Satellite coverage capability evaluation method and device, storage medium and electronic equipment

Abstract

The invention relates to the technical field of data processing, and particularly provides a satellite coverage capability evaluation method and device, a storage medium and electronic equipment, and the method can comprise the steps: obtaining a ground surface coverage area of a sub-satellite point position of each satellite in a plurality of satellites at any moment; rasterizing the earth surface area to obtain a coverage time matrix; calculating coverage parameters of the plurality of satellites in a preset time period based on the earth surface coverage area and the coverage time matrix; the coverage parameters are analyzed, an evaluation result is obtained, and the evaluation result is used for representing the coverage capability of the multiple satellites; the average coverage rate is used for determining whether the satellite observation data of the multiple satellites can meet the data assimilation requirement or not and / or providing a decision basis for applications such as satellite planning tasks and the like. According to some embodiments of the invention, comprehensive and accurate evaluation of the satellite coverage condition can be realized.

Description

Technical Field

[0001] This application relates to the technical field of data processing. Specifically, it relates to a method, device, storage medium and electronic device for evaluating satellite coverage capabilities. Background Art

[0002] With the continuous development of satellite remote sensing technology, the evaluation of the coverage performance of satellite constellations has become an important part of satellite applications. The existing analysis of the coverage performance of satellite constellations mainly focuses on issues such as the available communication duration of satellites. Such indicators are of key concern for communication and navigation satellites. Different from communication and navigation satellites that can interact with the ground at specific positions within a certain period before and after, a remote sensing satellite passes through a specific position once and usually obtains only one observation of the ground at a single time point. Currently, most of the analysis techniques for the coverage performance of remote sensing satellites are based on the method of calling external software tools through programming languages for coverage simulation. However, this way of relying on external software tools for processing, such as the difficulty in obtaining the STK software and the relatively high operation difficulty, requires technicians with rich experience; moreover, when the software is applied to different platforms, it may face compatibility and performance bottleneck problems, which will have a certain impact on the efficiency of satellite coverage capacity evaluation.

[0003] Therefore, how to provide a technical solution for an efficient method for evaluating satellite coverage capabilities has become an urgent technical problem to be solved. Summary of the Invention

[0004] Some embodiments of this application aim to provide a method, device, storage medium and electronic device for evaluating satellite coverage capabilities. Through the technical solutions of the embodiments of this application, the function of satellite coverage capacity evaluation can be improved, the efficiency of satellite coverage capacity evaluation can be enhanced, it is easy to implement and has a low cost, and it is convenient for popularization and implementation.

[0005] In a first aspect, some embodiments of the present application provide a method for evaluating satellite coverage capabilities, including: obtaining the surface coverage area corresponding to the sub-satellite point position of each satellite among multiple satellites at any moment; performing grid processing on the earth's surface area to obtain a coverage time matrix; wherein, the coverage time matrix represents the satellite coverage time of each grid; based on the surface coverage area and the coverage time matrix, calculating the coverage parameters of the multiple satellites within a preset period, where the coverage parameters include the average coverage rate; the coverage parameters further include at least one of the following: the total number of coverages, the average number of coverages, the average coverage interval, and the maximum coverage time interval; the preset period includes a fixed period of each day within a preset number of days or the preset period is a set time range; the average coverage rate is used to determine whether the satellite observation data of the multiple satellites can meet the data assimilation requirements and / or provide a decision basis for satellite planning tasks; analyzing the coverage parameters to obtain an evaluation result, where the evaluation result is used to characterize the coverage capabilities of the multiple satellites; the coverage capabilities include: coverage uniformity and / or coverage continuity.

[0006] Some embodiments of the present application determine the coverage parameters of multiple satellites by obtaining the surface coverage area of the sub-satellite point position of each satellite at any moment and the coverage time distance of all grids in the earth's surface area; and obtain the evaluation result by analyzing the coverage parameters. Some embodiments of the present application can achieve a comprehensive and accurate evaluation of satellite coverage capabilities, with a low complexity and easy implementation in the evaluation process, and can be applied to satellite (such as remote sensing satellite) capability evaluation scenarios.

[0007] In some embodiments, the obtaining the surface coverage area corresponding to the sub-satellite point position of each satellite among multiple satellites at any moment includes: determining the sub-satellite point position at the any moment by loading the satellite ephemeris data of each satellite; calculating the swath coverage area of each satellite when it is at the sub-satellite point position, and generating the surface coverage area of each satellite according to the relationship between the swath coverage area and the date line.

[0008] Some embodiments of the present application determine the spatial position (i.e., the sub-satellite point position) of the satellite by loading the satellite ephemeris data, and then obtain the surface coverage area of each satellite through the relationship between the swath coverage area at this sub-satellite point position and the date line, providing effective data support for the subsequent evaluation of satellite coverage capabilities.

[0009] In some embodiments, the performing grid processing on the earth's surface area to obtain a coverage time matrix includes: performing grid processing on the earth's surface area according to the grid size to obtain a plurality of grids; constructing the coverage time matrix through the satellite coverage time of each grid in the plurality of grids.

[0010] Some embodiments of the present application divide a region of the earth's surface into multiple grids, and then construct a coverage time matrix, which can facilitate the calculation of satellite coverage parameters, improve the calculation efficiency, and reduce the calculation complexity.

[0011] In some embodiments, the analyzing the coverage parameters to obtain an evaluation result includes: obtaining the coverage parameters within the preset time period; generating a coverage heat map for each type of coverage parameter in the coverage parameters, where the coverage heat map is used to intuitively represent the coverage capabilities of the multiple satellites.

[0012] Some embodiments of the present application generate a coverage heat map by analyzing different coverage parameters, so as to visually display the evaluation result representing the satellite coverage capabilities in the form of a heat map, with a high degree of visualization.

[0013] In some embodiments, the analyzing the coverage parameters to obtain an evaluation result includes: obtaining the average coverage rate of the multiple satellites in a specified area within the preset time period; when it is confirmed that the average coverage rate is not less than the coverage threshold, obtaining the evaluation result, where the evaluation result represents that the satellite observation data can meet the data assimilation requirements or provide a decision basis for the satellite planning task.

[0014] Some embodiments of the present application obtain an evaluation result by analyzing the average coverage rate of a specified area. Through the evaluation result, it can be confirmed that it can serve data assimilation and / or satellite planning tasks, with high practicability.

[0015] In some embodiments, the analyzing the coverage parameters to obtain an evaluation result includes: calculating the standard deviation and coefficient of variation of the total number of coverages in the coverage parameters; where the standard deviation and the coefficient of variation are inversely proportional to the coverage uniformity; calculating the time interval mean and maximum value of the maximum coverage time interval among all grids in the earth's surface area; where the time interval mean and the maximum value are inversely proportional to the coverage continuity.

[0016] Some embodiments of the present application analyze certain parameters in the coverage parameters to determine the coverage uniformity and coverage continuity, so as to achieve a comprehensive and accurate evaluation of the satellite coverage capabilities.

[0017] In some embodiments, the method further includes: when it is confirmed that the average coverage rate is less than the coverage threshold, changing the number or interval of the preset time periods until the average coverage rate of the preset time periods is not less than the coverage threshold, and obtaining the evaluation result that can provide a decision basis for the data assimilation or the satellite planning task.

[0018] Some embodiments of the present application adjust the number or interval of preset time periods when the average coverage rate does not meet the conditions, so as to obtain an evaluation result that meets the coverage threshold conditions, ensure that the evaluation result can provide a decision basis for data assimilation or satellite planning tasks, give suggestions on the reasonable use of satellite observation data, and achieve accurate data assimilation and accurate task planning.

[0019] In a second aspect, some embodiments of the present application provide a device for evaluating satellite coverage capabilities, including: a region acquisition module, configured to acquire the surface coverage region corresponding to the sub-satellite point position of each satellite among multiple satellites at any moment; a matrix construction module, configured to perform rasterization processing on the earth's surface region to obtain a coverage time matrix; wherein, the coverage time matrix represents the satellite coverage time of each grid; a parameter acquisition module, configured to calculate the coverage parameters of the multiple satellites within a preset time period based on the surface coverage region and the coverage time matrix, wherein the coverage parameters include an average coverage rate; the coverage parameters further include at least one of the following: total coverage times, average coverage times, average coverage interval, and maximum coverage time interval; the preset time period includes a fixed time period for each day within a preset number of days or the preset time period is a set time range; the average coverage rate is used to determine whether the satellite observation data of the multiple satellites can meet the requirements of data assimilation and / or provide a decision basis for satellite planning tasks; an evaluation module, configured to analyze the coverage parameters to obtain an evaluation result, wherein the evaluation result is used to characterize the coverage capabilities of the multiple satellites; the coverage capabilities include: coverage uniformity and / or coverage continuity.

[0020] In a third aspect, some embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method described in any embodiment of the first aspect can be implemented.

[0021] In a fourth aspect, some embodiments of the present application provide an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein when the processor executes the program, the method described in any embodiment of the first aspect can be implemented.

[0022] In a fifth aspect, some embodiments of the present application provide a computer program product, the computer program product includes a computer program, wherein when the computer program is executed by a processor, the method described in any embodiment of the first aspect can be implemented. Description of the Drawings

[0023] To more clearly illustrate the technical solutions of some embodiments of the present application, the following will briefly introduce the accompanying drawings required for use in some embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0024] Figure 1 System diagram for satellite coverage capacity evaluation provided for some embodiments of the present application; Figure 2 One of the method flowcharts for satellite coverage capacity evaluation provided for some embodiments of the present application; Figure 3 Thermal map of the distribution of the number of satellite observations provided for some embodiments of the present application; Figure 4 Thermal map of the average number of satellite coverages provided for some embodiments of the present application; Figure 5 Thermal map of the maximum satellite coverage interval provided for some embodiments of the present application; Figure 6 Another method flowchart for satellite coverage capacity evaluation provided for some embodiments of the present application; Figure 7 Block diagram of the device for satellite coverage capacity evaluation provided for some embodiments of the present application; Figure 8 Schematic diagram of an electronic device provided for some embodiments of the present application. Detailed implementation manners

[0025] The following will describe the technical solutions in some embodiments of the present application in combination with the accompanying drawings in some embodiments of the present application.

[0026] It should be noted that: Similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present application, terms such as "first", "second", etc. are only used for differential description and cannot be understood as indicating or implying relative importance.

[0027] In the related art, satellite coverage simulation depends on software such as STK. STK itself is a powerful professional tool, but its high cost and complex operation interface make it necessary for users to have a relatively high learning cost to master its use. In addition, the use threshold of STK software is high and it is difficult to obtain, and there may also be performance bottlenecks or compatibility problems in the interface call between Matlab and STK.

[0028] In the prior art, statistical analysis is mainly carried out for communication and navigation satellites; the statistical analysis ability for remote sensing satellites, including ocean satellites, needs to be improved. Before applying satellite observation data, it is usually necessary to evaluate the coverage of a fixed time interval over the globe or a specific sea area. These evaluations are crucial for judging whether the coverage ability of a certain type of payload (such as a microwave scatterometer) meets the application requirements, and can also provide a reference for future ocean satellite mission planning. However, although the prior art can calculate the interaction between the satellite's orbit and the Earth's surface, there are gaps in the coverage analysis of remote sensing satellites in different time intervals, resulting in the inability to accurately and quickly give decision support results in applications such as data assimilation that require precise knowledge of the coverage of each fixed time period in the preset number of days, and cannot effectively support future ocean satellite mission planning. In the existing remote sensing satellite coverage analysis, only some intuitive parameters are analyzed, and a comprehensive evaluation of the coverage performance of remote sensing satellites cannot be achieved. Moreover, each time STK is called through Matlab for simulation calculation, it involves cross-tool scheduling, and such a call process may affect the system efficiency; especially when frequent calls are required, this call method may increase additional overhead, and the processing speed may be affected.

[0029] As can be seen from the above related technologies, the function of evaluating the coverage ability of remote sensing satellites in the prior art needs to be strengthened, the efficiency needs to be improved, and the calculation cost needs to be improved.

[0030] In view of this, some embodiments of the present application provide a method for evaluating satellite coverage ability. This method can calculate the sub-satellite point position of each satellite at different times, and determine its surface coverage area according to the observed swath coverage area; by rasterizing the Earth's surface area, a coverage time matrix of the Earth's surface area can be constructed; based on the surface coverage area of each satellite and the coverage time matrix, the coverage parameters of multiple satellites can be calculated, and finally the coverage parameters are analyzed to obtain an evaluation result representing the satellite coverage ability. This evaluation result supports the visualization display of coverage parameters, as well as the evaluation of coverage uniformity and coverage uniformity; at the same time, it can confirm whether this evaluation result meets the conditions of data assimilation, so as to provide decision support for data assimilation tasks and future satellite planning tasks. The calculation complexity of the whole process is relatively low, the calculation efficiency is relatively high, the calculation overhead is reduced, and the practicability is relatively high. It should be noted that the method for evaluating satellite coverage ability provided by the present application can be applied to remote sensing satellites including ocean satellites, and the embodiments of the present application do not make specific limitations here.

[0031] The following combines the attached Figure 1 Exemplarily elaborates the overall composition structure of the satellite coverage ability evaluation system provided by some embodiments of the present application.

[0032] Such as Figure 1As shown in the figure, some embodiments of the present application provide a system diagram for satellite coverage capacity evaluation. The system for satellite coverage capacity evaluation may include: a terminal 100 and a server 200. Among them, the terminal 100 may send the satellite ephemeris data of each satellite to the server 200, or the server 200 may read the satellite ephemeris data from the terminal 100. The server 200 may calculate the satellite ephemeris data to obtain the sub-satellite point position (e.g., longitude and latitude information) of each satellite at any moment; determine its surface coverage area through its sub-satellite point position; and then combine the coverage time matrix of the earth's surface area to obtain the coverage parameters of multiple satellites within a preset period; and obtain the evaluation result by analyzing the coverage parameters.

[0033] In some other embodiments of the present application, if the terminal 100 has the relevant functions for the server 200 to calculate the satellite ephemeris data and subsequent data evaluation, the server 200 may not be set at this time. Specifically, it can be selected according to the actual situation, and the embodiments of the present application do not make specific limitations here. In addition, the terminal 100 may be a mobile terminal or a non-portable computer terminal, and the embodiments of the present application are not limited thereto.

[0034] The following combines the attached Figure 2 Exemplarily expounds the implementation process of satellite coverage capacity evaluation executed by the server 200 provided by some embodiments of the present application. The satellites mentioned in the following text may be remote sensing satellites for observing the ocean.

[0035] Please refer to the attached Figure 2 , Figure 2 is a flowchart of a method for satellite coverage capacity evaluation provided by some embodiments of the present application. The method for satellite coverage capacity evaluation may include: S210, obtain the surface coverage area corresponding to the sub-satellite point position of each satellite among multiple satellites at any moment.

[0036] For example, in some embodiments of the present application, the sub-satellite point position of each satellite at any moment t can be determined through the Skyfield library of python, and the surface coverage area can be calculated through the swath parameters of the sub-satellite point position.

[0037] In some embodiments of the present application, S210 may include: determining the sub-satellite point position at the arbitrary moment through the loaded satellite ephemeris data of each satellite; calculating the swath coverage area of each satellite at the sub-satellite point position, and generating the surface coverage area of each satellite according to the relationship between the swath coverage area and the date line.

[0038] For example, in some embodiments of the present application, the TLE data of the satellite (as a specific example of satellite ephemeris data) is loaded through the Skyfield library of Python (the Skyfield library is a pure Python astronomical calculation library designed specifically for Python), and based on this, the sub-satellite point position of each satellite (which can be abbreviated as the sub-satellite point) is calculated. TLE (Two-Line Elementset) data is a standard format commonly used to describe the orbits of artificial satellites, space stations, or other celestial bodies. It consists of two lines of data, each line containing multiple numbers and symbols, used to represent the orbital state information of the satellite at a certain moment. TLE data usually includes the following content: the first line contains the international identifier of the satellite, the launch year, the launch number, and relevant information about the orbital elements; the second line includes the orbital parameters of the satellite, such as the orbital inclination, the longitude of the ascending node, the eccentricity, etc. The TLE data of the satellite is loaded through the Skyfield library of Python, and the satellite.at(t) function is used to calculate the position of the satellite at any moment t, and then the satellite_at_time.subpoint() function is used to calculate the sub-satellite point of the satellite (that is, the sub-satellite point position includes latitude and longitude).

[0039] After that, through a parallel computing method (for example, using the joblib library, Joblib is a lightweight parallelization and memory optimization library for Python programs, especially suitable for data processing and numerical calculation tasks), the swath coverage area of each satellite at its current sub-satellite point is calculated respectively; it should be understood that different types of satellite payloads (such as ASCAT-B / C / D, HY-2 B / C / D, CFOSAT, etc.) need to dynamically adjust their swath parameters. The coverage polygon of each satellite can be accurately generated through the swath coverage area (as a specific example of the coverage area). If there are the following special situations between the swath coverage area and the International Date Line, splitting processing is required: if the coverage area of a certain satellite crosses the International Date Line, the coverage area of this satellite can be divided into two parts, that is, the two coverage areas on both sides of the International Date Line, to ensure the accuracy of the coverage performance calculation. The coverage polygon of each satellite is determined in the above manner.

[0040] S220, rasterize the Earth's surface area to obtain a coverage time matrix; wherein, the coverage time matrix represents the satellite coverage time of each grid.

[0041] For example, in some embodiments of the present application, by rasterizing the Earth's surface area, the satellite coverage time of different grids is obtained, and then the coverage time matrix of all satellites is constructed.

[0042] In some embodiments of the present application, S220 may include: rasterizing the earth surface area according to the grid size to obtain a plurality of grids; and constructing the coverage time matrix through the satellite coverage time of each grid in the plurality of grids.

[0043] For example, in some embodiments of the present application, the grid size can be set according to the actual situation. For example, the grid size is 0.25°×0.25°. Based on this grid size as the division basis, the earth surface area is divided into a plurality of grid points (i.e., a plurality of grids). Record the satellite coverage time of each grid point to generate the coverage time matrix. For example, the satellite coverage time of a grid point can be several time points (as a specific example of the satellite coverage time).

[0044] S230, calculate the coverage parameters of the multiple satellites within a preset time period based on the surface coverage area and the coverage time matrix, where the coverage parameters include the average coverage rate; the coverage parameters further include at least one of the following: the total number of coverages, the average number of coverages, the average coverage interval, and the maximum coverage time interval; the preset time period includes a fixed time period for each day within a preset number of days or the preset time period is a set time range.

[0045] For example, in some embodiments of the present application, determine the coverage situation of each grid point at the current or a future preset time period through the surface coverage area corresponding to each satellite and the satellite coverage time of each grid point. Among them, the preset time period can be a fixed time period for each day within a set number of preset days, such as the fixed time period from 0:00 to 3:00 every day within 30 days, and the preset number of days can be set to be not less than 7 days. Or the preset time period can be a set time interval, for example, 0 to 30 days or 3:00 to 6:00, etc. It should be understood that the preset time period can be set according to the actual application scenario, and the embodiments of the present application do not make specific limitations here.

[0046] Based on this coverage situation, relevant grid coverage parameters such as the coverage time for each grid point at each time, the statistical coverage times, and the coverage time intervals are calculated. And according to the spatial and temporal requirements (i.e., the preset time period), the total coverage times, average coverage times (i.e., the mean of coverage times), average coverage intervals, maximum coverage intervals (i.e., the maximum coverage time intervals) of all ocean satellites (as a specific example of multiple satellites) for each grid point are further calculated, as well as parameters such as the average coverage rate in the specified global area in different time intervals (i.e., the preset time period). Among them, the average coverage rate is used to determine whether the satellite observation data of multiple satellites can meet the data assimilation requirements and / or provide a decision basis for satellite planning tasks. It should be understood that through the current surface coverage area and satellite coverage time of each satellite, not only the current coverage parameters can be calculated, but also the coverage parameters in a certain period before can be calculated, and the coverage parameters in the future period can be predicted. Specifically, it can be determined according to the actual application scenario.

[0047] S240, analyze the coverage parameters to obtain an evaluation result, where the evaluation result is used to characterize the coverage ability of the multiple satellites; the coverage ability includes: coverage uniformity and / or coverage continuity.

[0048] The above process is described below by way of example.

[0049] In some embodiments of the present application, S240 may include: obtaining the coverage parameters within the preset time period; generating a coverage heat map for each type of coverage parameter in the coverage parameters, where the coverage heat map is used to intuitively characterize the coverage ability of the multiple satellites.

[0050] For example, in some embodiments of the present application, the coverage parameters of all satellites in the preset time period are statistically analyzed to generate a corresponding coverage heat map. For example, the coverage heat map is used to display the coverage parameters such as the total coverage times of ocean satellites, the average coverage times at fixed time periods every day, and the maximum coverage intervals, facilitating users to intuitively understand the coverage performance of the satellites.

[0051] The following shows three heat maps as examples.

[0052] As Figure 3 shown is the heat map of the distribution of the number of satellite observations (i.e., the total coverage times) for each grid point, Figure 3 which can show the satellite coverage situation in different regions of the world, and each grid area indicates the total coverage times. Figure 3 shows the global coverage situation of the microwave scatterometer payloads of a certain 6 satellites within a 24-hour time range (as a specific example of the preset time period).

[0053] As Figure 4The heat map of the average number of daily fixed-time coverages of the satellite provided by this application. This map can show the distribution of the average number of coverages in the world or a specified area, and the color change reflects the coverage frequency in different areas. Figure 4 It is the distribution of the average number of coverages of a certain 6-satellite microwave scatterometer payload globally within the time period from 0 to 6 (as a specific example of the preset time period).

[0054] Such as Figure 5 The heat map of the maximum coverage interval of the satellite provided by this application. This map can show the distribution of the maximum coverage interval in the world or a specified area, and the color change reflects the maximum coverage interval in different areas. Figure 5 It is the distribution of the maximum coverage interval of a certain 6-satellite microwave scatterometer payload within 24 hours.

[0055] By Figures 3 to 5 the distribution of a certain coverage parameter in, professionals can intuitively see the coverage capabilities of all satellites.

[0056] In some embodiments of this application, S240 may include: obtaining the average coverage rate of the multiple satellites in the specified area within the preset time period; when it is confirmed that the average coverage rate is not less than the coverage threshold, obtaining the evaluation result, and the evaluation result represents that the satellite observation data can meet the data assimilation requirements or provide a decision-making basis for the satellite mission planning.

[0057] For example, in some embodiments of this application, by analyzing the coverage situation in a specific area (i.e., the specified area) in different time intervals (i.e., the preset time period), the evaluation result is obtained. For example, it is judged whether the average coverage rate in each 6-hour time period (as a specific example of the preset time period) within 24 hours in a certain specific area is not less than 70% (as a specific example of the coverage threshold), and it is confirmed whether the satellite observation data can provide decision-making support for applications such as data assimilation or future mission planning (as a specific example of the satellite mission planning). That is, when the average coverage rate is not less than 70%, it can be considered that the satellite remote sensing data under this coverage ability can be effectively used for applications such as data assimilation; when the average coverage rate is less than 70%, the future mission planning needs to consider increasing the number of on-orbit satellites and optimizing the satellite orbits, that is, the future satellite orbits, as well as the number of on-orbit satellites and other mission planning can be optimized.

[0058] In some embodiments of this application, S240 may also include: when it is confirmed that the average coverage rate is less than the coverage threshold, then changing the number or interval of the preset time period until the average coverage rate is not less than the coverage threshold, and obtaining the evaluation result that can provide a decision-making basis for the data assimilation. Or by simulating an increase in the number of satellites until the average coverage rate is not less than the coverage threshold, and obtaining the evaluation result that can provide a decision-making basis for the mission planning of the number of on-orbit satellites.

[0059] For example, in some embodiments of the present application, if the average coverage rate satellite_coverage of a specific area within the time interval T (i.e., a preset time period, such as from 0 to 1 o'clock every day within 30 days) is < 70%, it is considered that the satellite constellation observation of this type does not meet the data assimilation requirements. If not satisfied, increase the length of the time interval (for example, T is increased from 1 hour to 2, 3, 4, 6, 12 hours, etc.), and continue to calculate the average coverage rate satellite_coverage until the requirement of 70% is met. The time interval T at this time is the time resolution that the assimilation product can achieve. If T does not meet the timeliness requirements of actual applications, a satellite can also be added through simulation to continue calculating whether T meets the average coverage rate requirements in this case until T ≤ 6, that is, at least four assimilation products can be generated per day (i.e., when T = 6, assimilation products can be generated at the four times of 6, 12, 18, and 24), which is used as the basis for future ocean satellite mission planning.

[0060] In some embodiments of the present application, S240 may include: calculating the standard deviation and coefficient of variation of the total number of coverages in the coverage parameters; wherein, the standard deviation and the coefficient of variation are inversely proportional to the coverage uniformity; calculating the time interval mean and maximum value of the maximum coverage time interval among all grids within the earth's surface area; wherein, the time interval mean and the maximum value are inversely proportional to the coverage continuity.

[0061] For example, in some embodiments of the present application, the evaluation of coverage uniformity specifically refers to whether the spatial distribution of the total number of coverages is uniform. If the total number of coverages in some areas is much higher than that in other areas, the uniformity is poor. Specifically, calculate the standard deviation and coefficient of variation (i.e., the ratio of the standard deviation to the average value) of the total number of coverages at all grid points. The smaller the standard deviation and the coefficient of variation, the better the coverage uniformity. The evaluation of coverage continuity refers to the continuity of coverage in time and whether there are long coverage blanks. Statistically calculate the average value (i.e., the time interval mean) and the maximum value of the maximum coverage interval at all grid points. The smaller the average value and the maximum value, the better the coverage continuity. The better the coverage uniformity and coverage continuity, the better the coverage ability of the satellite. When the standard deviation and the coefficient of variation in coverage uniformity are both less than the set threshold, and the average value and the maximum value in coverage continuity are both less than the set threshold, it can be considered that the evaluation result can meet the data assimilation requirements and provide a decision basis for satellite mission planning.

[0062] The following specifically describes the process of evaluating the satellite coverage ability provided by some embodiments of the present application in conjunction with the attached Figure 6 exemplarily.

[0063] Please refer to the attached Figure 6 , Figure 6A flowchart of a method for evaluating satellite coverage capabilities provided by some embodiments of the present application.

[0064] The above process will be described exemplarily below.

[0065] S610, Load the ephemeris data of each satellite. Through the ephemeris data of the satellite, obtain the sub-satellite point position of each satellite at any moment.

[0066] S620, Calculate the swath coverage area of each satellite when it is at the sub-satellite point position, and generate the surface coverage area of each satellite by judging whether it crosses the date line.

[0067] S630, Perform rasterization processing on the earth's surface area according to the grid size to obtain multiple grids.

[0068] S640, Construct a coverage time matrix through the satellite coverage time of each grid in multiple grids.

[0069] S650, Based on the surface coverage area and the coverage time matrix, calculate the coverage parameters of multiple satellites within a preset time period.

[0070] S660, Analyze the coverage parameters to obtain the evaluation result.

[0071] It can be understood that the specific implementation process of S610~S660 can refer to the method embodiments provided above. To avoid repetition, the detailed description is appropriately omitted here.

[0072] As can be seen from some embodiments of the present application above, the present application uses open-source libraries as an auxiliary based on Python to achieve rapid evaluation and analysis of satellite coverage. Especially in the processing of crossing the date line and different satellite swaths, it ensures the accurate calculation of the coverage area. The present application uses parallel computing, can handle large-scale satellite coverage simulations, and is applicable to complex satellite coverage evaluation and analysis. By introducing analyses such as coverage in different time intervals, it can finely evaluate the ocean satellite coverage of the whole world or a specific time interval, simultaneously realize data assimilation decision support, and can provide a reference for ocean satellite mission planning through simulation analysis. By introducing coverage quality evaluation indicators, it can more comprehensively evaluate the coverage performance of ocean satellites, which helps to provide a more scientific basis for mission planning and resource allocation. Moreover, the introduction of visualization tools makes the analysis of ocean satellite coverage performance more intuitive. The present application can not only be widely applied to ocean satellite coverage analysis, but also be extended to remote sensing satellite fields such as meteorological satellites.

[0073] Please refer to Figure 7 , Figure 7The block diagram of the satellite coverage capability evaluation device provided by some embodiments of the present application is shown. It should be understood that the satellite coverage capability evaluation device corresponds to the above method embodiment and can perform each step involved in the above method embodiment. The specific functions of the satellite coverage capability evaluation device can be found in the description above. To avoid repetition, the detailed description is appropriately omitted here.

[0074] Figure 7 The device for evaluating satellite coverage capability includes at least one software function module that can be stored in a memory in the form of software or firmware or solidified in the device for evaluating satellite coverage capability, and the device for evaluating satellite coverage capability includes: an area acquisition module 710, used to obtain the surface coverage area corresponding to the sub-satellite point position of each satellite in a plurality of satellites at any time; a matrix construction module 720, used to perform rasterization processing on the surface area of ​​the earth to obtain a coverage time matrix; wherein the coverage time matrix represents the satellite coverage time of each grid; a parameter acquisition module 730, used to calculate the coverage parameters of the plurality of satellites within a preset time period based on the surface coverage area and the coverage time matrix, Among them, the coverage parameters include an average coverage rate; the coverage parameters also include at least one of the following: a total number of coverage times, an average number of coverage times, an average coverage interval, and a maximum coverage time interval; the preset time period includes a fixed time period of each day in a preset number of days or the preset time period is a set time range; the average coverage rate is used to determine whether the satellite observation data of the multiple satellites can meet the data assimilation requirements and / or provide a decision-making basis for satellite planning tasks; an evaluation module 740 is used to analyze the coverage parameters and obtain evaluation results, wherein the evaluation results are used to characterize the coverage capabilities of the multiple satellites; the coverage capabilities include: coverage uniformity and / or coverage continuity.

[0075] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method, and will not be described in detail here.

[0076] Some embodiments of the present application further provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can implement the operations of the method corresponding to any of the above methods provided in the above embodiments.

[0077] Some embodiments of the present application further provide a computer program product, which includes a computer program, wherein when the computer program is executed by a processor, it can implement the operations corresponding to any of the above methods provided in the above embodiments.

[0078] like Figure 8As shown, some embodiments of the present application provide an electronic device 800, which includes: a memory 810, a processor 820, and a computer program stored on the memory 810 and executable on the processor 820. When the processor 820 reads the program from the memory 810 through a bus 830 and executes the program, the method of any of the above embodiments can be implemented.

[0079] The processor 820 can process digital signals and can include various computing architectures. For example, a complex instruction set computer architecture, a reduced instruction set computer architecture, or an architecture that implements a combination of multiple instruction sets. In some examples, the processor 820 can be a microprocessor.

[0080] The memory 810 can be used to store instructions executed by the processor 820 or data related to the instruction execution process. These instructions and / or data can include code for implementing some or all of the functions of one or more modules described in the embodiments of the present application. The processor 820 of the embodiments of the present disclosure can be used to execute the instructions in the memory 810 to implement the method shown above. The memory 810 includes a dynamic random access memory, a static random access memory, a flash memory, an optical memory, or other memories well known to those skilled in the art.

[0081] The above are only the embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0082] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

[0083] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent in such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the said element.

Claims

1. A method for evaluating satellite coverage capabilities, characterized in that, Including: Obtaining the surface coverage area corresponding to the sub-satellite point position of each satellite among multiple satellites at any moment; Performing rasterization processing on the Earth's surface area to obtain a coverage time matrix; wherein, the coverage time matrix represents the satellite coverage time of each grid; Based on the surface coverage area and the coverage time matrix, calculating the coverage parameters of the multiple satellites within a preset period, wherein the coverage parameters include an average coverage rate; the coverage parameters further include at least one of the following: total coverage times, average coverage times, average coverage interval, and maximum coverage time interval; the preset period includes a fixed period of each day within a preset number of days or the preset period is a set time range; the average coverage rate is used to determine whether the satellite observation data of the multiple satellites can meet the data assimilation requirements and / or provide a decision basis for satellite planning tasks; Analyzing the coverage parameters to obtain an evaluation result, wherein the evaluation result is used to characterize the coverage ability of the multiple satellites; the coverage ability includes: coverage uniformity and / or coverage continuity.

2. The method according to claim 1, characterized in that, The obtaining the surface coverage area corresponding to the sub-satellite point position of each satellite among multiple satellites at any moment includes: Determining the sub-satellite point position at the any moment by loading the satellite ephemeris data of each satellite; Calculating the swath coverage area of each satellite at the sub-satellite point position, and generating the surface coverage area of each satellite according to the relationship between the swath coverage area and the international date line.

3. The method according to claim 1 or 2, characterized in that, The performing rasterization processing on the Earth's surface area to obtain a coverage time matrix includes: Performing rasterization processing on the Earth's surface area according to the grid size to obtain a plurality of grids; Constructing the coverage time matrix through the satellite coverage time of each grid in the plurality of grids.

4. The method according to claim 1 or 2, characterized in that, The analyzing the coverage parameters to obtain an evaluation result includes: Obtaining the coverage parameters within the preset period; Generating a coverage heat map for each coverage parameter in the coverage parameters, wherein the coverage heat map is used to intuitively characterize the coverage ability of the multiple satellites.

5. The method according to claim 1 or 2, characterized in that, The analyzing the coverage parameters to obtain an evaluation result includes: Obtaining the average coverage rate of the multiple satellites in a specified area within the preset period; When it is confirmed that the average coverage rate is not less than the coverage threshold, obtaining the evaluation result, and the evaluation result characterizes that the satellite observation data can meet the data assimilation requirements or provide a decision basis for the satellite planning task.

6. The method according to claim 1 or 2, characterized in that, The analyzing the coverage parameters to obtain an evaluation result includes: Calculating the standard deviation and coefficient of variation of the total coverage times in the coverage parameters; wherein, the standard deviation and the coefficient of variation are inversely proportional to the coverage uniformity; Calculating the time interval mean and maximum value of the maximum coverage time interval among all grids in the Earth's surface area; wherein, the time interval mean and the maximum value are inversely proportional to the coverage continuity.

7. The method according to claim 5, wherein The method further includes: When it is confirmed that the average coverage rate is less than the coverage threshold, the number or interval of the preset time periods is changed until the average coverage rate of the preset time periods is not less than the coverage threshold, so as to obtain the evaluation result that can provide a decision basis for the data assimilation or the satellite planning task.

8. An apparatus for evaluating satellite coverage capabilities, characterized in that, Including: A region acquisition module, configured to acquire the surface coverage regions corresponding to the sub-satellite point positions of each satellite among multiple satellites at any moment; A matrix construction module, configured to perform rasterization processing on the earth surface region to obtain a coverage time matrix; wherein, the coverage time matrix represents the satellite coverage time of each grid; A parameter acquisition module, configured to calculate the coverage parameters of the multiple satellites within a preset time period based on the surface coverage regions and the coverage time matrix, wherein the coverage parameters include an average coverage rate; the coverage parameters further include at least one of the following: total coverage times, average coverage times, average coverage interval, and maximum coverage time interval; the preset time period includes a fixed time period for each day within a preset number of days or the preset time period is a set time range; the average coverage rate is used to determine whether the satellite observation data of the multiple satellites can meet the data assimilation requirements and / or provide a decision basis for the satellite planning task; An evaluation module, configured to analyze the coverage parameters to obtain an evaluation result, wherein the evaluation result is used to characterize the coverage ability of the multiple satellites; the coverage ability includes: coverage uniformity and / or coverage continuity.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, wherein the computer program, when run by a processor, executes the method according to any one of claims 1-7.

10. An electronic device, characterized in that, Including a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the computer program, when run by the processor, executes the method according to any one of claims 1-7.

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