Method and system for weather radar clearance environment assessment

Abstract

This application relates to a method and system for assessing the airspace environment of a weather radar. The method includes acquiring UAV mapping data and digital elevation model (DEM) data covering the radar assessment area; performing coordinate system-1 and vertical datum-based calibration on the UAV mapping data and DEM data; constructing a fused elevation model based on the UAV mapping data and DEM data; radially sampling the fused elevation model with the radar as the center at preset azimuth and range steps to obtain radial profile elevation sequences in each direction; obtaining the shielding elevation angle and corresponding shielding distance through the apparent elevation angle in each direction; and comparing the shielding elevation angle with a preset airspace threshold to obtain the assessment result. This application can complement the advantages of high-precision UAV mapping results and wide-area DEM, and automatically output operationally usable airspace conclusions and maps.

Description

Technical Field

[0001] This application relates to the fields of meteorological radar engineering, surveying and mapping remote sensing and geographic information processing technology, and in particular to a method and system for assessing the airspace environment of weather radar by combining UAV surveying and mapping with DEM data. Background Technology

[0002] Current airspace assessments typically employ manual angle measurement using latitude and longitude or extrapolation from a limited number of samples. However, this approach suffers from several drawbacks: firstly, it is inefficient and has limited coverage, making it difficult to generate comprehensive, all-around assessment maps; secondly, it is insensitive to the addition of new high-rise buildings and the replacement of towers and masts due to rapid urban development; and thirdly, while relying solely on publicly available wide-area digital elevation models (DEMs) offers broad coverage, their limited resolution makes it difficult to depict the details of local obstacles, leading to biases in occlusion angle assessments and operational risks. Summary of the Invention

[0003] This application provides a weather radar airspace environment assessment method and system that can complement the advantages of high-precision UAV mapping results with wide-area DEM, and automatically output operational airspace conclusions and maps.

[0004] According to one of the solutions in this application, a method for assessing the airspace environment using weather radar is provided, including:

[0005] Acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment area; Perform coordinate system alignment and vertical datum consistency correction between UAV mapping data and DEM data; A fused elevation model was constructed based on UAV mapping data and DEM data; Radial sampling is performed on the fused elevation model with the radar as the center and at preset azimuth and range steps to obtain radial profile elevation sequence in each direction; By using the apparent elevation angles from various directions, the shading elevation angle and the corresponding shading distance can be obtained; The shading elevation angle is compared with the preset clearance threshold to obtain the evaluation result.

[0006] In some embodiments, the process of performing coordinate system-1 and vertical datum-based calibration on the UAV mapping data and DEM data includes: Projection transformation is performed to convert the data into the same geographic projection coordinate system, thereby ensuring the consistency of geographic information. Elevation datum unification is achieved by transforming the elevation datum to unify them into the same vertical datum. Error correction is performed to ensure a high degree of data consistency.

[0007] In some embodiments, constructing the fused elevation model includes: By using a weighted fusion method, UAV data is prioritized in the near-field area, while DEM data is used in the far-field area.

[0008] In some embodiments, the fused elevation model is radially sampled with respect to the radar at preset azimuth and range steps to obtain radial profile elevation sequences in each direction, including: Extract radial profile data from each direction; A set of candidate obstacles is generated based on the height information and type label of each sampling point.

[0009] In some embodiments, obtaining the shielding elevation angle and the corresponding shielding distance from the apparent elevation angles in each direction includes: An equivalent Earth radius model is used to perform propagation geometry modeling of the radar beam and calculate the shielding elevation angle in each direction; Calculate the apparent elevation angle based on the location of each sampling point and the height of the obstacle; The maximum shielding elevation angle along the radial direction and its corresponding shielding distance are obtained.

[0010] In some embodiments, obtaining the assessment results includes at least outputting a conclusion that the airspace meets the standards, and generating at least one airspace assessment map or report. in: Generate an all-round shielding elevation angle distribution map to display the maximum shielding elevation angle in each direction of the radar in polar coordinates, thereby assessing the airspace environment around the radar station. Generate an obstruction distance distribution map to show the maximum obstruction distance in each direction of the radar, thereby identifying areas where radar beam propagation is obstructed.

[0011] According to one of the solutions in this application, a weather radar airspace environment assessment system is provided, comprising: The processing architecture is used to acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment range; to perform coordinate system-1 and vertical datum consistency correction on the UAV mapping data and DEM data; to construct a fused elevation model based on the UAV mapping data and DEM data; to perform radial sampling on the fused elevation model with the radar as the center at preset azimuth and range steps to obtain radial profile elevation sequences in each direction; and to obtain the shielding elevation angle and corresponding shielding distance through the apparent elevation angle in each direction. The evaluation framework is used to compare the shading elevation angle with the preset clearance threshold to obtain the evaluation result.

[0012] In some embodiments, the processing architecture includes: The data acquisition module is used at least to access UAV point clouds and wide-area DEMs, and to read radar station parameters; The coordinate datum unification module is used at least for projection transformation, vertical datum consistency, and system deviation correction. The fusion modeling module is used at least to build fusion elevation models; A radial sampling module, at least used to extract profile point sequences according to azimuth and distance steps; The beam geometry and shielding calculation module is used to calculate at least the maximum shielding elevation angle and its corresponding shielding distance.

[0013] In some embodiments, the evaluation architecture includes: The threshold determination and business output module is used at least for determining partition thresholds and generating compliance conclusions.

[0014] In some embodiments, the evaluation architecture further includes: The visualization and reporting module is used to output at least occlusion elevation angle maps and occlusion distance maps.

[0015] The weather radar airspace environment assessment method of various embodiments of this application at least acquires UAV mapping data and digital elevation model (DEM) data covering the radar assessment range; performs coordinate system-1 and vertical datum consistency correction on the UAV mapping data and DEM data; constructs a fused elevation model based on the UAV mapping data and DEM data; performs radial sampling on the fused elevation model with the radar as the center at preset azimuth and distance steps to obtain radial profile elevation sequences in each direction; obtains the shielding elevation angle and corresponding shielding distance through the apparent elevation angle in each direction; compares the shielding elevation angle with a preset airspace threshold to obtain the assessment result, thereby solving the problems of incomplete coverage, untimely updates, insufficient obstacle characterization, and difficulty in forming standardized business output of assessment results in the prior art. Through the weather radar airspace environment assessment method and system based on the fusion of UAV mapping and digital elevation model in various embodiments of this disclosure, the automated, refined, and traceable assessment of the airspace environment around the radar station can be achieved.

[0016] It should be understood that the foregoing general description and the following detailed description are exemplary and illustrative only, and are not intended to limit the scope of this application. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic diagram of the overall flow of a weather radar airspace environment assessment method according to an embodiment of this application is shown; Figure 2 This illustration shows a schematic diagram of the unification and elevation consistency of UAV grid and wide-area DEM coordinates according to an embodiment of this application; Figure 3 A schematic diagram of the all-around shielding elevation angle distribution (polar coordinates) according to an embodiment of this application is shown; Figure 4 This application shows an occlusion distance distribution diagram and a schematic diagram of non-compliant obstacle location according to an embodiment of the present application; Figure 5 This paper shows a block diagram of the modules of a weather radar airspace environment assessment system according to an embodiment of the present application; Figure 6 This paper shows a map of the shading angle distribution in an engineering project using DEM data from an embodiment of this application. Figure 7 The images shown are of site surveys involved in projects employing embodiments of this application; Figure 8 This illustrates the latitude, longitude, and altitude information of a wind turbine generator obtained by unmanned aerial vehicle (UAV) in an engineering project employing an embodiment of this application. Figure 9 The diagram illustrates the occlusion angle distribution of DEM+UAV mapping data used in an engineering project employing an embodiment of this application. Detailed Implementation

[0019] Various embodiments and features of this application are described herein with reference to the accompanying drawings.

[0020] It should be understood that various modifications can be made to the embodiments described herein. Therefore, the above description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this application will be apparent to those skilled in the art.

[0021] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0022] These and other features of this application will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0023] It should also be understood that although this application has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of this application.

[0024] The above and other aspects, features and advantages of this application will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0025] Specific embodiments of this application are described thereafter with reference to the accompanying drawings; however, it should be understood that the claimed embodiments are merely examples of this application, which can be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that could obscure the application. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but merely serve as the basis and representative basis for the claims to teach those skilled in the art to use this application in a variety of substantially any suitable detailed structures.

[0026] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in other embodiments,” all of which may refer to one or more of the same or different embodiments according to this application.

[0027] Weather radar is highly sensitive to changes in the height of surrounding terrain, buildings, towers, and other man-made structures. Deterioration of the airspace can lead to an expansion of low-elevation detection blind spots, an increase in near-range false echoes and obscuring bands, thus impacting core operations such as quantitative precipitation estimation and severe convection identification. Currently, methods typically employ manual angle measurement using latitude and longitude or extrapolation from limited sampling: firstly, these methods are inefficient and have limited coverage, making it difficult to generate comprehensive, all-range assessment maps; secondly, they are insensitive to new high-rise buildings and tower upgrades resulting from rapid urban development; and thirdly, relying solely on publicly available DEMs, while providing broad coverage, has limited resolution, making it difficult to depict details of local obstacles, leading to biased obscuring angle assessments and operational risks.

[0028] Based on the background section described above, this application provides illustrative solutions to address the deficiencies in the prior art through embodiments, but these are not intended to limit the scope of patent protection claimed in this application.

[0029] As one of the solutions, comprehensive Figure 1 This illustration shows a schematic flowchart of a weather radar airspace environment assessment method according to an embodiment of this application. The embodiment of this application provides a weather radar airspace environment assessment method, including: Acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment area; Perform coordinate system alignment and vertical datum consistency correction between UAV mapping data and DEM data; A fused elevation model was constructed based on UAV mapping data and DEM data; Radial sampling is performed on the fused elevation model with the radar as the center and at preset azimuth and range steps to obtain radial profile elevation sequence in each direction; By using the apparent elevation angles from various directions, the shading elevation angle and the corresponding shading distance can be obtained; The shading elevation angle is compared with the preset clearance threshold to obtain the evaluation result.

[0030] In light of the foregoing, this application aims to provide at least one method for assessing the airspace environment surrounding a weather radar. The purpose is to offer an assessment technology solution that can complement the advantages of high-precision UAV mapping results with wide-area DEMs, and automatically output operationally usable airspace conclusions and maps. In conjunction with the preceding and following text, the technical solutions of the various embodiments of this disclosure aim to solve at least one of the technical problems existing in the prior art, including incomplete coverage, untimely updates, insufficient obstacle characterization, and the difficulty in forming standardized operational outputs of assessment results. The various embodiments of this disclosure achieve automated, refined, and traceable assessment of the airspace environment surrounding radar stations.

[0031] In the specific implementation of the embodiments of this disclosure, the weather radar airspace environment assessment method, each part of the scheme can be exemplarily described through steps S1 to S7 in the following sections.

[0032] Step S1: Data acquisition and preprocessing.

[0033] In this embodiment, the target radar station parameters and spatial reference information are obtained, including: radar station latitude and longitude, and antenna phase center elevation. Maximum detection range Business Focus Elevation Angle Set .

[0034] Simultaneously, oblique photogrammetry point cloud data from UAV mapping is acquired, covering the radius surrounding the radar station. =5km range; Wide-area DEM data: coverage radius is The DEM raster.

[0035] The point cloud of the UAV is denoised to generate a high-resolution DSM / raster; the DEM is projected, filled with holes and resampled to make the two have a unified coordinate system and a unified vertical reference.

[0036] In some implementation schemes, such as Figure 2 As shown, the embodiments of this application can be as follows: performing coordinate system and vertical datum consistency correction on UAV mapping data and DEM data, including: projection transformation, thereby converting to the same geographic projection coordinate system to ensure the consistency of geographic information; elevation datum consistency, through elevation datum transformation, to unify to the same vertical datum; error correction to ensure the high consistency of data.

[0037] This embodiment unifies the coordinate system and vertical datum of UAV mapping data (DSM) and wide-area digital elevation model (DEM) data to ensure consistency after data fusion and provide a high-precision geographic coordinate basis for subsequent beam propagation and masking angle calculations. Specific implementation includes: projection transformation, converting UAV mapping data and DEM data into the same geographic projection coordinate system to ensure geographic information consistency; elevation datum consistency, performing elevation datum transformation on data within overlapping areas to unify them to the same vertical datum; and error correction, calculating system deviation based on sampling points within overlapping areas and correcting errors using a mathematical model to ensure high data consistency.

[0038] This embodiment improves data fusion accuracy, ensuring consistency across data from different sources and reducing errors caused by inconsistencies in coordinates and elevations. It provides a high-precision foundation for subsequent calculations by unifying coordinates and benchmarks, offering accurate geographic coordinate support for subsequent beam propagation model calculations.

[0039] In this embodiment, the alignment correction between the coordinate system and the vertical reference can be illustrated by step S2 in the following section.

[0040] Step S2: Coordinate unification and elevation consistency correction.

[0041] Unify the UAV raster and DEM raster to the same projection coordinate system and elevation datum. For the overlapping areas of the UAV raster and DEM raster, sample the point set. Calculate the system deviation: , in, For UAV elevation DSM, The elevation of the DEM is determined. A series of sampling points are selected in the overlapping area between the UAV DSM and DEM. Calculate the difference in elevation between the two points at each point, and then take the median of these differences as the systematic deviation. In the application scenario of this embodiment, the median is not sensitive to outliers, such as vegetation, buildings, and other non-ground points, and can more robustly estimate the overall vertical deviation between the two data.

[0042] Perform vertical reference correction on the drone: , Among them, the calculated system deviation The elevation of each pixel in the UAV's DSM is corrected to obtain the corrected DSM. This ensures that the elevation benchmark of the UAV DSM is consistent with the reference DEM, facilitating subsequent data fusion, change detection, or accuracy assessment.

[0043] In some implementation schemes, the embodiments of this application may include: constructing a fused elevation model, including: using a weighted fusion method to prioritize the use of UAV data in the near area and DEM data in the far area.

[0044] This embodiment utilizes weighted fusion technology to construct a high-precision fused elevation model by combining UAV mapping data and wide-area DEM data. The model prioritizes UAV data in the near-field region and uses DEM data in the far-field region to ensure an optimal balance between coverage and accuracy. The weighted fusion method provides detailed terrain information in the near-field region, ensuring accurate depiction of small-scale obstacles, while maintaining broad data coverage in the far-field region to avoid data gaps. A transition zone smoothing algorithm eliminates unnatural joins in the data fusion process, ensuring the continuity and stability of the fusion result.

[0045] The construction of the fused elevation model in this embodiment can be illustrated by step S3 in the following section of this document.

[0046] Step S3: Constructing the integrated elevation model.

[0047] Build coverage radius Fusion elevation model In the near-field region, high-resolution UAV data is prioritized, while wide-area DEM data is used in the far-field region, with a smooth transition in the transition zone. Weighted fusion can be employed. , In each location , integration of elevation It is the corrected drone DSM With DEM The weighted average.

[0048] Among them, weight Related to the radial distance r from the radar station, , Weight The range of values ​​indicates the degree of trust in the drone data: =1 indicates that drone data (near-field) is used exclusively; =0 indicates that DEM data (remote area) is used exclusively; 0< <1 indicates a mixed transition (transition band).

[0049] In some implementations, the embodiments of this application may involve radially sampling the fused elevation model with the radar as the center at preset azimuth and range steps to obtain radial profile elevation sequences in each direction, including: extracting radial profile data in each direction; labeling obstacle types according to the height information and type of each sampling point, and generating a set of candidate obstacles.

[0050] This embodiment can extract radial profiles from the fused elevation model and generate a set of potential obstacles. Through omnidirectional radial sampling, the terrain and obstacles around the radar station are identified, providing a foundation for subsequent shielding angle calculations and operational adjustments. For example, centered on the radar station, the fused elevation model is sampled according to a preset azimuth step (0.1°) and distance step (50 meters) to extract radial profile data in each direction. Based on the height information and type of each sampling point, obstacle types such as terrain, buildings, and towers are labeled, and a candidate obstacle set is generated, providing data support for subsequent shielding determination and rectification positioning.

[0051] The radial profile height sequence obtained in this embodiment can be illustrated by step S4 in the following section of this document.

[0052] Step S4: Radial profile extraction and candidate obstacle set generation.

[0053] Centered on the radar station, according to azimuth angle (Step size 0.1°) and distance Sampling was performed at a step size of 50 meters to obtain a radial profile point sequence: , The profile elevation is It can extract obstacle type labels (such as buildings, trees, etc.) for subsequent analysis. It also outputs obstacle type annotations (terrain / building / tower / iron tower), forming a candidate obstacle set to facilitate business rectification and location. x 0 ，y 0) represents the planar coordinates of the radar station; It is the radial distance (in 50-meter steps) from the sampling point to the radar station, from a minimum positive value (e.g., 50 meters) to the maximum radius. ; It is the azimuth angle, measured from due east, rotating counterclockwise (in steps of 0.1°), with a total of 3600 rays. Each For a given ground point, use polar coordinates Convert to Cartesian coordinates ( x, y ), used in fusion elevation models Mid-positioning.

[0054] In some implementations, the embodiments of this application may include: obtaining the shielding elevation angle and the corresponding shielding distance by using the apparent elevation angle in each direction, including: performing propagation geometry modeling of the radar beam using an equivalent Earth radius model, calculating the shielding elevation angle in each direction; calculating the apparent elevation angle based on the position of each sampling point and the height of the obstacle; and obtaining the maximum shielding elevation angle along the radial direction and its corresponding shielding distance.

[0055] This embodiment uses an equivalent Earth radius model (k=4 / 3) to model the propagation geometry of the radar beam, calculates the shielding elevation angle in each direction, and records the corresponding shielding distance. Based on the refractive index k (commonly 4 / 3), the refraction effect of the radar beam propagating in the atmosphere is simulated, and its propagation path is calculated. The apparent elevation angle, i.e., the geometric elevation angle of the obstacle relative to the radar station, is calculated based on the location of each sampling point and the height of the obstacle. For each direction from 0-360°, the maximum shielding elevation angle along the radial direction is calculated, and the shielding distance corresponding to this maximum value is recorded.

[0056] The modeling and occlusion determination in this embodiment can be illustrated by step S5 in the following section of this document.

[0057] Step S5: Radar beam propagation geometric modeling and masking determination.

[0058] In this embodiment, an equivalent Earth radius model (refractive index) is considered. k (Commonly k=4 / 3), Earth's radius For a given elevation angle With distance The beam centerline height can be expressed as: , Therefore, calculate the distance At this location, the centerline of the radar beam is positioned at a height relative to the mean sea level. Among these, H r The altitude of the radar antenna is at sea wave height. The radar elevation angle (relative to the horizontal plane); k Taking 4 / 3 as the equivalent Earth radius factor can be used to simulate atmospheric refraction; This is the actual Earth radius (approximately 6371 km). Based on the corresponding parameters, the geometrical rise altitude of the beam under the flat Earth assumption can be obtained, as well as the correction terms for Earth curvature and atmospheric refraction (which bend the beam path and change the equivalent altitude).

[0059] The apparent elevation angle (geometric elevation angle of the obstacle apex relative to the radar) at any point on the cross-section is defined as: , Therefore, the azimuth as seen from the radar can be calculated. ,distance The geometric elevation angle of the topographic point. Wherein, the numerator of the above formula is the difference between the equivalent height of the topographic point (actual elevation minus Earth's curvature correction) and the height of the radar antenna; the denominator is the horizontal distance. The elevation angle reflects the potential for terrain features to obstruct the radar line of sight; for example, the higher the elevation angle, the greater the potential obstruction.

[0060] For a certain direction from 0-360° Its shielding elevation angle is defined as the maximum value along the distance direction: , That is, along the direction From radar to maximum distance Between these values, the maximum elevation angle of all terrain points is considered. This value represents the minimum elevation angle that the radar must be set to in that azimuth for the beam to pass over all terrain obstacles (i.e., without being blocked).

[0061] The distance at which the maximum value is reached is recorded as the occlusion distance: , That is, by reaching the distance corresponding to the maximum apparent elevation angle, the location of the terrain obstacle that contributes the most to azimuthal obstruction is identified. For a specified service elevation angle... When there exists r such that It is determined that there is obstruction at that elevation angle in that direction.

[0062] In some implementations, the embodiments of this application may include at least outputting an airspace compliance conclusion and generating at least one airspace assessment map or report; wherein: generating an all-round shielding elevation angle distribution map to display the maximum shielding elevation angle in each direction of the radar in polar coordinates, thereby assessing the airspace environment around the radar station; generating a shielding distance distribution map to display the maximum shielding distance in each direction of the radar, thereby identifying the areas where radar beam propagation is obstructed.

[0063] This embodiment can compare the shielding elevation angle with the preset airspace threshold to determine the airspace compliance conclusion and generate at least one airspace assessment map or report.

[0064] like Figure 3 The diagram shows the all-around shielding elevation angle distribution: This diagram displays the maximum shielding elevation angle in each direction of the radar station in polar coordinates, providing a comprehensive assessment of the airspace surrounding the radar station. Compared to traditional methods, it accurately displays the shielding angle in each direction, especially in low elevation areas, thus ensuring higher accuracy in radar coverage assessment. This diagram provides a comprehensive view of the radar station environment, helping to optimize site selection and dynamic monitoring, and supporting more scientific airspace protection measures.

[0065] like Figure 4The obstruction distance distribution map shown illustrates the maximum obstruction distance in all directions of the radar station, helping to identify areas where radar beam propagation is obstructed. Compared to traditional methods, this map more intuitively marks the location of radar blind spots, providing data support for site adjustments and obstacle remediation, improving the stability and efficiency of the radar system, and demonstrating higher assessment accuracy, especially in complex terrain or urban construction environments.

[0066] This embodiment can be illustrated by step S6 and step S7 in the following sections of this document.

[0067] Step S6: Determining the operational airspace threshold and evaluating the zones.

[0068] Set the main detection direction set according to business management rules. AND non-principal direction set The system calculates the radius of the near / far zone segments, uses different thresholds, and outputs three levels of conclusions: "compliant / warning / non-compliant". It also outputs the coordinates of obstacles, obstacle height, obstruction distance, and a list of suggested rectifications for non-compliant locations.

[0069] Step S7: Drawings and reports are generated automatically.

[0070] The automatically generated business deliverables include: an all-round shielding elevation angle distribution map, a shielding distance distribution map, a clearance compliance zoning map, a key azimuth radial profile map and obstacle location table, and a standardized assessment report.

[0071] As one of the solutions, comprehensive Figure 5 This illustration shows a general flowchart of a weather radar airspace environment assessment method according to an embodiment of this application. The embodiments of this application provide a weather radar airspace environment assessment system, including: The processing architecture is used to acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment range; to perform coordinate system-1 and vertical datum consistency correction on the UAV mapping data and DEM data; to construct a fused elevation model based on the UAV mapping data and DEM data; to perform radial sampling on the fused elevation model with the radar as the center at preset azimuth and range steps to obtain radial profile elevation sequences in each direction; and to obtain the shielding elevation angle and corresponding shielding distance through the apparent elevation angle in each direction. The evaluation framework is used to compare the shading elevation angle with the preset clearance threshold to obtain the evaluation result.

[0072] In some implementations, embodiments of this application may be a weather radar airspace assessment system, including: Data acquisition module: used to access UAV point cloud and wide-area DEM, and read radar station parameters; Coordinate reference unification module: used for projection transformation, vertical reference consistency and system deviation correction; Fusion Modeling Module: Used to build fusion elevation models And preserve obstacle details; Radial sampling module: used to extract profile point sequences according to azimuth and distance steps; Beam geometry and masking calculation module: used for calculation and determination of occlusion at a specified elevation angle; Threshold determination and business output module: used for determining thresholds for different zones, generating rectification lists and compliance conclusions; Visualization and Reporting Module: Used to output occlusion elevation angle map, occlusion distance map, airspace compliance map, and report files; Storage module: Used to store fusion models, parameter versions and output results, enabling traceability.

[0073] Based on the content of the various technical solutions disclosed in the previous text, the technical solutions involved in the weather radar airspace environment assessment method and system disclosed herein, as well as the corresponding beneficial effects, can be further explained in detail through specific implementation methods and specific engineering implementation cases, such as the case of site selection for a weather radar in a certain region and a certain X-band weather radar.

[0074] In a certain year, a proposed site for an X-band weather radar was planned for the western part of the region. The proposed site elevation was 1510 meters, and the planned antenna installation height was 20 meters. Initially, DEM data was used to conduct an airspace environment assessment of the proposed radar site. The assessment revealed the following obstruction situation: Figure 6 As shown. Subsequent on-site surveys revealed nearly 200 wind turbines surrounding the proposed site. Figure 7 As shown, manually measuring the obstruction of wind turbines using a theodolite is time-consuming, labor-intensive, and inaccurate. To address this engineering challenge, the technical solution of this disclosed weather radar airspace environment assessment method and system is used to conduct UAV-based mapping of the wind turbines surrounding the site. The results are as follows: Figure 8 As shown, the survey results were fused with the DEM data, and the airspace environment of the proposed site was reassessed using the fused data. The assessment results are as follows. Figure 9 As shown in the figure, a comparison of the two assessment results reveals that using DEM data alone cannot accurately assess the airspace environment. Combining UAV mapping with DEM fusion methods provides a more accurate assessment of the airspace environment.

[0075] Based on the embodiments of this disclosure and actual engineering cases, compared with the prior art, the beneficial effects of the technical solutions involved in the weather radar airspace environment assessment method and system of this disclosure are at least reflected in the following aspects: 1) The use of high-precision data from UAVs in the near area significantly improves the ability to depict small-scale obstacles such as building complexes / towers and masts; 2) Wide-area DEMs are used in remote areas to ensure complete coverage and avoid insufficient coverage due to relying solely on drones; 3) By standardizing the baseline and fusing the transition zone, the step error of multi-source data splicing is reduced, and the stability of the occlusion angle is improved; 4) Automated output of all-round shielding elevation angle, shielding distance and "compliant / warning / non-compliant" business conclusions, facilitating the closed loop of airspace protection and rectification; 5) Parameters, data sources and versions are traceable, which is suitable for site demonstration, periodic review and dynamic supervision of urban construction.

[0076] This disclosure also provides a weather radar airspace environment assessment device, including one or more processing modules configured to perform the weather radar airspace environment assessment method described above, and at least configured to perform specific implementations of steps S1 to S7.

[0077] Based on the above-mentioned inventive concept, the weather radar airspace environment assessment method, apparatus, and system of various embodiments of this disclosure at least acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment range; perform coordinate system-1 and vertical reference consistency correction on the UAV mapping data and DEM data; construct a fused elevation model based on the UAV mapping data and DEM data; perform radial sampling on the fused elevation model with the radar as the center according to a preset azimuth step size and distance step size to obtain radial profile elevation sequence in each direction; obtain the shielding elevation angle and corresponding shielding distance through the apparent elevation angle in each direction; compare the shielding elevation angle with a preset airspace threshold to obtain the assessment result, thereby solving the problems of incomplete coverage, untimely updates, insufficient obstacle characterization, and difficulty in forming standardized business output of assessment results in the prior art. Through the weather radar airspace environment assessment method and system based on the fusion of UAV mapping and digital elevation model in various embodiments of this disclosure, the automated, refined, and traceable assessment of the airspace environment around the radar station can be achieved.

[0078] This application also provides a computer-readable storage medium storing computer-executable instructions thereon, which, when executed by a processor, mainly implement the weather radar airspace environment assessment method described above, including: Acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment area; Perform coordinate system alignment and vertical datum consistency correction between UAV mapping data and DEM data; A fused elevation model was constructed based on UAV mapping data and DEM data; Radial sampling is performed on the fused elevation model with the radar as the center and at preset azimuth and range steps to obtain radial profile elevation sequence in each direction; By using the apparent elevation angles from various directions, the shading elevation angle and the corresponding shading distance can be obtained; The shading elevation angle is compared with the preset clearance threshold to obtain the evaluation result.

[0079] The above embodiments are merely exemplary embodiments of this application and are not intended to limit this application. The scope of protection of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent substitutions to this application within its substance and scope of protection, and such modifications or equivalent substitutions should also be considered to fall within the scope of protection of this application.

Claims

1. Weather radar airspace environment assessment methods, including: Acquire UAV mapping data and digital elevation model (DEM) data covering the radar assessment area; Perform coordinate system alignment and vertical datum consistency correction between UAV mapping data and DEM data; A fused elevation model was constructed based on UAV mapping data and DEM data; Radial sampling is performed on the fused elevation model with the radar as the center and at preset azimuth and range steps to obtain radial profile elevation sequence in each direction; By using the apparent elevation angles from various directions, the shading elevation angle and the corresponding shading distance can be obtained; The shading elevation angle is compared with the preset clearance threshold to obtain the evaluation result.

2. The method according to claim 1, wherein the coordinate system of the UAV mapping data and the DEM data is aligned with the vertical datum, comprising: Projection transformation is performed to convert the data into the same geographic projection coordinate system, thereby ensuring the consistency of geographic information. Elevation datum unification is achieved by transforming the elevation datum to unify them into the same vertical datum. Error correction is performed to ensure a high degree of data consistency.

3. The method according to claim 2, wherein, Constructing a fused elevation model includes: By using a weighted fusion method, UAV data is prioritized in the near-field area, while DEM data is used in the far-field area.

4. The method according to claim 3, wherein, Radial sampling is performed on the fused elevation model centered on the radar at preset azimuth and range steps to obtain radial profile elevation sequences in each direction, including: Extract radial profile data from each direction; A set of candidate obstacles is generated based on the height information and type label of each sampling point.

5. The method according to claim 4, wherein, By using the apparent elevation angles from various directions, the shading elevation angle and the corresponding shading distance are obtained, including: An equivalent Earth radius model is used to perform propagation geometry modeling of the radar beam and calculate the shielding elevation angle in each direction; Calculate the apparent elevation angle based on the location of each sampling point and the height of the obstacle; The maximum shielding elevation angle along the radial direction and its corresponding shielding distance are obtained.

6. The method according to claim 5, obtaining the assessment result, includes at least outputting a conclusion that the airspace meets the standards, and generating at least one airspace assessment map or report; in: Generate an all-round shielding elevation angle distribution map to display the maximum shielding elevation angle in each direction of the radar in polar coordinates, thereby assessing the airspace environment around the radar station. Generate an obstruction distance distribution map to show the maximum obstruction distance in each direction of the radar, thereby identifying areas where radar beam propagation is obstructed.

7. Weather radar airspace assessment system, including: Processing architecture for acquiring UAV mapping data and digital elevation model (DEM) data covering the radar assessment range; The UAV mapping data and DEM data are calibrated to be consistent with the coordinate system and vertical reference. A fused elevation model is constructed based on the UAV mapping data and DEM data. The fused elevation model is radially sampled with the radar as the center according to the preset azimuth step and distance step to obtain the radial profile elevation sequence in each direction. The shielding elevation angle and the corresponding shielding distance are obtained through the apparent elevation angle in each direction. The evaluation framework is used to compare the shading elevation angle with the preset clearance threshold to obtain the evaluation result.

8. The system according to claim 7, wherein, Processing architecture, including: The data acquisition module is used at least to access UAV point clouds and wide-area DEMs, and to read radar station parameters; The coordinate datum unification module is used at least for projection transformation, vertical datum consistency, and system deviation correction. The fusion modeling module is used at least to build fusion elevation models; A radial sampling module, at least used to extract profile point sequences according to azimuth and distance steps; The beam geometry and shielding calculation module is used to calculate at least the maximum shielding elevation angle and its corresponding shielding distance.

9. The system according to claim 8, wherein, The evaluation architecture includes: The threshold determination and business output module is used at least for determining partition thresholds and generating compliance conclusions.

10. The system according to claim 9, wherein, The evaluation architecture also includes: The visualization and reporting module is used to output at least occlusion elevation angle maps and occlusion distance maps.

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