Method for collaborative optimization design of airspace and landing site of unmanned aerial vehicle comprehensive verification field

Abstract

This invention discloses a collaborative optimization design method for the airspace and take-off and landing sites of a UAV integrated verification field, relating to the field of UAV verification field technology. The method includes: constructing a joint digital twin model of the airspace and take-off and landing sites; calculating the circumscribed rectangle and safety distance based on the coordinates of the irregular polygonal airspace boundary, and quantifying the geometric matching degree between the runway extension line and the major axis of the circumscribed rectangle; when the matching degree is lower than a threshold, triggering a heading correction algorithm, using the major axis of the circumscribed rectangle as a reference, and combining performance parameters such as the UAV's minimum turning radius and maximum climb gradient to calculate the target take-off heading angle; generating a departure route and performing normal extrapolation correction based on the boundary coordinates to ensure the route is within the airspace and maintains a safety distance. This invention achieves dynamic collaborative optimization of irregular polygonal airspace and standard take-off and landing sites, breaking through the fixed heading design mode.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) verification field technology, specifically to a method for the collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields. Background Technology

[0002] With the rapid development of the drone industry, the integrated drone verification field, as the core infrastructure for conducting flight verification and personnel training, has become a key link in ensuring flight safety and verification efficiency through the coordinated design of its airspace and take-off and landing sites. Currently, most mainstream verification field design methods are based on the group standard T / CAGIS 4-2021 "General Requirements for Integrated Unmanned Aerial Vehicle Verification Fields" (hereinafter referred to as "the standard"). It assumes that the airspace is an ideal regular rectangle and adopts a static design mode that aligns the fixed runway azimuth angle with the long axis of the airspace. The geometric matching between the site and the airspace is achieved through manual experience adjustment. However, in actual engineering practice, due to military and civil aviation control and terrain restrictions, the approved airspace is mostly irregular polygons with significant geometric deviations from standard rectangles. Existing technologies have failed to effectively address the geometric matching problem between runway extensions and irregular airspace boundaries, leading to conflicts between fixed-heading takeoff routes and airspace boundaries, or severely low airspace utilization. In addition, traditional methods lack a dynamic coupling mechanism between UAV takeoff performance parameters and airspace constraints, making it difficult to optimize heading angles while ensuring safe distances. Therefore, existing technologies are insufficient to solve the problem of coordinating the optimization of irregular polygonal airspace and standard take-off and landing sites. There is an urgent need for a verification field design method that can dynamically adapt to irregular airspace boundaries and take into account runway constraints and flight performance. Summary of the Invention

[0003] To address the aforementioned technical issues, this paper presents a collaborative optimization design method for the airspace and take-off and landing sites of a comprehensive UAV verification field. This technical solution resolves the problem of the difficulty in coordinating irregular polygonal airspace with standard take-off and landing sites.

[0004] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A collaborative optimization design method for the airspace and take-off and landing sites of a comprehensive UAV verification field includes: S1. Construct a joint digital twin model of the airspace and take-off and landing site of the UAV integrated verification field. The take-off and landing site includes the runway and supporting facilities, and the airspace is an irregular polygonal airspace that has been approved. S2. Obtain the boundary coordinates of the irregular polygonal airspace and the azimuth data of the runway. Calculate the circumscribed rectangle of the irregular polygonal airspace based on the boundary coordinates and determine the safety distance. Calculate the matching parameters between the runway extension line and the major axis of the circumscribed rectangle and determine the geometric matching degree. S3. When the geometric matching degree is lower than the preset threshold, the heading correction algorithm is triggered. Based on the direction of the major axis of the circumscribed rectangle, the target takeoff heading angle is calculated in combination with the UAV takeoff performance parameters. S4. Generate a departure route based on the target takeoff heading angle, and perform boundary constraint correction on the departure route according to the boundary coordinates to ensure that the departure route is within the irregular polygonal airspace and maintains a safe distance from the boundary. Output a collaborative optimization scheme that includes the target takeoff heading angle and the corrected departure route.

[0005] Preferably, the steps for constructing the joint digital twin model of the airspace and take-off and landing site of the UAV integrated verification field in step S1 are as follows: Obtain topographic mapping data and facility layout data of the take-off and landing site, and construct a three-dimensional model of the take-off and landing site based on the topographic mapping data, including runway elevation, slope and spatial location of supporting facilities. Extract the horizontal projection boundary and vertical height range of the irregular polygonal spatial domain, and construct a three-dimensional spatial domain model including spatial domain boundary constraints; The three-dimensional model of the take-off and landing site is registered with the three-dimensional airspace model to ensure that the runway centerline and the reference axis of the airspace are in the same coordinate system, and a spatial mapping relationship between the take-off and landing site and the airspace is established to form the joint digital twin model.

[0006] Preferably, the step S2, which involves calculating the circumscribed rectangle of the irregular polygonal spatial region based on the boundary coordinates and determining the safety distance, comprises the following steps: The boundary coordinates of the irregular polygonal spatial domain are extracted from the joint digital twin model, wherein the boundary coordinates are the latitude and longitude or rectangular coordinates of each vertex of the irregular polygonal spatial domain; Boundary feature points of an irregular polygonal spatial domain are extracted based on boundary coordinates. The boundary feature points include the extreme points of the irregular polygonal spatial domain in each projection direction. The circumscribed rectangle is constructed based on the boundary feature points, and the direction of the long side of the circumscribed rectangle is determined as the major axis. The safety distance is determined based on the geometric dimensions of the circumscribed rectangle, and the safety distance is positively correlated with the length and width dimensions of the circumscribed rectangle.

[0007] Preferably, the steps in step S2 to calculate the matching parameters between the runway extension line and the major axis of the circumscribed rectangle, and to determine the geometric matching degree, are as follows: The direction of the runway extension line is determined based on the runway azimuth data. Extract the major axis direction vector of the circumscribed rectangle; Calculate the angle between the direction of the runway extension line and the vector of the major axis direction; Calculate the vertical projection distance from the runway entrance center point to the major axis direction vector to determine the entrance offset; The geometric matching degree is determined based on the weighted sum of the included angle and the entrance offset.

[0008] Preferably, the preset threshold in step S3 is determined based on the ratio of the length and width of the circumscribed rectangle to the length of the runway.

[0009] Preferably, the triggering of the heading correction algorithm in step S3 is based on the direction of the major axis of the circumscribed rectangle, and the steps are as follows: Extract the coordinate difference between the two endpoints of the major axis of the circumscribed rectangle to construct a direction vector, and normalize the direction vector to obtain the unit reference direction vector; The first deflection component is calculated based on the included angle in the geometric matching degree. The first deflection component is positively correlated with the included angle. The second deflection component is calculated based on the ratio of the entrance offset to the short side dimension of the circumscribed rectangle in the geometric matching degree. The first deflection component and the second deflection component are weighted and summed to obtain the heading deflection angle. A rotation matrix is ​​constructed based on the heading deflection angle. The rotation matrix is ​​then used to rotate and transform the unit reference direction vector. The transformed direction vector is then normalized to determine the target takeoff heading angle.

[0010] Preferably, the combination of UAV takeoff performance parameters in step S3 includes: Obtain the drone's minimum turning radius, maximum climb gradient, and takeoff speed; The minimum curvature radius constraint of the departure route is determined based on the minimum turning radius, the maximum allowable value of the departure climb angle is determined based on the maximum climb gradient, and the maximum allowable value is equal to the climb angle corresponding to the maximum climb gradient. The response time constraint of the heading adjustment is determined based on the takeoff speed. The target takeoff heading angle is calculated under the combined constraints of minimum radius of curvature, maximum allowable value, and response time.

[0011] Preferably, the calculation of the target takeoff heading angle in step S3 includes: Using the major axis of the circumscribed rectangle as the initial heading, a heading angle search space is established within the constraint boundary determined by the UAV takeoff performance parameters; The objective function is to maximize the geometric matching degree or minimize the inlet offset, and an iterative search is performed in the heading angle search space. When the convergence accuracy of the search results meets the preset conditions, the current search value is determined as the target takeoff heading angle.

[0012] Preferably, the step S4 of generating the departure route based on the target takeoff heading angle includes: The initial departure direction is determined based on the target takeoff heading angle. The climb trajectory and turning trajectory are calculated in combination with the UAV takeoff performance parameters. The climb trajectory and turning trajectory are discretized to generate a track point sequence. The track point sequence is then connected to form the departure route.

[0013] Preferably, in step S4, the boundary constraint correction of the departure route based on the boundary coordinates includes: Extract the boundary line segment of the irregular polygonal airspace, calculate the vertical distance from each track point on the departure route to the boundary line segment, and when the vertical distance is less than the safe distance, push the corresponding track point outward along the normal direction of the boundary line segment to meet the safe distance, so as to form the corrected departure route.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention proposes a dynamic construction and geometric matching quantification evaluation method for the circumscribed rectangle based on the characteristics of irregular polygonal airspace boundaries. This method achieves precise geometric adaptation between runway orientation and the main extension direction of the irregular airspace obtained through approval, breaking through the constraints of standard specifications on the ideal geometric shape of airspace. Furthermore, it proposes a heading correction algorithm using geometric matching degree as the decision threshold and the major axis direction of the airspace as the reference. Through a dual-component deflection compensation mechanism, it dynamically calculates the target takeoff heading angle, achieving coordinated optimization of heading angles between irregular airspace and standard takeoff and landing sites. This solves the conflict between fixed-heading takeoff routes and airspace boundaries, or issues related to airspace utilization. This paper addresses the technical contradictions associated with low performance. It proposes a method to transform performance parameters such as minimum turning radius, maximum climb gradient, and takeoff speed into geometric constraints, establishing a heading angle search space under performance constraints. This achieves integrated decision-making between geometric optimization objectives and flight safety physical boundaries, avoiding the flight control infeasibility problem caused by simple geometric optimization. Furthermore, it proposes a boundary constraint correction algorithm based on discrete waypoints. Through vertical distance detection and normal extrapolation mechanisms, it achieves safe maintenance and adaptive adjustment of departure routes within irregular polygonal airspace, improving airspace resource utilization efficiency while ensuring boundary safety margins. Attached Figure Description

[0015] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0016] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0017] Reference Figure 1 As shown, the collaborative optimization design method for the airspace and take-off and landing site of the UAV integrated verification field includes: S1. Construct a joint digital twin model of the airspace and take-off and landing site of the UAV integrated verification field. The take-off and landing site includes the runway and supporting facilities, and the airspace is an irregular polygonal airspace that has been approved. The aforementioned approved irregular polygonal airspace refers to flight airspace approved and designated by military and civil aviation airspace management departments based on low-altitude airspace management policies and actual airspace usage, for use as a comprehensive UAV verification field. Its horizontal projected boundary is typically L-shaped, trapezoidal, or an arbitrary polygon, and is not T / CAGIS. The ideal rectangles specified in the 4-2021 standard (Class A: 5000m×1000m, Class B: 3000m×500m, Class C: 1000m×200m) are different from standard rectangular airspace. Irregular polygonal airspaces typically form asymmetrical boundaries due to the need to avoid civil aviation routes, military training areas, or densely populated areas. Their major axis direction deviates from the ideal alignment direction of the test field runway, and the boundary exhibits significant anisotropy (e.g., one side of the boundary is closer to the runway threshold than the other). The boundary coordinates of this type of airspace are derived from airspace use approval documents (such as the "Low-Altitude Airspace Use Approval" or the "Temporary Flight Airspace Approval Certificate for Flight Control Area"). These documents provide the airspace boundary in the form of a vertex coordinate string, where each vertex contains longitude, latitude, and corresponding altitude (or only horizontal projection coordinates). These coordinates constitute the vertex sequence of the irregular polygon, serving as the direct data source for boundary coordinate extraction in this invention, and are used for subsequent calculation of the circumscribed rectangle and boundary constraint correction.

[0018] The steps for constructing the joint digital twin model of the airspace and take-off and landing site of the UAV integrated verification field in step S1 are as follows: Obtain topographic mapping data and facility layout data of the take-off and landing site, and construct a three-dimensional model of the take-off and landing site based on the topographic mapping data, including runway elevation, slope and spatial location of supporting facilities. Extract the horizontal projection boundary and vertical height range of the irregular polygonal spatial domain, and construct a three-dimensional spatial domain model including spatial domain boundary constraints; The three-dimensional model of the take-off and landing site is registered with the three-dimensional airspace model to ensure that the runway centerline and the reference axis of the airspace are in the same coordinate system, and a spatial mapping relationship between the take-off and landing site and the airspace is established to form the joint digital twin model.

[0019] S2. Obtain the boundary coordinates of the irregular polygonal airspace and the azimuth data of the runway. Calculate the circumscribed rectangle of the irregular polygonal airspace based on the boundary coordinates and determine the safety distance. Calculate the matching parameters between the runway extension line and the major axis of the circumscribed rectangle and determine the geometric matching degree. Step S2, which involves calculating the circumscribed rectangle of the irregular polygonal spatial region based on the boundary coordinates and determining the safety distance, is as follows: The boundary coordinates of the irregular polygonal spatial domain are extracted from the joint digital twin model, wherein the boundary coordinates are the latitude and longitude or rectangular coordinates of each vertex of the irregular polygonal spatial domain; Boundary feature points of an irregular polygonal spatial domain are extracted based on boundary coordinates. The boundary feature points include the extreme points of the irregular polygonal spatial domain in each projection direction. The circumscribed rectangle is constructed based on the boundary feature points, and the direction of the long side of the circumscribed rectangle is determined as the major axis. The safety distance is determined based on the geometric dimensions of the circumscribed rectangle. The safety distance is positively correlated with the length and width dimensions of the circumscribed rectangle. It should be noted that the safety distance... The determination of the safety distance follows the principle of positive correlation with the geometric dimensions of the airspace to ensure sufficient safety margins for airspaces of different scales. In this embodiment, the safety distance is dynamically determined based on the length and width dimensions (major axis length L, minor axis length W) of the circumscribed rectangle, as shown in the following formula:

[0020] in This is a proportionality coefficient (usually taken as 0.05 to 0.10). The fixed base distance (usually 50m to 100m) is used to ensure that the larger the airspace size, the greater the safety distance, but a reasonable proportion is maintained to avoid excessive shrinkage of the available airspace. In another implementation, the safety distance can be determined based on the airspace classification: when the length and width dimensions of the circumscribed rectangle meet the T / CAGIS 4-2021 Class A standard (L≥5000m and W≥1000m), Take 100m; if it meets the Class B standard (L≥3000m and W≥500m), take 50m; if it meets the Class C standard (L≥1000m and W≥200m), A safe distance of 20m is adopted. This safe distance will be used for boundary constraint correction of subsequent departure routes to ensure that the waypoints maintain this minimum interval with the airspace boundary.

[0021] The calculation of the circumscribed rectangle is based on the boundary coordinate sequence of the irregular polygonal spatial domain: First, the Cartesian coordinates (X, Y) of each vertex of the spatial boundary are extracted from the joint digital twin model to construct a point set. To reduce computational complexity and ensure a tight circumscribed rectangle envelope, Graham's scan method or Andrew's monotonic chain algorithm is used to perform convex hull operations on the point set P to obtain the vertex set of the convex polygon. ; Subsequently, the minimum area circumscribed rectangle of the convex polygon is calculated using the Rotating Calipers method: taking a certain edge of the convex hull as the starting edge, the area of ​​the circumscribed rectangle is calculated when the direction of that edge is used as one side direction of the rectangle. By rotating the calipers, all edges of the convex hull (a total of m edges) are traversed, and the parameters of the minimum area circumscribed rectangle (center point coordinates, long side direction angle θ, long side length L, short side length W) are recorded. The long side direction of the minimum area circumscribed rectangle is the major axis direction, and its direction vector is v=(cosθ,sinθ), the major axis length is equal to L, and the minor axis length is equal to W. This process ensures that the circumscribed rectangle tightly encloses the irregular spatial region, and the major axis direction reflects the main extension direction of the spatial region, providing a benchmark for subsequent geometric matching with the runway.

[0022] Step S2 involves calculating the matching parameters between the runway extension line and the major axis of the circumscribed rectangle to determine the geometric matching degree. The steps are as follows: The direction of the runway extension line is determined based on the runway azimuth data. Extract the major axis direction vector of the circumscribed rectangle; Calculate the angle between the direction of the runway extension line and the vector of the major axis direction; Calculate the vertical projection distance from the runway entrance center point to the major axis direction vector to determine the entrance offset; The geometric matching degree is determined based on the weighted sum of the included angle and the entrance offset.

[0023] Among them, the quantitative calculation of geometric matching degree is based on two core matching parameters: the angle between the runway extension line and the major axis of the circumscribed rectangle, and the entrance offset of the runway entrance center point relative to the major axis. First, the extension direction of the runway extension line is determined based on the runway azimuth data. At the same time, the extension direction of the major axis of the circumscribed rectangle is extracted, and the angle between the two directions is calculated. The smaller the angle, the better the alignment between the runway and the major axis of the airspace. Secondly, measure the perpendicular distance from the center point of the runway entrance to the major axis of the circumscribed rectangle. This distance is the entrance offset. The smaller the offset, the better the alignment between the runway entrance and the airspace centerline. Finally, the geometric matching degree is calculated comprehensively through a weighted evaluation model: the included angle and the entrance offset are normalized to make them fall within the same dimension range, and then weighted and summed according to preset weight coefficients. The included angle usually has the dominant weight, followed by the entrance offset. The geometric matching degree ranges from 0 to 1. The larger the value, the higher the geometric matching degree between the runway and the airspace. When the matching degree is lower than the preset threshold, it indicates that there is a significant geometric conflict between the current runway orientation and the irregular airspace, and the heading correction algorithm needs to be triggered to recalculate the target takeoff heading angle to achieve collaborative optimization.

[0024] S3. When the geometric matching degree is lower than the preset threshold, the heading correction algorithm is triggered. Based on the direction of the major axis of the circumscribed rectangle, the target takeoff heading angle is calculated in combination with the UAV takeoff performance parameters. The preset threshold mentioned in step S3 is determined based on the ratio of the length and width of the circumscribed rectangle to the runway length. The determination of the preset threshold follows the principle of adapting to the airspace geometry and runway scale to ensure that the timing of triggering the heading correction algorithm reflects both the severity of geometric conflict and the actual needs of verification fields of different sizes. Specifically, the threshold can be dynamically determined based on the ratio of the length and width of the circumscribed rectangle to the runway length: when the ratio of the major axis length of the circumscribed rectangle to the runway length is less than the first preset ratio, or the ratio of the minor axis length of the circumscribed rectangle to the runway length is less than the second preset ratio, it indicates that the airspace scale is relatively small compared to the runway size, and the runway extension is likely to approach the airspace boundary. In this case, the preset threshold of geometric matching degree should be set to a higher value so as to trigger the heading correction algorithm for heading optimization as early as possible.

[0025] The heading correction algorithm described in step S3, using the major axis direction of the circumscribed rectangle as a reference, consists of the following steps: Extract the coordinate difference between the two endpoints of the major axis of the circumscribed rectangle to construct a direction vector, and normalize the direction vector to obtain the unit reference direction vector; The first deflection component is calculated based on the included angle in the geometric matching degree. The first deflection component is positively correlated with the included angle. The second deflection component is calculated based on the ratio of the entrance offset to the short side dimension of the circumscribed rectangle in the geometric matching degree. The first deflection component and the second deflection component are weighted and summed to obtain the heading deflection angle. A rotation matrix is ​​constructed based on the heading deflection angle. The rotation matrix is ​​then used to rotate and transform the unit reference direction vector. The transformed direction vector is then normalized to determine the target takeoff heading angle.

[0026] When the geometric matching degree is lower than the preset threshold, the system triggers the heading correction algorithm and recalculates the target takeoff heading angle based on the direction of the major axis of the circumscribed rectangle. First, the coordinate difference between the two endpoints of the major axis of the circumscribed rectangle is extracted to construct a direction vector. This direction vector is then normalized to make its magnitude equal to the unit length, thus obtaining the unit reference direction vector, which represents the reference direction of the main extension direction of the spatial domain. Subsequently, the algorithm calculates the first deflection component based on the included angle in the geometric matching degree. This first deflection component is positively correlated with the included angle. That is, the larger the angle between the runway extension line direction and the major axis direction of the circumscribed rectangle, the larger the value of the first deflection component, indicating that a larger heading adjustment is needed to reduce the degree of deviation between the runway direction and the main extension direction of the airspace. Meanwhile, the second deflection component is calculated based on the ratio of the inlet offset to the short side dimension of the circumscribed rectangle in the geometric matching degree. This ratio reflects the degree of lateral deviation of the runway inlet from the airspace centerline. The larger the ratio, the larger the value of the second deflection component, indicating that lateral compensation is needed to better align the runway inlet with the available airspace. The first deflection component and the second deflection component are weighted and summed to obtain the heading deflection angle. The weight of the first deflection component is usually greater than that of the second deflection component to prioritize the consistency between the runway direction and the long axis direction of the airspace, while the second deflection component provides lateral position compensation. A rotation matrix is ​​constructed based on the obtained heading deflection angle. The unit reference direction vector is then rotated using this rotation matrix. The direction of the rotation transformation is determined by the sign of the included angle. The rotation angle is equal to the heading deflection angle. The transformed direction vector is then normalized again to eliminate calculation errors. The final target takeoff heading angle is the direction pointed to by this normalized direction vector.

[0027] The combination of UAV takeoff performance parameters mentioned in step S3 includes: Obtain the drone's minimum turning radius, maximum climb gradient, and takeoff speed; The minimum curvature radius constraint of the departure route is determined based on the minimum turning radius, the maximum allowable value of the departure climb angle is determined based on the maximum climb gradient, and the maximum allowable value is equal to the climb angle corresponding to the maximum climb gradient. The response time constraint of the heading adjustment is determined based on the takeoff speed. The target takeoff heading angle is calculated under the combined constraints of minimum radius of curvature, maximum allowable value, and response time.

[0028] The calculation of the target takeoff heading angle in step S3 includes: Using the major axis of the circumscribed rectangle as the initial heading, a heading angle search space is established within the constraint boundary determined by the UAV takeoff performance parameters; The objective function is to maximize the geometric matching degree or minimize the inlet offset, and an iterative search is performed in the heading angle search space. When the convergence accuracy of the search results meets the preset conditions, the current search value is determined as the target takeoff heading angle.

[0029] In calculating the target takeoff heading angle, the algorithm fully couples the UAV's takeoff performance parameters to ensure that the optimized heading not only meets geometric matching requirements but also conforms to the UAV's actual flight capabilities. Specifically, it needs to obtain three core performance parameters of the UAV: ​​minimum turning radius, maximum climb gradient, and takeoff speed. The minimum curvature radius constraint of the departure route is determined based on the minimum turning radius. That is, the turning radius of the departure route in the horizontal plane must be greater than or equal to the minimum turning radius. If the curvature radius of the departure turning trajectory corresponding to the target takeoff heading angle is less than this constraint value, it is determined that the heading angle exceeds the maneuverability range of the UAV and should be excluded from the search space. The maximum allowable value of the departure climb angle is determined based on the maximum climb gradient. This maximum allowable value is equal to the climb angle corresponding to the maximum climb gradient. The climb trajectory angle of the departure route must not exceed this value to ensure that the UAV has sufficient remaining power to complete the climb maneuver during the takeoff phase. The response time constraint for heading adjustment is determined based on the takeoff speed. That is, based on the ground speed change characteristics of the UAV from takeoff roll to takeoff, the time window available for heading adjustment is calculated. The heading adjustment command must be completed within this time window, and the adjustment rate should match the takeoff speed to avoid insufficient response or over-adjustment due to excessive speed. Under the combined constraints of the minimum radius of curvature, maximum allowable value, and response time, a heading angle search space is established. In practice, the initial heading is taken as the direction of the major axis of the circumscribed rectangle. A search boundary is established within the feasible region defined by the three constraints mentioned above. The objective function is to maximize the geometric matching degree or minimize the entry offset. An iterative search is performed within the heading angle search space. When the convergence accuracy of the search results meets preset conditions, such as the change in the objective function value obtained from multiple consecutive iterations being less than a preset threshold, or the heading angle adjustment range being less than the minimum adjustment step size, the search results are considered to have converged. The current search value is then determined as the target takeoff heading angle, thus achieving dynamic coupling between geometric optimization and flight performance constraints.

[0030] S4. Generate a departure route based on the target takeoff heading angle, and perform boundary constraint correction on the departure route according to the boundary coordinates to ensure that the departure route is within the irregular polygonal airspace and maintains a safe distance from the boundary. Output a collaborative optimization scheme that includes the target takeoff heading angle and the corrected departure route.

[0031] Step S4, which involves generating the departure route based on the target takeoff heading angle, includes: The initial departure direction is determined based on the target takeoff heading angle. The climb and turning trajectories are calculated using the UAV's takeoff performance parameters. These trajectories are then discretized to generate a sequence of waypoints, which are then connected to form the departure route. The specific implementation rules for trajectory discretization are as follows: the discretization interval for the climb trajectory is determined based on the altitude change rate corresponding to the maximum climb gradient, ensuring that the altitude difference between adjacent waypoints does not exceed the linear approximation range of the UAV's vertical maneuverability. The discretization of the turning trajectory is based on equal-angle division according to the arc length corresponding to the minimum turning radius, ensuring a uniform distribution of the heading angle change at each waypoint and avoiding abrupt curvature changes at the start and end of the turn. To address the anisotropic characteristics of irregular airspace boundaries, a denser discretization strategy is employed in segments close to the airspace boundary, reducing the standard discretization interval to one-third to one-half of the original interval to improve the accuracy of subsequent boundary constraint corrections.

[0032] In step S4, the boundary constraint correction of the departure route based on the boundary coordinates includes: Extract the boundary segments of the irregular polygonal airspace, calculate the vertical distance from each track point on the departure route to the boundary segment, and when the vertical distance is less than the safety distance, push the corresponding track point outward along the normal direction of the boundary segment to meet the safety distance to form the corrected departure route; wherein, the conflict resolution mechanism when a track point is close to multiple boundaries at the same time is as follows: when the vertical distance from a track point to two adjacent boundary segments is less than the safety distance, or when it is in the boundary angle region, calculate the position after pushing outward along the normal direction of each boundary, and select the outward scheme that makes the final position of the track point closest to the center of the airspace; if a new boundary violation occurs after the outward push (i.e., the corrected track point is closer to the other boundary), a secondary correction is triggered, and the track point position is appropriately adjusted back along the long axis of the airspace until all boundary constraints are met; for a local narrow area formed by a concave boundary, if it is found that multiple consecutive track points need to be outwarded and the outward directions are opposite (indicating that the route passes through a narrow channel), the channel is directly marked as a no-fly zone, and the heading angle is re-searched to avoid the geometric conflict area.

[0033] The supplementary explanation is the specific output format of the collaborative optimization scheme: the collaborative optimization scheme adopts a mixed storage of structured text and binary geographic data, and the core includes four parts of data: (1) metadata header, which records the target takeoff heading angle value, safety distance setting value, geometric matching degree calculation result and heading correction algorithm triggering identifier; (2) track point sequence, which stores the three-dimensional coordinates of each track point, the cumulative distance from the runway entrance, the correction identifier (marking whether the point has undergone boundary extrapolation correction) and the extrapolation distance value in CSV format; (3) airspace boundary topology, which stores the vertex coordinate sequence of irregular polygonal airspace and the direction vector of boundary line segments in WKT format for subsequent flight procedure verification; (4) constraint verification report, which records the statistical value of the actual vertical distance from each track point to the nearest boundary line segment, as well as the tracking deviation analysis of the route relative to the major axis of the circumscribed rectangle, for the approval department to check the balance between airspace utilization and safety margin.

[0034] Among them, T / CAGIS 4-2021 is the current group standard formulated by the China Association of Geographic Information Industry (CAGIS), which came into effect on March 22, 2021. It specifies the classification system and geometric parameter requirements for the integrated verification field of unmanned aerial vehicles.

[0035] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A collaborative optimization design method for the airspace and take-off and landing site of a comprehensive UAV verification field, characterized in that, Includes the following steps: S1. Construct a joint digital twin model of the airspace and take-off and landing site of the UAV integrated verification field. The take-off and landing site includes the runway and supporting facilities, and the airspace is an irregular polygonal airspace that has been approved. S2. Obtain the boundary coordinates of the irregular polygonal airspace and the azimuth data of the runway. Calculate the circumscribed rectangle of the irregular polygonal airspace based on the boundary coordinates and determine the safety distance. Calculate the matching parameters between the runway extension line and the major axis of the circumscribed rectangle and determine the geometric matching degree. S3. When the geometric matching degree is lower than the preset threshold, the heading correction algorithm is triggered. Based on the direction of the major axis of the circumscribed rectangle, the target takeoff heading angle is calculated in combination with the UAV takeoff performance parameters. S4. Generate a departure route based on the target takeoff heading angle, and perform boundary constraint correction on the departure route according to the boundary coordinates to ensure that the departure route is within the irregular polygonal airspace and maintains a safe distance from the boundary. Output a collaborative optimization scheme that includes the target takeoff heading angle and the corrected departure route.

2. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, The steps for constructing the joint digital twin model of the airspace and take-off and landing site of the UAV integrated verification field in step S1 are as follows: Obtain topographic mapping data and facility layout data of the take-off and landing site, and construct a three-dimensional model of the take-off and landing site based on the topographic mapping data, including runway elevation, slope and spatial location of supporting facilities. Extract the horizontal projection boundary and vertical height range of the irregular polygonal spatial domain, and construct a three-dimensional spatial domain model including spatial domain boundary constraints; The three-dimensional model of the take-off and landing site is registered with the three-dimensional airspace model to ensure that the runway centerline and the reference axis of the airspace are in the same coordinate system, and a spatial mapping relationship between the take-off and landing site and the airspace is established to form the joint digital twin model.

3. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, Step S2, which involves calculating the circumscribed rectangle of the irregular polygonal spatial region based on the boundary coordinates and determining the safety distance, is as follows: The boundary coordinates of the irregular polygonal spatial domain are extracted from the joint digital twin model, wherein the boundary coordinates are the latitude and longitude or rectangular coordinates of each vertex of the irregular polygonal spatial domain; Boundary feature points of an irregular polygonal spatial domain are extracted based on boundary coordinates. The boundary feature points include the extreme points of the irregular polygonal spatial domain in each projection direction. The circumscribed rectangle is constructed based on the boundary feature points, and the direction of the long side of the circumscribed rectangle is determined as the major axis. The safety distance is determined based on the geometric dimensions of the circumscribed rectangle, and the safety distance is positively correlated with the length and width dimensions of the circumscribed rectangle.

4. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, Step S2 involves calculating the matching parameters between the runway extension line and the major axis of the circumscribed rectangle to determine the geometric matching degree. The steps are as follows: The direction of the runway extension line is determined based on the runway azimuth data. Extract the major axis direction vector of the circumscribed rectangle; Calculate the angle between the direction of the runway extension line and the vector of the major axis direction; Calculate the vertical projection distance from the runway entrance center point to the major axis direction vector to determine the entrance offset; The geometric matching degree is determined based on the weighted sum of the included angle and the entrance offset.

5. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, The preset threshold mentioned in step S3 is determined based on the ratio of the length and width of the circumscribed rectangle to the length of the runway.

6. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, The heading correction algorithm described in step S3, using the major axis direction of the circumscribed rectangle as a reference, consists of the following steps: Extract the coordinate difference between the two endpoints of the major axis of the circumscribed rectangle to construct a direction vector, and normalize the direction vector to obtain the unit reference direction vector; The first deflection component is calculated based on the included angle in the geometric matching degree. The first deflection component is positively correlated with the included angle. The second deflection component is calculated based on the ratio of the entrance offset to the short side dimension of the circumscribed rectangle in the geometric matching degree. The first deflection component and the second deflection component are weighted and summed to obtain the heading deflection angle. A rotation matrix is ​​constructed based on the heading deflection angle. The rotation matrix is ​​then used to rotate and transform the unit reference direction vector. The transformed direction vector is then normalized to determine the target takeoff heading angle.

7. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, The combination of UAV takeoff performance parameters mentioned in step S3 includes: Obtain the drone's minimum turning radius, maximum climb gradient, and takeoff speed; The minimum curvature radius constraint of the departure route is determined based on the minimum turning radius, the maximum allowable value of the departure climb angle is determined based on the maximum climb gradient, and the maximum allowable value is equal to the climb angle corresponding to the maximum climb gradient. The response time constraint of the heading adjustment is determined based on the takeoff speed. The target takeoff heading angle is calculated under the combined constraints of minimum radius of curvature, maximum allowable value, and response time.

8. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, The calculation of the target takeoff heading angle in step S3 includes: Using the major axis of the circumscribed rectangle as the initial heading, a heading angle search space is established within the constraint boundary determined by the UAV takeoff performance parameters; The objective function is to maximize the geometric matching degree or minimize the inlet offset, and an iterative search is performed in the heading angle search space. When the convergence accuracy of the search results meets the preset conditions, the current search value is determined as the target takeoff heading angle.

9. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 1, characterized in that, Step S4, which involves generating the departure route based on the target takeoff heading angle, includes: The initial departure direction is determined based on the target takeoff heading angle. The climb trajectory and turning trajectory are calculated in combination with the UAV takeoff performance parameters. The climb trajectory and turning trajectory are discretized to generate a track point sequence. The track point sequence is then connected to form the departure route.

10. The method for collaborative optimization design of airspace and take-off and landing sites for integrated UAV verification fields according to claim 9, characterized in that, In step S4, the boundary constraint correction of the departure route based on the boundary coordinates includes: Extract the boundary line segment of the irregular polygonal airspace, calculate the vertical distance from each track point on the departure route to the boundary line segment, and when the vertical distance is less than the safe distance, push the corresponding track point outward along the normal direction of the boundary line segment to meet the safe distance, so as to form the corrected departure route.

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