Oval type scanning laser radar wave refraction correction error correction method

Abstract

The invention discloses an oval scanning laser radar wave refraction correction error correction method, which belongs to the technical field of airborne laser sounding, is used for airborne laser radar underwater topographic survey wave refraction correction, and comprises the following steps of: performing filtering processing on sea surface point cloud by adopting a statistical outlier removal filtering method; and extracting a sea surface gradient normal vector corresponding to each point by adopting an optimized moving least square method, simplifying the measurement process of the oval scanning laser radar to be carried out under a carrier coordinate system, constructing a refraction correction model by utilizing a Snell law and a vector decomposition method, and obtaining a corrected seabed point cloud coordinate. According to the method, the sea surface point cloud data is denoised, the actually measured sea surface point cloud is fitted through the moving least square method, polynomial fitting is replaced with covariance matrix characteristic decomposition, calculation is easy and convenient, polynomial fitting errors are avoided, the process is greatly simplified through vector decomposition calculation, and only a single solution exists.

Description

TECHNICAL FIELD

[0001] The application discloses an egg-shaped scanning laser radar wave refraction correction error correction method and belongs to the technical field of airborne laser depth sounding. BACKGROUND

[0002] Airborne laser depth sounding is one of efficient ocean depth sounding technologies developed in the past two or three decades, integrates a series of frontier technologies such as laser, automatic control, aviation, global navigation satellite system and computer, uses an airplane as a carrying platform, and is an advanced depth sounding method in which an airborne sensor transmits a laser beam to detect the depth of water below, has the advantages of fast speed, high coverage, strong flexibility and the ability to detect underwater areas inaccessible to ships, and has outstanding advantages in describing the seafloor topographic features of shallow sea areas, establishing an underwater three-dimensional obstacle model and island reef monitoring.

[0003] In recent years, the laser radar wave error correction technology is mostly to extract sea surface information, determine sea surface parameters in combination with a wave spectrum, construct an instantaneous sea surface model for error correction in a simulation sea surface mode, the commonly used wave spectrum models are the Pierson-Moscowitz spectrum, the Joint North Sea Wave Project spectrum and the Apel spectrum, the initial parameters of the wave spectrum are determined by extracting the sea surface information, the energy spectrum is converted into an instantaneous wave height by using a fast Fourier transform technology to establish a simulation sea surface model, this method can correct the errors caused by the influence of waves on the laser radar to a certain extent, but lacks the spatial and temporal characteristics of the measured sea surface point cloud.

[0004] Since the data collected by the laser radar during work is actually the state of the scanned object at a specific time point, and the real wave changes all the time, to correct the depth sounding errors caused by the wave, another important factor is how to track and correct each laser beam. The egg-shaped scanning laser radar has the characteristics of large scanning range and simple mechanical structure, but due to its unique off-axis rotating mirror structure, the scanning shape presents an irregular "egg-shaped" shape, so that the angle of the laser after reflecting the mirror is not as easy to calculate as the regular shape, at present, the refraction correction of the egg-shaped scanning laser radar is to calculate the refraction light vector by constructing a nonlinear equation set according to the angle relationship and coplanar condition, but the calculation process is complex and multiple solutions may occur. SUMMARY

[0005] The application aims to provide an egg-shaped scanning laser radar wave refraction correction error correction method to solve the problems in the prior art that the correction model lacks the spatial and temporal characteristics of the measured sea surface point cloud, the calculation process is complex and multiple solutions may occur.

[0006] The egg-shaped scanning laser radar wave refraction correction error correction method comprises the following steps: S1, the working environment of the airborne laser radar is sea condition less than or equal to three, wind force less than or equal to four, wave height less than or equal to 1.25 m, after obtaining the original sea surface point cloud data, K-dimensional tree is constructed for the original sea surface point cloud data set, filtering processing is carried out by using statistical outlier removal filtering algorithm, a density adaptive threshold function is introduced to dynamically correct the filtering processing threshold, and the preprocessed sea surface point cloud data is obtained; S2, K-dimensional tree is constructed for the preprocessed sea surface point cloud data set, the neighborhood radius is set based on the sea surface point cloud density, the neighborhood selection mode adopts fixed radius field, the sea surface point cloud in the neighborhood is fitted by using weighted least square method, the weight function selects Gaussian kernel function, the neighborhood points are centralized, then the covariance matrix is constructed to replace the polynomial fitting process, and the sea surface slope information is obtained by feature decomposition; S3, the carrier coordinate system and the auxiliary coordinate system are constructed by changing the angle through the off-axis rotating mirror, the included angle between the laser incidence and the mirror normal vector is calculated, the plane normal vector of the common plane of the laser incidence light, the mirror normal and the reflected light is calculated, the reflected light direction vector equation set is constructed, the incident light direction vector for constructing the instantaneous refraction correction model is obtained based on the included angle, the plane normal vector and the equation set, the refraction correction model is constructed by using Snell's law and vector decomposition method, and the corrected sea bottom point cloud coordinates are obtained based on the refraction correction model.

[0007] S1 includes S1.1, the working environment of the airborne laser radar is sea condition less than or equal to three, wind force less than or equal to four, wave height less than or equal to 1.25 m; after obtaining the original sea surface point cloud data, K-dimensional tree is constructed for the original sea surface point cloud data set; S1 includes S1.2, a density adaptive threshold function is introduced on the basis of the statistical outlier removal filtering algorithm, the point density of the surrounding neighborhood points , the basic standard deviation multiplier is dynamically corrected, and the formula is as follows: ; In the formula, is the corrected dynamic threshold, is the global reference threshold multiplier, is the sensitivity coefficient, is a variable starting from 1 and increasing, and the basic standard deviation multiplier is a multiplier for expanding or adjusting the standard deviation range.

[0008] S2 includes S2.1, K-dimensional tree is constructed for the preprocessed sea surface point cloud data set, the neighborhood search process is accelerated, the neighborhood radius is set according to the sea surface point cloud density, the neighborhood selection mode adopts fixed radius neighborhood, and the sea surface point cloud in the neighborhood is fitted by using weighted least square method. , The neighborhood point set is: ; wherein, is a set of neighborhood points, is a neighborhood point, is a variable starting from 1 and increasing, is the Euclidean distance, is the field radius; S2 includes S2.2, weighted least squares fitting is performed on the sea surface point cloud in the neighborhood, the fitting weight is inversely proportional to the distance from the neighborhood point to the target point, the weight function is selected as a Gaussian kernel function, and the formula is as follows: ; wherein, is the fitting weight, is a natural exponential function, is a point Euclidean distance from each point in the neighborhood, is the bandwidth of the Gaussian kernel, and the bandwidth of the Gaussian kernel is a parameter for controlling the smoothness of the Gaussian function; S2 includes S2.3, calculating the weighted centroid of the neighborhood point set : ; wherein, is the number of neighborhood points; S2 includes S2.4, centering the neighborhood points, and calculating the offset of the point to the centroid point: .

[0009] S2 includes S2.5, constructing a covariance matrix : ; wherein, respectively, the offset of the point to the centroid point in the coordinate axis ; performing eigenvalue decomposition on the covariance matrix to obtain a feature vector corresponding to the minimum eigenvalue, and the feature vector is a corresponding plane normal vector.

[0010] S3 includes S3.1, setting the angle between the mirror normal of the off-axis rotating mirror and the rotation axis to 7.5°, arranging the off-axis rotating mirror at an angle of 45° with the horizontal direction, and constructing a carrier coordinate system , the axis is directed towards the radar advancing direction, the axis is directed upwards, the axis is directed to the right to form a right front upper coordinate system, and is rotated around The shaft rotates 45° counterclockwise, so that The shaft coincides with the rotation axis, and an auxiliary coordinate system is constructed .

[0011] S3 includes S3.2, determining the laser incidence direction vector in the auxiliary coordinate system And the mirror normal vector : ; ; In the formula, The real-time angle of the off-axis rotating mirror; Calculate the included angle between the laser incidence and the mirror normal vector Is: ; In the formula, The length of the vector, The transpose symbol.

[0012] S3 includes S3.3, based on the coplanar relationship of the laser incidence light, the mirror normal and the reflected light, the normal vector of the plane is , the formula is as follows: ; Let the direction vector of the reflected light be , get the equation group: ; S3 includes S3.4, rotating Around the axis clockwise by 45° to get , The direction vector of the incident light when constructing the instantaneous refraction correction model : ; In the formula, The angle between and the axis, The angle between and the axis, The angle between and the axis.

[0013] S3 includes S3.5, let the instantaneous water surface normal vector penetrated by the laser be , the direction vector of the light after refraction by the water body is , and the cosine value of the incidence angle of the light before penetrating the water surface is: ; According to Snell's law and the triangle identity , the refraction angle of light penetrating the water surface The sine value is: ; In the formula, is the refractive index of the incident medium, is the refractive index of the refractive medium.

[0014] S3 includes S3.6, according to the vector operation law, decomposition along the normal and tangent of the incident plane, decomposition along the normal and tangent of the incident plane, according to Snell's law, and The parallel component satisfies the relationship The vertical component is related to the cosine of the refraction angle The decomposition formula of the incident light is: ; ; In the formula, represents the vertical component, represents the parallel component.

[0015] S3 includes S3.7, modeling as the sum of the vertical component and the parallel component: ; ; After sorting, the refraction vector expression after refraction by the water body is obtained: ; According to the refraction vector expression after refraction by the water body, the coordinates of the seabed point cloud are corrected: ; In the formula, is the corrected coordinate, is the slant range from the laser emission position to the sea surface point, is the propagation speed of light in air, is the time of light in water.

[0016] Compared with the prior art, the present application has the following beneficial effects: the present application directly processes the sea surface point cloud by using an optimized statistical outlier removal filter, introduces a density adaptive function to retain wave characteristics, can efficiently remove noise points caused by ambient light or scattering, and can retain the space-time characteristics of waves, fits the measured point cloud by using a moving least square method, uses characteristic decomposition of a covariance matrix instead of polynomial fitting, which is simple to calculate and avoids polynomial fitting errors, uses vector decomposition to greatly simplify the process, and only has a single solution. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is a technical flowchart of the present application; Figure 2 is a schematic diagram of the influence of wave refraction on the accuracy of a laser radar; Figure 3 is a sea surface point cloud denoising flowchart; Figure 4 is a carrier coordinate system schematic diagram; Figure 5 is an instantaneous refraction correction model schematic diagram; Figure 6 is a water surface original data point cloud; Figure 7 is a filtered sea surface point cloud; Figure 8 is a refraction correction effect schematic diagram. DETAILED DESCRIPTION

[0018] To make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the present application is described clearly and completely below. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0019] The oval scanning laser radar wave refraction correction error correction method comprises:

[0020] S1, the working environment of the airborne laser radar is sea conditions less than or equal to level three, wind less than or equal to four levels, wave height less than or equal to 1.25m, after obtaining the original sea surface point cloud data, a K-dimensional tree is constructed for the original sea surface point cloud data set, a statistical outlier removal filter algorithm is used for filtering processing, a density adaptive threshold function is introduced to dynamically correct the filtering processing threshold, and preprocessed sea surface point cloud data is obtained; S2, construct a K-dimensional tree for the pre-processed sea surface point cloud dataset, set a neighborhood radius based on the sea surface point cloud density, select the neighborhood in a fixed radius domain, perform a weighted least squares fitting on the sea surface point cloud in the neighborhood, select a Gaussian kernel function as the weight function, centralize the neighborhood points, then construct a covariance matrix to replace the polynomial fitting process, and perform feature decomposition to obtain sea surface slope information; S3, construct a carrier coordinate system and an auxiliary coordinate system by changing the angle through an off-axis rotating mirror, calculate the included angle between the laser incidence and the mirror normal vector, calculate the plane normal vector of the common plane of the laser incidence light, the mirror normal and the reflected light, construct a reflected light direction vector equation set, obtain the incident light direction vector for constructing the instantaneous refraction correction model based on the included angle, the plane normal vector and the equation set, construct a refraction correction model using Snell's law and vector decomposition method, and obtain the corrected sea bottom point cloud coordinates based on the refraction correction model.

[0021] S1 includes S1.1, the sea state of the airborne laser radar working environment is less than or equal to level three, the wind force is less than or equal to four levels, and the wave height is less than or equal to 1.25 m; after obtaining the original sea surface point cloud data, a K-dimensional tree is constructed for the original sea surface point cloud dataset; S1 includes S1.2, introducing a density adaptive threshold function on the basis of a statistical outlier removal filtering algorithm, calculating the point density of the surrounding neighborhood points , dynamically correcting the basic standard deviation multiplier , and the formula is as follows: ; In the formula, is the corrected dynamic threshold, is a global reference threshold multiplier, is a sensitivity coefficient, is a variable that starts from 1 and increases, and the basic standard deviation multiplier is a multiplier for expanding or adjusting the standard deviation range.

[0022] S2 includes S2.1, constructing a K-dimensional tree for the pre-processed sea surface point cloud dataset, accelerating the neighborhood search process, setting a neighborhood radius according to the sea surface point cloud density, selecting the neighborhood in a fixed radius neighborhood, and performing a weighted least squares fitting on the sea surface point cloud in the neighborhood , The neighborhood point set is: ; In the formula, is the neighborhood point set, is the neighborhood point of , a variable that starts from 1 and increases, is the Euclidean distance, For the radius of the field; S2 includes S2.2, weighted least squares fitting is performed on the sea surface point cloud in the neighborhood, the fitting weight is inversely proportional to the distance from the target point to the neighborhood point, the weight function selects a Gaussian kernel function, and the formula is as follows: ; In the formula, is the fitting weight, is a natural exponential function, is a point , and the Euclidean distance of each point in the neighborhood, is the bandwidth of the Gaussian kernel, and the bandwidth of the Gaussian kernel is a parameter for controlling the smoothness of the Gaussian function; S2 includes S2.3, calculating the weighted centroid of the neighborhood point set : ; In the formula, is the number of neighborhood points; S2 includes S2.4, centering the neighborhood points, and calculating the offset of the point to the centroid point :

[0023] S2 includes S2.5, constructing a covariance matrix : ; In the formula, is the offset of the point to the centroid point in the coordinate axis ; performing eigenvalue decomposition on the covariance matrix to obtain a feature vector corresponding to the minimum eigenvalue, and the feature vector is a corresponding plane normal vector.

[0024] S3 includes S3.1, setting the angle between the mirror normal of the off-axis rotating mirror and the rotation axis to 7.5°, arranging the off-axis rotating mirror at an angle of 45° with the horizontal direction, and constructing a carrier coordinate system , the axis is directed to the forward direction of the radar, the axis is upward, and the axis is to the right to form a right front upper coordinate system, rotating around the axis counterclockwise by 45°, so that the axis coincides with the rotation axis, and an auxiliary coordinate system is constructed .

[0025] S3 includes S3.2, determining the laser incidence direction vector and the mirror normal vector in the auxiliary coordinate system: ; ; wherein, is the real-time angle of the off-axis turning mirror; the included angle between the laser incident direction and the normal vector of the mirror is calculated as: ; wherein, is the vector length, is the transpose symbol.

[0026] S3 includes S3.3, based on the coplanar relationship of the laser incident light, the mirror normal and the reflected light, the normal vector of the coplanar plane is , and the formula is as follows: ; Suppose the direction vector of the reflected light is , and the equation group is obtained: ; S3 includes S3.4, rotating around axis clockwise by 45° to obtain , is the incident light direction vector when constructing the instantaneous refraction correction model : ; wherein, is the included angle between and axis, is the included angle between and axis, is the included angle between and axis.

[0027] S3 includes S3.5, suppose the instantaneous water surface normal vector of the laser penetration is , the direction vector of the light after water refraction is , and the cosine value of the incident angle before the light penetrates the water surface is: ; According to Snell's law and the triangle identity , the sine value of the refraction angle after the light penetrates the water surface is: ; wherein, is the refractive index of the incident medium, The refractive index of the refractive medium.

[0028] S3 includes S3.6, according to the vector operation law, the refracted vector is Decomposed along the normal and tangent of the incident plane, the refracted vector is Decomposed along the normal and tangent of the incident plane, according to Snell's law, the refracted vector is And The parallel component of the refracted vector satisfies the relationship The vertical component is related to the cosine of the refraction angle The decomposition formula of the incident light is: ; ; In the formula, The vertical component is The parallel component is

[0029] S3 includes S3.7, the refracted vector is modeled as the sum of the vertical component and the parallel component: ; ; After sorting, the refracted vector expression refracted by the water body is obtained: ; According to the refracted vector expression refracted by the water body, the seabed point cloud coordinates are corrected: ; In the formula, The corrected coordinates are The slant range from the laser emission position to the sea surface point, The propagation speed of light in air, The time of light in water.

[0030] To solve the technical problems of the present application, two aspects are taken as the starting point. First, analyze the causes of wave error. When the light beam contacts the water-air surface, due to the different refractive indices of light in different media, refraction effect will occur, as shown in Figure 2 , which can be specifically expressed by Snell's law as: ; Where , The refractive indices of the two media before and after the incident are , The propagation speeds of light in the two media before and after the incident are The incident angle is The reflection angle is

[0031] ​And due to the actual sea surface under the action of temperature, wind and other natural conditions, complex fluctuation changes will occur, resulting in an angle deviation between the tangential plane of the laser incidence on the sea surface and the horizontal plane, thereby causing the normal vector of the laser incidence surface to deviate, and further causing the refraction angle to change, and this influence increases linearly with water depth.

[0032] Secondly, based on the current development of laser radar equipment gradually developing towards high resolution and high frequency collection, in order to correct the depth error caused by waves, each laser needs to be accurately corrected, that is, by establishing an instantaneous refraction correction model for each sea surface laser foot point in the coordinate system, as shown in the following technical route is realized, as shown in the following technical route is realized, Figure 5 As shown in the following technical route is realized, Figure 1 As shown in the following technical route is realized, (1) First of all, due to the single-band laser radar carrying 532nm wavelength laser emitter blue-green laser has strong penetration to water body, and when propagating in medium, due to the influence of environmental light, aerosol and water scattering, there are many noise points in the collected sea surface point cloud, which cannot extract the correct sea surface point cloud, so first of all, the sea surface point cloud needs to be denoised to extract high-quality sea surface point cloud data set; (2) After obtaining the sea surface point cloud data, in order to retain the time and space characteristics of the collected sea surface, the sea surface slope information is directly extracted from the processed sea surface point cloud, so a suitable method is needed to extract accurate sea surface slope information; (3) Due to the irregular scanning trajectory of the oval scanning laser radar, the light incidence angle is different from other scanning methods, so a light tracking method suitable for oval scanning laser radar is needed to correct each laser.

[0033] Therefore, the present application obtains the following technical scheme: (1) Sea surface point cloud preprocessing, generally speaking, the working environment of airborne laser radar is recommended not to exceed three sea states, that is, wind force level 3-4, wave height 0.5m-1.25m, under this working environment, there is some surge on the sea surface, but no large fluctuation change, so the noise point density is far less than the sea surface point cloud density, and the overall sea surface point cloud data set conforms to the normal distribution, after obtaining the original sea surface point cloud data set, a K-dimensional tree is constructed to speed up the neighborhood search, the K-dimensional tree is a binary tree data structure for dividing the K-dimensional space point set by K-dimensional hyperplane, a statistical outlier removal filtering method is used to filter the sea surface point cloud, and a point The data set is searched for k+1 adjacent points, and then the average distance of The average distance of the adjacent points is calculated, a density adaptive function is introduced to dynamically adjust the threshold, the characteristics of the wave crest are judged and the outliers are removed, when the distance is greater than the threshold, the outliers are marked and removed, and when the distance is less than the threshold, the point cloud coordinates are output to obtain the processed sea surface point cloud, as shown in the following technical route is realized, Figure 3 As shown in the following technical route is realized, (2) The key of the refraction correction lies in whether the sea surface slope normal vector corresponding to each point can be extracted from the preprocessed sea surface point cloud. Since the sea wave is essentially a nonlinearly changing curved surface, local surface fitting needs to be performed for each sea surface laser point, and the normal vector calculation is performed. The application adopts the optimized moving least squares method (MLS) to realize this function; (3) The instantaneous sea surface correction model based on the oval scanning laser radar. The oval scanning laser radar has the advantages of large scanning range and simple mechanical structure compared with other scanning methods. However, due to the irregular scanning shape, the incident angle of the laser penetrating the water surface changes nonlinearly. Therefore, in order to determine the incident light direction vector when the laser penetrates the water surface, the whole process can be simplified in the carrier coordinate system, as shown in Figure 4 . Finally, the Snell's law and the vector decomposition method are used to construct the refraction correction model, and the light direction vector after refraction and the corrected seabed point cloud coordinates are calculated, as shown in Figure 5 . The instantaneous sea surface normal vector of the laser penetration is , the direction vector of the light after water refraction is , the incident light direction vector is , the incident angle of the light before penetrating the water surface is , the refraction angle of the light after penetrating the water surface is , the refractive index of the incident medium is , the refractive index of the refractive medium is , the vertical component of is , the parallel component of is , the vertical component of is , and the parallel component of is .

[0034] In order to verify the correction performance of the application on the wave refraction error, the single-band airborne laser radar developed by the team is used for test and test, the test site is the comprehensive surveying and mapping test field, the original point cloud data set is obtained by scanning the water body and underwater target in the pool by the equipment, and then the performance is verified by processing the original data set based on the application.

[0035] The original point cloud of the self-developed laser radar scanning the sea surface is shown in Figure 6 . It can be seen that there are many noise points due to water scattering and environmental light. After processing by the density adaptive statistical outlier removal filtering algorithm, the sea surface point cloud image is shown in Figure 7 . The noise points have been removed. The data comparison before and after filtering is shown in Table 1: Table 1, comparison of data before and after filtering .

[0036] The wind level was 1-2 on the test day, and the height change of the water surface point cloud data after filtering met the conditions.

[0037] The comparison of the sea bottom point cloud shape map before and after correction is shown in FIG. 2. Figure 8 The blue point cloud and the yellow point cloud are water surface point clouds, the red point cloud is the original water bottom point cloud without correction, and the green point cloud is the water bottom point cloud after wave refraction correction. It can be seen that the water depth deviation is obviously corrected. The bottom structure of the pool is in a three-step ladder type. The distance from the deepest part of the pool bottom to the water surface is about 3.85m on the test day. 10 groups of points were randomly taken from the water surface points and the water bottom points at the deepest part of the pool to calculate the water depth data. The comparison before and after correction is shown in Table 2: Table 2, comparison of refraction correction data .

[0038] According to the data comparison, the water depth deviation caused by the wave is well corrected, and the error is better than 5cm.

[0039] The above examples are only used to illustrate the technical solutions of the present application, but not to limit it. Although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can still be modified, or some or all of the technical features can be replaced by equivalents, without changing the essence of the corresponding technical solutions out of the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for correcting errors in wave refraction correction for an oval scan laser radar, characterized by, The application relates to a method for correcting seabed point cloud data of an airborne laser radar. S1, the working environment of the airborne laser radar is that the sea state is less than or equal to level three, the wind force is less than or equal to level four, and the wave height is less than or equal to 1.25 m; after original sea surface point cloud data are obtained, a K-dimensional tree is constructed for the original sea surface point cloud data set, a statistical outlier removal filtering algorithm is adopted for filtering processing, a density self-adaptive threshold function is introduced to dynamically correct the filtering processing threshold, and preprocessed sea surface point cloud data are obtained; S2, a K-dimensional tree is constructed for the preprocessed sea surface point cloud data set, a neighborhood radius is set based on the sea surface point cloud density, a fixed radius field is adopted as the neighborhood selection mode, sea surface point cloud in the neighborhood is subjected to weighted least square fitting, a Gaussian kernel function is selected as the weight function, the neighborhood points are centralized, then a covariance matrix is constructed to replace the polynomial fitting process, and feature decomposition is carried out to obtain sea surface slope information; S3, a carrier coordinate system and an auxiliary coordinate system are constructed by means of a deflection mirror transformation angle, the included angle between the laser incidence and the mirror normal vector is calculated, the plane normal vector of the common plane of the laser incidence light, the mirror normal and the reflected light is calculated, a reflected light direction vector equation set is constructed, the incident light direction vector for constructing an instantaneous refraction correction model is obtained based on the included angle, the plane normal vector and the equation set, a refraction correction model is constructed by means of the Snell law and vector decomposition, and the corrected seabed point cloud coordinates are obtained based on the refraction correction model.

2. The oval scan LiDAR wave refraction correction error correction method according to claim 1, characterized in that, S1 includes that the working environment of the airborne laser radar is that the sea state is less than or equal to level three, the wind force is less than or equal to level four, and the wave height is less than or equal to 1.25 m; After the original sea surface point cloud data are obtained, a K-dimensional tree is constructed for the original sea surface point cloud data set; S1 includes, S1.2, introducing a density adaptive threshold function on the basis of statistical outlier removal filtering algorithm, calculating the point Density of surrounding neighborhood points , the basic standard deviation multiplier is dynamically corrected, the formula is as follows: ； wherein is the modified dynamic threshold, is the global reference threshold multiplier, is the sensitivity coefficient, is a variable that is incremented from a starting value of 1, and the base standard deviation multiplier is a multiplier that expands or adjusts the range of the standard deviation.

3. The oval scan LiDAR wave refraction correction error correction method of claim 2, wherein, S2 includes S2.1, constructing a K-dimensional tree for the pre-processed sea surface point cloud dataset, accelerating the neighborhood search process, setting the neighborhood radius according to the sea surface point cloud density, and adopting a fixed radius neighborhood for neighborhood selection , The neighborhood point set is: ； wherein is a neighborhood point set, is a neighborhood point of is a variable that is incremented from a starting value of 1, is the Euclidean distance, is the radius of the field; S2 includes that sea surface point cloud in the neighborhood is subjected to weighted least square fitting, the fitting weight is inversely proportional to the distance of the neighborhood point to the target point, a Gaussian kernel function is selected as the weight function, and the formula is as follows: ； wherein is a fitting weight, is a natural exponential function, is a point is the Euclidean distance to each point in the neighborhood, is a bandwidth of the Gaussian kernel, the bandwidth of the Gaussian kernel being a parameter that controls the degree of smoothing of the Gaussian function; S2 comprises S2.3, computing a weighted centroid of the neighborhood point set : ； In the formula, is the number of neighborhood points; S2 comprises S2.4, centering the neighborhood points, computing the point offset to the centroid point : 。 4. The oval scan lidar wave refraction correction error correction method according to claim 3, characterized by, S2 comprises S2.5, constructing a covariance matrix : ； In the formula, respectively, the offset of the point to the centroid point in the coordinate axis ; the covariance matrix is eigenvalue decomposition, and a feature vector corresponding to the minimum eigenvalue is obtained, and the feature vector is a corresponding plane normal vector.

5. The oval scan lidar wave refraction correction error correction method according to claim 4, characterized by, S3 includes S3.1, the included angle between the mirror normal of the off-axis rotating mirror and the rotating shaft is 7.5°, the off-axis rotating mirror is arranged at an angle of 45° with the horizontal direction, and the laser is incident along the horizontal direction to construct the carrier coordinate system , The axis is towards the radar advancing direction, The axis is upwards, The axis is right to constitute a right front upper coordinate system, Around The axis is counterclockwise rotated by 45°, so that The axis coincides with the rotating shaft, and an auxiliary coordinate system is constructed .

6. The oval scan lidar wave refraction correction error correction method according to claim 5, wherein, S3 comprises S3.2, determining a laser incidence direction vector within the auxiliary coordinate system and the mirror normal vector : ； ； In the formula, is the real-time angle of the off-axis turning mirror; calculating the angle between the laser incidence and the mirror normal vector is: ； wherein is the vector length, is the transpose symbol.

7. The oval scan lidar wave refraction correction error correction method according to claim 6, characterized by, S3 comprises S3.3, based on the coplanar relationship of the laser incident light, the mirror normal and the reflected light, the normal vector of the coplanar plane is , the formula is as follows: ； Let the direction vector of the reflected light ray be , we obtain the system of equations: ； S3 comprises S3.4, to around clockwise by 45° to obtain , is the incident light direction vector when constructing the instantaneous refractive correction model : ； wherein is and the angle between the axes, is and the angle between the axes, is and the angle between the axes.

8. The oval scan lidar wave refraction correction error correction method according to claim 7, characterized by, S3 includes S3.5, the instantaneous water surface normal vector of the laser penetration is , the direction vector of the light ray after refraction by the water body is , and the cosine value of the incident angle of the light ray penetrating the water surface is . ； According to Snell's law and the triangle identity , the refractive angle of the light ray after penetrating the water surface The sine value is: ； wherein n0is the refractive index of the incident medium, n1is the refractive index of the refractive medium.

9. The oval scan lidar wave refraction correction error correction method according to claim 8, characterized by, S3 includes S3.6, according to the vector operation law, the parallel component of decomposition along the incident plane normal and tangential, according to Snell's law, decomposition along the incident plane normal and tangential, according to Snell's law, and the parallel component satisfies the relationship , the vertical component is related to the cosine of the refraction angle The decomposition formula of the incident light is: ； ； wherein represents the perpendicular component, represents the parallel component.

10. The oval scan lidar wave refraction correction error correction method according to claim 9, wherein, S3 comprises S3.7, to Modelled as the sum of a perpendicular component and a parallel component: ； ； After the arrangement, the refraction vector expression after water refraction is obtained: ； According to the refraction vector expression after water refraction, the seabed point cloud coordinates are corrected: ； wherein is the corrected back coordinate, is the slant range from the laser launch position to the sea surface point, is the speed of light in air, is the time of flight of the light in water.

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