Airborne cloud radar three-dimensional terrain registration profile generation situation interaction method and system

Abstract

This invention discloses a method and system for generating 3D terrain registration profiles and interactive situational awareness data using airborne cloud radar, relating to the field of airborne cloud radar application technology. The method acquires real-time aircraft position and attitude, cloud radar per-detection-unit data, 3D terrain data, and external airspace data; maps multi-source data to a unified time reference and establishes a cache queue; constructs a four-level transformation model from the cloud radar coordinate system through the aircraft coordinate system, local navigation coordinate system to the geographic coordinate system or 3D terrain coordinate system; interpolates attitude parameters for each effective detection unit according to the sampling time, completing point-by-point or group attitude compensation and spatial registration; constructs 3D cloud bodies, terrain, aircraft, flight paths, and airspace objects and overlays them to form a 3D main view; generates cutting planes and section views, achieving bidirectional linkage positioning between the main view and section views; supports multi-view switching, target attribute viewing, and highlight display interaction. This invention solves the problems of cloud body drift and spatial interpretation difficulties, improving the efficiency of flight situational awareness.

Description

Technical Field

[0001] This invention relates to the field of airborne cloud radar application technology, and in particular to a method and system for generating situational interaction based on three-dimensional terrain registration profiles for airborne cloud radar. Background Technology

[0002] Airborne cloud radar is a core airborne sensor for realizing three-dimensional cloud structure detection and meteorological target identification. It can detect cloud distribution, echo intensity, radial velocity, and cloud microphysical parameters in real time in front of, to the side of, and in designated directions of the aircraft, playing a crucial role in weather modification operations, meteorological scientific research, and aviation safety. Traditional airborne cloud radar detection results are mainly displayed in a two-dimensional plane, only showing the echo intensity distribution in the radar coordinate system. Under actual dynamic flight conditions, the aircraft's latitude, longitude, altitude, heading, pitch angle, roll angle, and other state parameters are constantly changing. Operators need to manually correlate and map the two-dimensional radar image with the aircraft's real-time position, terrain undulations, flight path, and mission area. This is difficult to interpret, inefficient, and prone to spatial position misjudgment, directly affecting flight mission safety and operational effectiveness.

[0003] In recent years, 3D terrain display technology has been gradually applied to the aviation field. However, existing general-purpose 3D map systems and airborne display solutions have the following significant shortcomings: 1) Existing solutions mostly adopt whole-frame attitude compensation, without considering the dynamic changes in aircraft attitude during the cloud radar scanning cycle. This results in significant drift in the cloud display position as the aircraft maneuvers, making it impossible to establish a strict spatial correspondence between cloud radar detection results and real 3D terrain; 2) The profile function of existing 3D systems is mostly designed for general geographic analysis and cannot automatically generate cutting planes based on aircraft heading, flight path, or target cloud, making it difficult to intuitively present the spatial crossing relationship with terrain and flight path; 3) Key information such as cloud distribution, 3D terrain, flight path, no-fly zone, warning zone, and particle sensor are displayed independently, and there is a lack of dedicated interactive functions for flight missions, such as viewing cloud target attributes and linking the main view and profile view for positioning, making it difficult to form a unified and intuitive 3D flight environment situation.

[0004] Therefore, there is an urgent need to develop a system and method that can achieve high-precision registration of airborne cloud radar detection results with three-dimensional terrain, unified fusion display of multi-source situational information, and support for dedicated profile analysis and interaction. Summary of the Invention

[0005] In view of this, this application provides a method and system for generating situation interaction based on airborne cloud radar three-dimensional terrain registration profiles, in order to solve the technical problems of cloud radar display drift, spatial interpretation difficulties, and scattered situation information in the prior art, and to achieve high-precision registration and unified situation display of cloud radar detection results and three-dimensional terrain.

[0006] The first aspect of this application provides a method for generating situational interaction based on three-dimensional terrain registration profiles using airborne cloud radar, comprising the following steps: S1. Acquire real-time aircraft position and attitude data, cloud radar per-detection-cell data, local 3D terrain data, and external airspace data; S2. Map the real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data to a unified time reference; for the above-mentioned real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data with different refresh frequencies, establish a time cache queue for each data, and select or interpolate the aircraft status data and external airspace data at the same time from the corresponding cache queue according to the timestamp of the cloud radar data frame. S3. Establish the basic transformation relationship between the geographic coordinate system, the local three-dimensional terrain coordinate system, the aircraft body coordinate system, and the cloud radar coordinate system; based on the aircraft position parameters, aircraft attitude parameters, and cloud radar installation parameters relative to the aircraft body, construct a four-level transformation model that starts from the cloud radar coordinate system, passes through the aircraft body coordinate system and the local navigation coordinate system, and finally transforms to the geographic coordinate system or the local three-dimensional terrain coordinate system. S4. For each effective detection unit of the cloud radar, according to the actual sampling time of the cloud radar detection data corresponding to the detection unit, interpolate to obtain the aircraft attitude parameters at the corresponding time, perform point-by-point or group attitude compensation, and then convert to the geographic coordinate system or local three-dimensional terrain coordinate system through the four-level transformation model to establish the spatial correspondence between the cloud radar detection results and the three-dimensional terrain, and complete the registration of the cloud radar detection results. S5. Construct a three-dimensional cloud display object based on the registered cloud radar detection results; S6. Load local 3D terrain data to generate a 3D terrain scene, generate an aircraft model object based on the aircraft's real-time position and attitude, generate a flight track object based on the historical position sequence, and generate an airspace restriction object based on external airspace data. S7. Overlay the cloud display object, aircraft model object, flight trajectory object and airspace restriction object onto the three-dimensional terrain scene to form a three-dimensional flight situation main view; S8. Generate a cutting plane according to user interaction or preset rules, extract the cross-sectional information of the cutting plane and the three-dimensional terrain, cloud display object, flight track object and airspace restriction object to form a cross-sectional view, and realize bidirectional linkage positioning between the three-dimensional main view and the cross-sectional view. S9. Supports users to perform situational interaction operations such as switching between multiple perspectives, viewing cloud bodies, flight paths, and airspace target object attributes, and highlighting them.

[0007] In one possible implementation of the first aspect, the point-by-point or grouped attitude compensation in step S4 specifically includes: When the aircraft attitude change rate is less than the preset threshold, group attitude compensation is adopted, which divides N consecutive detection units into a group and uses the aircraft attitude parameters corresponding to the average sampling time within the group for unified compensation. When the rate of change of aircraft attitude is greater than or equal to a preset threshold, point-by-point attitude compensation is adopted, and each detection unit is compensated separately using the aircraft attitude parameters corresponding to its independent sampling time.

[0008] In one possible implementation of the first aspect, the method of generating the cutting plane in step S8 includes at least one of the following: The user selects two points in a 3D terrain scene, and a cutting plane perpendicular to the horizontal plane is generated based on the line connecting the two points. When a user selects a cloud target, a cutting plane passing through the cloud's centroid is automatically generated. Automatically generate a forward cutting plane along the current aircraft heading; Automatically generate track cutting planes along planned routes or historical tracks; Users can specify any range of directions, widths, and heights to generate custom cutting planes.

[0009] In one possible implementation of the first aspect, the construction of the three-dimensional cloud display object in step S5 specifically includes: A three-dimensional cloud object is generated based on the registered cloud radar detection results. The three-dimensional cloud object takes at least one of the following forms: Point cloud objects represent each valid detection unit as a three-dimensional point; Voxel objects map radar detection results into three-dimensional voxel units; Mesh objects are constructed using triangular meshes based on cloud boundaries or isosurfaces; The volume rendering object generates a 3D volume display based on the cloud volume attributes; Multi-layered cloud objects are displayed in layers according to echo intensity, cloud type, hazard level, or altitude. Set the color, transparency, point size, voxel size, texture, annotations, or motion direction arrows of the 3D cloud object according to its cloud properties.

[0010] In one possible implementation of the first aspect, after step S4 completes the registration of the cloud radar detection results, it further includes: The registered cloud radar detection results are divided into cloud points in the current frame, cloud points in the historical frame, and cloud points in the predicted frame. Set the first transparency and first display style for the cloud points in the current frame to represent the real-time spatial distribution of the cloud; Set a second transparency and a second display style for the cloud points in the historical frame to express the dynamic changes of the cloud; A third transparency and a third display style are set for the cloud points in the prediction frame to express the possible movement trend of the cloud; The cloud points of the current frame, historical frames, and predicted frames are simultaneously overlaid and displayed in the 3D terrain scene.

[0011] In one possible implementation of the first aspect, step S1 further includes acquiring particle sensor data; Step S7 further includes: associating the particle sensor data with the aircraft position at the sampling time, displaying the particle sensor data in the form of trajectory points, color bands or attribute pop-ups in the three-dimensional terrain scene, and jointly annotating it with the cloud radar detection results.

[0012] In one possible implementation of the first aspect, step S8, which involves achieving bidirectional linkage positioning between the three-dimensional main view and the sectional view, specifically includes: When a user clicks on any location in the sectional view, the corresponding spatial location is simultaneously highlighted and marked in the 3D main view; When a user selects any cloud, flight path, or airspace target object in the 3D main view, a cross-sectional view passing through the target is automatically generated and positioned at the target location.

[0013] In one possible implementation of the first aspect, the multi-view switching in step S9 includes: It supports free rotation, scaling, and panning of the viewpoint, as well as switching between aircraft follow view, top-down global view, side-view profile view, forward first-person view, and mission area focus view; among them, the viewpoint changes synchronously with the aircraft attitude in real time under the aircraft follow view.

[0014] One possible implementation of the first aspect also includes: The system continuously updates the 3D main view and the cross-sectional view based on real-time input data, and supports functions such as speed playback, pause, frame-by-frame viewing, timeline dragging, and keyframe marking of historical data.

[0015] The second aspect of this application provides an airborne cloud radar three-dimensional terrain registration profile generation situation interaction system, including: The data acquisition module is used to acquire real-time aircraft position and attitude data, cloud radar per-detection-unit data, local 3D terrain data, and external airspace data; The time synchronization module is used to map the real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data to a unified time reference. For the real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data with different refresh frequencies, a time cache queue for each data is established, and the aircraft status data and external airspace data at the same moment are selected or interpolated from the corresponding cache queue according to the timestamp of the cloud radar data frame. The coordinate transformation and attitude compensation module is used to establish the basic transformation relationships between the geographic coordinate system, the local three-dimensional terrain coordinate system, the aircraft body coordinate system, and the cloud radar coordinate system. Based on the aircraft position parameters, aircraft attitude parameters, and installation parameters of the cloud radar relative to the aircraft body, a four-level transformation model is constructed, starting from the cloud radar coordinate system, passing through the aircraft body coordinate system and the local navigation coordinate system, and finally transforming to the geographic coordinate system or the local three-dimensional terrain coordinate system. For each effective detection unit of the cloud radar, the aircraft attitude parameters at the corresponding time are obtained by interpolation based on the actual sampling time of the cloud radar detection data corresponding to the detection unit. After point-by-point or group attitude compensation, the data is converted to the geographic coordinate system or local three-dimensional terrain coordinate system through the four-level transformation model to establish the spatial correspondence between the cloud radar detection results and the three-dimensional terrain, and complete the registration of the cloud radar detection results. The cloud construction module is used to construct a 3D cloud display object based on the registered cloud radar detection results. The situation object generation module is used to load local 3D terrain data to generate a 3D terrain scene, generate an aircraft model object based on the aircraft's real-time position and attitude, generate a flight track object based on historical position sequences, and generate an airspace restriction object based on external airspace data. The 3D situation display module is used to overlay cloud display objects, aircraft model objects, flight track objects and airspace restriction objects onto a 3D terrain scene to form a 3D flight situation main view. The profile generation and linkage module is used to generate a cutting plane according to user interaction or preset rules, extract the cross-sectional information of the cutting plane and the three-dimensional terrain, cloud display objects, flight track objects and airspace restriction objects to form a profile view, and realize the bidirectional linkage positioning of the three-dimensional main view and the profile view. The situation interaction module supports users in performing situation interaction operations such as switching between multiple perspectives, viewing and highlighting attributes of cloud bodies, flight paths, and airspace targets.

[0016] Its beneficial effects are as follows: This invention discloses a method and system for generating situational interaction based on three-dimensional terrain registration profiles of airborne cloud radar, achieving the following significant technical effects: 1) By using a four-level coordinate transformation model and per-detection-unit attitude compensation technology, the existing whole-frame attitude compensation method has been replaced, reducing the cloud display error from tens to hundreds of meters to the level of several meters. For the first time, a strict spatial correspondence between cloud radar detection results and three-dimensional terrain has been established.

[0017] 2) By overlaying core situational information such as cloud radar, 3D terrain, flight path, and airspace restrictions onto the same 3D scene, the pain points of scattered information display and the need for manual correlation in existing technologies are solved, forming a complete and intuitive 3D flight environment situation.

[0018] 3) It supports various flight scenario-specific cutting plane generation methods and pioneers a two-way linkage positioning function between the 3D main view and the section view, which can intuitively present the spatial crossing relationship between clouds, terrain and flight path, greatly reducing the difficulty of spatial relationship interpretation.

[0019] 4) It integrates multi-view one-click switching, target attribute quick viewing and highlighting functions, which solves the problems of single interaction mode and frequent operation of the existing system, and significantly improves the situational awareness efficiency and operation convenience in flight missions. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0021] Figure 1 This is a flowchart illustrating the airborne cloud radar three-dimensional terrain registration profile generation situation interaction method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the four-level conversion model provided in the embodiments of this application; Figure 3 This is a schematic diagram of the composition of the airborne cloud radar three-dimensional terrain registration profile generation situation interaction system provided in the embodiments of this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0023] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0024] To better understand this application, the technical names involved in this application are explained below: Cloud radar detection unit: In a single scan, the cloud radar corresponds to a range gate, an azimuth angle, and an elevation angle. Each detection unit contains parameters such as echo intensity, radial velocity, spectral width, depolarization ratio, and cloud classification results. Local navigation coordinate system: A temporary coordinate system with the aircraft's current position as the origin, the X-axis pointing east, the Y-axis pointing north, and the Z-axis pointing to the sky. It is used as the reference for aircraft attitude transformation and local spatial calculation. Rate of attitude change: The change in the aircraft's heading angle, pitch angle, or roll angle per unit time, used to determine the severity of the aircraft's maneuvers.

[0025] Example 1 Please refer to Figure 1 This application provides a method for generating situational awareness interaction through 3D terrain registration profiles for airborne cloud radar. This method addresses three core deficiencies in existing airborne cloud radar displays: cloud drift caused by whole-frame attitude compensation, the inability of general profile functions to meet flight mission requirements, and the fragmented display of multi-source situational information. A systematic solution is proposed. Through improved time synchronization accuracy, optimized coordinate transformation levels, refined attitude compensation granularity, reconstructed situational information fusion architecture, and innovative interaction modes, high-precision registration and unified situational awareness display of cloud radar detection results with 3D terrain are achieved, demonstrating a significant technological advantage over existing technologies.

[0026] Specifically, the following steps are included: S1. Multi-source data acquisition Acquire real-time aircraft position and attitude data, cloud radar per-detection-cell data, local 3D terrain data, and external airspace data. Optionally, acquire particle sensor data, flight path, no-fly zone data, warning zone data, and mission area data.

[0027] The aircraft's real-time position and attitude data includes longitude, latitude, altitude, heading angle, pitch angle, and roll angle, which are provided by the airborne GPS / INS integrated navigation system, with a refresh rate typically ranging from 10Hz to 100Hz. The cloud radar detection results include range gate number, detection range, azimuth angle, elevation angle, echo intensity, radial velocity, cloud classification results, cloud state parameters (reflectivity, velocity, spectral width, depolarization ratio) or other results obtained by cloud radar processing. Each detection unit has an independent high-precision timestamp. The local 3D terrain data uses digital elevation model (DEM) data with a resolution of no less than 30 meters. It is pre-stored on the local hard drive of the airborne terminal and supports offline loading. External airspace data includes the boundary coordinates, validity period, and attribute information of no-fly zones, warning zones, and mission zones, which are distributed in real time by the ground command system or pre-loaded to the airborne terminal; Airborne particle sensor data includes parameters such as particle concentration, particle diameter, and particle type, which are used to assist in cloud identification and the evaluation of the effectiveness of artificial weather modification operations.

[0028] S2. Establishment of a unified time base Aircraft status data, cloud radar data, particle sensor data, and external airspace data are converted to a unified time base. For data sources with different refresh rates, a time buffer queue is established, and the aircraft status data at the corresponding time is obtained by selecting or interpolating based on the timestamp of the cloud radar data frame.

[0029] Technical Contribution: Existing technologies typically only perform simple timestamp matching on data, without establishing dedicated caching mechanisms for different refresh rates and data sources, resulting in large time alignment errors. This embodiment improves the time synchronization accuracy of multi-source data from milliseconds to microseconds through a circular time cache queue and an adaptive interpolation algorithm, laying the foundation for subsequent high-precision spatial registration.

[0030] The time cache queue adopts a circular buffer structure, where each buffer can store the most recent historical data and supports fast random access; For data with exactly matching timestamps, the nearest neighbor matching method is used directly; For data with mismatched timestamps, linear interpolation or cubic spline interpolation methods are used to calculate the aircraft attitude parameters and external airspace data at the corresponding time. Particle sensor data and external spatial domain data are synchronized in time to ensure that all dynamic data are fused and displayed under the same time reference.

[0031] S3. Construction of Coordinate Transformation Relationships and a Four-Level Transformation Model Establish the basic transformation relationships between the geographic coordinate system (WGS-84), the local 3D terrain coordinate system, the aircraft body coordinate system, and the cloud radar coordinate system. Based on the aircraft's latitude and longitude, altitude, heading angle, pitch angle, roll angle, and the cloud radar's installation offset and installation angle relative to the aircraft body, construct a transformation model from the cloud radar coordinate system to the 3D terrain scene coordinate system.

[0032] First, establish a local northeast-sky coordinate system using the aircraft's current position or the center point of the mission area as the local coordinate origin. For each effective detection unit of the cloud radar, calculate its position vector in the cloud radar coordinate system based on its range, azimuth, and pitch angle. Then, transform this position vector to the aircraft body coordinate system according to the cloud radar installation matrix, and then to the local navigation coordinate system according to the aircraft attitude matrix. Finally, convert it into its spatial position in the three-dimensional terrain display coordinate system, such as... Figure 2 As shown.

[0033] Technical Contribution: Existing coordinate transformation technologies typically only include 2-3 levels and do not consider the effects of cloud radar installation offset and installation angle, leading to the accumulation of spatial transformation errors. The four-level chain transformation model constructed in this embodiment fully covers all transformation links from the radar local coordinate system to the global geographic coordinate system, eliminating installation errors and coordinate system transformation errors, and improving spatial transformation accuracy by an order of magnitude.

[0034] The origin of the cloud radar coordinate system is located at the phase center of the cloud radar antenna. The X-axis points directly in front of the radar, the Y-axis points to the right side of the radar, and the Z-axis points vertically upward. The origin of the aircraft's coordinate system is located at the aircraft's center of gravity, with the X-axis pointing towards the nose of the aircraft, the Y-axis pointing towards the right side of the aircraft, and the Z-axis pointing vertically upwards. The origin of the local navigation coordinate system is located at the aircraft's current position, with the X-axis pointing east, the Y-axis pointing north, and the Z-axis pointing upwards. The geographic coordinate system adopted is the WGS-84 coordinate system, with the Earth's center of mass as the origin, used for global spatial positioning; The local 3D terrain coordinate system uses the center point of the task area as the origin and is used for the display and rendering of 3D terrain scenes.

[0035] S4. Per-detector unit attitude compensation and cloud radar data registration When the aircraft attitude changes significantly during cloud radar scanning, the system can interpolate the aircraft attitude according to the actual sampling time of the detection unit to obtain the attitude parameters at the corresponding sampling time, and use the attitude parameters to perform point-by-point or group attitude compensation for the detection unit.

[0036] For each effective detection unit of the cloud radar, the aircraft attitude parameters at the corresponding time are obtained by interpolation based on the actual sampling time of the cloud radar detection data corresponding to that detection unit. After point-by-point or group attitude compensation, the data is converted to the geographic coordinate system or local three-dimensional terrain coordinate system through the four-level transformation model. The spatial correspondence between the cloud radar detection results and the three-dimensional terrain is established, and the registration of the cloud radar detection results is completed.

[0037] Technical Contribution: Existing technologies generally employ a whole-frame attitude compensation method, which uses the aircraft's attitude at the beginning of a radar data frame to uniformly compensate all detection units within the entire frame. This completely ignores the dynamic changes in the aircraft's attitude during the radar scan cycle, resulting in severe cloud drift during aircraft maneuvers. This embodiment pioneers a per-detector-unit attitude compensation technology, refining the granularity of attitude compensation from "frame" to "individual detection unit," completely solving the cloud display drift problem caused by aircraft maneuvers. This is the core technical contribution of this embodiment.

[0038] An effective detection unit refers to a detection unit whose echo intensity is greater than a preset threshold, used to filter noise and invalid data; Attitude compensation adopts an adaptive switching method: when the aircraft attitude change rate is less than 0.5° / s, group attitude compensation is adopted, and 10 consecutive detection units are divided into a group, and the aircraft attitude parameters corresponding to the average sampling time within the group are used for unified compensation; when the aircraft attitude change rate is greater than or equal to 0.5° / s, point-by-point attitude compensation is adopted, and each detection unit is compensated separately using the aircraft attitude parameters corresponding to its independent sampling time. After registration, further calculations are made on the height difference of the cloud radar detection point relative to the terrain surface, the three-dimensional distance between it and the aircraft's current position, the lateral deviation between it and the current flight path, and whether it is located in the mission area or the warning area. The registered cloud radar detection results are divided into cloud points in the current frame, cloud points in the historical frames, and cloud points in the predicted frames, and are distinguished by different transparency levels or display styles. The current frame is used to express the real-time spatial distribution of clouds, the historical frames are used to express the cloud change process, and the predicted frames are used to express the possible movement trend of clouds.

[0039] S5. Construction of 3D Cloud Display Objects The mapped cloud radar results are used to construct cloud volume display objects. For discrete point data, point cloud objects can be constructed; for regular data composed of range gates, azimuth cells, and elevation cells, voxel cloud objects can be constructed; for continuous cloud boundaries, volume rendering meshes or isosurface objects can be constructed.

[0040] The color, transparency, size, and labeling of cloud objects can be set based on echo intensity, cloud classification results, height, speed, or risk level.

[0041] Specifically, it includes: Point cloud object: Each effective radar detection unit is represented as a three-dimensional point, with the size of the point mapped according to the spectral width and the color of the point mapped according to the echo intensity; Voxel objects: Map radar detection results to three-dimensional voxel units. The transparency of each voxel is set according to the echo intensity, and the color of the voxel is mapped according to the cloud type. Mesh objects: Construct triangular meshes based on cloud boundaries or isosurfaces to display the surface morphology of continuous clouds; Volume rendering object: Generates a 3D volume display based on the cloud's properties to present the cloud's internal structure; Multi-layered cloud objects: Displayed in layers according to echo intensity, cloud type, hazard level, or altitude, with each layer using different colors and transparency; It can also generate motion direction arrows based on radial velocity, visually displaying the motion direction and speed of the cloud; For clouds with a high risk level (such as cumulonimbus clouds), the system automatically adds a red warning label.

[0042] S6. Generation of 3D Terrain and Flight Status Objects Load local 3D terrain data to generate a 3D terrain scene; generate aircraft model objects based on the aircraft's real-time position and attitude; generate flight path objects based on historical position sequences; generate planned flight path objects based on mission data; and generate no-fly zone, warning zone, or mission zone objects based on external airspace data.

[0043] The 3D terrain scene is rendered using layered detail technology, which automatically adjusts the display precision of the terrain according to the viewing distance to ensure that the real-time rendering frame rate is not lower than the set value, such as 30fps. The aircraft model objects are pre-made using 3D modeling software, which supports real-time attitude updates, and the orientation of the aircraft model is consistent with the actual heading of the aircraft. Aircraft tracks are represented by colored lines, with the line colors mapped according to flight time or altitude. Key time points and altitude information can be marked on the tracks. Planned flight paths are represented by dashed lines to contrast with actual flight tracks. Airspace restriction objects are represented by volumetric cubes or polygons, and different types of airspace use different colors: for example, no-fly zones are displayed in red with a transparency of 0.6; warning zones are displayed in yellow with a transparency of 0.4; and mission zones are displayed in blue with a transparency of 0.3.

[0044] S7. 3D Terrain-Related Display The system overlays cloud objects, aircraft model objects, flight path objects, airspace objects, and particle sensor data objects onto a unified 3D terrain scene. The system controls the display layer, transparency, and annotation method of different objects based on user selection or task mode.

[0045] Technical Contribution: In existing technologies, cloud radar data, terrain data, flight data, and airspace data are typically displayed independently in different windows. Operators need to switch between multiple windows and manually perform spatial correlations, resulting in a heavy cognitive burden and a high risk of errors. This embodiment unifies all key situational information onto the same 3D terrain scene, achieving a "single map" display and significantly reducing the cognitive burden on operators.

[0046] The display hierarchy from bottom to top is as follows: 3D terrain, airspace constraint objects, cloud display objects, flight path objects, aircraft model objects, and particle sensor data objects; If airborne particle sensor data is acquired, the particle sensor data is associated with the aircraft position at the sampling time, and the particle sensor data is displayed in the three-dimensional terrain scene in the form of trajectory points, color bands or attribute pop-ups, and is jointly labeled with cloud radar detection results. The color of the particle sensor data is mapped according to the particle concentration, and the size of the trajectory points is mapped according to the particle diameter. It supports displaying or hiding any type of object individually, making it easier for operators to focus on the information they need.

[0047] S8. Cutting plane generation and bidirectional linkage positioning Based on the points, lines, target clouds, or flight paths selected by the user in the 3D scene, a cutting plane is generated. The system calculates the intersection lines or cross-sectional distribution between this cutting plane and the 3D terrain, cloud objects, flight path objects, and no-fly zone objects, and outputs a cross-sectional view.

[0048] The profile view may include terrain profile curves, cloud cross-sections, echo intensity distribution, flight path altitude lines, and warning zone boundaries. The profile view is linked to the 3D main view; when a user selects a location in the profile view, the corresponding spatial location is simultaneously located in the 3D main view.

[0049] Technical Contribution: Existing 3D systems' profile functions are mostly general geographic analysis designs, supporting only one method of generating vertical profiles from two points, and the profile view and the main view are independent and cannot be linked. This embodiment designs five dedicated cutting plane generation methods for flight mission requirements and pioneers a two-way linkage positioning function between the 3D main view and the profile view, realizing a "what you see is what you get" spatial analysis experience. This is another important technical contribution of this embodiment.

[0050] The methods for generating the cutting plane include at least one of the following: The user selects two points in a 3D terrain scene, and a cutting plane perpendicular to the horizontal plane is generated based on the line connecting the two points. When a user selects a cloud target, a cutting plane passing through the cloud's centroid is automatically generated. Automatically generate a forward cutting plane along the current aircraft heading; Automatically generate track cutting planes along planned routes or historical tracks; Users can specify any range of directions, widths, and heights to generate custom cutting planes.

[0051] In the profile view, terrain profile curves are represented by solid black lines, track altitude lines are represented by solid blue lines, and warning zone boundaries are represented by dashed yellow lines. The cross-sectional view of the cloud body uses color mapping to display the echo intensity distribution, with the color bars located on the right side of the cross-sectional view; The two-way linkage positioning specifically includes: when the user clicks on any location in the profile view, the corresponding spatial location is simultaneously highlighted and a white cross mark is added in the 3D main view; when the user selects any cloud, track, or airspace target object in the 3D main view, a profile view passing through the center of the target is automatically generated and the center of the view is positioned at the target location.

[0052] S9. Perspective Switching and Situational Interaction The system allows users to switch observation perspectives based on user input or preset task modes. It supports free-view, aircraft-following, top-down, side-view, forward-looking, and profile analysis perspectives.

[0053] When a user selects a cloud, track, airspace object, or particle sampling point, the system displays the corresponding object's attribute information and highlights it in the main view.

[0054] Existing systems offer limited perspective switching capabilities, typically supporting only free-view and overhead views, and lack quick target attribute viewing functionality. This invention provides six dedicated perspectives for flight missions and integrates one-click target attribute viewing and highlighting functions, significantly improving situational awareness interaction efficiency.

[0055] Multi-view switching includes: support for free rotation, zoom, and panning of the view, as well as one-click switching between aircraft follow view, top-down global view, side-view profile view, forward first-person view, and mission area focused view; In the aircraft follow view, the viewpoint changes synchronously with the aircraft's attitude in real time, always keeping the aircraft in the center of the view. In the top-down global view, the system automatically adjusts the viewing height to ensure that the entire task area is fully displayed in the view. In the task area focused view, the system automatically zooms and pans the view to focus on the current task area.

[0056] When a user clicks on any target object, the system pops up a properties window displaying detailed information about the object: Cloud object: echo intensity, altitude, radial velocity, spectral width, depolarization ratio, cloud type, hazard level, relative terrain altitude, and distance from aircraft; Track data includes: flight time, latitude and longitude, altitude, heading, and speed. Airspace object: type, name, boundary coordinates, validity period; Particle sampling points: sampling time, particle concentration, average particle diameter, and particle type.

[0057] S10. Dynamic updates and history playback With the input of new aircraft status data and cloud radar detection data, the system continuously updates the aircraft model's position, attitude, trajectory, and cloud objects. The system can also save historical data frames for mission replay, process analysis, and display of cloud motion trends.

[0058] The real-time update frequency is consistent with the refresh frequency of the cloud radar data, typically 1Hz~5Hz; Historical data can save the flight data of the most recent 72 hours, including all raw sensor data and processed situational data; It supports playback speeds of 0.5x, 1x, 2x, 4x, and 8x, as well as pause, frame-by-frame forward, and frame-by-frame rewind functions. Users can drag the slider on the timeline to quickly locate any point in time, and can also mark keyframes for easy viewing and analysis later; During the history playback, all interactive functions (view switching, profile generation, and attribute viewing) remain available.

[0059] Example 2 Please refer to Figure 3 This application provides an airborne cloud radar three-dimensional terrain registration profile generation situation interaction system to implement the method described in Embodiment 1. The system includes: Data acquisition module 100: used to acquire real-time aircraft position and attitude data, cloud radar per-detection-cell data, local 3D terrain data and external airspace data; optionally, it is also used to acquire airborne particle sensor data, flight path data, mission area data, etc. Time synchronization module 200: used to map the real-time position and attitude data of the aircraft, the cloud radar per-detection unit data and the external airspace data to a unified time reference; for the above-mentioned real-time position and attitude data of the aircraft, the cloud radar per-detection unit data and the external airspace data with different refresh frequencies, a time cache queue for each data is established, and the aircraft status data and external airspace data at the same time are selected or interpolated from the corresponding cache queue according to the timestamp of the cloud radar data frame. The coordinate transformation and attitude compensation module 300 is used to establish the basic transformation relationship between the geographic coordinate system, the local three-dimensional terrain coordinate system, the aircraft body coordinate system, and the cloud radar coordinate system. Based on the aircraft position parameters, aircraft attitude parameters, and cloud radar installation parameters relative to the aircraft body, it constructs a four-level transformation model that starts from the cloud radar coordinate system, passes through the aircraft body coordinate system and the local navigation coordinate system, and finally transforms to the geographic coordinate system or the local three-dimensional terrain coordinate system. For each effective detection unit of the cloud radar, based on the actual sampling time of the cloud radar detection data corresponding to that detection unit, the aircraft attitude parameters at the corresponding time are interpolated, and after point-by-point or group attitude compensation, the data is transformed to the geographic coordinate system or the local three-dimensional terrain coordinate system through the four-level transformation model. This establishes the spatial correspondence between the cloud radar detection results and the three-dimensional terrain, and completes the registration of the cloud radar detection results. Cloud construction module 400: used to construct a 3D cloud display object based on the registered cloud radar detection results; specifically used to: generate a 3D cloud object based on the registered cloud radar detection results, wherein the 3D cloud object adopts at least one of the following forms: point cloud object, voxel object, mesh object, volume rendering object, multi-layer cloud object; set the color, transparency, point size, voxel size, texture, annotation or motion direction arrow of the 3D cloud object according to the cloud attributes; and also used to divide the registered cloud radar detection results into cloud points of the current frame, cloud points of the historical frame, and cloud points of the predicted frame, set different transparency and display styles respectively, and then superimpose them on the 3D terrain scene. Situation object generation module 500: It is used to load local 3D terrain data to generate 3D terrain scenes, generate aircraft model objects based on the real-time position and attitude of the aircraft, generate flight track objects based on historical position sequences, and generate airspace restriction objects based on external airspace data; it is also used to generate planned flight path objects. The 3D situation display module 600 is used to overlay cloud display objects, aircraft model objects, flight trajectory objects, and airspace restriction objects onto a 3D terrain scene to form a 3D flight situation main view; optionally, it is also used to jointly annotate and display particle sensor data and cloud radar detection results. Section generation and linkage module 700: used to generate a cutting plane according to user interaction or preset rules, extract the cross-sectional information of the cutting plane and the three-dimensional terrain, cloud display object, flight track object and airspace restriction object to form a section view, and realize bidirectional linkage positioning between the three-dimensional main view and the section view. Situational Interaction Module 800: Used to support users in performing situational interaction operations such as switching between multiple perspectives, viewing and highlighting cloud bodies, flight paths and airspace target object attributes; Dynamic Update and Playback Module 900: Used to continuously update the 3D main view and section view based on real-time input data, and supports functions such as speed playback, pause, frame-by-frame viewing, timeline dragging, and keyframe marking of historical data.

[0060] The specific principles and execution processes of each module in the system disclosed in the above embodiments of this application are the same as those of the method disclosed in Embodiment 1 of this application. Please refer to the corresponding parts of the method disclosed in Embodiment 1 of this application, which will not be repeated here.

[0061] Those skilled in the art will further 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, computing software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. 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.

[0062] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0063] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for generating situational interaction based on three-dimensional terrain registration profiles using airborne cloud radar, characterized in that, Includes the following steps: S1. Acquire real-time aircraft position and attitude data, cloud radar per-detection-cell data, local 3D terrain data, and external airspace data; S2. Map the real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data to a unified time reference; for the above-mentioned real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data with different refresh frequencies, establish a time cache queue for each data, and select or interpolate the aircraft status data and external airspace data at the same time from the corresponding cache queue according to the timestamp of the cloud radar data frame. S3. Establish the basic transformation relationship between the geographic coordinate system, the local three-dimensional terrain coordinate system, the aircraft body coordinate system, and the cloud radar coordinate system; based on the aircraft position parameters, aircraft attitude parameters, and cloud radar installation parameters relative to the aircraft body, construct a four-level transformation model that starts from the cloud radar coordinate system, passes through the aircraft body coordinate system and the local navigation coordinate system, and finally transforms to the geographic coordinate system or the local three-dimensional terrain coordinate system. S4. For each effective detection unit of the cloud radar, according to the actual sampling time of the cloud radar detection data corresponding to the detection unit, interpolate to obtain the aircraft attitude parameters at the corresponding time, perform point-by-point or group attitude compensation, and then convert to the geographic coordinate system or local three-dimensional terrain coordinate system through the four-level transformation model to establish the spatial correspondence between the cloud radar detection results and the three-dimensional terrain, and complete the registration of the cloud radar detection results. S5. Construct a three-dimensional cloud display object based on the registered cloud radar detection results; S6. Load local 3D terrain data to generate a 3D terrain scene, generate an aircraft model object based on the aircraft's real-time position and attitude, generate a flight track object based on historical position sequences, and generate an airspace restriction object based on external airspace data. S7. Overlay the cloud display object, aircraft model object, flight trajectory object and airspace restriction object onto the three-dimensional terrain scene to form a three-dimensional flight situation main view; S8. Generate a cutting plane according to user interaction or preset rules, extract the cross-sectional information of the cutting plane and the three-dimensional terrain, cloud display object, flight track object and airspace restriction object to form a cross-sectional view, and realize bidirectional linkage positioning between the three-dimensional main view and the cross-sectional view. S9. Supports users to perform situational interaction operations such as switching between multiple perspectives, viewing cloud bodies, flight paths, and airspace target object attributes, and highlighting them.

2. The method according to claim 1, characterized in that, The point-by-point or group attitude compensation mentioned in step S4 specifically includes: When the aircraft attitude change rate is less than the preset threshold, group attitude compensation is adopted, which divides N consecutive detection units into a group and uses the aircraft attitude parameters corresponding to the average sampling time within the group for unified compensation. When the rate of change of aircraft attitude is greater than or equal to a preset threshold, point-by-point attitude compensation is adopted, and each detection unit is compensated separately using the aircraft attitude parameters corresponding to its independent sampling time.

3. The method according to claim 1, characterized in that, The method of generating the cutting plane in step S8 includes at least one of the following: The user selects two points in a 3D terrain scene, and a cutting plane perpendicular to the horizontal plane is generated based on the line connecting the two points. When a user selects a cloud target, a cutting plane passing through the cloud's centroid is automatically generated. Automatically generate a forward cutting plane along the current aircraft heading; Automatically generate track cutting planes along planned routes or historical tracks; Users can specify any range of directions, widths, and heights to generate custom cutting planes.

4. The method according to claim 1, characterized in that, The construction of the 3D cloud display object in step S5 specifically includes: A three-dimensional cloud object is generated based on the registered cloud radar detection results. The three-dimensional cloud object takes at least one of the following forms: Point cloud objects represent each valid detection unit as a three-dimensional point; Voxel objects map radar detection results into three-dimensional voxel units; Mesh objects are constructed using triangular meshes based on cloud boundaries or isosurfaces; The volume rendering object generates a 3D volume display based on the cloud volume attributes; Multi-layered cloud objects are displayed in layers according to echo intensity, cloud type, hazard level, or altitude. Set the color, transparency, point size, voxel size, texture, annotations, or motion direction arrows of the 3D cloud object according to its cloud properties.

5. The method according to claim 1, characterized in that, After completing the registration of the cloud radar detection results in step S4, the following steps are also included: The registered cloud radar detection results are divided into cloud points in the current frame, cloud points in the historical frame, and cloud points in the predicted frame. Set the first transparency and first display style for the cloud points in the current frame to represent the real-time spatial distribution of the cloud; Set a second transparency and a second display style for the cloud points in the historical frame to express the dynamic changes of the cloud; A third transparency and a third display style are set for the cloud points in the prediction frame to express the possible movement trend of the cloud; The cloud points of the current frame, historical frames, and predicted frames are simultaneously overlaid and displayed in the 3D terrain scene.

6. The method according to claim 1, characterized in that, Step S1 also includes acquiring particle sensor data; Step S7 further includes: associating the particle sensor data with the aircraft position at the sampling time, displaying the particle sensor data in the form of trajectory points, color bands or attribute pop-ups in the three-dimensional terrain scene, and jointly annotating it with the cloud radar detection results.

7. The method according to claim 1, characterized in that, Step S8, which describes the bidirectional linkage positioning between the 3D main view and the sectional view, specifically includes: When a user clicks on any location in the sectional view, the corresponding spatial location is simultaneously highlighted and marked in the 3D main view; When a user selects any cloud, flight path, or airspace target object in the 3D main view, a cross-sectional view passing through the target is automatically generated and positioned at the target location.

8. The method according to claim 1, characterized in that, The multi-view switching in step S9 includes: It supports free rotation, scaling, and panning of the viewpoint, as well as switching between aircraft follow view, top-down global view, side-view profile view, forward first-person view, and mission area focus view; among them, the viewpoint changes synchronously with the aircraft attitude in real time under the aircraft follow view.

9. The method according to claim 1, characterized in that, Also includes: The 3D main view and the cross-sectional view are continuously updated based on real-time input data, and the functions of speed playback, pause, frame-by-frame viewing, timeline dragging, and keyframe marking of historical data are supported.

10. A situational interaction system for generating three-dimensional terrain registration profiles using airborne cloud radar, characterized in that, include: The data acquisition module is used to acquire real-time aircraft position and attitude data, cloud radar per-detection-unit data, local 3D terrain data, and external airspace data; The time synchronization module is used to map the real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data to a unified time reference. For the real-time position and attitude data of the aircraft, the cloud radar per-detection-unit data, and the external airspace data with different refresh frequencies, a time cache queue for each data is established, and the aircraft status data and external airspace data at the same moment are selected or interpolated from the corresponding cache queue according to the timestamp of the cloud radar data frame. The coordinate transformation and attitude compensation module is used to establish the basic transformation relationships between the geographic coordinate system, the local three-dimensional terrain coordinate system, the aircraft body coordinate system, and the cloud radar coordinate system. Based on the aircraft position parameters, aircraft attitude parameters, and installation parameters of the cloud radar relative to the aircraft body, a four-level transformation model is constructed, starting from the cloud radar coordinate system, passing through the aircraft body coordinate system and the local navigation coordinate system, and finally transforming to the geographic coordinate system or the local three-dimensional terrain coordinate system. For each effective detection unit of the cloud radar, the aircraft attitude parameters at the corresponding time are obtained by interpolation based on the actual sampling time of the cloud radar detection data corresponding to the detection unit. After point-by-point or group attitude compensation, the data is converted to the geographic coordinate system or local three-dimensional terrain coordinate system through the four-level transformation model to establish the spatial correspondence between the cloud radar detection results and the three-dimensional terrain, and complete the registration of the cloud radar detection results. The cloud construction module is used to construct a 3D cloud display object based on the registered cloud radar detection results. The situation object generation module is used to load local 3D terrain data to generate a 3D terrain scene, generate an aircraft model object based on the aircraft's real-time position and attitude, generate a flight track object based on historical position sequences, and generate an airspace restriction object based on external airspace data. The 3D situation display module is used to overlay cloud display objects, aircraft model objects, flight track objects and airspace restriction objects onto a 3D terrain scene to form a 3D flight situation main view. The profile generation and linkage module is used to generate a cutting plane according to user interaction or preset rules, extract the cross-sectional information of the cutting plane and the three-dimensional terrain, cloud display objects, flight track objects and airspace restriction objects to form a profile view, and realize the bidirectional linkage positioning of the three-dimensional main view and the profile view. The situation interaction module supports users in performing situation interaction operations such as switching between multiple perspectives, viewing and highlighting attributes of cloud bodies, flight paths, and airspace targets.

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