Method and device for calculating satellite phased array beam coverage area
By employing spherical resampling and spherical area integration methods, the problems of coordinate non-uniformity and projection distortion in the calculation of satellite phased array beam coverage area were solved, achieving high-precision coverage area calculation and improving the coverage performance evaluation of satellite communication systems.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING GUODIAN GAOKE TECH CO LTD
- Filing Date
- 2026-04-10
- Publication Date
- 2026-07-31
AI Technical Summary
In existing technologies, the method for calculating the coverage area of satellite phased array beams ignores non-uniform coordinate sampling and map projection distortion, resulting in a large deviation between the calculated results and the actual area.
By performing spherical resampling, the coverage markers on non-uniformly distributed coordinate points are transformed to a set of uniformly distributed sampling points on the spherical domain. Then, spherical area integration is performed in the spherical coordinate system to calculate the actual coverage area of the beam on the Earth's surface.
It significantly improves the accuracy and reliability of satellite communication system coverage performance assessment, eliminates calculation errors caused by coordinate non-uniformity and projection distortion, and is applicable to the calculation of coverage area of beams of any shape.
Smart Images
Figure CN122496076A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of satellite communication technology, and in particular to a method and apparatus for calculating the coverage area of a satellite phased array beam. Background Technology
[0002] In satellite communication systems, phased array antennas have become core equipment for low-Earth orbit satellite constellations due to their ability to rapidly scan and flexibly shape beams. Accurately assessing the coverage area of phased array beams on the Earth's surface is of great significance for key aspects such as system capacity planning, inter-beam interference coordination, frequency resource reuse, and satellite-to-ground link budget analysis.
[0003] Typically, beam coverage is presented as a beam footprint map. A beam footprint map is a binary image generated by coordinate mapping based on the antenna pattern, used to visually represent the area covered by the beam on the Earth's surface. However, in related technologies, area calculations based on beam footprint maps often ignore the effects of non-uniform coordinate sampling and map projection distortion, leading to a significant deviation between the calculated coverage area and the actual area on the Earth's surface.
[0004] Therefore, there is an urgent need for a method to calculate the coverage area of satellite phased array beams, so as to accurately calculate the true coverage area of irregularly shaped beams on the Earth's surface and eliminate the calculation errors introduced by non-uniform coordinates and projection distortion. Summary of the Invention
[0005] The purpose of this application is to provide a method and apparatus for calculating the coverage area of a satellite phased array beam, which accurately calculates the true area of irregular beam coverage regions with high precision, and significantly improves the accuracy and reliability of satellite communication system coverage performance evaluation.
[0006] This application provides a method for calculating the coverage area of a satellite phased array beam, including: Obtain a binarized beam footprint map of the satellite phased array beam; perform spherical resampling on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, to obtain resampled coverage marker data; based on the resampled coverage marker data, perform spherical area integration in the spherical coordinate system to calculate the sum of the spherical micro-areas corresponding to all sampling points marked as covered, to obtain the actual coverage area of the phased array beam on the Earth's surface.
[0007] Optionally, the step of performing spherical resampling processing on the coverage identifiers in the beam footprint map, transforming the coverage identifiers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, to obtain resampled coverage identifier data, includes: creating a uniform grid on the sphere with geographic latitude and longitude as coordinates, and generating uniform grid points based on a set latitude and longitude range, longitude interval, and latitude interval; calculating the coverage status estimate at each grid point using a spherical interpolation method based on the coverage identifier values on the original non-uniform coordinate points; comparing the coverage status estimate with a preset threshold, and generating a binarized coverage identifier based on the comparison result, to obtain the resampled coverage identifier data.
[0008] Optionally, the step of calculating the coverage status estimate of each grid point using spherical interpolation based on the coverage identifier value at the original non-uniform coordinate points includes: for any target grid point, converting the latitude and longitude coordinates of the target grid point into antenna coordinates in the antenna coordinate system based on the coordinate transformation relationship between the non-uniform coordinate points in the pre-established original footprint map and the latitude and longitude coordinates of each grid point in the uniform grid; within a local neighborhood centered on the target grid point, finding multiple neighboring non-uniform sampling points and the corresponding binarized coverage identifier value from the beam footprint map; and using a spherical interpolation algorithm to calculate the coverage status estimate of the target grid point based on the coverage identifier values of the multiple neighboring non-uniform sampling points.
[0009] Optionally, the step of performing spherical area integration in spherical coordinates based on the resampled coverage identification data to calculate the sum of the spherical micro-area areas corresponding to all sampling points identified as covered, and obtaining the actual coverage area of the phased array beam on the Earth's surface, includes: calculating the spherical micro-area of the grid cell represented by each sampling point according to the position coordinates of each sampling point in the sampling point set on the sphere; and summing the spherical micro-area areas corresponding to all sampling points identified as covered to obtain the total coverage area.
[0010] This application also provides a satellite phased array beam coverage area calculation device, including: The acquisition module is used to acquire a binary beam footprint map of the satellite phased array beam; the resampling module is used to perform spherical resampling processing on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, and obtaining the resampled coverage marker data; the area calculation module is used to perform spherical area integration in the spherical coordinate system based on the resampled coverage marker data, calculate the sum of the spherical micro-area areas corresponding to all sampling points marked as coverage, and obtain the actual coverage area of the phased array beam on the Earth's surface.
[0011] Optionally, the resampling module is specifically used to create a uniform grid on the sphere with geographic latitude and longitude as coordinates, and generate uniform grid points based on a set latitude and longitude range, longitude interval, and latitude interval; the resampling module is also specifically used to calculate the coverage status estimate at each grid point using a spherical interpolation method based on the coverage identifier value at the original non-uniform coordinate points; the resampling module is also specifically used to compare the coverage status estimate with a preset threshold, and generate a binarized coverage identifier based on the comparison result, thereby obtaining the resampled coverage identifier data.
[0012] Optionally, the resampling module is specifically used to convert the latitude and longitude coordinates of any target grid point into antenna coordinates in the antenna coordinate system based on the coordinate transformation relationship between the non-uniform coordinate points in the pre-established original footprint map and the latitude and longitude coordinates of each grid point in the uniform grid. The resampling module is also specifically used to find multiple neighboring non-uniform sampling points and the corresponding binarized coverage identifier value of each non-uniform sampling point in the beam footprint map within a local neighborhood centered on the target grid point. The resampling module is also specifically used to calculate the coverage status estimate of the target grid point based on the coverage identifier values of the multiple neighboring non-uniform sampling points using a spherical interpolation algorithm.
[0013] Optionally, the area calculation module is specifically used to calculate the spherical micro-element area of the grid unit represented by each sampling point based on the position coordinates of each sampling point on the sphere in the sampling point set; the area calculation module is also specifically used to accumulate the spherical micro-element areas corresponding to all sampling points identified as covered to obtain the total coverage area.
[0014] This application also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the satellite phased array beam coverage area calculation method as described above.
[0015] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the above-described satellite phased array beam coverage area calculation methods.
[0016] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the satellite phased array beam coverage area calculation method as described above.
[0017] The method and apparatus for calculating the coverage area of a satellite phased array beam provided in this application first obtain a binarized beam footprint map of the satellite phased array beam. Then, the coverage markers in the beam footprint map are subjected to spherical resampling processing, transforming the coverage markers on non-uniformly distributed coordinate points into a set of uniformly distributed sampling points on a spherical domain, resulting in resampled coverage marker data. Finally, based on the resampled coverage marker data, spherical area integration is performed in a spherical coordinate system to calculate the sum of the spherical micro-areas corresponding to all sampling points marked as covered, thus obtaining the actual coverage area of the phased array beam on the Earth's surface. In this way, by transforming the non-uniformly distributed original beam footprint data to a uniform grid through spherical resampling, the calculation errors caused by coordinate non-uniformity and projection distortion are easily eliminated. By directly accumulating the micro-area based on the spherical geometric model through spherical area integration, high-precision calculation of the true area of irregular beam coverage regions is accurately achieved, significantly improving the accuracy and reliability of satellite communication system coverage performance evaluation. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a flowchart illustrating the method for calculating the coverage area of a satellite phased array beam provided in this application; Figure 2 This is a schematic diagram of the resampling process from a non-uniform footprint map to a spherical uniform grid provided in this application; Figure 3 This is a schematic diagram illustrating the principle of spherical infinitesimal element area integral calculation provided in this application; Figure 4 This is a schematic diagram of the satellite phased array beam coverage area calculation device provided in this application; Figure 5 This is a schematic diagram of the structure of the electronic device provided in this application. Detailed Implementation
[0020] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions 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, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0021] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, "and / or" in the specification and claims indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship. All actions involving the acquisition of signal information or data in this application are performed in accordance with the relevant data protection laws and policies of the country where the application is located and with authorization from the owner of the relevant device.
[0022] In related technologies, the following schemes are mainly used to calculate the coverage area of satellite phased array beams: The first type is the geometric approximation method. This method simplifies the beam coverage area into a regular geometric shape, such as a circle or ellipse, and estimates the coverage diameter using the beamwidth and satellite altitude, thus calculating the coverage area. This method is computationally simple, but it assumes that the beam shape is regular and symmetrical. However, actual phased array beams are affected by multiple factors such as antenna element arrangement, beam pointing, sidelobe level, and Earth curvature, resulting in irregularly shaped coverage areas. The geometric approximation method cannot accurately reflect the true coverage area, and the estimation error is relatively large, failing to meet the requirements of high-precision system design and performance evaluation.
[0023] The second type is the pixel integration method based on beam footprint maps. This method directly counts the covered pixels in the beam footprint map and combines this with the map projection scale to calculate the area. However, this type of method has inherent drawbacks. First, beam footprint maps typically use the azimuth and elevation angles of the antenna as coordinates. The distribution of sampling points on the Earth's surface under this coordinate system is non-uniform, and directly accumulating the area of the original coordinate points will produce systematic bias. Second, when projecting the spherical coverage area onto a planar image, projection distortion is inevitably introduced. For example, under Mercator-like projections, the area of high-latitude regions will be significantly magnified. Existing technologies often ignore the above-mentioned non-uniform sampling and projection distortion problems, resulting in a large difference between the area calculated based on the planar image and the actual area on the Earth's surface.
[0024] To address the aforementioned technical problems in related technologies, this application provides a method for calculating the coverage area of a satellite phased array beam. Compared with the technical solutions in related technologies, this method has the following beneficial effects: 1. High calculation accuracy: This scheme overcomes the errors caused by the non-uniformity of the original footprint map coordinates and the projection deformation through spherical interpolation, and accurately calculates the area on the curved surface through spherical surface integration. Compared with the traditional method based on plane approximation, the accuracy is significantly improved.
[0025] 2. The method has strong universality: This scheme does not depend on a specific beam shape (regular or irregular) and is applicable to the area calculation of any complex coverage pattern generated by phased array beamforming.
[0026] 3. Good engineering practicality: The process is clear, can be automated, and can be seamlessly connected to the beam footprint generation process to provide real-time beam coverage area indicators for satellite communication systems.
[0027] 4. Decoupling from beamforming technology: This solution is a post-processing technology that is independent of specific beamforming algorithms and antenna pattern acquisition methods, and has high versatility.
[0028] The method for calculating the coverage area of satellite phased array beams provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.
[0029] like Figure 1 As shown in the embodiment of this application, a method for calculating the coverage area of a satellite phased array beam is provided. This method may include the following steps 101 to 103: Step 101: Obtain the binarized beam footprint map of the satellite phased array beam.
[0030] The beam footprint map uses azimuth and elevation angles, which represent the position on the Earth's surface, as coordinates, and each coordinate point in the beam footprint map has a binary coverage identifier.
[0031] For example, the beam footprint map described above is a binarized beam footprint map of a low-Earth orbit satellite phased array beam generated using a satellite phased array beam footprint calculation method. This footprint map uses the azimuth angle representing the position on the Earth's surface. and pitch angle Using coordinates, each coordinate point in the image has a binary coverage indicator; a pixel value of 1 represents coverage, and 0 represents no coverage. The footprint map has a resolution of M×N, meaning it contains M azimuth angle sampling points and N pitch angle sampling points, denoted as... .
[0032] It should be noted that in this footprint diagram The sampling interval between ' and θ' is non-uniform, and the coordinate points Their distribution across the Earth's surface is also uneven.
[0033] Step 102: Perform spherical resampling on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, to obtain the resampled coverage marker data.
[0034] The spherical interpolation method includes any one of the following: spherical nearest neighbor interpolation, spherical linear interpolation, and spherical spline interpolation.
[0035] For example, in order to perform accurate area integration, it is necessary to eliminate the error caused by the non-uniformity of coordinates in the original footprint map, create a uniform grid on the sphere, and map the overlay markers in the original footprint map onto this uniform grid.
[0036] Specifically, step 102 above may also include the following steps: 102a, 102b, and 102c: Step 102a: Create a uniform grid on the sphere with geographic latitude and longitude as coordinates, and generate uniform grid points based on the set latitude and longitude range, longitude interval and latitude interval.
[0037] For example, this embodiment selects geographical latitude and longitude as coordinates to construct a uniform target grid. Specifically, a longitude range is set. and latitude range Grid spacing is and (e.g., 0.1°), generate I×J uniformly distributed grid points. ,in , These grid points will become the target sampling points for subsequent resampling. Simultaneously, it is necessary to establish non-uniform coordinate points in the original footprint map. Latitude and longitude coordinates of the target grid point The coordinate transformation relationship between them.
[0038] Step 102b: Based on the coverage identifier values at the original non-uniform coordinate points, calculate the estimated coverage state at each grid point using the spherical interpolation method.
[0039] Specifically, step 102b above may also include steps 102b1 to 102b3: Step 102b1: For any target grid point, based on the coordinate transformation relationship between the non-uniform coordinate points in the pre-established original footprint map and the latitude and longitude coordinates of each grid point in the uniform grid, convert the latitude and longitude coordinates of the target grid point into antenna coordinates in the antenna coordinate system.
[0040] Step 102b2: Within the local neighborhood centered on the target grid point, find multiple neighboring non-uniform sampling points and the corresponding binarized coverage identifier value of each non-uniform sampling point from the beam footprint map.
[0041] Step 102b3: Using a spherical interpolation algorithm, calculate the estimated coverage status of the target grid point based on the coverage identifier values of the multiple neighboring non-uniform sampling points.
[0042] For example, traversing each grid point Perform the following operations: First, using the coordinate transformation relationship described above, convert the latitude and longitude coordinates of the current grid point. Convert to antenna coordinate system Then, in the context of Within the local neighborhood of the center, find several neighboring non-uniform sampling points from the original beam footprint map. The corresponding binarized coverage identifier values are then used; finally, a spherical interpolation algorithm is employed to calculate the estimated coverage status of the current target grid point based on the coverage identifier values of these neighboring sampling points. .
[0043] Specifically, in one implementation, spherical nearest neighbor interpolation is used. For the current target grid point, the spherical distance (great circle distance) between it and all non-uniform sampling points in the original footprint map is calculated. The original sampling point with the smallest spherical distance is selected, and the coverage flag value (0 or 1) of the sampling point is directly assigned to the current target grid point as its coverage state estimate.
[0044] In another implementation, spherical linear interpolation is used. For the current target grid point, K neighboring non-uniform sampling points are selected in its local neighborhood. The coverage identifier values of these sampling points and their spherical distances to the target point are obtained. A weighted calculation is performed based on the spherical distances to obtain a coverage probability estimate between 0 and 1 as the coverage state estimate. For example, an inverse distance weighting method can be used, where sampling points that are closer to each other have a larger weight.
[0045] Step 102c: Compare the estimated coverage status with a preset threshold, and generate a binarized coverage identifier based on the comparison result to obtain the resampled coverage identifier data.
[0046] For example, the calculated coverage state estimate Compare with a preset threshold (e.g., 0.5). If If the value is ≥0.5, the coverage identifier of the target grid point is assigned a value of 1; otherwise, it is assigned a value of 0. Thus, the original non-uniformly distributed binarized coverage identifier data is transformed into binarized coverage identifier data on a uniformly distributed set of sampling points on the spherical domain, resulting in resampled coverage identifier data. Specifically, as follows Figure 2 The diagram shows a schematic of the resampling process from a non-uniform footprint map to a spherical uniform grid.
[0047] It should be noted that step 102 above ultimately outputs a uniformly distributed and binarized coverage matrix on the latitude and longitude grid, which is the aforementioned coverage identification data.
[0048] Step 103: Based on the resampled coverage identification data, perform spherical area integration in spherical coordinate system to calculate the sum of the spherical micro-element areas corresponding to all sampling points identified as covered, and obtain the actual coverage area of the phased array beam on the Earth's surface.
[0049] For example, after obtaining the above coverage identification data, the spherical micro-element area of each grid cell can be calculated, and the actual coverage area of the phased array beam on the Earth's surface can be obtained.
[0050] Specifically, step 103 above may also include the following steps 103a1 and 103a2: Step 103a1: Calculate the spherical micro-element area of the grid cell represented by each sampling point based on the position coordinates of each sampling point on the sphere in the sampling point set.
[0051] Step 103a2: Sum the areas of the spherical micro-elements corresponding to all the sampling points that are marked as covered to obtain the total coverage area.
[0052] For example, for a uniform latitude and longitude grid, located at latitude A small grid cell at that location (can be used) To indicate the span, use The area of a spherical infinitesimal element (in radians) It can be calculated using the following formula: (Formula 1) in, For any grid cell in a uniform grid at latitude The area of the spherical infinitesimal element at that point, R For the Earth's radius, Longitude interval The interval is the latitude.
[0053] For example, traversing the entire I×J grid, for all The grid points are used to determine the area of their corresponding spherical infinitesimal elements. The sum is accumulated, and the sum S is the actual coverage area of the beam on the Earth's surface, which can be expressed by the following formula: (Formula 2) The unit of the sum S is usually square kilometers. This process is as follows: Figure 3 The diagram shown illustrates the principle of calculating the area integral of a spherical infinitesimal element.
[0054] It should be noted that, to verify the effect, a symmetrical beam pointing towards the nadir point is assumed. Traditional methods approximate its coverage as a circle, estimating the diameter and calculating the area using the beamwidth. Simultaneously, the calculation method of this scheme calculates the area based on a footprint map generated from a high-precision radiation pattern. Comparison reveals that, due to the influence of antenna pattern sidelobes and spherical geometry, the area calculated by this scheme is more accurate, showing a considerable difference (e.g., 5%-15%) compared to the results of traditional approximation methods. This difference is not negligible in scenarios such as system interference analysis. This demonstrates the practical value of this scheme in improving the accuracy of area calculation.
[0055] The satellite phased array beam coverage area calculation method provided in this application overcomes the errors caused by the non-uniformity of the original footprint map coordinates and projection distortion through spherical resampling processing; further, it accurately calculates the true coverage area on the curved surface through spherical area integration. Compared with traditional methods based on planar approximation, the calculation accuracy of this application embodiment is significantly improved. At the same time, this method does not depend on a specific beam shape and is applicable to the area calculation of any complex coverage pattern generated by phased array beamforming. It has the advantages of strong universality and good engineering practicality, and can provide accurate data support for the coverage performance evaluation and resource optimization of satellite communication systems.
[0056] The satellite phased array beam coverage area calculation method provided in this application first obtains a binarized beam footprint map of the satellite phased array beam. Then, it performs spherical resampling on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points into a uniformly distributed set of sampling points on a spherical domain, obtaining resampled coverage marker data. Finally, based on the resampled coverage marker data, it performs spherical area integration in a spherical coordinate system to calculate the sum of the spherical micro-area areas corresponding to all sampling points marked as covered, obtaining the actual coverage area of the phased array beam on the Earth's surface. Thus, by transforming the non-uniformly distributed original beam footprint data to a uniform grid through spherical resampling, the calculation errors caused by coordinate non-uniformity and projection distortion are easily eliminated. By directly accumulating the micro-area based on the spherical geometric model through spherical area integration, high-precision calculation of the true area of irregular beam coverage regions is accurately achieved, significantly improving the accuracy and reliability of satellite communication system coverage performance evaluation.
[0057] It should be noted that the satellite phased array beam coverage area calculation method provided in this application embodiment can be executed by a satellite phased array beam coverage area calculation device, or a control module within that device for executing the calculation method. This application embodiment uses the satellite phased array beam coverage area calculation device executing the calculation method as an example to illustrate the satellite phased array beam coverage area calculation device provided in this application embodiment.
[0058] It should be noted that, in the embodiments of this application, the satellite phased array beam coverage area calculation methods shown in the accompanying drawings are all illustrated by way of example with reference to one of the accompanying drawings in the embodiments of this application. In specific implementation, the satellite phased array beam coverage area calculation methods shown in the accompanying drawings of the above methods can also be implemented in conjunction with any other accompanying drawings shown in the above embodiments, which will not be elaborated here.
[0059] The satellite phased array beam coverage area calculation device provided in this application is described below. The satellite phased array beam coverage area calculation method described below can be referred to in correspondence with the method described above.
[0060] Figure 4 This is a schematic diagram of the structure of the satellite phased array beam coverage area calculation device provided in the embodiments of this application, as shown below. Figure 4 As shown, it specifically includes: The acquisition module 401 is used to acquire a binary beam footprint map of the satellite phased array beam; the resampling module 402 is used to perform spherical resampling processing on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, and obtaining the resampled coverage marker data; the area calculation module 403 is used to perform spherical area integration in the spherical coordinate system based on the resampled coverage marker data, calculate the sum of the spherical micro-element areas corresponding to all sampling points marked as coverage, and obtain the actual coverage area of the phased array beam on the Earth's surface.
[0061] Optionally, the resampling module 402 is specifically used to create a uniform grid on the sphere with geographic latitude and longitude as coordinates, and generate uniform grid points based on the set latitude and longitude range, longitude interval, and latitude interval; the resampling module 402 is also specifically used to calculate the coverage status estimate at each grid point using a spherical interpolation method based on the coverage identifier value at the original non-uniform coordinate points; the resampling module 402 is also specifically used to compare the coverage status estimate with a preset threshold, and generate a binarized coverage identifier based on the comparison result, thereby obtaining the resampled coverage identifier data.
[0062] Optionally, the resampling module 402 is specifically used to convert the latitude and longitude coordinates of any target grid point into antenna coordinates in the antenna coordinate system based on the coordinate transformation relationship between the non-uniform coordinate points in the pre-established original footprint map and the latitude and longitude coordinates of each grid point in the uniform grid. The resampling module 402 is also specifically used to find multiple neighboring non-uniform sampling points and the corresponding binarized coverage identifier value of each non-uniform sampling point in the beam footprint map within a local neighborhood centered on the target grid point. The resampling module 402 is also specifically used to calculate the coverage status estimate of the target grid point based on the coverage identifier values of the multiple neighboring non-uniform sampling points using a spherical interpolation algorithm.
[0063] Optionally, the area calculation module 403 is specifically used to calculate the spherical micro-element area of the grid unit represented by each sampling point based on the position coordinates of each sampling point on the sphere in the sampling point set; the area calculation module 403 is also specifically used to accumulate the spherical micro-element areas corresponding to all sampling points identified as covered to obtain the total coverage area.
[0064] The satellite phased array beam coverage area calculation device provided in this application first acquires a binarized beam footprint map of the satellite phased array beam. Then, it performs spherical resampling on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points into a uniformly distributed set of sampling points on a spherical domain, obtaining resampled coverage marker data. Finally, based on the resampled coverage marker data, it performs spherical area integration in a spherical coordinate system to calculate the sum of the spherical micro-area areas corresponding to all sampling points marked as covered, obtaining the actual coverage area of the phased array beam on the Earth's surface. Thus, by transforming the non-uniformly distributed original beam footprint data to a uniform grid through spherical resampling, calculation errors caused by coordinate non-uniformity and projection distortion are easily eliminated. By directly accumulating the micro-area based on the spherical geometric model through spherical area integration, high-precision calculation of the true area of irregular beam coverage regions is accurately achieved, significantly improving the accuracy and reliability of satellite communication system coverage performance evaluation.
[0065] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5As shown, the electronic device may include a processor 510, a communications interface 520, a memory 530, and a communication bus 540. The processor 510, communications interface 520, and memory 530 communicate with each other via the communication bus 540. The processor 510 can call logical instructions in the memory 530 to execute a method for calculating the coverage area of a satellite phased array beam. This method includes: first, acquiring a binarized beam footprint map of the satellite phased array beam; then, performing spherical resampling processing on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on a spherical domain, obtaining resampled coverage marker data; finally, based on the resampled coverage marker data, performing spherical area integration in a spherical coordinate system to calculate the sum of the spherical micro-areas corresponding to all sampling points marked as covered, thus obtaining the actual coverage area of the phased array beam on the Earth's surface. Thus, by converting the non-uniformly distributed original beam footprint data to a uniform grid through spherical resampling, the calculation errors caused by coordinate non-uniformity and projection deformation are easily eliminated; by directly accumulating the area of infinitesimal elements based on the spherical geometric model through spherical surface integration, the true area of the irregular beam coverage area is accurately calculated with high precision, which significantly improves the accuracy and reliability of satellite communication system coverage performance evaluation.
[0066] Furthermore, the logical instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0067] On the other hand, this application also provides a computer program product, which includes a computer program stored on a computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer can execute the satellite phased array beam coverage area calculation method provided by the above methods. The method includes: first, obtaining a binarized beam footprint map of the satellite phased array beam; then, performing spherical resampling processing on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on a spherical domain, to obtain resampled coverage marker data; finally, based on the resampled coverage marker data, performing spherical area integration in a spherical coordinate system to calculate the sum of the spherical micro-areas corresponding to all sampling points marked as covered, to obtain the actual coverage area of the phased array beam on the Earth's surface. Thus, by converting the non-uniformly distributed original beam footprint data to a uniform grid through spherical resampling, the calculation errors caused by coordinate non-uniformity and projection deformation are easily eliminated; by directly accumulating the area of infinitesimal elements based on the spherical geometric model through spherical surface integration, the true area of the irregular beam coverage area is accurately calculated with high precision, which significantly improves the accuracy and reliability of satellite communication system coverage performance evaluation.
[0068] In another aspect, this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described methods for calculating the coverage area of satellite phased array beams. The method includes: first, acquiring a binarized beam footprint map of the satellite phased array beam; then, performing spherical resampling processing on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on a spherical domain, obtaining resampled coverage marker data; finally, based on the resampled coverage marker data, performing spherical area integration in a spherical coordinate system to calculate the sum of the spherical micro-areas corresponding to all sampling points marked as covered, thereby obtaining the actual coverage area of the phased array beam on the Earth's surface. Thus, by converting the non-uniformly distributed original beam footprint data to a uniform grid through spherical resampling, the calculation errors caused by coordinate non-uniformity and projection deformation are easily eliminated; by directly accumulating the area of infinitesimal elements based on the spherical geometric model through spherical surface integration, the true area of the irregular beam coverage area is accurately calculated with high precision, which significantly improves the accuracy and reliability of satellite communication system coverage performance evaluation.
[0069] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.
[0070] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A method for calculating the coverage area of a satellite phased array beam, characterized in that, include: Obtain the binarized beam footprint map of the satellite phased array beam; The coverage markers in the beam footprint map are subjected to spherical resampling processing, which transforms the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, thus obtaining the resampled coverage marker data. Based on the resampled coverage identification data, a spherical area integration operation is performed in the spherical coordinate system to calculate the sum of the spherical micro-element areas corresponding to all sampling points identified as covered, thereby obtaining the actual coverage area of the phased array beam on the Earth's surface.
2. The method according to claim 1, characterized in that, The beam footprint map uses azimuth and elevation angles, which represent the position on the Earth's surface, as coordinates, and each coordinate point in the beam footprint map has a binary coverage identifier.
3. The method according to claim 1, characterized in that, The spherical resampling process performed on the coverage markers in the beam footprint map transforms the coverage markers at non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on a spherical domain, resulting in resampled coverage marker data, including: Create a uniform grid on the sphere with geographic latitude and longitude as coordinates, and generate uniform grid points based on the set latitude and longitude range, longitude interval, and latitude interval; Based on the coverage identifier values at the original non-uniform coordinate points, the estimated coverage state at each grid point is calculated using the spherical interpolation method. The estimated coverage status is compared with a preset threshold, and a binarized coverage identifier is generated based on the comparison result to obtain the resampled coverage identifier data.
4. The method according to claim 3, characterized in that, The spherical interpolation method includes any one of the following: spherical nearest neighbor interpolation, spherical linear interpolation, and spherical spline interpolation.
5. The method according to claim 3 or 4, characterized in that, The step of calculating the estimated coverage state at each grid point using spherical interpolation based on the coverage identifier values at the original non-uniform coordinate points includes: For any target grid point, based on the coordinate transformation relationship between the non-uniform coordinate points in the pre-established original footprint map and the latitude and longitude coordinates of each grid point in the uniform grid, the latitude and longitude coordinates of the target grid point are converted into antenna coordinates in the antenna coordinate system; Within a local neighborhood centered on the target grid point, find multiple neighboring non-uniform sampling points and the corresponding binarized coverage identifier value of each non-uniform sampling point from the beam footprint map; A spherical interpolation algorithm is used to calculate the estimated coverage status of the target grid point based on the coverage identifier values of the multiple neighboring non-uniform sampling points.
6. The method according to claim 1, characterized in that, Based on the resampled coverage identification data, a spherical area integration operation is performed in a spherical coordinate system to calculate the sum of the spherical micro-areas corresponding to all sampling points identified as covered, thereby obtaining the actual coverage area of the phased array beam on the Earth's surface, including: Based on the position coordinates of each sampling point in the sampling point set on the sphere, calculate the spherical micro-element area of the grid cell represented by each sampling point; The total coverage area is obtained by summing the areas of the spherical micro-elements corresponding to all the sampling points that are identified as covered.
7. The method according to claim 6, characterized in that, The area of any spherical infinitesimal element in a grid cell is calculated using the following formula: ； in, For any grid cell in a uniform grid at latitude The area of the spherical infinitesimal element at that point, R For the Earth's radius, Longitude interval The interval is the latitude.
8. A satellite phased array beam coverage area calculation device, characterized in that, The device includes: The acquisition module is used to acquire the binarized beam footprint map of the satellite phased array beam; The resampling module is used to perform spherical resampling processing on the coverage markers in the beam footprint map, transforming the coverage markers on non-uniformly distributed coordinate points to a set of sampling points uniformly distributed on the spherical domain, and obtaining the resampled coverage marker data. The area calculation module is used to perform spherical area integration in a spherical coordinate system based on the resampled coverage identification data, calculate the sum of the spherical micro-element areas corresponding to all sampling points identified as covered, and obtain the actual coverage area of the phased array beam on the Earth's surface.
9. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the satellite phased array beam coverage area calculation method as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the steps of the satellite phased array beam coverage area calculation method as described in any one of claims 1 to 7.