A longitudinal section extraction method based on radar point cloud

Abstract

The present invention discloses a longitudinal section extraction method based on radar point clouds, which relates to the technical field of radar point cloud data processing. The radar point cloud data is converted from a geometric coordinate system to a mileage-offset coordinate system. In the mileage-offset coordinate system, the converted point cloud data is sliced ​​according to a preset length and width. Slope change points are screened out in each slice area obtained according to terrain changes. The slope change point set is inversely converted from the mileage-offset coordinate system to a geometric coordinate system to obtain a longitudinal section point set in the geometric coordinate system. The present invention restores the slope change points from the mileage-offset coordinate system to the original geometric coordinate system. The reversibility and consistency of the data during the coordinate system conversion process are ensured, the spatial accuracy of the point set is retained, and it is convenient for direct application to road design software or GIS systems. 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 collaboration 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 longitudinal section extraction method based on radar point cloud. Background Art

[0002] Longitudinal section surveying involves measuring and setting the centerline or sideline of a route on-site based on the design route document. Based on the route mileage and terrain variations, the elevation data is collected point by point to form a longitudinal section. This longitudinal section data allows designers to obtain information such as ground elevation and slope, which is a key basis for road longitudinal slope design.

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

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

[0005] (2) Project the extracted measuring points onto the vertical plane of the ground in the direction of the line position;

[0006] (3) In the vertical plane projection, select the terrain slope change points according to the terrain changes, and connect the slope change points in sequence to obtain the cross section at this location.

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

[0008] Another method is to select points on the center line at a specified interval and connect them in sequence to form a longitudinal section, such as Figure 3 For points 7, 8, and 9, this method does not take into account the actual ground line undulations and cannot accurately reflect the slope change points such as slopes and bumps. Summary of the Invention

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

[0010] A longitudinal section extraction method based on radar point cloud includes the following steps:

[0011] Step 1: Convert the radar point cloud data from the geometric coordinate system to the mileage-offset coordinate system: Based on the straight-curve table of the designed route, convert the coordinates (X, Y) of each point in the point cloud into a mileage-offset coordinate system (S, D) with the mileage S as the horizontal axis and the offset D as the vertical axis. The designed route is represented as an east-west straight line in the mileage-offset coordinate system.

[0012] Step 2: Slice the converted point cloud data according to the preset length and width in the mileage-offset coordinate system;

[0013] Step 3: In each slice area obtained in step 2, the slope change points are selected according to the terrain changes;

[0014] Step 4: Inversely transform 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;

[0015] Step 5: Output the longitudinal section report in a format that includes mileage, north coordinate, east coordinate, offset and elevation information.

[0016] By adopting the above technical solution, point cloud data is converted from a geometric coordinate system to a mileage-offset coordinate system, making the designed route appear as a straight line in the coordinate system and simplifying subsequent data processing. This solves the problem of distortion of slope change points on curved sections caused by misaligned 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. Large-scale point cloud data is segmented into slices of data blocks with preset lengths and widths. This reduces the amount of data processed at a time, improving computational efficiency and memory utilization. It is particularly suitable for extracting longitudinal sections of long roads, avoiding system freezes or crashes caused by excessive data volume. Slope change points are dynamically identified within the slice area based on changes in terrain elevation. This accurately captures real terrain undulations (such as slopes and bumps), avoiding the flaw of traditional fixed-spacing sampling methods that ignore sudden terrain changes, and improving the authenticity and engineering reliability of longitudinal section data.

[0017] 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.

[0018] Providing a structured data output format simplifies the data analysis process for designers, supporting rapid decision-making and multi-system collaboration.

[0019] Optionally, 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;

[0020] 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.

[0021] 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.

[0022] 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.

[0023] By adopting the above technical solutions, conversion algorithms are designed for straight lines, transition curves, and circular curves. This adapts to complex road alignments, ensures coordinate conversion accuracy for the entire road section (including curved connecting sections), and avoids the cumulative error caused by a single algorithm.

[0024] Optionally, in the coordinate transformation of the transition curve segment, the bisection iterative process of the perpendicular foot point mileage includes:

[0025] Step a, setting the mileage increments corresponding to the start and end points 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 the midpoint and the target point;

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

[0028] In step d, the final midpoint mileage is used as the footpoint mileage, and the offset is calculated using the curvature radius formula.

[0029] By adopting this technical solution, we can quickly converge the footpoint mileage using the bisection method. While maintaining millimeter-level calculation accuracy, we can reduce the number of iterations by over 50%, significantly improving the processing efficiency of transition curve segments.

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

[0031] By adopting the above technical solution, we limit the slice width to 0.5-1 meter and the length to 50-100 meters. This balances the data block granularity, avoiding redundant calculations caused by too small slices and loss of terrain details caused by too large slices, thus optimizing resource allocation.

[0032] Optionally, in step 3, the method for screening the slope change points is: in the vertical plane projection, identifying the terrain slope change points according to the elevation change rate.

[0033] By adopting the above technical solutions, slope change points can be dynamically identified based on sudden changes in terrain, reducing manual intervention, enhancing automation capabilities, and avoiding missed or misdetected key terrain features.

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

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

[0036] For the transition curve segment, the geometric coordinates are calculated by combining Taylor expansion and tangent direction angle;

[0037] For circular curve segments, the geometric coordinates are calculated based on the relationship between the center angle and radius.

[0038] By adopting the above technical solutions, inverse transformation formulas are designed for different alignments. This ensures the mathematical rigor of coordinate restoration, avoids spatial deviations caused by differences in coordinate systems, and improves the engineering usability of the longitudinal section point set.

[0039] Optionally, 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.

[0040] A computer-readable storage medium stores a computer program. When the program is executed by a processor, a longitudinal section extraction method based on radar point cloud is implemented.

[0041] An electronic device includes a memory and a processor. The memory stores a computer program designed using a longitudinal section extraction method based on radar point clouds 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 longitudinal section extraction results.

[0042] Optionally, a display is further included, 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 longitudinal section extraction method based on radar point clouds, converting 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 method 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. Large-scale point cloud data is segmented into sheet-like data blocks of preset length and width. This reduces the amount of data processed at a single time, improving computational efficiency and memory utilization. It is particularly suitable for longitudinal section extraction of long-distance roads, avoiding system freezes or crashes caused by excessive data volume. Slope change points are dynamically identified within the slice area based on changes in terrain elevation. It accurately captures 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 and engineering reliability of longitudinal section data.

[0045] 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.

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

[0047] Figure 1 It is a schematic flow chart of a longitudinal section extraction method based on radar point cloud according to the present invention;

[0048] Figure 2 It is a schematic diagram of a traditional longitudinal section extraction method in the background technology of the present invention;

[0049] Figure 3 It is a schematic diagram of an improved longitudinal section extraction method in the background technology of the present invention;

[0050] Figure 4 is a schematic diagram of a point cloud and a road centerline diagram 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 This is a schematic diagram of linear coordinate conversion in a specific embodiment of the present invention;

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

[0054] Figure 81 is a schematic diagram of the mileage calculation process using the transition curve bisection method in a specific embodiment of the present invention;

[0055] Figure 9 2 is a schematic diagram of circular curve coordinate conversion in a specific embodiment of the present invention;

[0056] Figure 10 It is a schematic diagram of the point cloud slicing process in a specific embodiment of the present invention. DETAILED DESCRIPTION

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

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

[0059] Reference Figures 1-9 ,Example 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: Based on the straight-curve table of the designed route, convert the coordinates (X, Y) of each point in the point cloud into a mileage-offset coordinate system (S, D) with the mileage S as the horizontal axis and the offset D as the vertical axis. The designed route is represented as an east-west straight line in the mileage-offset coordinate system.

[0061] Step 2: Slice the converted point cloud data according to the preset length and width in the mileage-offset coordinate system;

[0062] Step 3: In each slice area obtained in step 2, the slope change points are selected according to the terrain changes;

[0063] Step 4: Inversely transform 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 the longitudinal section report in a format that 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 embodiment 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 for Length (positive on the left and negative on the right), that is:

[0100]

[0101]

[0102] Transition curve coordinate conversion:

[0103] Let point P be any point in the transition curve segment of the point cloud, and its coordinates in the geometric coordinate system XOY are ; Take the starting point of the transition curve as the origin and the tangent direction as the horizontal axis , the left hand direction of the vertical axis is the vertical axis , establish a coordinate system , the coordinates of point P are marked as , and the conversion relationship is as follows:

[0104]

[0105] Draw a perpendicular line through P to ease the curve, and the foot of the perpendicular is , then the mileage of point P That is Mileage, P point offset D P for Length (positive on the left and negative on the right), that is:

[0106]

[0107]

[0108] Where:

[0109] express The length of the transition curve.

[0110] The key steps above are mileage and coordinates , where the mileage and coordinates have the following relationship (taking the first quadrant as an example, expanding with 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 of the transition curve end point, and the relevant parameters can be obtained through the straight curve table; the variable l represents the mileage increment from the starting point.

[0113] Get the target point from the geometric relationship Can be used The length is minimized, and the binary method is used here to calculate Mileage, the process is as follows:

[0114] The starting point of the transition curve is Start, and the corresponding mileage increment is 0; the end point is End, and the corresponding mileage increment is ; Take the midpoint between Start and End as Mid, and the corresponding mileage increment is ;

[0115] Calculating Line Segments 、 length:

[0116]

[0117]

[0118] like , change Mid to the new Start point and delete the original Start point (such as Figure 7 ), take the midpoint between Start and End as Mid, corresponding to the mileage ;like , change Mid to the new End point and delete the original End point, take the midpoint between Start and End as Mid, corresponding to the mileage ;

[0119] Repeat the above steps, and the final Mid mileage increment is:

[0120]

[0121] Where n is the number of cycles, take l S The integer solution is ≤0.0005mm, which means the accuracy is better than 1mm.

[0122] at this time That is , substituting into equations (3.1.5)-(3.1.7) we can get the mileage of point P and offset .

[0123] Circular curve coordinate conversion:

[0124] Let point P be any point in the circular curve segment of the point cloud, and its coordinates in the geometric coordinate system XOY are ; Take the starting point of the circular curve as the origin and the tangent direction as the horizontal axis , the left hand direction of the vertical axis is the vertical axis , establish a coordinate system , the coordinates of point P are marked as , and the conversion relationship is as follows:

[0125]

[0126] The center of the circular curve is OY, and the central angle is , in the coordinate system Among them:

[0127]

[0128]

[0129]

[0130] The mileage increment of P is , the radius of the circular curve is R, then:

[0131]

[0132]

[0133] The length of P-OY is , then:

[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 divides the point cloud into slices, significantly improving data reading efficiency. Slice widths of 0.5-1m and lengths of 50-100m are typical.

[0137] Screening slope change points: Dynamically identify slope change points based on terrain elevation changes within the slice area;

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

[0139] This calculation process is the inverse of the above calculation process, and also needs to be calculated based on the three line shapes: straight line, transition curve, and circular curve.

[0140] Linear coordinate transformation:

[0141] First, by mileage , offset Calculate the coordinate system of point P Center coordinates:

[0142]

[0143]

[0144] The coordinates of point P are transformed 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 longitudinal section extraction method based on radar point cloud, characterized in that: The following steps are involved: Step 1: Convert the radar point cloud data from the geometric coordinate system to the mileage-offset coordinate system: Based on the straight-curve table of the designed route, convert the coordinates (X, Y) of each point in the point cloud into a mileage-offset coordinate system (S, D) with the mileage S as the horizontal axis and the offset D as the vertical axis. The designed route is represented as an east-west straight line in the mileage-offset coordinate system. Step 2: Slice the converted point cloud data according to the preset length and width in the mileage-offset coordinate system; Step 3: In each slice area obtained in step 2, the slope change points are selected according to the terrain changes; Step 4: Inversely transform 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; Step 5: Output the longitudinal section report in a format that includes mileage, northing coordinate, easting coordinate, offset, and elevation information; In step 1, coordinate conversion is performed according to the linear type of the designed line, which includes a straight line, a transition curve, and a circular curve; 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. 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. 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.

2. The method for extracting longitudinal sections based on radar point clouds according to claim 1, characterized in that: In the coordinate transformation of a transition curve segment, the bisection iterative process of the perpendicular foot point mileage includes: Step a, setting the mileage increments corresponding to the start and end points 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, and iterate until the preset accuracy is reached; In step d, the final midpoint mileage is used as the footpoint mileage, and the offset is calculated using the curvature radius formula.

3. The method for extracting longitudinal sections based on radar point clouds according to claim 1, wherein: In step 2, the slice width is 0.5-1m and the slice length is 50-100m.

4. The method for extracting longitudinal sections based on radar point clouds according to claim 3, characterized in that: In step 3, the method for screening slope change points is: in the vertical plane projection, the terrain slope change points are identified according to the elevation change rate.

5. The method for extracting longitudinal sections based on radar point clouds according to claim 4, characterized in that: The inverse conversion in step 4 includes the following methods: For straight line segments, the mileage-offset coordinates are restored to the geometric coordinate system through the coordinate rotation matrix; For the transition curve segment, the geometric coordinates are calculated by combining Taylor expansion and tangent direction angle; For circular curve segments, the geometric coordinates are calculated based on the relationship between the center angle and radius.

6. The method for extracting longitudinal sections based on radar point clouds according to claim 5, characterized in that: The report output format in step 5 is: mileage, north coordinate, east coordinate, offset, elevation, and is stored or displayed in table form.

7. A computer-readable storage medium, characterized in that A computer program is stored, and when the program is executed by a processor, a longitudinal section extraction method based on radar point cloud according to any one of claims 1 to 6 is implemented.

8. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program designed using a longitudinal section extraction method based on a radar point cloud according to any one of claims 1 to 6 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 a longitudinal section extraction result.

9. The electronic device according to claim 8, characterized in that: The system also includes a display, which is communicatively connected to the processor, and the processor controls the display to display the longitudinal section extraction result.

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