Pitch-rotation matrix (around the Y-axis) for; ; Bow rotation matrix (around the Z-axis) for: ; Multiplying in sequence yields Moment buoy complete attitude rotation matrix : .

[0027] 2. Construction Time-shift matrix: ; In the formula, , and These represent the X-axis translation, Y-axis translation, and vertical heave displacement in the geodetic coordinate system, respectively.

[0028] 3. Synthesize the positive transformation matrix of the buoy carrier relative to the earth: .

[0029] 4. Solving for spatial offset: Solving the simultaneous plane equations and Solve Moment angle offset (including roll angle offset) Tilting angle offset Vertical deflection angle offset and spatial distance offset .

[0030] The specific solution method is as follows: (a) Using the pre-defined fixed observation plane equation in the geodetic coordinate system Let be the reference plane, and its normal vector be . . The real-time normal vector of the instantaneous measurement plane is The value is obtained in real time from the buoy attitude rotation matrix.

[0031] (b) The angular offset is the tilt angle deviation between the dynamic instantaneous measurement plane and the fixed observation plane in the three coordinate axis directions, which is solved by the projection of the angle between the spatial normal vectors.

[0032] Roll angle offset for: ; Pitch angle offset for: ; Vertical deflection for: ; In the formula, , These are the reference normal vectors for the X and Y axes of the geodetic coordinate system, respectively.

[0033] (c) Using the formula for the perpendicular distance from a spatial point to a plane, select the center point of the dynamic laser downlight measurement plane and solve for its relative distance to the reference plane. Spatial distance offset This refers to the combined offset of the buoy's vertical rise and fall plus its horizontal drift: ; In the formula, for The geodetic coordinates of the center point of the plane are measured instantaneously at all times. The positive and negative values ​​represent the direction of plane offset, and the absolute value represents the magnitude of the offset distance. It is used to compensate for the vertical offset error of the sheet light and the overall translation error of the plane.

[0034] S4: Correction of particle imaging position deviation The three-axis angular offsets obtained by solving S3 ( , , Construct a plane tilt correction matrix This is used to quantify and compensate for tilt bias in the measurement plane for each frame. Correction matrix The construction method is as follows: Single-axis correction sub-matrices are constructed using the three-axis angular offsets, following the axis-order coupling rules of roll, pitch, and vertical yaw angles. These are then multiplied according to the attitude coupling order to obtain the global tilt correction matrix. Among these, roll tilt... longitudinal tilt Vertical deflection angle The individual axis correction sub-matrices are as follows: ; ; ; The instantaneous plane tilt correction matrix is ​​obtained through coupling: .

[0035] This matrix is ​​a dedicated error correction matrix for each instantaneous observation plane, which can counteract the spatial plane deflection caused by the buoy's attitude tilt, thus correcting the distorted particle coordinates. Finally, through step-by-step reverse coordinate mapping, the distorted particle coordinates within the tilted dynamic plane are precisely corrected to the standard coordinates of the fixed observation plane. ; In the formula, To dynamically and instantaneously observe the pixel coordinates of a single particle, These are the standard particle space coordinates mapped to a fixed observation plane in the geodetic coordinate system.

[0036] S5: Two-dimensional velocity vector compensation Cross-correlation calculations are performed on the original particle images to obtain the original two-dimensional velocity vector under the buoy's motion state. Combined with the real-time heave displacement of the buoy, the particle out-of-plane velocity measurement error caused by the thickness deformation of the vertically downward-facing light is calculated. Angle coupling compensation, translation compensation, and out-of-plane error compensation are performed on the original velocity vector to obtain the standard velocity vector of the fixed observation plane.

[0037] (1) Determining the original flow velocity: Perform cross-correlation calculations on the corrected standard particle image region to solve for the original flow velocity vector of the dynamic instantaneous measurement plane. ; (2) Quantification of surface error: Spatial distance offset calculated based on S3 This characterizes the deviation of the current frame light dynamic instantaneous measurement plane from the fixed observation plane, and constructs the out-of-plane flow velocity error by combining the sheet light thickness error coefficient. , The thickness and flow rate error coefficient of the sheet is obtained from the factory calibration. (3) Full-dimensional velocity coupling compensation: The correction matrix corresponding to the three-axis angular offset is used to eliminate the tilt projection error, and the particle out-of-plane velocity measurement deviation is corrected by combining the spatial distance offset. At the same time, the additional velocity caused by the horizontal drift of the carrier is offset. Finally, the formula for solving the standard velocity vector of the fixed observation plane is: ; In the formula, Add current velocity to the horizontal drift of the buoy. To completely eliminate plane tilt, spatial drift, and vertical deviation errors, the standard two-dimensional velocity vector corresponding to the fixed observation plane in the geodetic coordinate system.

[0038] Example 2: To evaluate the technical effects of the present invention, the following tests were conducted. A conventional marine monitoring buoy without active attitude stabilization was used in a nearshore shallow water test. The average water depth was 11.5 m, the effective wave height was 0.2–0.7 m, and the surface current velocity was 0.04–0.9 m / s. The laser and underwater camera in the PIV system were installed approximately 1.1 m below the waterline. The underwater depth of the original reference film's optical plane was 2.4 m, and the camera's rectangular observation area was approximately 40 cm × 30 cm. During the test, the particle image acquisition frame rate was 300 fps, and the buoy attitude sampling frequency was 1000 Hz. During image acquisition, small high-frequency jitter was not considered abnormal frames; only extreme abnormal frames with a horizontal offset greater than 70 cm, a tilt angle greater than 8°, and a duration of more than 3 frames were automatically removed.

[0039] The specific process is as follows: (1) During the low tide and windless window period, the buoy was placed still, the four-level coordinate joint calibration was completed, the light plane equation of the reference sheet was solidified, and the horizontal fixed observation plane parameters at an underwater depth of 2.4 m were recorded on the shore. (2) Routine marine observation, microsecond-level synchronous acquisition of particle images and buoy six-degree-of-freedom data, buoy real-time generation of ±0.38 m heave, 0~6° three-axis tilt angle, and maximum 62 cm horizontal bidirectional drift; (3) Construct a homogeneous transformation matrix frame by frame and calculate the offset of the dynamic instantaneous measurement plane relative to the fixed observation plane in each frame; (4) Remap the pixel coordinates of all tracer particles using the inverse matrix and normalize them to a fixed observation plane; (5) Solve the flow velocity using the original cross-correlation, and combine the heave data to compensate for the surface error of the light-emitting plate, and correct the vector angle and translation deviation; (6) Interpolate to fill in the flow field voids, remove extreme surge abnormal frames, and form a continuous flow field dataset with a fixed observation plane based on 3-minute time series images.

[0040] Based on the simulation of six-DOF ocean wave motion by buoys and the batch solution of underwater PIV flow field data, and after calibration and verification by near-shore prototype testing, the following results were obtained: (1) Measurement results without using the correction method of the present invention Without compensation for the three core errors caused by the buoy's six degrees of freedom disturbance—planar tilt, vertical heave, and horizontal drift—the measurement results are significantly distorted, as detailed below: (a) Due to continuous disturbance from the waves, the instantaneous measurement plane of each frame jitters continuously. The maximum horizontal offset of the time frame plane can reach 0.62 m, and the maximum vertical offset in the water depth direction can reach 0.38 m. The tilt angle of the single frame plane fluctuates randomly from 0 to 6°. The measurement spaces corresponding to the imaging frame sequence do not overlap, making it impossible to achieve time-series fusion of multi-frame data.

[0041] (b) Changes in buoy attitude lead to spatial distortion in particle imaging, and vertical heave of the sheet light causes a large number of tracer particles to deviate from the standard velocity measurement plane, resulting in a decrease in the effective particle recognition rate of more than 35%, and severe distortion in particle imaging and velocity measurement.

[0042] (c) The average relative error of the measured flow velocity is about 21.6%, and the relative error can reach up to 32.5% in the low flow velocity area (≤0.2 m / s). There is a significant problem of velocity overestimation in the high flow velocity area. At the same time, the horizontal drift of the buoy itself will superimpose false background flow velocity, resulting in large flow velocity measurement error and low data reliability.

[0043] (2) Measurement results after applying the correction method of the present invention After modification by the method of this invention, the composite measurement error caused by buoy disturbance is effectively eliminated, and the accuracy and stability of the measurement data are significantly improved, as follows: (a) After correction, the position error of the time frame measurement plane is ≤2.4 mm and the plane tilt angle correction error is ≤0.04°, which effectively solves the problem of time frame measurement plane misalignment caused by buoy disturbance.

[0044] (b) Through reverse correction and off-plane error compensation, the corrected tracer particle recognition rate is improved to over 92%, and the effective particle coverage in the measurement plane is effectively improved.

[0045] (c) The average relative error of flow velocity measurement is 3.1%, and the maximum relative error in the low flow velocity region is ≤3.5%, which greatly optimizes the accuracy of flow velocity measurement and makes the error controllable.

[0046] In summary, the corrected temporal flow field data has a unified spatial reference, small error dispersion, and strong temporal continuity, and can accurately extract the core flow field parameters in the region to be measured, as shown in Table 1.

[0047] Table 1 Comparison of Measurement Results

[0048] As shown in Table 1, the traditional uncorrected algorithm suffers from core problems such as large planar offset, particle imaging distortion, and high velocity measurement error due to the influence of buoy coupling disturbances. This invention effectively eliminates the measurement error caused by buoy disturbances through four-level coordinate system joint correction, multi-dimensional offset compensation, particle remapping, and adaptive interpolation reconstruction. The measurement accuracy and data stability are both significantly improved. Figure 4 As shown.

Claims

1. A planar correction method for underwater PIV flow field measurement based on a buoy platform, characterized in that, Includes the following steps: Step S1: Construct a four-level coordinate system mapping system adapted to vertically down-illuminated sheet light. Complete offline joint calibration under the condition of buoy being stationary and without wind and waves, and solidify the coordinate mapping parameters of the pixel coordinate system, underwater camera coordinate system, buoy carrier coordinate system, and geodetic coordinate system. The calibration obtains the reference sheet light plane equation of the vertically down-illuminated laser sheet light in the buoy carrier coordinate system, and at the same time, the preset fixed observation plane parameters in the geodetic coordinate system are entered. Step S2: Synchronously acquire single-frame particle images and corresponding instantaneous six-degree-of-freedom motion data of the buoy during image exposure, including geodetic coordinates, roll, pitch, bow roll, horizontal translation, and vertical heave; Step S3: Based on the noise-reduced six-degree-of-freedom motion data, calculate the rotation matrix and translation matrix of the buoy relative to the geodetic coordinate system frame by frame, merge them to generate a real-time homogeneous positive transformation matrix, and use the fixed observation plane in the geodetic coordinate system as the reference plane to solve the spatial offset parameters of the instantaneous measurement plane in the current frame relative to the reference plane; the spatial offset parameters include angular offset, horizontal offset, and vertical rise and fall offset. Step S4: Solve the inverse transformation compensation matrix based on the homogeneous forward transformation matrix, and use the inverse transformation compensation matrix to progressively reverse map the pixel coordinates of all effective tracer particles in a single frame image, converting the particle coordinates in the dynamic instantaneous measurement plane into the standard particle coordinates in the fixed observation plane. Step S5: Perform cross-correlation calculation on the original particle image to obtain the original two-dimensional velocity vector. Combine the real-time heave displacement of the buoy to complete the sheet light separation error compensation. Combine the spatial offset parameters to complete the velocity vector angle and translation coupling compensation, and obtain the standard velocity vector of the fixed observation plane in the geodetic coordinate system.

2. The planar correction method for underwater PIV flow field measurement based on a buoy platform according to claim 1, characterized in that, In step S1, the offline joint calibration includes: underwater refraction distortion calibration of the camera, optical distortion calibration of the lens, laser-guided optical plane calibration, and relative position calibration between the camera and the buoy carrier.

3. The planar correction method for underwater PIV flow field measurement based on a buoy platform according to claim 1, characterized in that, Step S2 uses an adaptive gain Kalman filter to reduce noise. The higher the sea state and wave height, the greater the adaptive gain value of the filter, thus filtering out the high-frequency micro-vibration attitude noise of the buoy.

4. The planar correction method for underwater PIV flow field measurement based on a buoy platform according to claim 1, characterized in that, In step S2, the time difference between particle image exposure, laser stroboscopic imaging, and six-degree-of-freedom data sampling is ≤1μs.

5. The planar correction method for underwater PIV flow field measurement based on a buoy platform according to claim 1, characterized in that, The error compensation logic for the light separation plane in step S5 is as follows: the effective velocimetric plate thickness is dynamically corrected based on the real-time heave value of the buoy, so as to offset the velocity error caused by the deviation of the tracer particles from the standard velocimetric plane due to the rise and fall of the buoy.

6. The planar correction method for underwater PIV flow field measurement based on a buoy platform according to claim 1, characterized in that, The preset fixed observation plane parameters can be remotely customized, including depth, horizontal tilt angle, and observation length and width boundaries.

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