An airport clearance three-dimensional visualization management system

Abstract

The application discloses an airport clearance three-dimensional visualization management system, and particularly relates to the technical field of three-dimensional space analysis, and parameterized modeling is carried out on clearance limiting surfaces such as an approach surface, a take-off climb surface, a missed approach surface, a transition surface, a horizontal surface and a conical surface based on the Technical Standard for Civil Airport Flight Zones. On this basis, a high-fidelity scene of airport characteristic ground objects is constructed, accurate registration of the limiting surface, ground objects and terrain is realized, a terrain self-adaptive permissible height computer mechanism is introduced into the platform, normal projection fast mode, terrain enhanced profile mode and dynamic switching of a mixed mode of the two are supported, through multi-temporal remote sensing images and change detection technology, the platform can automatically identify and label over-limit obstacles, generate a risk list and link to a patrol task scheduling. Meanwhile, three-dimensional modeling and automatic detection of reference height protection zones and flight procedure protection zones are provided, and data management and intelligent retrieval functions are equipped, forming a traceable digital clearance management archive system.

Description

Technical Field

[0001] This invention relates to the field of three-dimensional spatial analysis technology, and more specifically, to an airport airspace three-dimensional visualization management system. Background Technology

[0002] Airport airspace management is crucial for ensuring safe space margins for aircraft during takeoff, landing, and flight procedures. Its core lies in determining the spatial relationship between the restricted surface and surrounding obstacles, and managing the risk of exceeding limits. Current technologies primarily rely on two-dimensional drawings or static three-dimensional models, often using the restricted surface normal projection method to calculate permissible heights. However, this method is prone to calculation errors in complex areas with significant terrain undulations or where man-made structures overlap with natural landforms, leading to missed or incorrect over-limit assessments.

[0003] In addition, traditional systems generally lack the ability to link with multi-temporal ground feature change detection, making it difficult to detect newly added or renovated oversized obstacles in a timely manner; in terms of patrol management, they rely heavily on manual experience to plan routes and lack a task priority scheduling mechanism based on risk lists and operational status, resulting in low patrol efficiency and untimely response.

[0004] Meanwhile, existing data management methods are fragmented and lack unified multidimensional indexes and spatial information associations, failing to provide efficient support for subsequent flight procedure protection zone analysis, historical data backtracking, and regulatory reporting. Therefore, there is an urgent need for an airport airspace 3D visualization management system that integrates high-precision restriction surface modeling, terrain-adaptive clearance height calculation, dynamic obstacle monitoring, intelligent patrol scheduling, and full lifecycle data management to improve the accuracy, efficiency, and informatization level of airspace protection. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an airport airspace three-dimensional visualization management system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: An airport airspace clearance 3D visualization management system includes the following modules: The constraint surface modeling and datum transformation module is used to establish the local runway coordinate system and parametrically model the constraint surfaces in the local runway coordinate system. The constraint surfaces include the approach surface, takeoff and climb surface, miss landing surface, transition surface, inner horizontal surface, outer horizontal surface, and conical surface. The constraint surface model is then transformed to the geographic coordinate system and combined with geoid correction to achieve unified elevation datum. The permitted height calculation and terrain adaptive analysis module is used to determine the average slope angle and elevation undulation, calculate the comprehensive discrimination value by weighted summation, and select the permitted height calculation mode in combination with the adaptive hysteresis band strategy. When the comprehensive discrimination value is greater than Permissible height is calculated using a terrain-enhanced profile model; when the comprehensive discrimination value is less than The permissible height is calculated using the fast mode of normal projection; when the comprehensive discrimination value is in [ , Simultaneously, two modes are executed, and the permissible height is determined by using the conservative minimum value method based on the calculation results of both modes; whereby... To switch thresholds, The hysteresis band is half the width; The obstacle dynamic monitoring and risk labeling module is used to compare the permitted height with the obstacle height to determine whether there is an over-limit situation; for over-limit obstacles, a risk list is automatically generated and highlighted in the 3D scene, recording their location coordinates, height, area occupied and impact range.

[0007] In a preferred embodiment, the formula for calculating the hysteresis band half-width is as follows: ;in and The upper and lower limits of the hysteresis band half-width are defined as the engineering limits, and the exponents p and q are the sensitivity controls for the two factors. γ(t) represents the data reliability and the scenario complexity value.

[0008] In a preferred embodiment, data reliability is determined by a combination of the sensor source signal-to-noise ratio, terrain grid resolution, and data acquisition timeliness.

[0009] In a preferred embodiment, elevation data is first extracted from a high-precision digital elevation model or a triangulated network reconstructed by oblique photogrammetry, and slope, curvature, and undulation are calculated. The slope is obtained by averaging the elevation gradient norm of the neighborhood; the curvature is calculated by the discrete Laplacian operator or local quadratic surface fitting to obtain the mean absolute curvature; and the undulation is obtained by the standard deviation of the neighborhood elevation. The three features are compared with the benchmark values ​​and normalized proportionally to the 0 to 1 range. Then, they are weighted and fused according to preset weight coefficients to obtain the scene complexity value.

[0010] In a preferred embodiment, the terrain enhancement profile mode lays out profile sampling lines along the main slope direction of the point to be detected and the direction orthogonal to it, obtains the noise-reduced elevation curve within the profile range, and calculates the intersection elevation point along the normal direction of the constraint surface point by point. After deducting the safety margin, the permissible height in each profile direction is obtained, and finally the minimum value or the permissible height is determined by confidence weighted average.

[0011] In a preferred embodiment, the normal projection fast mode obtains the intersection point elevation by analytical or numerical intersection along the normal direction of the constraint surface, and determines the permissible height after deducting the measurement error correction, terrain grid correction, and operational safety redundancy.

[0012] In a preferred embodiment, the obstacle height is obtained by calling up multi-temporal high-resolution remote sensing images or oblique photography data to detect ground feature changes and invert height.

[0013] In a preferred embodiment, the system further includes a patrol task scheduling and mobile terminal interaction module, which generates patrol routes based on the risk list, patrol priority, runway operation window and weather conditions, and sends them to the patrol officer's terminal.

[0014] In a preferred embodiment, it further includes a data management and intelligent retrieval module, which is used to centrally store clearance limit surface parameters, 3D models, remote sensing images, inspection records, inspection reports and historical data, and establish multi-dimensional indexes and metadata tags to realize bidirectional association and retrieval with the 3D scene.

[0015] The technical effects and advantages of this invention are as follows: This invention establishes a local runway coordinate system at runway threshold points and performs parametric constraint surface modeling. By combining three-parameter or seven-parameter Helmert transform with geoid correction, it achieves high-precision unification of the constraint surface model and geospatial data, effectively eliminating calculation errors caused by different coordinate and elevation benchmarks and improving the accuracy of clearance determination. The system introduces a comprehensive discrimination quantity based on average slope angle and elevation undulation, and dynamically selects the permissible height calculation mode using an adaptive hysteresis band strategy. This enables rapid calculation in flat terrain and maintains judgment accuracy in complex terrain, avoiding frequent mode switching or sluggish response. When the comprehensive discrimination quantity is in the critical range, it simultaneously executes the terrain enhancement profile mode and the normal projection fast mode, fusing the results according to the conservative minimum principle, balancing computational efficiency and safety, and effectively improving the safety margin when uncertainties exist.

[0016] This invention also generates an over-limit risk list by comparing permitted heights with obstacle heights, and highlights over-limit targets in a 3D scene. Combined with their location, height, and area footprint, this provides intuitive and accurate risk visualization support for operation control and maintenance personnel. The system can generate optimal patrol routes based on the risk list, patrol priorities, runway operation windows, and weather conditions, and distribute these routes to patrol personnel's mobile terminals, enabling intelligent scheduling and execution of patrol tasks. It can collect on-site data in real time and transmit and alert immediately, thereby improving the efficiency and focus of patrol operations. Furthermore, it centrally stores airspace management-related restriction surface parameters, 3D models, remote sensing images, inspection reports, and historical records, establishing multi-dimensional indexes and metadata tags, and linking them with the 3D scene for centralized data management, rapid retrieval, and traceability, significantly improving information management and utilization efficiency. Attached Figure Description

[0017] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a schematic diagram of the structure of an airport airspace three-dimensional visualization management system according to the present invention; Figure 2 This is a schematic diagram of the adaptive hysteresis band strategy of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1 This invention provides a three-dimensional visualization management system for airport airspace, such as... Figure 1 As shown, it includes the following modules: The constraint surface modeling and datum transformation module is used to establish the local runway coordinate system and parametrically model the constraint surfaces in the local runway coordinate system. The constraint surfaces include the approach surface, takeoff and climb surface, miss landing surface, transition surface, inner horizontal surface, outer horizontal surface, and conical surface. The constraint surface model is transformed to the geographic coordinate system and the elevation datum is unified by combining geoid correction.

[0020] Specifically, a local runway coordinate system is first established at the runway end threshold point. The origin of this coordinate system is set at the runway end threshold point, the X-axis points in the positive direction along the runway centerline, the Y-axis points to the left side of the runway, and the Z-axis points vertically upward, using orthographic elevation as the elevation reference. All limiting surfaces are parametrically modeled in this local coordinate system, with parameters including slope, lateral divergence rate, inner width, surface length, and initial elevation. The value range is set according to the "Technical Standards for Civil Airport Flight Areas".

[0021] For the approach face, its half-width varies with the longitudinal distance. According to the formula Linearly increasing, where, Represents the inner width, i.e., the starting section of the limiting surface (longitudinal distance). The total width at point 0 is obtained by looking up the corresponding airport category and runway type in the "Technical Standards for Civil Airport Flight Areas"; Represents the lateral divergence rate, which is the linear expansion ratio of the limit face half-width as the longitudinal distance increases. It is specified by the standard clauses and takes different values ​​for different face types (e.g., 0.125 is often used for the approach face). Representing longitudinal distance, it refers to the distance measured along the centerline of the limiting surface from the starting section of the limiting surface (such as the runway end threshold line) in the local runway coordinate system. Represents half width.

[0022] Longitudinal elevation is calculated using the following formula: Linear increase, of which, Vertical elevation; Represents the initial elevation, the elevation at the starting point of the restriction surface, which is usually the orthographic elevation of the runway end threshold point (determined in conjunction with runway elevation measurement results). Represents the slope, limiting the rate of elevation of the surface along the longitudinal direction, i.e., the amount of height increase per meter of longitudinal extension. The value varies depending on the surface type as specified by the standard (e.g., approach surfaces are often 1:50, i.e., S = 0.02). The coordinates of any point on the surface can be obtained from This indicates that the longitudinal distance s ranges from zero to the surface length L, and the absolute value of the lateral coordinate y does not exceed half the width w(s). The takeoff climb surface has the same form as the approach surface, using only specific parameters of the takeoff procedure; the go-around surface also adopts the same structure, but allows for segmented construction at the program axis inflection points while ensuring continuity at the joints.

[0023] The transition surface is defined by the runway edge or approach side as the generatrix, and the normal lateral distance d is calculated as follows: Elevation, among which Represents the elevation of the parent edge, the elevation of the parent edge point at longitudinal position s (elevation value on the runway edge or approach face side). Represents the slope of the transition surface, the slope of the transition surface that rises outwards, as specified by the standard (a common value is 1:7, i.e.) ≈0.142857); It represents the lateral distance of the transition surface, the horizontal distance measured outward from the parent edge (runway edge or approach surface side) using the normal vector.

[0024] Both the inner and outer horizontal planes are fixed elevation planes, each taken at a fixed height above the reference elevation; the conical surface is determined by the inner radius of the conical surface. (i.e., the horizontal radius of the outer edge of the inner horizontal plane, determined by the airport category and relevant standards) starting from the radius direction with a slope Increasing sequentially, its elevation satisfies the following formula: This continues until the applicable upper limit of the conical surface is reached, which is increased according to the above formula; where It represents the elevation of the inner horizontal plane, usually taken as the airport reference elevation plus a fixed height (such as 45 meters), as specified by the standard; Represents the slope of a conical surface, the slope that rises outward from the outer edge of the inner horizontal plane, a standard specified value (e.g., 1:20, i.e.) = 0.05); Represents the horizontal radius, which is the horizontal distance from the airport reference point or the center point of the inner horizontal plane to the calculated location; The inner radius of the conical surface refers to the horizontal radius of the outer edge of the inner horizontal plane, determined by the airport category and standards. After generating various restriction surfaces, the minimum value of all restriction surfaces is taken as the final restriction elevation for the permissible height at the same location, ensuring that the strictest constraints are applied to airspace determination.

[0025] After completing the geometric construction in the local coordinate system, it needs to be transformed to a geographic coordinate system (CGCS2000 or WGS-84) to achieve accurate alignment with the actual geographical location. The transformation process uses a three-parameter or seven-parameter Helmert transform, where the three-parameter form involves adding a translation vector to the original coordinate vector. The seven-parameter form adds a scale correction m (where m represents the scale correction, a scaling factor in Helmert's seven parameters used to unify the scale) and a small-angle rotation matrix to this basis. Its approximate expression is: ;in , , The rotation angle, a small-angle rotation among Helmert's seven parameters, defines the attitude difference between the two coordinate systems on the three axes.

[0026] The resulting geocentric coordinates are then converted to latitude, longitude, and height using the geodetic coordinate and ECEF coordinate conversion formula. The undulations N are then corrected using a geoid model, and the orthographic height is obtained by H=hN, thus achieving a unified elevation datum. N represents the geoid undulations, calculated by a geoid model (such as CGG2020), and is used to convert the ellipsoidal height h to the orthographic height H.

[0027] By combining the above-mentioned constraint surface equation definition, coordinate and elevation datum transformation, and accuracy control strategy, the geometric rigor and spatial alignment accuracy of the clearance 3D model in this embodiment are ensured, providing a reliable spatial data foundation for subsequent clearance altitude determination, obstacle detection, and flight safety assessment.

[0028] The Airport Feature 3D Scene Construction Module is used to carry out unified 3D modeling and scene reconstruction of airport feature features within the coverage area of ​​the airspace protection zone after the 3D model of the airspace protection zone restriction surface is completed.

[0029] First, field data collection personnel used high-resolution digital cameras, laser scanners, and panoramic acquisition equipment to conduct multi-angle, comprehensive on-site photography of key airport facilities such as terminals, runways, taxiways, aprons, navigation beacons, radar towers, oil depots, perimeter fencing, and signage. This data captured surface texture features, structural details, and precise spatial location and size information. The acquired raw data underwent noise reduction, registration, and texture mapping optimization by the data processing module to ensure a high degree of consistency between the geometric shapes and the actual ground features.

[0030] Subsequently, according to pre-defined airport feature classification standards, each type of target is standardized, including uniform scaling factors, material parameters, texture coordinate systems, and illumination reflection attributes, forming reusable standardized 3D model units. These standardized models are then stored in a feature model library. The library's structure supports indexing and management based on facility type, spatial location, acquisition time, and version information for rapid subsequent retrieval and updates. During the scene assembly stage, based on airport geographic coordinates and terrain elevation data, the 3D restriction surface of the airspace protection zone is precisely registered with the feature model in the geographic coordinate system. Each model is then embedded into the scene according to its actual location, orientation, and elevation, constructing a high-fidelity 3D scene of the entire airport. This scene not only allows for roaming, zooming, and layered display within the platform but also enables data interaction with subsequent modules such as obstacle monitoring, patrol navigation, and flight procedure protection zone analysis. It provides a complete visual representation of the static basic environment within the airport's airspace, offering an intuitive and high-precision 3D spatial reference for airspace management monitoring, analysis, and decision-making.

[0031] The Permitted Height Calculation and Terrain Adaptive Analysis module is used to automatically calculate and dynamically monitor the permitted height of obstacles at any location around the airport after the unified scene construction of the 3D restriction surface and characteristic features of the airport's airspace protection zone is completed. This process first calls the established 3D airspace model, transforms the geographic coordinates of the location to be detected to the local runway coordinate system through a 3 / 7 parameter Helmert transform and elevation datum correction, and projects it onto the corresponding restriction surface geometric space. Subsequently, the theoretical permitted height value at this location is accurately calculated through spatial intersection operations. Combined with multi-temporal high-resolution remote sensing imagery and oblique photography data, feature change detection and height inversion are performed to determine whether newly added or reconstructed buildings pose a risk of exceeding limits.

[0032] In normal environments, the permissible height calculation method is based on the projection of the constraint surface's normal direction. This involves finding the intersection point of the point to be detected along the normal direction in the constraint surface equation and using the elevation of this intersection point as the permissible height. However, in environments surrounding airports with significant topographic relief (such as airports near mountains, water, or plateaus), there may be a significant difference in elevation between the geometric projection of the constraint surface and the actual terrain surface, especially in areas with steep slopes or where artificial structures overlap with natural landforms. Traditional normal projection methods are prone to misjudgments near the constraint surface boundary. For example, when constructing a new building on the windward side of a hillside, its apex may not exceed the clearance range in the horizontal projection, but the calculation along the normal direction will underestimate the actual spatial distance to the constraint surface, leading to missed detections.

[0033] To balance computational efficiency in flat terrain with accuracy in complex terrain, this embodiment introduces a terrain-adaptive method selection mechanism before calculating the permissible height. First, taking the three-dimensional coordinates p of the point to be detected as the center, the elevation data of a high-precision digital elevation model (DEM) or an oblique photogrammetry 3D reconstruction model is extracted within a radius R to determine the average slope angle and elevation undulation within this range.

[0034] The average slope angle refers to the local surface inclination calculated from the terrain elevation data collected within a specified neighborhood radius R centered on the point to be detected. Physically, it represents the average angle of inclination of the terrain in that neighborhood relative to the horizontal plane. The average slope angle reflects the overall tilt trend of the terrain surface; a larger value indicates a steeper terrain. In clearance protection determination, a larger average slope angle implies a more complex geometric relationship between the limiting surface and the terrain, making simple normal projection prone to errors. Therefore, more attention needs to be paid to such areas in terrain adaptive selection mechanisms.

[0035] Elevation relief refers to the magnitude of elevation changes within the same neighborhood, expressed as the standard deviation of elevation values. Elevation relief reflects the degree of unevenness of the local surface; a larger value indicates significant topographic relief, potentially indicating areas with rapid elevation changes such as hills, valleys, or building clusters. These areas also increase the risk of misjudgment or omission in clearance calculations.

[0036] The calculation formula is as follows: ;in Represents the comprehensive discrimination measure. Represents the average slope angle. Represents elevation undulation. and These are the benchmarks for the average slope angle and elevation undulation, respectively (used for normalization, with values ​​determined by historical samples or set according to engineering thresholds). and The weights are used to reflect the proportion of attention given to the two types of complexity; for example... =0.6, =0.4.

[0037] In this embodiment, to avoid frequent switching or unstable determination due to fluctuations in terrain feature parameters during the switching of the calculation method for permissible height determination, a three-mode switching strategy based on adaptive hysteresis band is introduced. When the comprehensive discrimination value is greater than... Permissible height is calculated using a terrain-enhanced profile model; when the comprehensive discrimination value is less than The permissible height is calculated using the fast mode of normal projection; when the comprehensive discrimination value is in [ , Simultaneously, it executes the calculation processes of terrain enhancement profile mode and normal projection fast mode, and outputs the combined calculation results of the two according to preset fusion rules as the permissible height determination value, so as to balance safety margin and calculation response speed within the transition range. The switching threshold; The process for obtaining the hysteresis band half-width is as follows: First, the signal-to-noise ratio of the sensor source is obtained. Before each permitted height calculation, the input raw elevation data is processed to separate the signal and noise: first, a sliding window low-pass filter is used to obtain the smoothed terrain signal component, and then the noise component is obtained by subtracting the smoothed result from the raw data. The root mean square value of each component is then calculated. and The signal-to-noise ratio is defined as: ; and linearly normalize it to map it to the interval [0,1] as The normalization upper and lower limits are determined by the historical calibration dataset.

[0038] The terrain raster resolution *r* is directly obtained from the spatial index of the input digital elevation model (DEM) or oblique photogrammetric 3D mesh: for regular raster DEMs, the terrain raster resolution is equal to the ground projection spacing between adjacent grid points; for triangular mesh (TIN) models, the terrain raster resolution can be taken as the average side length of the model within the detection area. A reference resolution is also set. (e.g., 0.5 meters), and introduce the resolution ratio when calculating data reliability. Suppress the uncertainty caused by excessively coarse resolution.

[0039] Data timeliness It is obtained directly from the difference between the timestamp of the input data and the current calculation time. A time decay constant is set. And adopt an exponential decay term Mapping the impact of time lag to reliability weights, when data update delays approach or exceed... When this weight decreases significantly, it prompts greater conservatism in hysteresis band calculation.

[0040] The above three factors are calculated using the following formula: Overall data reliability ; Scene complexity γ(t) serves as a crucial input parameter for dynamic adjustment of the hysteresis band half-width, directly reflecting the impact of local terrain geometry on computational stability and the risk of misjudgment during the permissible height determination process. To ensure that this parameter accurately characterizes terrain undulation and complexity at different spatial locations, elevation data is extracted from a high-precision digital elevation model (DEM) or a triangulated network (TIN) reconstructed from oblique photogrammetry within a radius R around the location to be inspected, and geometric features such as slope, curvature, and undulation are calculated.

[0041] Specifically, the slope index is obtained by averaging the norms of the neighborhood elevation gradient, reflecting the degree of surface inclination; the curvature index is calculated by using the discrete Laplace operator or fitting a local quadratic surface to determine the mean absolute curvature, used to characterize the degree of abrupt changes in terrain; and the undulation index uses the standard deviation of the neighborhood elevation to represent the amplitude of elevation fluctuations, sensitively reflecting nonlinear undulations such as cliff lines and terraces. These three features are compared with the baseline slope, baseline curvature, and baseline undulation obtained from offline calibration, and then normalized proportionally to the [0,1] interval. The normalized results are then weighted according to coefficients. , , Perform weighted fusion (e.g.) =0.45、 =0.30、 =0.25), and the scene complexity value γ(t) is obtained from it, as shown in the following formula: ;in, , , ; The average value of the neighborhood gradient norm. Represents the baseline gradient; Represents the average absolute value of the neighborhood curvature (discrete Laplace). Represents the reference curvature; Represents elevation undulation. Represents the baseline relief. The neighborhood is generally a circular or square area with a radius of R (in terrain raster data, it is a window centered on that point and containing a certain number of pixels), used to extract the surrounding elevation values ​​for geometric feature calculations.

[0042] To determine the width of the uncertain band, the hysteresis band half-width h(t) is defined; the formula for calculating the hysteresis band half-width is as follows: This formula will Linear mapping in Inside, and The upper and lower limits of the hysteresis band half-width are set for engineering purposes; this prevents excessively narrow bands from causing frequent switching, and excessively wide bands from causing sluggish response; for example... =0.5 meters, =3.0 meters; the exponents p and q are used to control the sensitivity to the two factors. For example, an exponent p of 2.0 means that when the data reliability decreases slightly, the increase in the hysteresis band half-width is relatively gradual, so as to avoid excessively widening the allowable range when there is a single low signal-to-noise ratio fluctuation or short-term data timeliness degradation; an exponent q of 1.5 means that the sensitivity to scene complexity is slightly higher than that of linear response. When the monitoring area has a steep change in slope, increased curvature or increased elevation fluctuation, the hysteresis band half-width will expand more significantly to enhance the safety margin in complex environments.

[0043] When the comprehensive discriminant value is greater than The specific steps for calculating the permissible height using the terrain-enhanced profile model are as follows: Under a unified coordinate reference, the topographic gradient information of the point to be detected is first extracted, the main slope aspect unit vector is calculated, and the projection direction of the constraint surface normal onto the horizontal plane is obtained simultaneously. These two constitute the main direction set for profile analysis. When the angle between the two directions is less than a certain angle (e.g., 10 degrees), a horizontal vector orthogonal to the main direction is added as the second profile direction.

[0044] In each profile direction, with the point to be detected as the center, profile sampling lines are laid out on the horizontal plane according to the half length of the profile (0.6 to 1.0 times the neighborhood radius) and the sampling interval (not less than half the DEM grid resolution and not less than 0.25 meters). Mean smoothing is then performed within the horizontal bandwidth perpendicular to the profile (1 to 2 times the DEM grid resolution) to obtain the noise-reduced profile elevation curve.

[0045] Subsequently, starting from each sampling point in the profile, intersections are found point by point along the normal direction of the constraint surface. For planar constraint surfaces, an analytical method is used; for general curved surfaces, a one-dimensional numerical root-finding method is used. The recommended convergence accuracy is 0.001–0.01 meters. The permissible height for each sampling point is obtained by subtracting the ground elevation at that point from the intersection elevation, and then subtracting the safety margin. Within each profile, the minimum permissible height is selected as the result for that direction; for multiple directions, the minimum value is taken, or the permissible height is determined by a confidence-weighted average (the confidence level can be calculated from the slope modulus and balance factor). The permissible height, under given terrain conditions and constraint surface limitations, is the maximum height allowed to be reached upwards from the ground starting point at the target location, without crossing the constraint surface and while meeting the safety margin requirements.

[0046] like Figure 2 As shown, when the comprehensive discriminant is less than The specific steps for calculating the permissible height using the normal projection fast mode are as follows: First, under a unified local coordinate system and elevation datum, the planar coordinates of the point to be detected are projected onto the elevation model (DEM or TIN). The ground elevation value at that location is obtained through an interpolation function, and the three-dimensional coordinates of the ground starting point are determined accordingly. Then, the normal vector of the constraint surface is obtained according to its geometric definition, and it is normalized as the direction of the projection ray. The ray equation extending from the ground starting point along the normal vector is constructed.

[0047] For planar constraint surfaces, the intersection points of the ray and the constraint surface are directly obtained using analytical methods, and the elevation value of the intersection point is taken as the constraint elevation. For general implicit curved surface constraint surfaces, numerical root-finding methods such as Newton's iteration, secant method, or bisection method are used, with a suggested iteration convergence error tolerance of 0.001–0.01 meters. When calculating the permissible height, the ground elevation is subtracted from the intersection elevation, and then a safety margin is deducted. The safety margin includes measurement error correction (e.g., 0.05–0.10 m), terrain grid discretization correction (e.g., 0.05–0.20 m), and operational safety redundancy (e.g., 0.10–0.30 m). The final permissible height is then determined.

[0048] When the comprehensive discriminant is in [ , Simultaneously, the calculation processes of the terrain enhancement profile mode and the normal projection fast mode are executed, and the calculation results of both are output as the permissible height using the conservative minimum method, as shown in the following formula: ; Indicates the permitted height. This indicates the permissible height obtained by performing the terrain-enhanced profile model calculation; This represents the permitted height obtained by performing the fast mode calculation of normal projection.

[0049] The obstacle dynamic monitoring and risk labeling module is used to cross-compare the permitted height with the real-time height measurement data of the obstacle after the permitted height is determined, identify the obstacle that exceeds the limit, and integrate and package the information of the obstacle that exceeds the limit into a risk list; the information of the obstacle that exceeds the limit includes the latitude and longitude of the obstacle, the height of the building, and the area it occupies.

[0050] The patrol task scheduling and mobile terminal interaction module is used to conduct patrol task scheduling and execution management for airport feature features within the restricted area of ​​the airspace protection zone after completing the dynamic monitoring and risk labeling of obstacle clearance height, so as to ensure the rapid discovery and timely handling of potential risks.

[0051] First, based on the constructed 3D airspace model and feature scene, as well as the risk list, the system automatically selects target facilities requiring priority inspection. It then generates the optimal inspection route plan by considering their geographical location, risk level, inspection priority, and personnel work sequence. This plan, while considering the shortest path, also adjusts the path based on runway operational status, control area openness, and weather conditions to ensure that inspection activities do not affect flight operation safety. Inspection tasks are distributed to the inspectors' mobile terminals via the platform. The terminal's built-in navigation function guides the inspectors to each target location sequentially according to the planned route. During the inspection, the terminal's camera, recording module, or text input module collects on-site information, including exterior photos of the target facilities, descriptions of structural changes, records of abnormal signs, and information on temporary obstacles. All collected inspection data is instantly transmitted back to the platform's backend via a secure, encrypted wireless network. Spatial associations are established with the corresponding feature features in the 3D scene, and metadata such as the inspector's name, inspection time, location information, and route trajectory are automatically added, forming a complete inspection log. During inspections, if new obstacles, damaged facilities, or other airspace safety hazards are discovered, inspectors can immediately mark the problem location and trigger an alarm. This alarm will then be linked to the dynamic monitoring module, updating the risk list and generating a work order which will be pushed to the relevant management departments. In this way, the inspection work and the aforementioned dynamic monitoring achieve information sharing and business linkage, enabling the airspace management system to further implement on-site inspections and closed-loop management while maintaining high-precision static modeling and dynamic risk perception, ensuring the continuous controllability of the airport's airspace status and safe operation.

[0052] After completing the scheduling and execution of the airspace protection zone patrol mission, precise modeling and automatic detection were carried out for the reference altitude protection zone stipulated by the Civil Aviation Administration of China (CAAC) to expand the scope of airspace management and strengthen the supervision of key altitude control areas. First, the boundary parameters and restrictions of the reference altitude protection zone issued by the CAAC were retrieved. Combined with the airport's actual geographic coordinates, elevation datum, and runway layout information, a custom geometric coordinate system for the reference altitude protection zone was established using the same spatial analysis method as the aforementioned airspace restriction surface. Within this coordinate system, a three-dimensional reference altitude restriction surface model was generated according to the specified horizontal projection range and height threshold. To ensure seamless integration of the model with the existing three-dimensional airspace scene, after modeling, precise geographic coordinate transformation and elevation datum unification were performed, and the model was spatially overlaid with the constructed airspace protection zone model, allowing the spatial relationship between the reference altitude protection zone and the airspace restriction surface to be intuitively presented on the platform. Subsequently, an automatic evaluation algorithm was invoked to detect the height of all ground obstacles within the reference altitude coverage area one by one. The detection results were compared with the specified reference altitude threshold to determine in real time whether any exceedances were possible. For detected over-limit targets, they are automatically highlighted in the 3D scene, and their precise location, over-limit extent, surrounding operating environment, and impact on flight procedures are recorded. Simultaneously, the analysis results are archived in the data management module as a report for retrieval by operations departments and regulatory agencies. Through this process, the supervision of the reference altitude protection zone complements the aforementioned airspace restriction surface monitoring and patrol management, achieving comprehensive altitude control from key local areas to the entire airspace. This effectively prevents over-limit obstacles from threatening flight safety and provides accurate altitude benchmarks for subsequent analysis of the flight procedure protection zone.

[0053] After completing the modeling and over-limit detection of the reference altitude protection zone, we further carried out 3D modeling and obstacle analysis for the flight procedure protection zone, which is crucial to airport operations, to ensure the safety margin of the flight path corridor and critical operational areas.

[0054] First, based on the airport's existing flight procedure design data, including takeoff and landing tracks, turning points, holding lines, and go-around paths, data such as protection zone boundary parameters, axis orientation, longitudinal profile slope, and lateral spread rate for each procedure are extracted. Combined with runway location, navigation beacon coordinates, and elevation information, a custom geometric coordinate system based on the procedure axis is established. Within this coordinate system, corresponding three-dimensional constraint surface models are generated according to the type and purpose of the flight procedure protection zone. Through mathematical projection and coordinate transformation, these models are accurately superimposed onto the previously constructed 3D scene of the airport's airspace protection zone, achieving a spatially integrated presentation of the flight procedure protection zone, airspace constraint surface, and reference altitude protection zone. After model fusion, an automatic evaluation algorithm is invoked to perform batch height detection on ground buildings, structures, and natural terrain within the coverage area of ​​the flight procedure protection zone, calculating their vertical distances relative to the protection zone constraint surface. The results are compared with safety margin standards to determine whether there are any risks of exceeding or approaching height restrictions. For targets identified as risky, they are automatically marked with warning icons in the 3D scene, and associated with information such as their location, extent of exceeding limits, potential affected flight paths, and operational phases. Simultaneously, an analysis report is generated for reference by navigation departments, operations scheduling, and airspace management personnel. Through this step, the safety status of the flight procedure protection zone can be linked with the aforementioned airspace restriction surface monitoring, patrol management, and reference altitude protection zone detection, constructing a multi-layered safety protection system covering the entire airport's critical airspace, thereby providing continuous, accurate, and traceable spatial safety assurance for flight operations.

[0055] The data management and intelligent retrieval module is used to provide comprehensive data management and intelligent retrieval functions after completing the 3D modeling and obstacle detection of the flight procedure protection zone, so as to realize the centralized storage, structured management and efficient retrieval of various data and files in the process of airspace management.

[0056] The system allows users to directly upload data such as airspace restriction surface parameter files, 3D model data, remote sensing imagery, patrol records, inspection reports, flight operation analysis results, relevant approval documents, and design drawings to the backend database within a secure environment with access control. All data is automatically tagged with metadata such as upload time, uploader, data category, associated feature number, and spatial location upon entry into the database, and undergoes verification and formatting to ensure data integrity and consistency. An index system and multi-dimensional search fields are established for each type of data, allowing users to perform combined queries based on various conditions such as geographical location, time interval, facility category, task number, or keywords, enabling rapid location and immediate retrieval of required data. When linked with the aforementioned 3D scenes and analysis results, users can directly retrieve all associated historical records, inspection data, and handling documents by clicking on a specific obstacle or facility object in the platform, achieving bidirectional association between spatial and data information. This function not only supports direct previewing of commonly used document, image, and 3D model formats within the platform but also allows batch export of specified data as needed for submission to regulatory authorities or external technical analysis. Through the data management module, the platform integrates static standard documents, dynamic monitoring results, and historical handling records in the airspace management process into a controllable and traceable digital archive system. This enables this embodiment to not only complete the business loop from modeling, monitoring, inspection to risk handling, but also to accumulate long-term data and knowledge, thus providing a solid data foundation for the continuous optimization and decision support of airport airspace management.

[0057] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0058] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0059] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0060] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0061] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An airport clearance three-dimensional visualization management system, characterized in that, Includes the following modules: The constraint surface modeling and datum transformation module is used to establish the local runway coordinate system and parametrically model the constraint surfaces in the local runway coordinate system. The constraint surfaces include the approach surface, takeoff and climb surface, miss landing surface, transition surface, inner horizontal surface, outer horizontal surface, and conical surface. The constraint surface model is then transformed to the geographic coordinate system and combined with geoid correction to achieve unified elevation datum. The permitted height calculation and terrain adaptive analysis module is used to determine the average slope angle and elevation undulation, and calculates the comprehensive discrimination value by weighted summation. The formula for calculating the hysteresis band half-width is as follows: ； in, and The upper and lower limits of the hysteresis band half-width are defined as the engineering limits, and the exponents p and q are used to control the sensitivity to the two factors. For data reliability, Represents the complexity of the scenario; The data reliability It is determined by a combination of the sensor source signal-to-noise ratio, terrain grid resolution, and data acquisition timeliness. The scene complexity value The acquisition steps are as follows: First, extract elevation data from the high-precision digital elevation model or the triangulation network reconstructed by oblique photogrammetry, and calculate the slope, curvature, and undulation. The slope is obtained by averaging the elevation gradient norm of the neighborhood; the curvature is calculated by the discrete Laplacian operator or local quadratic surface fitting to obtain the mean absolute curvature; and the undulation is obtained by the standard deviation of the neighborhood elevation. The three features are compared with the benchmark values ​​and normalized to the 0 to 1 range according to the ratio. Then, they are weighted and fused according to the preset weight coefficients to obtain the scene complexity value. When the comprehensive discriminant value is greater than The permissible height is calculated using a terrain-enhanced profile mode. The terrain-enhanced profile mode lays out profile sampling lines along the main slope direction and the direction orthogonal to it of the point to be detected, obtains the noise-reduced elevation curve within the profile range, and calculates the intersection elevation point along the normal direction of the limiting surface point by point. After deducting the safety margin, the permissible height of each profile direction is obtained, and finally the minimum value or the weighted average according to the confidence level is taken to determine the permissible height. When the comprehensive discriminant value is less than The permissible height is calculated using the normal projection fast mode. The normal projection fast mode obtains the intersection point elevation by analytical or numerical intersection along the normal direction of the limiting surface, and determines the permissible height after deducting the measurement error correction, terrain grid correction and operational safety redundancy. When the comprehensive discriminant is in Simultaneously, the terrain enhancement profile mode and the normal projection fast mode are executed, and the permissible height is determined by using the conservative minimum method based on the calculation results of both modes; wherein To switch thresholds, The hysteresis band is half the width; The obstacle dynamic monitoring and risk labeling module is used to compare the permitted height with the obstacle height to determine whether there is an over-limit situation; for over-limit obstacles, a risk list is automatically generated and highlighted in the 3D scene, recording their location coordinates, height, area occupied and impact range.

2. The airport airspace three-dimensional visualization management system according to claim 1, characterized in that: Obstacle heights are obtained by detecting ground feature changes and retrieving heights by calling up multi-temporal high-resolution remote sensing images or oblique photography data.

3. The airport airspace three-dimensional visualization management system according to claim 1, characterized in that: It further includes a patrol task scheduling and mobile terminal interaction module, which is used to generate patrol routes based on risk lists, patrol priorities, runway operation windows and weather conditions, and send them to the patrol personnel's terminals.

4. The airport airspace three-dimensional visualization management system according to claim 1, characterized in that: It further includes a data management and intelligent retrieval module, which is used to centrally store clearance limit surface parameters, 3D models, remote sensing images, inspection records, inspection reports and historical data, and establish multi-dimensional indexes and metadata tags to achieve bidirectional association and retrieval with 3D scenes.

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