A radar detection capability calculation method and system

Abstract

The present disclosure relates to a radar detection capability calculation method and system, the method comprising: S100: acquiring a line-of-sight detection parameter, calculating a minimum effective detection distance of a radar and initializing a radar cone of vision ellipse equation; S200: acquiring a trajectory line and initializing a device limit field of view parameter; S300: sequentially selecting a radar stay point from the trajectory line; S400: performing coordinate system transformation with the radar stay point as a 3D space origin, two-dimensional projection and updating a device limit boundary slope; S500: sequentially selecting a to-be-scanned point, performing line-of-sight detection on the to-be-scanned point to obtain a line-of-sight detection result; S600: if the line-of-sight detection result completely meets a preset line-of-sight detection condition, returning to S500; otherwise, continuing to S700; S700: if the radar stay point is the last trajectory point in the trajectory line, then the line-of-sight detection result is summarized as a final detection result, and S800 is continued; otherwise, returning to S300; and S800: outputting the final detection result.

Description

Technical Field

[0001] This disclosure relates to the field of rail transit, specifically to a method and system for calculating radar detection capabilities. This disclosure can be applied to the calculation of the detection capabilities of vehicle-mounted lidar, thereby assisting in radar detection capability assessment, obstacle detection, and other tasks. Background Technology

[0002] Currently, vehicle-mounted LiDAR is mainly used in autonomous driving and robotic tracking scenarios, with its application in rail transit just beginning. In rail transit, vehicle-mounted LiDAR, often simply referred to as "radar," plays a crucial role in obstacle detection. Unlike its auxiliary role in autonomous driving, rail transit demands higher requirements for system perception and safety, needing to meet the industry's highest safety level (SIL4). This places stringent requirements on the availability, consistency, and verifiable performance indicators of detection equipment. For example, radar-based obstacle detection systems require clearly defined performance boundaries for each system function. The maximum radar detection capability (also known as "line of sight") at each location on the train is a critical performance indicator for ensuring the safe operation of rail transit.

[0003] Assessing the radar's detection capability boundary in tunnel sections is an important safety parameter. Traditional methods determine the radar's detection range at each location in the tunnel through on-site measurements or tests. However, this approach is not only time-consuming and labor-intensive, but also makes it difficult to standardize measurement criteria across all scenarios. It also places high demands on the measurement personnel. Furthermore, the detection range often fluctuates due to trackside equipment during the measurement process, requiring extensive manual verification and correction.

[0004] Existing research and engineering practices mainly focus on LiDAR-based train mapping and localization (SLAM), obstacle detection, and track environment perception. For example, Dias S. et al. proposed a localization framework combining LiDAR and GPS in 2004 for track obstacle detection, incorporating track terrain parameters. Stein D. et al., in their paper "Rail Detection Using LiDAR Sensors," explored the application of LiDAR to onboard localization and track identification, focusing on the detection and identification of tracks, sleepers, and supporting structures. However, existing technical solutions often concentrate on the levels of "whether there is an obstacle," "track geometry recognition," and "point cloud or image recognition," rather than specifically addressing parameters such as "maximum effective radar detection range," "maximum radar detection capability," "continuous measurement along the entire line," and "quantification of obstruction degree," lacking an effective assessment of radar detection capabilities and robustness.

[0005] Current radar detection capability assessment methods are mainly based on on-site measurements. However, on-site measurement methods are difficult to apply in large-scale engineering projects and have many shortcomings: First, they require a large amount of manpower for on-site measurements, which is time-consuming and labor-intensive and cannot achieve 100% coverage of the entire line, requiring segmented testing. Second, in scenarios with complex track terrain and abundant trackside equipment, measurement results are prone to jumps or discontinuities, seriously affecting train control efficiency and requiring a significant increase in manual verification, retesting, and parameter optimization. Third, it is difficult to establish unified measurement standards for different track environments, requiring judgment based on human experience or heuristic rules. For example, it is necessary to manually assess the degree of obstruction required to determine whether the radar lacks obstacle detection capability, which is obviously very difficult. Therefore, for safety reasons, radar is directly considered to lack detection capability as long as obstruction occurs in the radar detection area, but this also leads to a significant decrease in the availability of the sensing system. Summary of the Invention

[0006] To address the problems existing in the prior art, this disclosure proposes a radar detection capability calculation method and system to solve at least one technical problem mentioned in the background art. The technical solution adopted in this disclosure is as follows: In a first aspect, this disclosure provides a method for calculating radar detection capability, the method comprising: Step S100: Obtain the line-of-sight detection parameters, calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters, and initialize the radar line-of-sight cone ellipse equation based on the minimum effective detection range of the radar. Step S200: Obtain sequentially arranged trajectory lines without data jumps using radar, and initialize device boundary field of view parameters based on the trajectory lines; the trajectory lines include several trajectory points; the device boundary field of view parameters include iteration start point, iteration end point, and device boundary boundary slope, etc., the iteration start point is the first trajectory point, the iteration end point is the last trajectory point, and the device boundary boundary slope is used to identify the radar's frontal view direction; Step S300: Select a trajectory point from the trajectory line in sequence as the radar dwell point. The radar dwell point is used to identify the current position of the radar (which is also the current position of the train). Step S400: Using the radar stopping point as the origin in the 3D space, perform coordinate system transformation on each of the subsequent trajectory points, and then convert the 3D space into a two-dimensional projection in the radar's frontal view based on the perspective after coordinate transformation, and update the slope of the device boundary based on the two-dimensional projection. Step S500: Select one of the subsequent trajectory points in sequence as the point to be scanned. The radar, located at the radar dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results. The line-of-sight detection results include the corresponding radar dwell point, the point to be scanned, the radar line-of-sight distance, the percentage of visibility of the safety clearance, and the percentage of visibility of the radar cone, etc. Step S600: If the line-of-sight detection result fully meets the preset line-of-sight detection conditions, it means that the radar has not yet reached the maximum line-of-sight at the radar dwell point, and the subsequent trajectory points should continue to be scanned. Therefore, return to step S500. Otherwise, it indicates that the radar has reached its maximum line of sight at the radar dwell point, and the radar cannot obtain reliable data by continuing to scan the subsequent trajectory points. Therefore, the line of sight detection of the subsequent trajectory points at the radar dwell point should be terminated, and step S700 should continue to be executed. Step S700: If the radar dwell point is the iteration endpoint, it means that the radar has completed line-of-sight detection of the trajectory line. Then, all the line-of-sight detection results are summarized into the final detection result, and step S800 is executed. Otherwise, return to step S300. Step S800: Output the final detection result.

[0007] Preferably, in step S100, the line-of-sight detection parameters include the length, width and height of the equipment clearance, the length, width and height of the safety clearance, the train's running direction, the radar field of view, as well as the radar's farthest detection distance, the minimum train visibility threshold and the maximum train visibility threshold, etc. Preferably, in step S100, the radar sight cone ellipse equation is used to represent the radar field of view.

[0008] Preferably, in step S100, the line-of-sight detection parameters can exist in the form of a parameter configuration file, which can be directly loaded and obtained during implementation.

[0009] Preferably, step S400 includes the following steps: Step S410: Using the radar stationary point as the origin in the 3D space, perform coordinate system transformation on all trajectory points in the 3D space based on the pose information of the radar stationary point; Step S420: Calculate the spatial rotation angle of the radar dwell point relative to the radar; Step S430: Based on the spatial rotation angle, convert the 3D space into a two-dimensional projection in the radar's frontal view direction; Step S440: Calculate the slope values ​​between the radar dwell point and each subsequent trajectory point on the two-dimensional projection, and use the slope value closest to the radar central axis to update the slope of the equipment boundary.

[0010] Preferably, step S440 includes the following steps: Step S441: Select one of the subsequent trajectory points from the radar dwell point as the trajectory point to be calculated in sequence; Step S442: Use the slope value between the calculated trajectory point and the trajectory point to be calculated as a temporary slope value; Step S443: If the temporary slope value is closer to the radar center axis than the slope of the equipment clearance boundary, then update the slope of the equipment clearance boundary with the temporary slope value; otherwise, ignore the temporary slope value and return to step S441.

[0011] Steps S441 to S443 update the equipment clearance boundary slope in the equipment clearance field of view parameters. This involves assigning the slope value closest to the radar's central axis among all slope values ​​between the radar dwell point and all subsequent trajectory points to update the equipment clearance boundary slope. The slope value closest to the radar's central axis is the equipment clearance boundary slope of the radar at the radar dwell point.

[0012] Preferably, in step S600, the preset line-of-sight detection conditions include: a) The radar line-of-sight distance of the trajectory point is less than or equal to the radar's furthest detection distance; b) The train visibility threshold corresponding to the radar line-of-sight distance on the preset train visibility threshold curve, where the safety clearance visibility percentage is ≥ 0.5%.

[0013] Preferably, in step S600, the preset line-of-sight detection condition further includes: c) The slopes of the equipment clearance boundaries corresponding to the trajectory points do not intersect vertically or horizontally. Condition c) can be used as an additional enhanced judgment condition to help determine whether the radar has reached its maximum line-of-sight at the radar dwell point.

[0014] A second aspect of this disclosure provides a radar detection capability calculation system, the system comprising: An initialization module is used to acquire line-of-sight detection parameters, calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters, and initialize the radar line-of-sight cone ellipse equation based on the minimum effective detection range of the radar. The detection preparation module is used to acquire sequentially arranged trajectory lines without data jumps through radar, and to initialize the device boundary field of view parameters based on the trajectory lines; the trajectory lines include several trajectory points; the device boundary field of view parameters include the iteration start point, the iteration end point, and the device boundary boundary slope, etc., the iteration start point is the first trajectory point, the iteration end point is the last trajectory point, and the device boundary boundary slope is used to identify the radar's frontal view direction; The stop point selection module is used to select a trajectory point from the trajectory line in sequence as the radar stop point. The radar stop point is used to identify the current position of the radar (which is also the current position of the train). The parameter update module is used to perform coordinate system transformation on each of the subsequent trajectory points with the radar stationary point as the origin in the 3D space, and then convert the 3D space into a two-dimensional projection in the radar's frontal view based on the perspective after coordinate transformation, and update the slope of the equipment boundary based on the two-dimensional projection. The scanning and detection module is used to sequentially select one of the subsequent trajectory points as the point to be scanned. The radar, located at the radar dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results. The line-of-sight detection results include the corresponding radar dwell point, the point to be scanned, the radar line-of-sight distance, the percentage of visibility of the safety clearance, and the percentage of visibility of the radar cone. The maximum line-of-sight determination module is used to determine that if the line-of-sight detection result fully meets the preset line-of-sight detection conditions, it means that the radar has not yet reached the maximum line-of-sight at the radar dwell point, and should continue to scan the subsequent trajectory points. Therefore, it returns to the execution scanning detection module. Otherwise, it indicates that the radar has reached its maximum line of sight at the radar dwell point, and the radar cannot obtain reliable data by continuing to scan the subsequent trajectory points. Therefore, the line of sight detection of the subsequent trajectory points at the radar dwell point should be terminated, and the traversal judgment module should continue to be executed. The traversal determination module is used to summarize all the line-of-sight detection results into the final detection result if the radar dwell point is the end point of the iteration, indicating that the radar has completed the line-of-sight detection of the trajectory line, and continue to execute the final result output module; otherwise, it returns to the dwell point selection module.

[0015] Preferably, the system further includes a final result output module for outputting the final detection result.

[0016] In a third aspect, this disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the radar detection capability calculation method described above.

[0017] In a fourth aspect, this disclosure provides an electronic device including a processor and a memory, the processor being configured to execute a computer program stored in the memory to implement the radar detection capability calculation method described above.

[0018] The beneficial effects of this disclosure are as follows: This disclosure proposes a method and system for calculating radar detection capability, which enables a more automated method for evaluating radar detection capability, reduces labor costs, and decreases reliance on human experience, thus meeting the requirements of engineering applications. This invention focuses on the problem of calculating radar detection capability in rail transit obstacle detection applications. It only requires a train equipped with radar to travel at low speed along the entire line once, and the use of the SLAM algorithm to construct a point cloud map and trajectory line. Then, based on the trajectory line and line parameters, the maximum detection distance at each location on the line can be calculated. Through this disclosure, the maximum line-of-sight distance achievable by the radar at each trajectory point can be accurately obtained, and the line-of-sight detection results obtained by the radar scanning other subsequent trajectory points at each trajectory point can be summarized, making obstacle detection and analysis in rail transit more convenient.

[0019] Compared to traditional on-site measurement methods, this disclosure fully considers the impact of changes in road terrain on radar field of view, and can accurately calculate the percentage of radar detection area obstructed by curves, slope changes, etc., making the calculated maximum radar detection distance smoother and more reliable. Since the percentage of obstruction changes continuously, the maximum radar detection distance calculated by this disclosure is also very smooth, solving the distance jump problem of manual measurement methods.

[0020] Based on the physical attenuation law of light in air, this disclosure also constructs a mathematical model of laser attenuation and fits a more reasonable percentage threshold curve, thereby optimizing and adapting the occlusion threshold, reducing the blindness of manually setting the occlusion threshold and the conservatism of radar detection capability calculation results, and improving the reliability and adaptability of this disclosure.

[0021] When this method is implemented, the radar's maximum detection range parameters at all locations along the entire line can be obtained with just one low-speed data acquisition along the entire line, which has many advantages over manual measurement methods: (1) This disclosure significantly reduces labor costs while achieving 100% coverage across the entire industry.

[0022] (2). This disclosure can accurately calculate the percentage of radar detection area obstructed by changes in the terrain and equipment clearance, so that the radar detection capability calculation results have excellent characteristics of continuity and smoothness.

[0023] (3). This disclosure constructs a mathematical model of laser attenuation based on the physical attenuation law of light in air, automatically adapts the occlusion threshold, reduces the dependence on human experience, and improves system availability. Attached Figure Description

[0024] The accompanying drawings, which form part of this application, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0025] Figure 1 This is a flowchart of a radar detection capability calculation method provided in Embodiment 1 of this disclosure.

[0026] Figure 2 This is a schematic diagram of the line-of-sight detection parameters described in Embodiment 1 of this disclosure.

[0027] Figure 3 This is a schematic diagram of the radar sight cone described in Embodiment 1 of this disclosure.

[0028] Figure 4 This is an example diagram of the radar trajectory line and radar coordinate system described in Embodiment 1 of this disclosure.

[0029] Figure 5 This is an example diagram illustrating the conversion of the 3D space described in Embodiment 1 of this disclosure into a two-dimensional projection in the radar's frontal view direction.

[0030] Figure 6 This is a schematic diagram illustrating the principle of converting the 3D space into the two-dimensional projection as described in Embodiment 1 of this disclosure.

[0031] Figure 7 This is an example diagram illustrating the distance along the orbital arc, the straight-line distance, and the axial distance involved in calculating radar line-of-sight distance using existing technologies.

[0032] Figure 8 This is a schematic diagram showing the obstruction of the rear radar (train) by the equipment clearance described in Embodiment 1 of this disclosure.

[0033] Figure 9 This is an example diagram showing the visible area of ​​the safety clearance described in Embodiment 1 of this disclosure.

[0034] Figure 10 This is a schematic diagram illustrating the impact of a curve on radar field of view as described in Embodiment 1 of this disclosure; the dashed line represents the tangent direction between the train's current position and the track, the solid line represents the track, and the arrow icon on the solid line represents the train.

[0035] Figure 11 This is a schematic diagram illustrating the calculation of the radar sight cone visibility percentage as described in Embodiment 1 of this disclosure.

[0036] Figure 12 This is an example diagram of the preset train visibility threshold curve described in Embodiment 1 of this disclosure.

[0037] Figure 13 This is an example diagram of the viewing distance file described in Embodiment 1 of this disclosure.

[0038] Figure 14 This is an architecture diagram of a radar detection capability calculation system as described in Embodiment 2 of this disclosure. Detailed Implementation

[0039] The present disclosure will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the present application can be combined with each other.

[0040] The following detailed descriptions are exemplary and intended to provide further detailed explanation of this disclosure. Unless otherwise specified, all technical terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure.

[0041] Currently, radar is mainly used in autonomous driving and robotic tracking scenarios, and its application in rail transit is just beginning. A crucial role of radar in rail transit is obstacle detection. Unlike its auxiliary role in autonomous driving, rail transit has much higher system safety requirements (SIL4 level), making the assessment of radar's detection capability boundaries in tunnel sections a critical safety parameter. Traditional methods determine the radar's detection range at each location in the tunnel through on-site measurements or tests. However, this approach is not only time-consuming and labor-intensive, but also struggles to standardize measurement criteria across all scenarios, places high demands on measurement personnel, and often results in jumps in detection range due to trackside equipment, requiring extensive manual verification and correction.

[0042] The detection performance of a detection system at a certain location on the track refers to the farthest distance at which the radar can reliably detect an obstacle at the current location, also known as the "farthest line-of-sight" or "line-of-sight range." In the engineering application of rail transit detection systems, "obstacles" here specifically refer to trains. In rail transit, especially in tunnel sections, a large number of devices need to be installed, and the locations of curves and junctions are even more complex, causing the radar's detection range to be frequently obstructed by tunnel walls or track equipment, thus reducing the radar's train detection performance. Existing methods cannot determine to what extent the radar's detection range is obstructed before it loses its ability to detect trains. Therefore, for safety reasons, if the radar's detection area is obstructed, it is directly assumed that the radar has no detection capability. However, this also leads to a significant decrease in the availability of the detection system.

[0043] To improve the availability of the detection system, two major challenges in existing technologies must be addressed: first, calculating the percentage of radar's effective detection range that is obstructed (i.e., the obstruction percentage); and second, determining the level of obstruction (i.e., the obstruction threshold) that would cause the radar to lose its ability to stably detect trains. It is important to note that the obstruction threshold is not constant, as radar detection capability inherently decreases with distance. Therefore, the radar's detection capability at 200m will inevitably be inferior to its detection capability at 100m. Thus, the obstruction threshold should be a distance-mapping function. Example 1: like Figure 1 As shown, Embodiment 1 of this disclosure provides a method for calculating radar detection capability, the method including steps S100 to S800.

[0044] Step S100: Obtain the line-of-sight detection parameters, calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters, and initialize the radar line-of-sight cone ellipse equation based on the minimum effective detection range of the radar.

[0045] Furthermore, step S100 can be further subdivided into steps S110 to S130.

[0046] Step S110: Obtain line-of-sight detection parameters, including the length, width and height of the equipment clearance, the length, width and height of the safety clearance, the train's running direction, the radar field of view, the radar's farthest detection distance, the minimum train visibility threshold, and the maximum train visibility threshold.

[0047] Considering the varying conditions of different lines and radar parameters, to improve the adaptability of the method, specific line-of-sight detection parameters can be designed as parameter configuration files. During implementation, these configuration files are directly loaded to obtain the line-of-sight detection parameters. The parameter configuration files can be configured as follows: Figure 2 As shown. It should be noted that... Figure 2 This is just an example illustration and does not limit the specific design method and format of line-of-sight detection parameters.

[0048] Step S120: Calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters.

[0049] Because the field of view of radar on the market is usually cone-shaped, the field of view of radar is simply referred to as the "radar field of view cone". For example... Figure 3 As shown, the longitudinal section of the radar's field of view is an ellipse, which is the range that the radar can see—that is, the radar's field of view, and this ellipse gradually increases in size as the radar's detection range extends.

[0050] Figure 3 middle, This is the radar's longitudinal elevation view. Let denot be the extended distance in the radar's line-of-sight direction, and let the ellipse be the radar's field of view at the distance. The rectangle represents the longitudinal section of the safety clearance. When the rectangle (the longitudinal section of the safety clearance) is inscribed within the ellipse (the longitudinal section of the radar's field of view cone), the radar's field of view completely encompasses the safety clearance. Therefore, the radar can perfectly see the entire safety clearance, and the extended range is [limited / limited]. Equal to the minimum effective detection range of radar When the extended distance Less than At that time, the ellipse cannot cover the entire rectangle, causing the radar to be unable to see the complete safety clearance, therefore it is smaller than... The extended range of this area is called the radar blind zone. The minimum effective detection range of a radar. The technical meaning of is to serve as a distance threshold for measuring whether radar can see the complete safety clearance; when the extended distance d < At that time, the radar cannot see the complete safety clearance; when the extended distance d≥ Only then can the radar see the complete safety clearance. Based on spatial relationships, the minimum effective detection range of the radar can be deduced. Satisfy the following formula: ; in, This is the minimum effective detection range of the radar. The length of the longitudinal semi-axis of the ellipse. The horizontal axis is... The vertical axis is... The lateral deployment angle of the radar. This is the radar's longitudinal elevation view. It was not drawn directly; the drawing method is referenced. The drawing method simply expands the angle from the horizontal direction of the radar. , The drawing and calculation are both existing technologies.

[0051] Step S130: Initialize the radar sight cone ellipse equation based on the minimum effective detection range of the radar, the radar sight cone ellipse equation being used to represent the radar field of view.

[0052] The minimum effective detection range of the radar is obtained according to step S120. Then, the length of the lateral half-axis of the radar cone ellipse in the initial state can be easily calculated. Ra、 Longitudinal half-axis length Rb The expression is as follows: .

[0053] Furthermore, it can be based on the obtained Ra、Rb Thus, the equation of the radar sight cone ellipse is obtained as follows: .

[0054] Step S200: Obtain sequentially arranged trajectory lines without data jumps through radar, and initialize the device boundary field of view parameters based on the trajectory lines; the trajectory lines include several trajectory points; the device boundary field of view parameters include the iteration start point, the iteration end point, and the device boundary boundary slope, etc., the iteration start point is the first trajectory point, the iteration end point is the last trajectory point, and the device boundary boundary slope is used to identify the radar's frontal view direction.

[0055] Further, step S200 may include steps S210 to S230.

[0056] Step S210: Obtain the radar trajectory line, which includes multiple trajectory points.

[0057] Furthermore, SLAM technology can be used to obtain the radar's trajectory lines.

[0058] Step S220: Verify all trajectory points on the trajectory line obtained in step S210. If all trajectory points are arranged in order and there is no data jump, continue to step S230; otherwise, output an error and return to step S210.

[0059] As is well known, the direction of a radar's line of sight is the direction in which its detection laser is emitted, i.e., the radar's detection direction. The trajectory line, however, is a derivative of SLAM mapping, representing the radar's operational trajectory and serving as crucial input data for line-of-sight detection. The trajectory line consists of a series of radar trajectory points. These points describe the radar's position and orientation relative to world coordinates at each location during train movement. By utilizing the pose information of these trajectory points for spatial transformation, the train can be converted from the world coordinate system to a radar coordinate system with the radar as its origin. Just as... Figure 4 As shown. The pose information of a trajectory point is usually represented by the coordinates of the trajectory point on the x, y, and z axes and quaternions.

[0060] It is obvious that the radar line of sight extends along the trajectory line. The trajectory line is the basis of line-of-sight detection, and its accuracy is very important. Therefore, before starting line-of-sight detection, this disclosure verifies the trajectory line to ensure that all trajectory points in the trajectory line meet the conditions of sequential arrangement and no data jumps. If the acquired trajectory line fails the verification, an error is output, and the process returns to step S210 to acquire a new trajectory line.

[0061] Step S230: Initialize the device boundary field of view parameters based on the trajectory line.

[0062] Further, in step S230, initializing the device boundary field of view parameters based on the trajectory line may include the following steps: Step S231: Take the first trajectory point as the starting point of the iteration; Step S232: Use the slope between the first trajectory point and the second trajectory point as the initial slope, and initialize the slope of the equipment boundary using the initial slope; Step S233: Take the last trajectory point as the endpoint of the iteration.

[0063] The device clearance boundary slope is initialized by the initial slope, that is, the initial slope is assigned to the device clearance boundary slope.

[0064] It is important to note that initializing the device's boundary field of view parameters is to prepare for subsequent iterations of line-of-sight detection. For example... Figure 4 As shown, the trajectory line can include trajectory points. T 1 to trajectory point T k Select the first trajectory point T 1 serves as the starting point for iteration, and the starting point is combined with the second trajectory point. T 2. Calculate the initial slope. The initial slope is assigned to the equipment clearance boundary slope to initialize the equipment clearance boundary slope. Additionally, the last trajectory point... T k The endpoint of the current line of sight is considered to be the last trajectory point seen by the radar at its current line of sight. T k Subsequently, line-of-sight detection is performed iteratively on each trajectory point, and the slope of the device boundary is updated during the line-of-sight detection.

[0065] Step S300: Select a trajectory point from the trajectory line in sequence as the radar dwell point. The radar dwell point is used to identify the current position of the radar (which is also the current position of the train).

[0066] Step S400: Using the radar stopping point as the origin in 3D space, perform coordinate system transformation on each of the subsequent trajectory points, and then convert the 3D space into a two-dimensional projection in the radar's frontal view based on the coordinate transformation perspective, and update the slope of the device boundary based on the two-dimensional projection.

[0067] It should be noted that the subsequent track points refer to the track points ordered after the radar rest point. Assume the radar rest point is a track point. T 2, then the trajectory point T 3 to trajectory point T k These are the trajectory points described later, and other cases are similar.

[0068] Further, step S400 may include steps S410 to S440.

[0069] Step S410: Using the radar stationary point as the origin in the 3D space, perform coordinate system transformation on all trajectory points in the 3D space based on the pose information of the radar stationary point.

[0070] It is important to note that coordinate system transformation always takes place in 3D space. That is, a transformation from 3D coordinates to 3D coordinates only changes the position of the spatial origin; the relative positions of the various trajectory points remain unchanged. In other words, after the coordinate system transformation, the relative positions of the various trajectory points remain unchanged. Only the radar stationary point (i.e., the radar's current position, the train's current position) becomes the origin of the coordinate system, while the coordinates of other trajectory points become their distances relative to the radar stationary point.

[0071] Furthermore, coordinate system transformations can be accomplished using transformation matrices.

[0072] Furthermore, the transformation matrix can be as follows: ; in, It is a three-dimensional translation vector, corresponding to the coordinates of the trajectory point, representing the three-dimensional translation distance between other trajectory points and the origin (radar dwell point); It is a rotation matrix and can be converted to and from quaternions.

[0073] Step S420: Calculate the spatial rotation angle of the radar dwell point relative to the radar.

[0074] Step S430: Based on the spatial rotation angle, convert the 3D space into a two-dimensional projection in the radar's frontal view direction.

[0075] To facilitate the calculation of the train visibility threshold, a model is constructed as follows: Figure 12 The preset train visibility threshold curve shown requires first projecting the 3D space onto a 2D plane in the radar's line of sight—that is, converting the 3D space into a two-dimensional projection in the radar's line of sight. To achieve this, the spatial rotation relationship of the radar's stationary point needs to be calculated. It is well known that two points in space can determine a straight line; therefore, the spatial rotation angle of the radar's stationary point relative to the radar can be calculated through the positional relationship between the radar's stationary point and adjacent trajectory points. Then, based on this spatial rotation angle, a sine / cosine calculation can be performed to obtain the 3D space converted into a two-dimensional projection in the radar's line of sight, as shown below. Figure 5 As shown.

[0076] Figure 5 In the image, the right-hand plane is a two-dimensional projection of the radar's frontal view. For example... Figure 6As shown, converting the 3D space into a 2D projection in the radar's frontal view essentially involves first converting the world coordinate system into a 3D radar coordinate system within the 3D space, and then converting the 3D radar coordinate system into a 2D radar coordinate system in the radar's frontal view. Both the 2D and 3D radar coordinate systems use the radar's resting point (the radar's current position) as the origin and indicate the relative position of each trajectory point with respect to the radar's resting point. Of course, the 3D radar coordinate system stores the pose information of each trajectory point.

[0077] Step S440: Calculate the slope values ​​between the radar dwell point and each subsequent trajectory point on the two-dimensional projection, and use the slope value closest to the radar central axis to update the slope of the equipment boundary.

[0078] Further, step S440 includes the following steps: Step S441: Select one of the subsequent trajectory points from the radar dwell point as the trajectory point to be calculated in sequence; Step S442: Use the slope value between the calculated trajectory point and the trajectory point to be calculated as a temporary slope value; Step S443: If the temporary slope value is closer to the radar center axis than the slope of the equipment clearance boundary, then update the slope of the equipment clearance boundary with the temporary slope value; otherwise, ignore the temporary slope value and return to step S441.

[0079] Steps S441 to S443 update the equipment clearance boundary slope in the equipment clearance field of view parameters. This involves assigning the slope value closest to the radar's central axis among all slope values ​​between the radar dwell point and all subsequent trajectory points to update the equipment clearance boundary slope. The slope value closest to the radar's central axis is the equipment clearance boundary slope of the radar at the radar dwell point.

[0080] In practice, the slope value calculated on the left side of the rail transit is often positive, and the slope value calculated on the right side of the rail transit is often positive as well. Ultimately, both are aimed at obtaining a slope value closer to the radar's central axis. Therefore, step S440 directly uses whether the slope is closer to the radar's central axis than the existing equipment clearance boundary slope as the criterion for updating the equipment clearance boundary slope. Thus, it is not necessary to be particular about the positive or negative sign of the slope value; it can be achieved directly through comparison of absolute values.

[0081] Step S500: Select one of the subsequent trajectory points in sequence as the point to be scanned. The radar, located at the radar dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results. The line-of-sight detection results include the corresponding radar dwell point, the point to be scanned, the radar line-of-sight distance, the percentage of visibility of the safety clearance, and the percentage of visibility of the radar cone.

[0082] It is understood that each of the aforementioned line-of-sight detection results is composed of a corresponding set of radar dwell point, scan point, radar line-of-sight distance, safety clearance visibility percentage, and radar cone visibility percentage. Combining the corresponding radar dwell point, scan point, radar line-of-sight distance, safety clearance visibility percentage, and radar cone visibility percentage into the line-of-sight detection result ensures the uniqueness of the radar line-of-sight detection data at the radar dwell point and scan point, and facilitates subsequent output, analysis, and display operations.

[0083] Further, in step S500, the radar performs line-of-sight detection on the point to be scanned at the radar dwell point to obtain a set of corresponding line-of-sight detection results, including the following steps S510 to S530.

[0084] Step S510: Calculate the radar line-of-sight distance based on the two-dimensional projection.

[0085] More specifically, calculating the radar line-of-sight distance may include: calculating the absolute value of the difference in abscissa between the corresponding point to be scanned and the radar stationary point, and using the absolute value of the difference in abscissa as the radar line-of-sight distance, as shown in the following expression: The radar line-of-sight distance = |x-coordinate of the point to be scanned - x-coordinate of the radar stationary point|; The horizontal axis of the two-dimensional projection extends along the track direction.

[0086] In common knowledge, the radar line-of-sight distance calculated in step S510 can be achieved using various existing technologies, such as orbital arc distance, coordinate distance, Euclidean distance, etc. For example, a two-dimensional coordinate system can be constructed on a two-dimensional projection to aid the calculation. The reason is that, as... Figure 7 As shown, the black dot represents the radar, L1 is the distance along the track arc, L2 is the straight-line distance, and L3 is the axial distance. In terms of accuracy, L1>L2>L3, but because the radius of curvature of the track is often very large, in reality, L1≈L2≈L3. Therefore, the radar line-of-sight distance can be calculated using existing technologies such as coordinate distance, Euclidean distance, and track arc distance. These methods are applicable to calculating radar line-of-sight distances in this disclosure and even in the field of rail transit technology.

[0087] Although step S510 uses coordinate distance calculation for demonstration, it does not mean that step S510 must be implemented in this way. The choice of which existing technology is used to implement step S510 does not affect the implementation of this disclosure.

[0088] Step S520: Calculate the visible percentage of the safety clearance using the overlapping area between the equipment clearance and the safety clearance, and the total area of ​​the safety clearance.

[0089] Ideally, radar can see up to its maximum detection range. However, due to the presence of walls, equipment, and other objects on-site, the radar's field of view can be obstructed, causing the actual line-of-sight distance to be less than the maximum detection range. In fields such as rail transportation, it is well known that no equipment can be installed within its clearance limits. However, if there is a curve ahead, the outer edge of the clearance limit ahead may also obstruct the view of trains behind, such as... Figure 8 As shown, the red box represents the equipment clearance, the red line indicates the left boundary of the equipment clearance, and the gray line indicates that the radar is blocked because the equipment clearance is exceeded at the bend. Of course... Figure 8 This is merely an illustrative diagram. In actual practice, additional equipment may be installed beyond the equipment clearance, but this will not affect the implementation of this disclosure and will not be elaborated upon here. The overlapping area between the equipment clearance and the safety clearance, as well as the total area of ​​the safety clearance, can be obtained using existing means such as radar. This is common knowledge and will not be elaborated upon here.

[0090] For ease of understanding, Figure 9 In the diagram, the red box represents the equipment clearance, and the blue box represents the safety clearance, with the overlapping area of ​​the red and blue boxes being [missing information]. The visible area representing the safety clearance. The total area of ​​the safety clearance. Overlapping area. Shadows were added for easier display.

[0091] Therefore, the formula for calculating the visible percentage of the safety clearance can be as follows: ; in, 1 represents the percentage of the safety clearance that is visible; The overlapping area between the equipment clearance and the safety clearance represents the visible area of ​​the safety clearance. The total area of ​​the safety clearance.

[0092] Step S530: Calculate the visible percentage of the radar cone using the longitudinal section of the radar cone and the longitudinal section of the rear end of the train.

[0093] As is well known, because the light signals emitted by radar travel in a straight line, when there is a curve or slope in front of the radar, the radar may not be able to see the train in front, or can only see a part of the train. This is another important reason why the radar's line of sight cannot reach its maximum detection range. Figure 10 As shown.

[0094] To facilitate understanding, through Figure 11The diagram shows the radar cone in red, the tail of the train in front in blue, and the shaded area representing the area where the radar can see the train in front. , These are the two foci of the ellipse. The rectangle intersects the ellipse at two points; these two intersection points are connected to the right focus of the ellipse. Connecting them, we can obtain a triangular sector, the area of ​​which is denoted as . ,in addition , , These are the areas of the triangles marked in the diagram. (Combined with...) Figure 11 As shown, the area of ​​the shaded region can be deduced. The calculation formula is as follows: ; The ellipse is represented by the radar cone ellipse equation, and is a triangular sector. The area can be obtained by integral calculation.

[0095] Therefore, the formula for calculating the radar sight cone visibility percentage can be as follows: ; in, The percentage of the radar's visible cone; The overlapping area of ​​the radar's longitudinal section and the longitudinal section of the train's rear end represents the area of ​​the train's rear end that can be seen within the radar's field of view. S 总2 This represents the area of ​​the longitudinal section at the rear end of the train ahead.

[0096] It should be noted that the radar sight cone visibility percentage does not necessarily have to be obtained in the manner described above; it can also be obtained using other existing technologies. Since the calculation methods of other existing technologies are similar, they will not be elaborated upon here.

[0097] Step S600: If the line-of-sight detection result fully meets the preset line-of-sight detection conditions, it means that the radar has not yet reached the maximum line-of-sight at the radar dwell point, and the subsequent trajectory points should continue to be scanned. Therefore, return to step S500. Otherwise, it indicates that the radar has reached its maximum line of sight at the radar dwell point, and the radar cannot obtain reliable data by continuing to scan the subsequent trajectory points. Therefore, the line of sight detection of the subsequent trajectory points at the radar dwell point should be terminated, and step S700 should continue to be executed.

[0098] Further, in step S600, the preset line-of-sight detection conditions include: a) The radar line-of-sight distance is less than or equal to the radar's maximum detection distance; b) The train visibility threshold corresponding to the radar line-of-sight distance on the preset train visibility threshold curve, where the safety clearance visibility percentage is ≥ 0.5%. c) The overall trend of the slope of the equipment clearance boundary did not show any vertical or horizontal intersection.

[0099] It is important to note that there is a corresponding relationship between the radar line-of-sight distance, the percentage of visibility in the safety clearance, and the slope of the equipment clearance boundary for each set of line-of-sight detection results. Therefore, the percentage of visibility in the safety clearance can be compared with the train visibility threshold corresponding to the radar line-of-sight distance on the preset train visibility threshold curve to determine whether the percentage of visibility in the safety clearance has reached the corresponding train visibility threshold. This allows for analysis of whether the radar can meet the obstacle detection requirements at the given radar line-of-sight distance. At the corresponding radar line-of-sight distance, the percentage of visibility in the safety clearance should be greater than or equal to the corresponding train visibility threshold for the radar to meet the obstacle detection requirements.

[0100] The overall trend of the slope of the equipment clearance boundary is based on the overall trend between all historical equipment clearance boundary slopes and the latest updated equipment clearance boundary slope. If vertical or horizontal intersections occur, it indicates an anomaly in the radar's line-of-sight (detection direction), meaning the radar has reached its maximum line-of-sight. Continuing to scan further trajectory points from the current radar stationary point can no longer guarantee data reliability.

[0101] Furthermore, the process of constructing the preset train visibility threshold curve includes the following steps: Step (1): Initialize the radar's maximum detection range D Minimum train visibility threshold H min and maximum train visibility threshold H max ; Step (2): Based on the attenuation law of light in the air, the train visibility threshold formula is constructed as follows: H x = H min + ; in, x This represents the radar line-of-sight distance, i.e., the distance between the obstacle and the radar's stopping point; H x Represents radar line-of-sight distance x The train visibility threshold of the radar; D This represents the furthest detection range of the radar. H minThis represents the minimum train visibility threshold; H max This represents the maximum train visibility threshold. is the attenuation coefficient, and is a constant; Step (3): Based on the radar's farthest detection distance, minimum train visibility threshold, maximum train visibility threshold, and train visibility threshold formula, plot the preset train visibility threshold curve.

[0102] like Figure 12 As shown, the preset train visibility threshold curve is plotted on a plane coordinate system, with the horizontal axis ( x The vertical axis () indicates the radar's line-of-sight range, and the horizontal axis () indicates the radar's line-of-sight range. y The train visibility threshold corresponding to the axle identifier.

[0103] The train visibility threshold represents the percentage of the train's visible portion relative to the entire train. This threshold is the detection threshold for the radar at a specific distance; the radar must detect more than this threshold for it to stably perform obstacle detection at that distance. The train visibility portion is the portion of the train detected by the radar.

[0104] For ease of understanding, such as Figure 12 As shown, the maximum detection range of the radar is set. D =200m, minimum train visibility threshold H min =17.7%, maximum train visibility threshold H max =100%, and combined with the train visibility threshold formula, the preset train visibility threshold curve is plotted. When the radar's line-of-sight distance is 0m, the radar must detect more than 17.7% of the train portion to be considered as being able to stably perform obstacle detection under the condition of 0m line-of-sight distance; similarly, when the radar's line-of-sight distance is 200m, the radar must detect 100% of the train portion to be considered as being able to stably perform obstacle detection under the condition of 200m line-of-sight distance.

[0105] Step S700: If the radar dwell point is the iteration endpoint, it means that the radar has completed line-of-sight detection of the trajectory line. Then, all the line-of-sight detection results are summarized into the final detection result, and step S800 is executed. Otherwise, return to step S300.

[0106] It is understandable that step S700 uses the radar dwell point as the iteration endpoint as an example condition for terminating the iteration. However, this disclosure can be flexibly considered in its implementation, as there may often be no need to continue iterating when the last three trajectory points are reached. Therefore, the penultimate trajectory point can also be used as the endpoint.T k-1 Or the third to last trajectory point T k-2 As a condition for terminating the iteration, such as determining if the radar dwell point is the second to last trajectory point. T k-1 Or the third to last trajectory point T k-2 If the radar is considered to have completed line-of-sight detection of the trajectory line, then all the line-of-sight detection results are summarized into a final detection result, and then step S800 is executed. Of course, this is based on the iteration endpoint. T k As a condition for terminating the iteration, the last iteration may lack practical significance, but it is sufficient to handle or ignore any null values ​​that may be generated based on common sense, such as designing the program to ignore or skip null values.

[0107] Step S800: Output the final detection result.

[0108] Furthermore, the final detection result can be output as a line-of-sight file, such as... Figure 13 As shown.

[0109] The working principle is as follows: Step S100 initializes the radar and other systems, determining the line-of-sight detection parameters, minimum effective radar detection range, etc.; Step S200 acquires the radar trajectory line and initializes the equipment clearance field-of-sight parameters, specifying the iteration start point, iteration end point, and equipment clearance boundary slope, etc. Steps S300 to S700 are large iterative loop steps. The core idea is to use each trajectory point sequentially as a radar dwell point, performing coordinate system transformation, 3D spatial projection, and line-of-sight scanning of subsequent trajectory points using the radar dwell point as the origin of 3D space. Steps S500 to S600 are small iterative loop steps, that is, scanning subsequent trajectory points sequentially at the radar dwell point until the radar's maximum line-of-sight is reached. It should be noted that, each time the radar's maximum line-of-sight is reached, the radar may not necessarily complete line-of-sight detection for all subsequent trajectory points after the radar dwell point. The purpose of steps S500 to S600 is to determine the maximum line-of-sight achievable by the radar at each trajectory point. In step S700, the condition for ending the large iteration loop is set—the radar dwell point is the iteration endpoint, indicating that the entire trajectory line has completed line-of-sight detection. In this case, the large iteration ends, and all line-of-sight detection results are summarized into the final detection result. Step S800 is responsible for outputting the final detection result.

[0110] Example 2: like Figure 14 As shown in Embodiment 2 of this disclosure, a radar detection capability calculation system is provided, the system comprising: Initialization module 100 is used to acquire line-of-sight detection parameters, calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters, and initialize the radar line-of-sight cone ellipse equation based on the minimum effective detection range of the radar. The detection preparation module 200 is used to acquire sequentially arranged trajectory lines without data jumps through radar, and to initialize the device boundary field of view parameters based on the trajectory lines; the trajectory lines include several trajectory points; the device boundary field of view parameters include the iteration start point, the iteration end point, and the device boundary boundary slope, etc., the iteration start point is the first trajectory point, the iteration end point is the last trajectory point, and the device boundary boundary slope is used to identify the radar's frontal view direction; The stop point selection module 300 is used to select a trajectory point from the trajectory line in sequence as the radar stop point. The radar stop point is used to identify the current position of the radar (which is also the current position of the train). The parameter update module 400 is used to perform coordinate system transformation on each of the subsequent trajectory points with the radar stopping point as the origin in the 3D space, and then convert the 3D space into a two-dimensional projection in the radar's frontal view based on the perspective after coordinate transformation, and update the slope of the equipment boundary based on the two-dimensional projection. The scanning detection module 500 is used to sequentially select one of the subsequent trajectory points as the point to be scanned. The radar, located at the radar dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results. The line-of-sight detection results include the corresponding radar dwell point, the point to be scanned, the radar line-of-sight distance, the percentage of visibility of the safety clearance, and the percentage of visibility of the radar cone. The maximum line-of-sight determination module 600 is used to determine that if the line-of-sight detection result fully meets the preset line-of-sight detection conditions, it means that the radar has not yet reached the maximum line-of-sight at the radar dwell point, and should continue to scan the subsequent trajectory points. Therefore, it returns to the execution scanning detection module 500. Otherwise, it indicates that the radar has reached its maximum line of sight at the radar dwell point, and the radar cannot obtain reliable data by continuing to scan the subsequent trajectory points. Therefore, the line of sight detection of the subsequent trajectory points at the radar dwell point should be terminated, and the traversal judgment module 700 should continue to be executed. The traversal determination module 700 is used to summarize all the line-of-sight detection results into the final detection result if the radar dwell point is the iteration endpoint, indicating that the radar has completed the line-of-sight detection of the trajectory line, and continue to execute the final result output module 800; otherwise, it returns to the execution of the dwell point selection module 300. The final result output module 800 is used to output the final detection result.

[0111] The initialization module 100, detection preparation module 200, stop point selection module 300, parameter update module 400, scanning detection module 500, maximum viewing distance determination module 600, traversal determination module 700, and final result output module 800 in the system correspond to steps S100, S200, S300, S400, S500, S600, S700, and S800 in the method, respectively.

[0112] It is worth noting that the system described in Embodiment 2 is only one system implementation of the radar detection capability calculation method described in Embodiment 1, and does not limit the radar detection capability calculation method described in Embodiment 1 to depend on the system described in Embodiment 2.

[0113] Example 3: Embodiment 3 of this disclosure provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the radar detection capability calculation method as described in Embodiment 1. Alternatively, a radar detection capability calculation system as described in Example 2 can be implemented.

[0114] The computer-readable storage medium includes volatile or non-volatile, removable or non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules, or other data). Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory or other memory technologies, CD-ROM (Compact Disc Read-Only Memory), DVD or other optical disc storage, cartridges, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer.

[0115] Example 4: Embodiment 4 of this disclosure provides an electronic device, which includes a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the radar detection capability calculation method described in Embodiment 1.

[0116] Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0117] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0118] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0119] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0120] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0121] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0122] In summary, the radar detection capability calculation method and system provided in embodiments 1-4 of this disclosure offer a more automated radar detection capability assessment method, reducing labor costs and reliance on human experience to meet engineering application requirements. This invention focuses on the radar detection capability calculation problem in rail transit obstacle detection applications. It only requires a train equipped with radar to travel at low speed along the entire line once, and the SLAM algorithm to construct a point cloud map and trajectory line. Then, based on the trajectory line and line parameters, the maximum detection distance at each location on the line can be calculated. This disclosure allows for the accurate determination of the maximum line-of-sight distance achievable by the radar at each trajectory point, and it also allows for the aggregation of line-of-sight detection results obtained by the radar scanning other subsequent trajectory points at each trajectory point, making rail transit obstacle detection and analysis more convenient.

[0123] Compared to traditional on-site measurement methods, this disclosure fully considers the impact of changes in road terrain on radar field of view, and can accurately calculate the percentage of radar detection area obstructed by curves, slope changes, etc., making the calculated maximum radar detection distance smoother and more reliable. Since the percentage of obstruction changes continuously, the maximum radar detection distance calculated by this disclosure is also very smooth, solving the distance jump problem of manual measurement methods.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure and not to limit them. Although this disclosure has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of this disclosure. Any modifications or equivalent substitutions that do not depart from the spirit and scope of this disclosure should be covered within the protection scope of the claims of this disclosure.

Claims

1. A method for calculating radar detection capability, characterized in that, The method includes: Step S100: Obtain the line-of-sight detection parameters, calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters, and initialize the radar line-of-sight cone ellipse equation based on the minimum effective detection range of the radar. Step S200: Obtain sequentially arranged trajectory lines without data jumps using radar, and initialize device boundary field of view parameters based on the trajectory lines; the trajectory lines include several trajectory points; the device boundary field of view parameters include an iteration start point, an iteration end point, and a device boundary boundary slope, the iteration start point is the first trajectory point, the iteration end point is the last trajectory point, and the device boundary boundary slope is used to identify the radar's frontal view direction; Step S300: Select a trajectory point from the trajectory line in sequence as the radar dwell point, the radar dwell point is used to identify the current position of the radar; Step S400: Using the radar stopping point as the origin in the 3D space, perform coordinate system transformation on each of the subsequent trajectory points, and then convert the 3D space into a two-dimensional projection in the radar's frontal view based on the perspective after coordinate transformation, and update the slope of the device boundary based on the two-dimensional projection. Step S500: Select one of the subsequent trajectory points in sequence as the point to be scanned. The radar, located at the radar dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results. The line-of-sight detection results include the corresponding radar dwell point, the point to be scanned, the radar line-of-sight distance, the safety clearance visibility percentage, and the radar cone visibility percentage. Step S600: If the line-of-sight detection result fully meets the preset line-of-sight detection conditions, it means that the radar has not yet reached the maximum line-of-sight at the radar dwell point, and the subsequent trajectory points should continue to be scanned. Therefore, return to step S500. Otherwise, it indicates that the radar has reached its maximum line of sight at the radar dwell point, and the radar cannot obtain reliable data by continuing to scan the subsequent trajectory points. Therefore, the line of sight detection of the subsequent trajectory points at the radar dwell point should be terminated, and step S700 should continue to be executed. Step S700: If the radar dwell point is the iteration endpoint, it means that the radar has completed line-of-sight detection of the trajectory line. Then, all the line-of-sight detection results are summarized into the final detection result, and step S800 is executed. Otherwise, return to step S300. Step S800: Output the final detection result.

2. The radar detection capability calculation method as described in claim 1, characterized in that, In step S100, The line-of-sight detection parameters include the length, width, and height of the equipment clearance, the length, width, and height of the safety clearance, the train's running direction, the radar field of view, the radar's farthest detection distance, the minimum train visibility threshold, and the maximum train visibility threshold. The radar field-of-view ellipse equation is used to represent the radar field of view.

3. The radar detection capability calculation method as described in claim 1, characterized in that, Step S200 includes the following steps: Step S210: Obtain the radar trajectory line, which includes multiple trajectory points; Step S220: Verify all trajectory points in the trajectory line obtained in step S210. If all trajectory points are arranged in order and there is no data jump, continue to step S230; otherwise, output an error and return to step S210. Step S230: Initialize the device boundary field of view parameters based on the trajectory line.

4. The radar detection capability calculation method as described in claim 3, characterized in that, In step S230, initializing the device's bounded field of view parameters based on the trajectory line includes the following steps: Step S231: Take the first trajectory point as the starting point of the iteration; Step S232: Use the slope between the first trajectory point and the second trajectory point as the initial slope, and assign the initial slope to the slope of the equipment boundary. Step S233: Take the last trajectory point as the endpoint of the iteration.

5. The radar detection capability calculation method as described in claim 1, characterized in that, Step S400 includes the following steps: Step S410: Using the radar stationary point as the origin in the 3D space, perform coordinate system transformation on all trajectory points in the 3D space based on the pose information of the radar stationary point; Step S420: Calculate the spatial rotation angle of the radar dwell point relative to the radar; Step S430: Based on the spatial rotation angle, convert the 3D space into a two-dimensional projection in the radar's frontal view direction; Step S440: Calculate the slope values ​​between the radar dwell point and each subsequent trajectory point on the two-dimensional projection, and use the slope value closest to the radar central axis to update the slope of the equipment boundary.

6. The radar detection capability calculation method as described in claim 5, characterized in that, Step S440 includes the following steps: Step S441: Select one of the subsequent trajectory points from the radar dwell point as the trajectory point to be calculated in sequence; Step S442: Use the slope value between the calculated trajectory point and the trajectory point to be calculated as a temporary slope value; Step S443: If the temporary slope value is closer to the radar center axis than the slope of the equipment clearance boundary, then update the slope of the equipment clearance boundary with the temporary slope value; otherwise, ignore the temporary slope value and return to step S441.

7. The radar detection capability calculation method as described in claim 2, characterized in that, In step S500, the radar, located at its dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results, including the following steps: Step S510: Calculate the radar line-of-sight distance based on the two-dimensional projection; The calculation of the radar line-of-sight distance includes: calculating the absolute value of the difference in the horizontal coordinates between the corresponding point to be scanned and the radar stationary point, and using the absolute value of the difference in the horizontal coordinates as the radar line-of-sight distance. The specific expression is as follows: The radar line-of-sight distance = |x-coordinate of the point to be scanned - x-coordinate of the radar stationary point|; Wherein, the horizontal axis of the two-dimensional projection extends along the track direction; Step S520: Calculate the visible percentage of the safety clearance using the overlapping area between the equipment clearance and the safety clearance, and the total area of ​​the safety clearance, as shown below: ； in, 1 represents the percentage of the safety clearance that is visible; The overlapping area between the equipment clearance and the safety clearance represents the visible area of ​​the safety clearance. The total area of ​​the safety clearance; Step S530: Calculate the visible percentage of the radar cone using the longitudinal section of the radar sight cone and the longitudinal section of the rear end of the train ahead, as shown below: ； in, The overlapping area of ​​the radar's longitudinal section and the longitudinal section of the train's rear end represents the area of ​​the train's rear end that can be seen within the radar's field of view. S 总2 This represents the area of ​​the longitudinal section at the rear end of the train ahead.

8. The radar detection capability calculation method as described in claim 7, characterized in that, In step S600, the preset line-of-sight detection conditions include: a) The radar line-of-sight distance is less than or equal to the radar's maximum detection distance; b) The train visibility threshold corresponding to the radar line-of-sight distance on the preset train visibility threshold curve, where the safety clearance visibility percentage is ≥ 0.5%. c) The overall trend of the slope of the equipment clearance boundary did not show any vertical or horizontal intersection.

9. The radar detection capability calculation method as described in claim 8, characterized in that, The process of constructing the preset train visibility threshold curve includes the following steps: Step (1): Initialize the radar's maximum detection range D Minimum train visibility threshold H min and maximum train visibility threshold H max ; Step (2): Based on the attenuation law of light in the air, the train visibility threshold formula is constructed as follows: H x = H min + ； in, x This represents the radar line-of-sight distance, i.e., the distance between the obstacle and the radar's stopping point; H x Represents radar line-of-sight distance x The train visibility threshold of the radar; D This represents the furthest detection range of the radar. H min This represents the minimum train visibility threshold; H max This represents the maximum train visibility threshold. is the attenuation coefficient, and is a constant; Step (3): Based on the radar's farthest detection distance, minimum train visibility threshold, maximum train visibility threshold, and train visibility threshold formula, plot the preset train visibility threshold curve.

10. A radar detection capability calculation system, characterized in that, The system includes: An initialization module is used to acquire line-of-sight detection parameters, calculate the minimum effective detection range of the radar based on the line-of-sight detection parameters, and initialize the radar line-of-sight cone ellipse equation based on the minimum effective detection range of the radar. The detection preparation module is used to acquire sequentially arranged trajectory lines without data jumps through radar, and to initialize the device boundary field of view parameters based on the trajectory lines; the trajectory lines include several trajectory points; the device boundary field of view parameters include an iteration start point, an iteration end point, and a device boundary boundary slope, the iteration start point is the first trajectory point, the iteration end point is the last trajectory point, and the device boundary boundary slope is used to identify the radar's frontal view direction; The dwell point selection module is used to select a trajectory point from the trajectory line in sequence as the radar dwell point, and the radar dwell point is used to identify the current position of the radar. The parameter update module is used to perform coordinate system transformation on each of the subsequent trajectory points with the radar stationary point as the origin in the 3D space, and then convert the 3D space into a two-dimensional projection in the radar's frontal view based on the perspective after coordinate transformation, and update the slope of the equipment boundary based on the two-dimensional projection. The scanning detection module is used to sequentially select one of the subsequent trajectory points as the point to be scanned. The radar, located at the radar dwell point, performs line-of-sight detection on the point to be scanned to obtain a set of corresponding line-of-sight detection results. The line-of-sight detection results include the corresponding radar dwell point, the point to be scanned, the radar line-of-sight distance, the safety clearance visibility percentage, and the radar cone visibility percentage. The maximum line-of-sight determination module is used to determine that if the line-of-sight detection result fully meets the preset line-of-sight detection conditions, it means that the radar has not yet reached the maximum line-of-sight at the radar dwell point, and should continue to scan the subsequent trajectory points. Therefore, it returns to the execution scanning detection module. Otherwise, it indicates that the radar has reached its maximum line of sight at the radar dwell point, and the radar cannot obtain reliable data by continuing to scan the subsequent trajectory points. Therefore, the line of sight detection of the subsequent trajectory points at the radar dwell point should be terminated, and the traversal judgment module should continue to be executed. The traversal determination module is used to, if the radar stopping point is the iteration endpoint, it means that the radar has completed line-of-sight detection of the trajectory line, then all the line-of-sight detection results are summarized into the final detection result, and the final result output module is continued to be executed; otherwise, the execution of the stopping point selection module is returned. The final result output module is used to output the final detection result.

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