Laser radar imaging simulation method based on laser beam ray tracing

Abstract

The invention belongs to the technical field of information technology and environmental perception, and particularly relates to a laser radar imaging simulation method based on laser beam ray tracing. The method comprises the following steps: 1, setting a detection distance, a field angle, a resolution ratio, a position and an attitude angle of a simulation laser radar, and setting a position, a size and an attitude angle of an aerial target model; 2, calculating an external attitude angle and an internal attitude angle of the simulation laser radar; 3, calculating a direction vector of a scanning line of the simulation laser radar in a world coordinate system; 4, judging whether the scanning line intersects with the target model bounding ball or not according to the direction vector, if yes, entering the next step, and if not, returning to the step 3 to traverse the next scanning line; 5, calculating intersection points of the scanning lines and the target model bounding ball, and arranging the intersection points according to a scanning sequence to obtain target simulation ideal point cloud data; 6, simulating noise data; and step 7, injecting the noise data into the target simulation point cloud data to obtain target simulation real point cloud data.

Description

Technical Field

[0001] This invention belongs to the fields of information technology and environmental perception technology, specifically a laser radar imaging simulation method based on laser beam ray tracing. Background Technology

[0002] The working principle of lidar 3D scanning is to emit a laser beam into the observation environment and then receive the echo reflected from the target. Distance is measured by comparing the time difference between the emitted beam and the echo. LiDAR can quickly acquire 3D point cloud data of the observation scene, thus serving environmental perception and 3D scene detection. Airborne lidar refers to lidar sensors mounted on manned or unmanned aircraft, primarily used for acquiring 3D point cloud data in the air.

[0003] Based on lidar point cloud data simulation technology, a lidar point cloud data simulation environment for aerial target monitoring can be developed. This environment can generate simulated lidar point cloud data and simulate the emission, reflection, and reception processes of the laser beam. The lidar data simulation environment plays a crucial role in lidar system requirement definition, system design, and point cloud data processing algorithm verification. Currently, mainstream lidar imaging simulation methods are mainly divided into two categories, each with its own significant limitations. The first is based on point cloud interpolation and projection. This method typically relies on a pre-acquired high-precision 3D scene model and a registered real-intensity image. However, this method lacks physical realism, often neglecting the physical characteristics of the laser beam itself, failing to simulate complex optical effects, and struggling to model noise. The second is based on voxel or image rendering. This method discretizes the 3D scene into a voxel mesh or uses multi-view images for 3D reconstruction, then simulates imaging by calculating the laser's propagation within the voxels. The drawbacks of this method are its enormous computational resource consumption and the potential for detail loss and jagged edges. Summary of the Invention

[0004] Purpose of the invention: To provide a lidar imaging simulation technology based on laser beam ray tracing, which simulates the lidar emitting laser rays onto the surface of a target model to simulate the three-dimensional point cloud data collected by the lidar. In order to better simulate the data acquisition process in the real environment, the module supports users to customize the performance parameters of the lidar and the surface reflectivity of the target, and import the motion trajectories of the target and the lidar to simulate the dynamic process of the movement of the aerial target.

[0005] Laser radar imaging simulation technology based on laser beam ray tracing can provide a design basis for the design of key indicators such as angular resolution, detection range, and field of view of laser radar sensors in aerial target detection scenarios, avoiding problems of over-design and insufficient indicator requirements; at the same time, it can provide simulated point cloud data for point cloud processing software, and iterate and optimize point cloud processing algorithm models by simulating different application scenarios.

[0006] Digital simulation technology for lidar point cloud data provides a cost-effective method to simulate and understand the working principle of lidar and supports related applications such as obstacle avoidance and aerial target surveillance. Technical solution: A laser radar imaging simulation method based on laser beam ray tracing, comprising the following steps: Step 1: Set the detection range, field of view, resolution, position, and attitude angle of the simulated lidar; set the position, size, and attitude angle of the aerial target model. Step 2: Calculate the external and internal attitude angles of the simulated lidar; Step 3: Calculate the direction vector of the scan line of the simulated lidar in the world coordinate system; Step 4: Determine whether the scan line intersects with the bounding sphere of the target model based on the direction vector. If yes, proceed to the next step; otherwise, return to step 3 and traverse the next scan line. Step 5: Calculate the intersection points of the scan lines and the bounding sphere of the target model, and arrange the intersection points according to the scan order to obtain the target simulation ideal point cloud data; Step Six: Simulate noise data; Step 7: Inject noise data into the target simulation point cloud data to obtain the target simulation real point cloud data.

[0007] Furthermore, in step two, the radar's external attitude angles are a directional description of the radar in the space system, including pitch angle, roll angle, and tilt angle. The external attitude angles are... This represents the transformation relationship from the radar body coordinate system to the world coordinate system; The radar's internal attitude angle is the angle at which the scanning beams are adjusted within the radar system. The internal attitude angle is... This represents the transformation relationship from the radar lens coordinate system to the radar body coordinate system; The calculation process for the external attitude angle is as follows: Let the coordinates of the target be in the world coordinate system. The coordinates of the target in the radar body coordinate system; The transformation matrix from the radar body coordinate system to the world coordinate system is:

[0008] This transformation process requires rotation along the z-axis. y-axis rotation Finally, rotate along the x-axis. ; The radar's position in the world coordinate system is ; The calculation process for the internal attitude angles is as follows: First, translate the world coordinate system to... Then, rotate the world coordinate system until the Z-axis of the radar coordinate system aligns with the origin of the world coordinate system. This rotation requires obtaining the rotation matrix and rotation angle. Before rotation, the coordinates of the origin of the world coordinate system in the radar coordinate system are... The coordinates of the origin of the rotated world coordinate system in the radar coordinate system are: The process of obtaining the rotation matrix and rotation angle is as follows: The vector before rotation is The rotated vector is , Let be the position vector of the radar relative to the world coordinate system. By the definition of the dot product of vectors, then the vector... to vector The rotation angle is shown in the following formula:

[0009] vector , They can form a plane, and the axis of rotation must be perpendicular to this plane. The axis of rotation can be obtained using the cross product of vectors. ; The rotation matrix R is obtained using Rodriguez's rotation formula, with respect to the rotation axes in the formula. Normalization yields the unit vector of the rotation axis. Rotate around it θ Angle, using Rodriguez's rotation formula, yields the rotation matrix. In this context, I is a 3×3 identity matrix. It is an antisymmetric matrix of cross product; (4) The internal attitude angles are obtained using SVD decomposition, where... The rotation matrix R is the first Line 1 Column elements.

[0010]

[0011] in, .

[0012] Furthermore, in step three, we assume that L is the distance from the emission source O to the scanning point C. θ2 is the horizontal scanning angle, and α2 is the vertical scanning angle; Coordinates of scan point C in the radar lens coordinate system As shown in the following formula:

[0013] Scan line vector Direction vector for:

[0014] Point Transform the coordinates to the world coordinate system to obtain... ; In the world coordinate system, the direction vector of the scan line for: .

[0015] Furthermore, in step four, the coordinates of the center of the sphere enclosed by the target model in the world coordinate system are: , radius is ; The process for determining whether they intersect is as follows: The parametric equations of the scan line in the world coordinate system are:

[0016] The equation of the enclosing sphere in the world coordinate system is:

[0017] Substituting the parametric equations of the scan line in the world coordinate system into the equations of the enclosing sphere, we obtain:

[0018] By solving the quadratic equation, we obtain: ,like Then the ray and the surrounding sphere have no intersection; if Then the ray is tangent to the surrounding sphere; if Then the ray of light intersects the sphere at two points.

[0019] Furthermore, in step five, the calculation process is as follows: Suppose the scan line has intersected with the triangular facet target model, and the three vertices of the triangular facet target model are... , , The intersection points on the target model of the triangular facets are as follows:

[0020] midpoint Inside the triangular facet, The following conditions must be met:

[0021] Since the intersection point lies on both the triangular facet and the ray, the parametric equation for the scan line is as follows: R ( t )= T ( u , v ),get:

[0022] Simplifying the above equation, we get:

[0023] Solve using Cramer's rule, let... ,get:

[0024] because Further simplification of the above equation yields:

[0025] The coordinates of the intersection point were calculated. The distance between the simulated lidar and the intersection point is .

[0026] Furthermore, in step six, the simulated noise includes radar noise and meteorological noise.

[0027] Furthermore, the meteorological noise simulation process is as follows: (1) Collect lidar point cloud data under different meteorological conditions; (2) Statistically analyze the relationship between different measured rainfall and cloud cover and point cloud noise, and establish empirical models of point cloud noise corresponding to different meteorological conditions.

[0028] Furthermore, the radar noise simulation process is as follows: Assuming that within the gate, the total number of photoelectrons generated by background radiation and dark counting is... Therefore, theoretically, the average number of noise photoelectrons received in each cell is... As shown in the following formula, This represents the total number of intervals evenly divided by the gating gate;

[0029] The trigger probability of a lidar within a certain time interval follows a Poisson distribution. The probability of a small interval being triggered for:

[0030] Let be any small interval, where For lidar in The number of photoelectrons received in the interval theory The lidar is in front. The intervals were not triggered and in The probability that the interval is triggered; Therefore, it is only necessary to determine the number of photons received in each time interval. The probability of the lidar being triggered in each time interval is calculated based on the above formula. If the precise distance value of a certain pixel is The interval number where the initial photoelectron is located for:

[0031] Then the lidar is in The trigger probability of an interval can be divided into the following three cases: (a) When the target is located in the interval ( When triggered before the interval, the probability of triggering is determined by background noise and dark current. The interval before the non-triggered and in Probability of interval triggering:

[0032] (b) When the target is located in the interval ( When triggered in an interval, the probability of Gm-APD cell triggering is determined by background noise and dark count. The previous interval was not triggered, background noise, dark count, and target reflected photoelectrons. Probability of interval triggering:

[0033] (c) When triggered after the target's location, the probability of Gm-APD pixel triggering is determined by background noise, dark count, and target reflected photoelectrons. The previous interval was not triggered, background noise, and dark count were in Probability of interval triggering: .

[0034] Furthermore, in step seven, three-dimensional noise points for lidar are generated based on meteorological noise point clouds and lidar imaging noise point clouds. These noise points are then added to the simulated point cloud data to simulate the real lidar scanning process.

[0035] Beneficial effects: The laser beam ray tracing-based lidar imaging simulation technology proposed in this invention can simulate the working state of a lidar sensor, actively emitting laser beams and receiving reflected echo information from aerial targets to generate simulated point cloud data of aerial targets. It supports customization of lidar hardware parameters, target models, target trajectories, and weather conditions, enabling better simulation of the lidar data acquisition process in real-world environments. The results can be widely applied to the acquisition of 3D point cloud data of aerial targets in various scenarios, providing support for environmental perception applications such as obstacle avoidance and aerial target surveillance, and possesses promising market application prospects. Attached Figure Description

[0036] Figure 1 Flowchart of LiDAR imaging simulation technology based on laser beam ray tracing.

[0037] Figure 2 Flowchart for determining the virtual radar coordinate system.

[0038] Figure 3 Schematic diagram of radar coordinate system rotation.

[0039] Figure 4 Schematic diagram of forward-looking imaging with lidar.

[0040] Figure 5 : Schematic diagram of the algorithm for finding the intersection of a laser beam and a target model. Detailed Implementation

[0041] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0042] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0043] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linking," and "socketing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral structure; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0045] A laser radar imaging simulation technology based on laser beam ray tracing is a point cloud data generation and processing simulation algorithm for laser radar detection applications. It supports calculating and generating simulated point clouds based on a designed laser radar scanning aerial target scene, supports the simulation injection of meteorological conditions and noise points, and supports radar, target model, and target trajectory setting functions. It can generate simulated 3D point cloud data based on imported data. The steps include: Step 1: Setting key parameters for point cloud data simulation technology, including aerial target model, target trajectory, key parameters of lidar, etc. Calculate the direction vector of the laser in the world coordinate system based on the preset parameter information of lidar and target. Step 2: Target point cloud data generation. Simulate the working state of the lidar to calculate and generate a simulated point cloud of the scene, and store and import the simulated point cloud. Step 3: Noise simulation, realizing the simulation of different working conditions and noise injection; In step one, the key parameter settings for point cloud data simulation technology include the following steps: 1-1 Set the key parameters of the simulated radar, including detection range, field of view, resolution, position and attitude angle, etc. Then set the dynamic parameters of the target model such as position, size and attitude, determine the position and attitude of the target, and determine the lidar coordinate system.

[0046] 1-2 Based on the geometric principles of radar imaging, a lidar system uses a laser emitting component to emit light within a certain field of view, and simultaneously uses a receiving component to receive the reflected light within that range. Calculate the direction vector of the lidar scan line in the world coordinate system. Step two, the generation of target point cloud data, includes the following steps: 1-3 Determine whether the scanning ray intersects with the bounding sphere of the target model. If they intersect, proceed to the next step; otherwise, traverse the next scanning ray. 1-4 The intersection points of the scanning ray and the target model are calculated using the ray model cross detection algorithm. The intersection points are arranged in the scanning order to obtain the accurate distance image and the target simulation point cloud data. Step three, the noise simulation, includes the following steps: 1-5 Meteorological conditions are injected. Based on the point cloud data actually collected by lidar under different meteorological conditions, an empirical model of meteorological conditions is established. The influence of meteorological conditions on lidar scanning is added to the simulated point cloud data in the form of noise points. 1-6 Artificially set noise. Based on the imaging noise mechanism of lidar, establish a simulation probability model of trigger noise to simulate the imaging noise point cloud when lidar is working.

[0047] Example like Figure 1 As shown, firstly, the target model, target trajectory, and lidar parameters are set to construct a lidar scanning simulation environment; simultaneously, a noise model is set to simulate different meteorological conditions and lidar imaging noise environment; then, the ray-model cross-detection algorithm is used to calculate the collision between the scanning ray and the target model, obtain the intersection point, and thus generate simulated point cloud data, completing the lidar scanning data acquisition of aerial targets under the set scenario.

[0048] The determination of the lidar coordinate system is shown in the attached figure. Figure 2 As shown, the specific steps are as follows: Step 1: Calculate the radar's external attitude angles.

[0049] The external attitude angles of a radar are a directional description of the radar in a space system, including pitch angle, roll angle, and tilt angle. Let the external attitude angles be... x-axis rotation y-axis rotation Z-axis rotation The unit is degrees, assuming the radar's location is in... Therefore, the transformation matrix from the world coordinate system to the radar coordinate system is: (1) In the formula, Let these be the coordinates of the point in the world coordinate system. Let be the coordinates of the point in the radar coordinate system. Inverting the above equation, we obtain the transformation matrix from the radar coordinate system to the world coordinate system: (2) This transformation process requires rotation along the z-axis. y-axis rotation Finally, rotate along the x-axis. .

[0050] Step 2: Calculate the internal attitude angles of the radar.

[0051] As attached Figure 3 As shown, let the radar's coordinates in the world coordinate system be... First, translate the world coordinate system to... Then, rotate the world coordinate system until the Z-axis of the radar coordinate system is aligned with the origin of the world coordinate system (currently, the model is at the origin of the world coordinate system by default, so the radar and the model are aligned). The rotation of the coordinate system requires obtaining the rotation matrix and rotation angle. Before rotation, the coordinates of the origin of the world coordinate system in the radar coordinate system are... The coordinates of the origin of the rotated world coordinate system in the radar coordinate system are: The process of obtaining the rotation matrix and rotation angle is as follows: (1) Calculate the rotation angle. The vector before rotation is: The rotated vector is , Let be the position vector of the radar relative to the world coordinate system. By the definition of the dot product of vectors, then the vector... to vector The rotation angle is shown in the following formula: (3) (2) Determine the axis of rotation. Vector , They can form a plane, and the axis of rotation must be perpendicular to this plane, using vectors. , The axis of rotation can be obtained by cross product. ; (3) Obtain the rotation matrix. The rotation matrix R is obtained using Rodriguez's rotation formula. The rotation axes in the formula are... Normalization yields the unit vector of the rotation axis. Rotate around it θ The angle can be obtained from Rodrigues' rotation formula, which gives the rotation matrix. In this context, I is a 3×3 identity matrix. It is an antisymmetric matrix of cross product.

[0052] (4) (4) The internal attitude angles are obtained by using SVD decomposition, where The rotation matrix R is the first Line 1 Column elements.

[0053] (5) in,

[0054] Step 3: After calculating the internal attitude angles of the radar, further calculate the transformation matrix from the world coordinate system to the radar coordinate system.

[0055] The specific steps for calculating the direction vector of the scanning light rays in a lidar system are as follows: Step 1: Calculate the coordinates of the scanning point and the ray vector in the radar coordinate system; Assume L is the distance from the emission source O to the scanning point C, as shown in the attached figure. Figure 4 As shown in the schematic diagram of forward-looking imaging with a lidar, the coordinates of the scanning point C in the lidar coordinate system can be calculated using geometric calculations. As shown in the following formula: (6) in, The horizontal scanning angle, This is the vertical scanning angle.

[0056] Ray vector Direction vector for: (7) Step 2: Calculate the coordinates of the scan point in the world coordinate system and the ray vector; Direction vector in radar coordinate system Transform the points to the model (world) coordinate system. Substituting into the formula, we obtain the point in the world coordinate system. The coordinates are Therefore, in the world coordinate system, the direction vector of light rays is... for: (8) in, These are the coordinates of the radar launch point in the world coordinate system.

[0057] The algorithm flow for finding the intersection between lidar rays and the 3D model is attached. Figure 5 As shown, the specific steps are as follows: Step 1: Determine the intersection of the scanning ray and the surrounding sphere.

[0058] (1) Let the coordinates of the starting point of the ray be... The direction vector is ,because It is a unit vector, so The parametric equations for the laser scanning line are: (9) (2) Assume the center of the enclosing sphere of the model is The radius of the enclosing sphere is Then the equation of the enclosing sphere is: (10) (3) Determine whether the laser line intersects the surrounding sphere. Substituting the laser beam into the equation for the sphere, we get: (11) By solving the quadratic equation, we obtain: Only need to judge Whether there is a solution is the key. Then the ray and the surrounding sphere have no intersection; if Then the ray is tangent to the surrounding sphere; if Then the ray of light intersects the sphere at two points.

[0059] Step 2: If the intersection of the ray and the bounding sphere has been determined, then the intersection points of the scanning ray and the model triangular facets are further calculated. These triangular facets are the basic elements that make up the model surface. The coordinates and distance values ​​of the intersection points are obtained. The ray-model cross-intersection detection algorithm is used to solve for the intersection points of the scanning ray and the model facets.

[0060] (1) Suppose that the ray has intersected the triangular facet, and the three vertices of the triangular facet are... , , The intersection points on the triangular facets are as follows: (12) midpoint Inside the triangular facet, The following conditions must be met: (13) (2) Since the intersection point lies on both the triangle and the ray, we have We can obtain: (14) Simplifying the above equation, we get: (15) (3) Solve using Cramer's rule, let... We can obtain: (16) because Further simplification of the above equation yields: (17) Calculated ,if All satisfied Then the ray intersects the triangle, and the distance between the emitting light source and the intersection point is... The accurate distance image can be obtained by arranging the obtained intersection points in the scanning order.

[0061] When in foggy or rainy weather conditions, the scanning light emitted by the lidar will be backscattered or diverted when it encounters airborne particles, resulting in noise in distance and reflectivity measurements in point clouds. The specific steps of the weather condition injection simulation process are as follows: (1) Collect lidar point cloud data under different meteorological conditions; (2) Statistically analyze the relationship between different measured rainfall and cloud cover and point cloud noise, and establish empirical models of point cloud noise corresponding to different meteorological conditions; (3) Load the point cloud noise model into the simulation scene of the LiDAR scanning target, and model the meteorological environment. When the LiDAR scans, it will be affected by meteorological factors, which will be reflected in the point cloud data.

[0062] A meteorological noise model is set up, and a meteorological noise point cloud is generated based on the ray-model cross-detection method. The generated noise point cloud is then added to the simulation point cloud data.

[0063] The main sources of imaging noise in lidar are background radiation noise and dark count. Dark count is related to the multiplication region material of lidar. The noise in lidar manifests as: the average initial number of background noise generated within the range gate by background radiation of a certain intensity, and the average initial number of noise generated within the range gate by dark count of avalanche photodiode (APD).

[0064] The specific settings for the imaging noise probability model of the lidar are as follows: Assuming that within the gate, the total number of photoelectrons generated by background radiation and dark counting is... Therefore, theoretically, the average number of noise photoelectrons received in each cell is... As shown in the following formula, This represents the total number of intervals evenly divided by the gate selection.

[0065] (18) The trigger probability of a lidar within a certain time interval follows a Poisson distribution. Small intervals ( The probability of being triggered (for any small interval) for: (19) In the formula For lidar in The number of photoelectrons received in the interval theory. The lidar is in front. The intervals were not triggered and in The probability of an interval being triggered. Therefore, it is only necessary to determine the number of photons received within each time interval. Therefore, the probability of the lidar being triggered in each time interval can be calculated based on the above formula.

[0066] If the precise distance value of a certain pixel is The interval number where the initial photoelectron is located for: (20) Then the lidar is in The trigger probability of an interval can be divided into the following three cases: (a) When the target is located in the interval ( When triggered before the interval, the probability of triggering is determined by background noise and dark current. The interval before the non-triggered and in The probability of interval triggering, i.e.: (twenty one) (b) When the target is located in the interval ( When triggered in an interval, the probability of Gm-APD cell triggering is determined by background noise and dark count. The previous interval was not triggered, background noise, dark count, and target reflected photoelectrons. The probability of interval triggering, i.e.: (twenty two) (c) When triggered after the target's location, the probability of Gm-APD pixel triggering is determined by background noise, dark count, and target reflected photoelectrons. The previous interval was not triggered, background noise, and dark count were in The probability of interval triggering, i.e.: (twenty three) Based on the aforementioned lidar noise mechanism, three-dimensional noise points are generated for lidar, and these noise points are added to the simulated point cloud data to simulate the real lidar scanning process.

[0067] The above description is merely a specific embodiment of the present invention, providing a detailed description of the invention. Parts not covered herein are conventional techniques. However, the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A laser radar imaging simulation method based on laser beam ray tracing, characterized in that: The steps are as follows: Step 1: Set the detection range, field of view, resolution, position, and attitude angle of the simulated lidar; set the position, size, and attitude angle of the aerial target model. Step 2: Calculate the external and internal attitude angles of the simulated lidar; Step 3: Calculate the direction vector of the scan line of the simulated lidar in the world coordinate system; Step 4: Determine whether the scan line intersects with the bounding sphere of the target model based on the direction vector. If yes, proceed to the next step; otherwise, return to step 3 and traverse the next scan line. Step 5: Calculate the intersection points of the scan lines and the bounding sphere of the target model, and arrange the intersection points according to the scan order to obtain the target simulation ideal point cloud data; Step Six: Simulate noise data; Step 7: Inject noise data into the target simulation point cloud data to obtain the target simulation real point cloud data.

2. The method according to claim 1, characterized in that: In step two, the radar's external attitude angles are the directional description of the radar in the space system, including pitch angle, roll angle, and tilt angle. The external attitude angles are... This represents the transformation relationship from the radar body coordinate system to the world coordinate system; The radar's internal attitude angle is the angle at which the scanning beams are adjusted within the radar system. The internal attitude angle is... This represents the transformation relationship from the radar lens coordinate system to the radar body coordinate system; The calculation process for the external attitude angle is as follows: Let the coordinates of the target be in the world coordinate system. The coordinates of the target in the radar body coordinate system; The transformation matrix from the radar body coordinate system to the world coordinate system is: This transformation process requires rotation along the z-axis. y-axis rotation Finally, rotate along the x-axis. ; The radar's position in the world coordinate system is ; The calculation process for the internal attitude angles is as follows: First, translate the world coordinate system to... Then, rotate the world coordinate system until the Z-axis of the radar coordinate system is aligned with the origin of the world coordinate system; the rotation of the world coordinate system requires obtaining the rotation matrix and rotation angle. The coordinates of the origin of the world coordinate system before rotation in the radar coordinate system are: The coordinates of the origin of the rotated world coordinate system in the radar coordinate system are: The process of obtaining the rotation matrix and rotation angle is as follows: The vector before rotation is The rotated vector is , Let be the position vector of the radar relative to the world coordinate system. By the definition of the dot product of vectors, then the vector... to vector The rotation angle is shown in the following formula: vector , They can form a plane, and the axis of rotation must be perpendicular to this plane. The axis of rotation can be obtained using the cross product of vectors. ; The rotation matrix R is obtained using Rodriguez's rotation formula, with respect to the rotation axes in the formula. Normalization yields the unit vector of the rotation axis. Rotate around it θ Angle, using Rodriguez's rotation formula, yields the rotation matrix. In this context, I is a 3×3 identity matrix. It is an antisymmetric matrix of cross product; (4) The internal attitude angles are obtained using SVD decomposition, where... The rotation matrix R is the first Line number Column elements.

3. in, .

4. The method according to claim 2, characterized in that: In step three, assume L is the distance from the emission source O to the scanning point C. θ 2 is the horizontal scanning angle, and α2 is the vertical scanning angle; Coordinates of scan point C in the radar lens coordinate system As shown in the following formula: Scan line vector Direction vector for: Point Transform the coordinates to the world coordinate system to obtain... ; In the world coordinate system, the direction vector of the scan line for: 。 5. The method according to claim 3, characterized in that: In step four, the coordinates of the center of the sphere enclosed by the target model in the world coordinate system are: , radius is ; The process for determining whether they intersect is as follows: The parametric equations of the scan line in the world coordinate system are: The equation of the enclosing sphere in the world coordinate system is: Substituting the parametric equations of the scan line in the world coordinate system into the equations of the enclosing sphere, we obtain: By solving the quadratic equation, we obtain: ,like Then the ray and the surrounding sphere have no intersection; if Then the ray is tangent to the surrounding sphere; if Then the ray of light intersects the sphere at two points.

6. The method according to claim 4, characterized in that: In step five, the calculation process is as follows: Suppose the scan line has intersected with the triangular facet target model, and the three vertices of the triangular facet target model are... , , The intersection points on the target model of the triangular facets are as follows: midpoint Inside the triangular facet, The following conditions must be met: Since the intersection point lies on both the triangular facet and the ray, the parametric equation for the scan line is as follows: R ( t )= T ( u , v ),get: Simplifying the above equation, we get: Solve using Cramer's rule, let... ,get: because Further simplification of the above equation yields: The coordinates of the intersection point were calculated. The distance between the simulated lidar and the intersection point is .

7. The method according to claim 5, characterized in that: In step six, the simulated noise includes radar noise and meteorological noise.

8. The method according to claim 6, characterized in that: The meteorological noise simulation process is as follows: (1) Collect lidar point cloud data under different meteorological conditions; (2) Statistically analyze the relationship between different measured rainfall and cloud cover and point cloud noise, and establish empirical models of point cloud noise corresponding to different meteorological conditions.

9. The method according to claim 7, characterized in that: The radar noise simulation process is as follows: Assuming that within the gate, the total number of photoelectrons generated by background radiation and dark counting is... Therefore, theoretically, the average number of noise photoelectrons received in each cell is... As shown in the following formula, This represents the total number of intervals evenly divided by the gating gate; The trigger probability of a lidar within a certain time interval follows a Poisson distribution. The probability of a small interval being triggered for: Let be any small interval, where For lidar in The number of photoelectrons received in the interval theory The lidar is in front. The intervals were not triggered and in The probability that the interval is triggered; Therefore, it is only necessary to determine the number of photons received in each time interval. The probability of the lidar being triggered in each time interval is calculated based on the above formula. If the precise distance value of a certain pixel is The interval number where the initial photoelectron is located for: Then the lidar is in The trigger probability of an interval can be divided into the following three cases: (a) When the target is located in the interval ( When triggered before the interval, the probability of triggering is determined by background noise and dark current. The interval before the non-triggered and in Probability of interval triggering: (b) When the target is located in the interval ( When triggered in an interval, the probability of Gm-APD cell triggering is determined by background noise and dark count. The previous interval was not triggered, background noise, dark count, and target reflected photoelectrons. Probability of interval triggering: (c) When triggered after the target's location, the probability of a Gm-APD pixel triggering is determined by background noise, dark count, and the target's reflected photoelectrons. The previous interval was not triggered, background noise, and dark count were in Probability of interval triggering: 。 10. The method according to claim 8, characterized in that: In step seven, three-dimensional noise points for lidar are generated based on meteorological noise point clouds and lidar imaging noise point clouds. These noise points are then added to the simulated point cloud data to simulate the real lidar scanning process.

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