Longitudinal section extraction method based on radar point cloud

Abstract

The invention discloses a longitudinal section extraction method based on radar point cloud, and relates to the technical field of radar point cloud data processing, radar point cloud data is converted from a geometric coordinate system to a mileage-offset distance coordinate system, and under the mileage-offset distance coordinate system, the converted point cloud data is sliced according to preset length and width; slope change points are screened out in all the obtained slice areas according to topographic changes; inversely transforming the slope change point set from the mileage-offset distance coordinate system to the geometric coordinate system to obtain a longitudinal section point set under the geometric coordinate system; according to the method, the grade change point is restored to the original geometric coordinate system from the mileage-offset distance coordinate system. Reversibility and consistency of data in the coordinate system conversion process are ensured, the spatial accuracy of the point set is reserved, and the method can be directly applied to road design software or a GIS system conveniently. A standardized longitudinal section report is generated, a structured data output format is provided, the data analysis process of designers is simplified, and rapid decision making and multi-system cooperation are supported.

Description

Technical Field

[0001] The present invention relates to the technical field of radar point cloud data processing, and in particular to a method for extracting a longitudinal section based on radar point cloud. Background Art

[0002] Longitudinal section measurement refers to the work of setting the center line or side line of a line on the ground according to the design line file, and collecting the elevation of the line position point by point according to the line position mileage and terrain changes to form a longitudinal section. Through the longitudinal section data, designers can obtain information such as the elevation of ground points and slopes, which is one of the important bases for road longitudinal slope design.

[0003] The main steps of the cross-section extraction method are as follows:

[0004] (1) In the horizontal plane projection diagram of the point cloud, a rectangular area is divided based on the "distance from the point to the design section", and all measurement points within the rectangular area are extracted;

[0005] (2) The extracted measurement points are projected onto the vertical plane of the ground in the line position direction;

[0006] (3) In the vertical plane projection, terrain change points are selected according to terrain changes, and the change points are connected in sequence to obtain the cross-section here.

[0007] The road longitudinal section is the section formed by the change points at the road center line. When the line is straight, the method for extracting section points is the same as that of the cross-section, and the point cloud can be selected along the line direction and the change points can be selected; in actual situations, the route linearity also includes transition curves and circular curves. Taking Figure 2 as an example, when the line is a curve, the selected rectangular range cannot fit the line, and only by "increasing the selected width" or "decreasing the selected length" can the points in the selected range be made to fit the line as much as possible; if the selected width is too wide, the selected change points may deviate too far from the center line and be distorted; if the selected length is too long, the efficiency will be greatly reduced.

[0008] Another method is to take points at specified intervals on the road center line and connect them in sequence to form a longitudinal section. For example, Figure 3 points 7, 8, and 9 in , this method does not consider the undulation of the actual ground line and cannot accurately reflect the change points such as slopes and embankments. Summary of the Invention

[0009] In order to solve the technical problems of highway alignment evaluation in highway reconstruction and expansion projects, the present invention provides a method for extracting a longitudinal section based on radar point cloud. The following technical solution is adopted:

[0010] A method for extracting a longitudinal section based on radar point cloud, comprising the following steps:

[0011] Step 1, convert the radar point cloud data from the geometric coordinate system to the mileage-offset coordinate system: According to the straight and curve table of the designed line, convert the coordinates (X, Y) of each point in the point cloud to the mileage-offset coordinate system (S, D) with mileage S as the horizontal axis and offset D as the vertical axis, where the designed line appears as an east-west straight line in the mileage-offset coordinate system;

[0012] Step 2, under the mileage-offset coordinate system, slice the converted point cloud data according to the preset length and width;

[0013] Step 3, within each sliced area obtained in Step 2, screen out the grade change points respectively according to the terrain change;

[0014] Step 4, inversely convert the grade change point set from the mileage-offset coordinate system to the geometric coordinate system to obtain the longitudinal section point set in the geometric coordinate system;

[0015] Step 5, output the longitudinal section report, and the format includes mileage, north coordinate, east coordinate, offset and elevation information.

[0016] By adopting the above technical solution, the point cloud data is converted from the geometric coordinate system to the mileage-offset coordinate system, making the designed line appear as a straight line in the coordinate system, which simplifies the subsequent data processing. It solves the problem of grade change point distortion caused by the non-fitting of rectangular frame selection in the curved section, significantly improves the extraction accuracy and efficiency of the curved section (such as the transition curve and the circular curve), and reduces the need for manual adjustment of the frame selection range. The large-scale point cloud data is segmented into sheet-like data blocks with preset length and width. It reduces the amount of data processed at one time, improves the calculation efficiency and memory utilization rate, especially suitable for the longitudinal section extraction of long-distance roads, and avoids system freezing or crashing caused by excessive data volume. Dynamically identify the grade change points according to the terrain elevation change within the sliced area. Accurately capture the real terrain undulations (such as slopes, ridges, etc.), avoid the defect of ignoring terrain mutations in the traditional fixed-spacing sampling method, and improve the authenticity and engineering reliability of the longitudinal section data.

[0017] Restore the grade change points from the mileage-offset coordinate system to the original geometric coordinate system. Ensure the reversibility and consistency of the data during the coordinate system conversion, retain the spatial accuracy of the point set, and facilitate direct application to road design software or GIS systems. Generate a standardized longitudinal section report, including mileage, coordinates, offset and elevation information.

[0018] Provide a structured data output format, simplify the data analysis process of designers, and support rapid decision-making and multi-system collaboration.

[0019] Optionally, in Step 1, perform coordinate conversion according to the alignment type of the designed line, and the alignment type includes straight line, transition curve and circular curve;

[0020] For a straight-line segment, with the starting point as the origin, the end-point direction as the horizontal axis, and the vertical direction as the vertical axis, calculate the mileage and offset of a point through a coordinate rotation matrix;

[0021] For a transition curve segment, with the starting point as the origin and the tangent direction as the horizontal axis, calculate the mileage of the foot point through Taylor expansion and bisection iteration, and determine the offset in combination with the radius of curvature;

[0022] For a circular curve segment, with the starting point as the origin and the tangent direction as the horizontal axis, calculate the mileage and offset through the relationship between the central angle and the radius.

[0023] By adopting the above technical solution, conversion algorithms are designed respectively for straight lines, transition curves, and circular curves. It adapts to complex road alignments, ensures the coordinate conversion accuracy of the entire road section (including curve connection sections), and avoids cumulative errors caused by a single algorithm.

[0024] Optionally, in the coordinate conversion of the transition curve segment, the bisection iteration process of the mileage of the foot point includes:

[0025] Step a, set the mileage increment corresponding to the starting point and the end point of the transition curve as the initial interval;

[0026] Step b, calculate the coordinates corresponding to the midpoint of the current interval, and compare the distance between this midpoint and the target point;

[0027] Step c, adjust the interval range according to the distance size, and loop and iterate until the preset accuracy is reached;

[0028] Step d, use the final midpoint mileage as the mileage of the foot point, and calculate the offset in combination with the radius of curvature formula.

[0029] By adopting the above technical solution, the mileage of the foot point converges quickly through the bisection method. While ensuring millimeter-level calculation accuracy, the number of iterations is reduced by more than 50%, significantly improving the processing efficiency of the transition curve segment.

[0030] Optionally, in step 2, take the slice width as 0.5 - 1 m and the slice length as 50 - 100 m.

[0031] By adopting the above technical solution, the slice width is limited to 0.5 - 1 meter and the length is 50 - 100 meters. It balances the data chunking granularity, avoiding redundant calculations caused by too small slices and preventing the loss of terrain details due to too large slices, and optimizing resource allocation.

[0032] Optionally, in step 3, the method for screening the grade change points is: in the vertical plane projection, identify the terrain grade change points based on the elevation change rate.

[0033] By adopting the above technical solution, the grade change points are dynamically identified based on terrain mutations. It reduces manual intervention, enhances the automation ability, and avoids missing or misdetecting key terrain features.

[0034] Optionally, the inverse transformation in step 4 includes the following methods:

[0035] For straight line segments, restore the mileage-offset coordinates to the geometric coordinate system through a coordinate rotation matrix;

[0036] For transition curve segments, calculate the geometric coordinates by combining the Taylor expansion and the tangent direction angle;

[0037] For circular curve segments, calculate the geometric coordinates based on the relationship between the central angle and the radius.

[0038] By adopting the above technical solution, inverse transformation formulas are designed for different alignments. Ensure the mathematical rigor of coordinate restoration, avoid spatial deviations caused by coordinate system differences, and improve the engineering usability of the longitudinal section point set.

[0039] Optionally, the format of the report output in step 5 is: mileage, northing, easting, offset, elevation, and it is stored or displayed in tabular form.

[0040] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a longitudinal section extraction method based on radar point cloud.

[0041] An electronic device includes a memory and a processor. The memory stores a computer program designed by a longitudinal section extraction method based on radar point cloud and radar point cloud data to be processed. The processor is communicatively connected to the memory, inputs the radar point cloud data to be processed into the computer program, and runs the computer program to output the longitudinal section extraction result.

[0042] Optionally, it further includes a display, which is communicatively connected to the processor, and the processor controls the display to display the longitudinal section extraction result.

[0043] In summary, the present invention includes at least one of the following beneficial technical effects:

[0044] The present invention can provide a method for extracting vertical profiles based on radar point clouds, which converts the point cloud data from the geometric coordinate system to the mileage-offset coordinate system, making the designed line appear as a straight line in the coordinate system and simplifying subsequent data processing. It solves the problem of distorted breakpoints caused by non-fitting rectangular box selection in curved sections, significantly improves the extraction accuracy and efficiency of curved sections (such as transition curves and circular curves), and reduces the need for manual adjustment of the box selection range. It divides the large-scale point cloud data into sheet-like data blocks with preset length and width. Reduces the amount of data processed at one time, improves the computing efficiency and memory utilization rate, and is especially suitable for the extraction of vertical profiles of long-distance roads, avoiding system jams or crashes caused by excessive data volume. Dynamically identifies breakpoints within the sliced area based on terrain elevation changes. Accurately captures real terrain undulations (such as slopes and ridges), avoids the defect of ignoring terrain mutations in traditional fixed-spacing sampling methods, and improves the authenticity and engineering reliability of vertical profile data.

[0045] Restores the breakpoints from the mileage-offset coordinate system to the original geometric coordinate system. Ensures the reversibility and consistency of the data during the coordinate system conversion, retains the spatial accuracy of the point set, and is convenient for direct application to road design software or GIS systems. Generates a standardized vertical profile report, including mileage, coordinates, offset, and elevation information.

[0046] Provides a structured data output format, simplifies the data analysis process for designers, and supports rapid decision-making and multi-system collaboration. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is a schematic flow chart of a method for extracting vertical profiles based on radar point clouds according to the present invention;

[0048] Figure 2 is a schematic diagram of a traditional method for extracting vertical profiles in the background art of the present invention;

[0049] Figure 3 is a schematic diagram of an improved method for extracting vertical profiles in the background art of the present invention;

[0050] Figure 4 is a schematic diagram of point clouds and road centerlines in a specific embodiment of the present invention;

[0051] Figure 5 is a schematic diagram of a typical road centerline in a specific embodiment of the present invention;

[0052] Figure 6 is a schematic diagram of straight line coordinate conversion in a specific embodiment of the present invention;

[0053] Figure 7 is a schematic diagram of transition curve coordinate conversion in a specific embodiment of the present invention;

[0054] Figure 8Schematic diagram of the mileage calculation process of the easement curve dichotomy method in a specific embodiment of the present invention;

[0055] Figure 9 Schematic diagram of the coordinate transformation of the circular curve in a specific embodiment of the present invention;

[0056] Figure 10 Schematic diagram of the point cloud slicing process in a specific embodiment of the present invention. Detailed implementation manners

[0057] The present invention will be further described in detail below with reference to the accompanying drawings.

[0058] An embodiment of the present invention discloses a longitudinal section extraction method based on radar point cloud.

[0059] Refer to Figures 1-9 , Embodiment 1, a longitudinal section extraction method based on radar point cloud, comprising the following steps:

[0060] Step 1, convert the radar point cloud data from the geometric coordinate system to the mileage-offset coordinate system: According to the straight-curve table of the designed line, convert the coordinates (X, Y) of each point in the point cloud to the mileage-offset coordinate system (S, D) with mileage S as the horizontal axis and offset D as the vertical axis, where the designed line appears as an east-west straight line in the mileage-offset coordinate system;

[0061] Step 2, under the mileage-offset coordinate system, slice the converted point cloud data according to a preset length and width;

[0062] Step 3, in each sliced area obtained in Step 2, screen out the slope change points respectively according to the terrain change;

[0063] Step 4, inversely convert the slope change point set from the mileage-offset coordinate system to the geometric coordinate system to obtain the longitudinal section point set in the geometric coordinate system;

[0064] Step 5, output a longitudinal section report, and the format includes mileage, north coordinate, east coordinate, offset and elevation information.

[0065] Convert point cloud data from a geometric coordinate system to a mileage-offset coordinate system, so that the designed route appears as a straight line in the coordinate system, simplifying subsequent data processing. This solves the problem of distortion of slope change points on curved sections due to the mismatch of rectangular selections, significantly improving the extraction accuracy and efficiency of curved sections (such as transition curves and circular curves), and reducing the need for manual adjustment of the selection range. Split large-scale point cloud data into slice-like data blocks of preset length and width. This reduces the amount of data processed at a time, improves computing efficiency and memory utilization, and is particularly suitable for longitudinal section extraction of long-distance roads, avoiding system freezes or crashes caused by excessive data volume. Dynamically identify slope change points within the slice area based on terrain elevation changes. Accurately capture real terrain undulations (such as slopes and bumps), avoiding the defect of traditional fixed-spacing sampling methods that ignore sudden terrain changes, and improving the authenticity of longitudinal section data and engineering reliability.

[0066] Restores slope change points from a mileage-offset coordinate system to their original geometric coordinate system. This ensures data reversibility and consistency during the coordinate system conversion process, preserving the spatial accuracy of the point set for direct application in road design software or GIS systems. Generates standardized longitudinal section reports containing mileage, coordinates, offsets, and elevation information.

[0067] Providing a structured data output format simplifies the data analysis process for designers, supporting rapid decision-making and multi-system collaboration.

[0068] In embodiment 2, in step 1, coordinate conversion is performed according to the linear type of the designed line, where the linear type includes a straight line, a transition curve, and a circular curve;

[0069] For a straight line segment, the starting point is taken as the origin, the end point direction is the horizontal axis, and the vertical direction is the vertical axis. The mileage and offset of the point are calculated using the coordinate rotation matrix.

[0070] For the transition curve segment, the starting point is taken as the origin and the tangent direction is taken as the horizontal axis. The foot point mileage is calculated iteratively by Taylor expansion and bisection method, and the offset is determined by combining the curvature radius.

[0071] For a circular curve segment, the starting point is taken as the origin and the tangent direction is taken as the horizontal axis. The mileage and offset are calculated based on the relationship between the central angle and radius.

[0072] Conversion algorithms are designed for straight lines, transition curves, and circular curves. These algorithms adapt to complex road alignments, ensuring coordinate conversion accuracy for the entire road section (including curved connecting sections) and avoiding the cumulative error caused by a single algorithm.

[0073] In Example 3, in the coordinate transformation of the transition curve segment, the bisection iterative process of the perpendicular foot point mileage includes:

[0074] Step a, setting the mileage increments corresponding to the start and end points of the transition curve as the initial interval;

[0075] Step b, calculate the coordinates corresponding to the midpoint of the current interval and compare the distance between the midpoint and the target point;

[0076] Step c: adjust the interval range according to the distance, and iterate until the preset accuracy is reached;

[0077] In step d, the final midpoint mileage is used as the footpoint mileage, and the offset is calculated using the curvature radius formula.

[0078] The bisection method is used to quickly converge the footpoint mileage. While maintaining millimeter-level calculation accuracy, the number of iterations is reduced by more than 50%, significantly improving the processing efficiency of transition curve segments.

[0079] In Example 4, in step 2, the slice width is 0.5-1m and the slice length is 50-100m.

[0080] Limit the slice width to 0.5-1 meter and the length to 50-100 meters. Balance the data block granularity to avoid redundant calculations caused by too small slices and loss of terrain details caused by too large slices, thus optimizing resource allocation.

[0081] In Example 5, in step 3, the method for screening the slope change points is: in the vertical plane projection, the terrain slope change points are identified according to the elevation change rate.

[0082] Dynamically identify slope change points based on sudden terrain changes. Reduce manual intervention, enhance automation capabilities, and avoid missed or misdetected key terrain features.

[0083] In Example 6, the inverse conversion in step 4 includes the following method:

[0084] For straight line segments, the mileage-offset coordinates are restored to the geometric coordinate system through the coordinate rotation matrix;

[0085] For the transition curve segment, the geometric coordinates are calculated by combining Taylor expansion and tangent direction angle;

[0086] For circular curve segments, the geometric coordinates are calculated based on the relationship between the center angle and radius.

[0087] Design inverse transformation formulas for different alignments to ensure the mathematical rigor of coordinate restoration, avoid spatial deviations caused by coordinate system differences, and improve the engineering usability of longitudinal section point sets.

[0088] In Example 7, the report output in step 5 is in the format of mileage, northing coordinate, easting coordinate, offset, and elevation, and is stored or displayed in a table format.

[0089] Example 8, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements a longitudinal section extraction method based on radar point cloud.

[0090] Example 9, an electronic device, including a memory and a processor, wherein the memory stores a computer program designed using a longitudinal section extraction method based on radar point cloud and radar point cloud data to be processed, and the processor is communicatively connected to the memory, inputs the radar point cloud data to be processed into the computer program, and runs the computer program to output the longitudinal section extraction result.

[0091] Example 10 further includes a display, which is communicatively connected to the processor, and the processor controls the display to display the longitudinal section extraction results.

[0092] The following specific embodiments are used to illustrate the implementation principle of the present invention:

[0093] Convert point cloud coordinates from the geometric coordinate system to the odometry-offset coordinate system.

[0094] The road centerline in the geometric coordinate system consists of three basic line shapes, namely straight line, transition curve and circular curve. Figure 4 For example, the common road linear connection is "straight line - transition curve - circular curve - transition curve - straight line". The basic linear connection points are also called nodes ( Figure 4 In ZH, HY, YH, HZ), the curves on both sides of the node have the same azimuth and curvature radius. The coordinates, mileage, azimuth and other curve elements of each point can be obtained through the straight-curve table of the designed route. For the convenience of description, the straight-slow point ZH is taken as an example. Indicates its mileage, Indicates the offset, Indicates azimuth, 、 They represent the north coordinate and east coordinate in the geometric coordinate system respectively.

[0095] The following describes the coordinate transformation methods for three types of lines: straight lines, transition curves, and circular curves.

[0096] Linear coordinate transformation:

[0097] Let point P be any point in the line segment of the point cloud, and its coordinates in the geometric coordinate system XOY are ; The starting point of the straight line is the origin and the end point is the horizontal axis , the left hand direction of the vertical axis is the vertical axis , establish a coordinate system , point P in the coordinate system The middle mark is , and the conversion relationship is as follows:

[0098]

[0099] Do it through P The perpendicular line to the axis, with the foot of the perpendicular being , then the mileage of point P That is Mileage, offset is Length (positive to the left and negative to the right), that is:

[0100]

[0101]

[0102] Coordinate transformation of the transition curve:

[0103] Let point P be any point on the transition curve segment of the point cloud, and its coordinates in the geometric coordinate system X-O-Y are ; with the starting point of the transition curve as the origin and the tangent direction as the horizontal axis , and the left-hand direction perpendicular to the horizontal axis as the vertical axis , establish a coordinate system , and the coordinates of point P are denoted as , and its transformation relationship is as follows:

[0104]

[0105] Draw a perpendicular line from P to the transition curve, and the foot of the perpendicular is , then the mileage of point P is mileage, and the offset D of point P P is length (positive to the left and negative to the right), that is:

[0106]

[0107]

[0108] In the formula:

[0109] represents the length of the transition curve segment.

[0110] The key steps above lie in mileage and coordinates calculation. Among them, there is the following relationship between mileage and coordinates (taking the first quadrant as an example, expanded by Taylor's formula, accurate to 15 terms):

[0111]

[0112] In the formula represents the total length of the transition curve, R represents the curvature radius at the end of the transition curve, and relevant parameters can be obtained from the straight and curve table; the variable l represents the mileage increment from the starting point.

[0113] From the geometric relationship, the target point can make The length reaches the minimum value, and the bisection method is used here for calculation. The mileage is as follows:

[0114] Denote the starting point of the transition curve as Start, and the corresponding mileage increment as 0; the ending point as End, and the corresponding mileage increment as ; Take the midpoint of Start and End and denote it as Mid, and the corresponding mileage increment as ;

[0115] Calculate the lengths of line segments , :

[0116]

[0117]

[0118] If , change Mid to the new Start point and delete the original Start point (as Figure 7 ), take the midpoint of Start and End and denote it as Mid, and the corresponding mileage ; If , change Mid to the new End point and delete the original End point, take the midpoint of Start and End and denote it as Mid, and the corresponding mileage ;

[0119] Loop the above steps. Finally, the mileage increment of Mid is:

[0120]

[0121] In the formula, n is the number of loops, take the integer solution when l S ≤0.0005mm, that is, the accuracy is better than 1mm.

[0122] At this time is , substitute it into formulas (3.1.5)-(3.1.7) to obtain the mileage of point P and the offset .

[0123] Coordinate transformation of the circular curve:

[0124] Let point P be any point on the circular curve segment of the point cloud, and its coordinates in the geometric coordinate system X-O-Y are ; Take the starting point of the circular curve as the origin, the tangent direction as the horizontal axis , and the left-hand direction perpendicular to the horizontal axis as the vertical axis , establish a coordinate system , and denote the coordinates of point P as , and its transformation relationship is as follows:

[0125]

[0126] Let the center of the circular curve be OY and the central angle be , in the coordinate system there are:

[0127]

[0128]

[0129]

[0130] Let the mileage increment of P be , and the radius of the circular curve be R, then there are:

[0131]

[0132]

[0133] Let the length of P - OY be , then there are:

[0134]

[0135] Point cloud slicing, see Figure 10 :

[0136] Set the length and width of the pre - processed point cloud in the mileage - offset coordinate system, and slice the point cloud. This step batches the point cloud into slices, which can greatly improve the data reading efficiency. Generally, the slice width is taken as 0.5 - 1m, and the slice length is 50 - 100m.

[0137] Screen the slope - change points: Dynamically identify the slope - change points according to the terrain elevation change within the sliced area;

[0138] Convert the set of slope - change points from the mileage - offset coordinate system to the geometric coordinate system:

[0139] This calculation process is the inverse operation of the above - mentioned calculation process, and also needs to be calculated separately according to the three line types of straight line, transition curve, and circular curve.

[0140] Straight - line coordinate conversion:

[0141] First, calculate the coordinates of point P in the coordinate system from the mileage and the offset :

[0142]

[0143]

[0144] Convert the coordinates of point P from the coordinate system Transform to the geometric coordinate system:

[0145]

[0146] Transition curve coordinate conversion:

[0147] First, according to mileage calculate Point in coordinate system Central coordinates (taking the first quadrant as an example):

[0148]

[0149] Where:

[0150] Calculate the coordinate system of point P Center coordinates:

[0151] remember , , according to formula (3.1.21):

[0152]

[0153]

[0154]

[0155]

[0156]

[0157] Circular curve coordinate conversion:

[0158] First, by mileage , offset Calculate the coordinate system of point P Lower coordinates:

[0159] The central angle corresponding to point P:

[0160]

[0161]

[0162]

[0163] The coordinates of point P are changed from Coordinate system conversion to geometric coordinate system:

[0164]

[0165] Output report:

[0166] Output the slope change points in the longitudinal section format. The format is "mileage, northing coordinate, easting coordinate, offset, elevation" as shown in Table 1:

[0167] Table 1 Longitudinal section report format example

[0168]

[0169] The above are all preferred embodiments of the present invention, and are not intended to limit the scope of protection of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for extracting a longitudinal section based on radar point cloud, characterized in that, It includes the following steps: Step 1, convert the radar point cloud data from the geometric coordinate system to the mileage-offset coordinate system: According to the straight and curved table of the designed line, convert the coordinates (X, Y) of each point in the point cloud to the mileage-offset coordinate system (S, D) with mileage S as the horizontal axis and offset D as the vertical axis, where the designed line appears as a straight line in the east-west direction in the mileage-offset coordinate system; Step 2, under the mileage-offset coordinate system, slice the converted point cloud data according to the preset length and width; Step 3, within each sliced area obtained in Step 2, screen out the slope change points respectively according to the terrain change; Step 4, inversely convert the set of slope change points from the mileage-offset coordinate system to the geometric coordinate system to obtain the set of longitudinal section points in the geometric coordinate system; Step 5, output the longitudinal section report, and the format includes mileage, north coordinate, east coordinate, offset and elevation information.

2. The method for extracting a longitudinal section based on radar point cloud according to claim 1, wherein: In Step 1, the coordinate conversion is carried out according to the linear type of the designed line, and the linear type includes straight line, transition curve and circular curve; For the straight line segment, with the starting point as the origin, the ending point direction as the horizontal axis, and the vertical direction as the vertical axis, calculate the mileage and offset of the point through the coordinate rotation matrix; For the transition curve segment, with the starting point as the origin and the tangent direction as the horizontal axis, calculate the mileage of the foot point through the Taylor expansion formula and the bisection method iteration, and determine the offset in combination with the radius of curvature; For the circular curve segment, with the starting point as the origin and the tangent direction as the horizontal axis, calculate the mileage and offset through the relationship between the central angle and the radius.

3. A method for extracting a longitudinal section based on radar point cloud according to claim 1, characterized in that, In the coordinate conversion of the transition curve segment, the bisection method iteration process of the mileage of the foot point includes: Step a, set the mileage increment corresponding to the starting point and the ending point of the transition curve as the initial interval; Step b, calculate the coordinates corresponding to the midpoint of the current interval, and compare the distance between the midpoint and the target point; Step c, adjust the interval range according to the distance size, and loop and iterate until the preset accuracy is reached; Step d, take the final midpoint mileage as the mileage of the foot point, and calculate the offset in combination with the radius of curvature formula.

4. A method for extracting a longitudinal section based on radar point cloud according to claim 1, characterized in that: In Step 2, the slice width is taken as 0.5 - 1m, and the slice length is taken as 50 - 100m.

5. A method for extracting a longitudinal section based on radar point cloud according to claim 4, characterized in that: In Step 3, the method for screening the slope change points is: in the vertical plane projection, identify the terrain slope change points according to the elevation change rate.

6. The method for extracting a longitudinal section based on radar point cloud according to claim 5, characterized in that: The inverse conversion in Step 4 includes the following methods: For the straight line segment, restore the mileage-offset coordinates to the geometric coordinate system through the coordinate rotation matrix; For the transition curve segment, calculate the geometric coordinates in combination with the Taylor expansion formula and the tangent direction angle; For the circular curve segment, calculate the geometric coordinates through the relationship between the central angle and the radius.

7. A method for extracting a longitudinal section based on radar point cloud according to claim 6, characterized in that: The format of the report output in Step 5 is: mileage, north coordinate, east coordinate, offset, elevation, and it is stored or displayed in tabular form.

8. A computer-readable storage medium, characterized in that, There is a computer program stored, and when the program is executed by a processor, it realizes a method for extracting the longitudinal section based on radar point cloud as described in any one of claims 1 - 7.

9. An electronic device, characterized in that, It includes a memory and a processor. The memory stores a computer program designed by using a method for extracting the longitudinal section based on radar point cloud as described in any one of claims 1 - 7 and the radar point cloud data to be processed. The processor is communicatively connected to the memory, inputs the radar point cloud data to be processed into the computer program, and runs the computer program to output the longitudinal section extraction result.

10. An electronic device according to claim 9, characterized in that: It further includes a display, which is communicatively connected to the processor, and the processor controls the display to show the longitudinal section extraction result.

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