Giant satellite base communication performance degradation analysis method for coverage multiple number sensitivity

Abstract

The invention discloses a huge satellite base communication performance degradation analysis method for coverage multiple number sensitivity, and relates to the field of orbit analysis. The problems that an effective evaluation mode for the influence of the coverage multiple number and other performance is lacked and the sensitivity of the coverage multiple number and other performance changes caused by the constellation to the satellite number change is measured are solved. The method comprises the following steps of: 1, counting the satellite coverage condition of a specified place under the condition of step-by-step calculation and the satellite coverage condition of the specified place under the condition of geometric solution calculation; step 2, calling a satellite set which covers the place D in the time period T as S, arranging different coverage time periods corresponding to members in the satellite set S according to an ascending order of coverage ending time, and arranging members corresponding to the same coverage ending time according to an ascending order of coverage starting time; and step 3, determining the splicing time period number according to the average coverage multiple number and the target average coverage multiple number, and completing the sensitivity test. The method is applied to the field of spacecraft system simulation.

Description

Technical Field

[0001] The invention relates to the field of orbit analysis, and in particular to a method for analyzing the degradation of communication performance of a giant star constellation targeting at the sensitivity of coverage multiplicity. Background Art

[0002] In the orbit prediction and coverage assessment of the satellite constellation, it is first necessary to parse the constellation two-line metadata and implement orbit recursion. Specifically, this includes reading and identifying the constellation two-line metadata and processing it according to the common format. Next, the model is initialized according to the SGP4 orbit model and the actual variables read, and the orbit state is recursively deduced according to the current time to obtain the accurate orbit information of the satellite.

[0003] When calculating the coverage of a certain area by a constellation, the coverage area is first discretized into a sufficient number of sampling points. Next, it is necessary to calculate whether the line between the satellite and each sampling point is within the coverage cone of the satellite and determine whether the line passes through the earth. Finally, by summarizing the coverage of each sampling point, a specific numerical result is obtained.

[0004] At present, the measurement methods for constellation coverage multiplicity and other performance are mainly based on the fixed constellation that has been designed, and the number, position distribution and relative phase relationship of satellites in the constellation remain basically unchanged. However, for constellations in dynamic processes, such as the dynamic increase or decrease in the number of satellites, constellation reconstruction, etc., there is a lack of effective evaluation methods for the impact on performance such as coverage multiplicity. In addition, there is also a lack of systematic methods for measuring the sensitivity of constellations to changes in performance such as coverage multiplicity caused by changes in the number of satellites. These problems need to be solved urgently in dynamic constellation design and performance optimization. Summary of the invention

[0005] Aiming at the problem that there is no effective evaluation method for the impact of performance such as coverage multiplicity and the sensitivity of constellation to the change of performance such as coverage multiplicity caused by the change of the number of satellites, the present invention proposes a communication performance degradation analysis method for the giant star constellation with respect to the sensitivity of coverage multiplicity, and the method comprises:

[0006] Step 1: Count the satellite coverage of the designated location when the step length is calculated and the satellite coverage of the designated location when the geometric solution is calculated;

[0007] Step 2: The satellite set that has covered the location D within the time period T is called S. The different coverage periods corresponding to the members in the satellite set S are arranged in ascending order according to the end coverage time, and the members corresponding to the same coverage end time are arranged in ascending order according to the start coverage time;

[0008] Step 3: Determine the number of splicing time periods based on the average coverage density and the target average coverage density, analyze the curve relationship between the number of satellites after weight reduction and the reduction in coverage density in local areas, and complete the sensitivity test.

[0009] Furthermore, a preferred method is proposed, wherein the statistics of satellite coverage of a designated location in step 1 are calculated by stepping the step length, including:

[0010] Step 1. Create a new table Table1, the table header includes satellite name, start coverage time and end coverage time;

[0011] Step 12: For each time i, read all satellite information covering location D;

[0012] Step 13: For each satellite name Name_j, check whether there is a corresponding row in the table; if so, update the end coverage time of the row and add 1; if there is no corresponding row in the table, add a new row, set the start coverage time of the row to the current time i, and the end coverage time to i;

[0013] Step 14: Repeat steps 12 and 13 until all satellite information at the current moment is processed, and then continue to the next moment i+1 until all moments in the entire period T are processed.

[0014] Furthermore, a preferred method is proposed, wherein the satellite coverage of the designated location calculated by geometric solution in step 1 includes:

[0015] Use geometric methods to obtain the start and end coverage times of each satellite for a specified location within a time period T;

[0016] Select a fixed time step and discretize the entire period T into multiple time points, with each time point separated by the selected step;

[0017] At each discrete time point, check whether all satellites cover the specified location. Record the satellite coverage corresponding to these moments.

[0018] The coverage information of each discrete time point is organized into a table or data format to display the satellite coverage at each moment.

[0019] Furthermore, a preferred method is proposed, wherein the step 2 comprises:

[0020] Sort Table1 in ascending order by the End Coverage Time column;

[0021] For the sorted table, sort it in ascending order according to the start coverage time column;

[0022] Calculate the initial average coverage weight Ca1 of location D in time period T;

[0023] Calculate the average coverage weight Ca2 of site D after weight reduction;

[0024] The average coverage density Cc that needs to be reduced is obtained according to the initial average coverage density and the average coverage density;

[0025] Decompose Cc into an integer part CcI and a decimal part CcF, where the integer part CcI represents the number of complete time periods that need to be spliced, and the decimal part CcF represents the additional weight reduction that needs to be processed;

[0026] Create Table2 with the same header as Table1 to record the concatenated results;

[0027] Initialize the number of weights that have been reduced Cn = 0, which is used to track the weight of weights that have been processed currently;

[0028] According to CcI, select the time periods in Table 1 for splicing to achieve the integer part weight reduction requirement;

[0029] For the fractional part CcF, select an appropriate time period for partial splicing to meet the weight reduction requirements.

[0030] Furthermore, a preferred embodiment is proposed, wherein the processing flow of the integer part includes:

[0031] Step 21: Initialize the current end time, find the end row S1 of the initial time Tb of the coverage period T from Table1, if there is no matching row, search downward in the order of time until the appropriate row is found; stack the S1 row into Table2, and delete the S1 row from Table1; set Ten to the value of the end coverage time column of the S1 row, and go to step 22;

[0032] Step 22: If Ten is greater than or equal to the end time Te of time period T, it means that enough time periods have been processed, the current reduced weight Cn is increased by 1, and the process goes to step 24; if Ten is less than Te, it means that not all time periods have been processed, and the process goes to step 23;

[0033] Step 23: Search for row S2 in the start coverage time column of Table1 that is equal to the current end time Ten. If no matching row is found, add or subtract the search based on Ten. Take S3 as the found row, stack S3 into Table2, and delete S3 from Table1. Update Ten to the value of the "end coverage time" column of S3, and go to step 22.

[0034] Step 24: If the currently reduced multiplicity Cn is greater than or equal to the integer part CcI, exit the loop and enter step 5; if Cn is less than CcI, return to step 21 to continue processing;

[0035] Step 25: Once Cn reaches or exceeds CcI, the entire process ends.

[0036] Furthermore, a preferred method is proposed, wherein the processing flow of the decimal part includes:

[0037] Step 26: Set the current end time Ten to 0, and search for the end row S1 of the initial time Tb of the coverage period in Table1; if not found, search downward in time order and stack the found row S1 into Table2, and then delete row S1 from Table1; update Ten to the value of the end coverage time column of row S1;

[0038] Step 27: If Ten-Tb is greater than or equal to (Te-Tb)*CcF, then the process ends and goes to step 29; if Ten-Tb is less than (Te-Tb)*CcF, then go to step 28;

[0039] Step 28. Search for row S2 equal to Ten in the start coverage time column of Table1. If not found, add or subtract from Ten to search. The last row S3 of row S2 found will be stacked into Table2, and row S3 will be deleted from Table1. Ten will be updated to the value of the end coverage time column of row S3. Return to step 27 and continue processing.

[0040] Step 29: If the conditions are met to end the process, then end the process.

[0041] Furthermore, a preferred method is proposed, where the average coverage weight at discrete moments is:

[0042]

[0043] Among them, T b is the coverage start time, T e is the coverage end time, δ step is the step size of discrete operation, C i T b +i*δ step The coverage multiplicity at a moment.

[0044] Furthermore, a preferred method is proposed, in which the average coverage weight at the consecutive moments is:

[0045]

[0046] Among them, C(t) is the coverage multiplicity at time t.

[0047] Based on the same inventive concept, the present invention also proposes a computer device, including a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a method for analyzing the communication performance degradation of the giant star constellation for coverage multiplicity sensitivity as described in any one of the above items.

[0048] Based on the same inventive concept, the present invention also proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of a method for analyzing the performance degradation of supergiant constellation communication for coverage multiplicity sensitivity as described in any of the above items are executed.

[0049] The present invention is beneficial in that:

[0050] The present invention discloses a method for analyzing the degradation of communication performance of a giant star constellation for sensitivity to coverage multiplicity. The method uses two methods, step-by-step calculation and geometric solution, to count the coverage of satellites to a designated location. This dual calculation method ensures the accuracy and reliability of the evaluation results, takes into account the errors that may be caused by different calculation models, and thus provides a more comprehensive coverage analysis. In step 2, the coverage periods in the satellite set S are arranged in ascending order according to the end coverage time and the start coverage time. This systematic sorting method simplifies data management, facilitates subsequent analysis and processing, and improves efficiency. In step 3, the number of splicing periods is determined according to the average coverage multiplicity and the target average coverage multiplicity, and the curve relationship between the number of satellites after weight reduction and the reduction of coverage multiplicity in the local area is analyzed to complete the sensitivity test. This method allows researchers to accurately measure and adjust the performance of the constellation design to ensure that it meets specific coverage requirements and performance standards. By dynamically testing the sensitivity of satellite coverage multiplicity, the method can adapt to the impact of changes in constellation configuration on performance, and help designers optimize the satellite constellation layout to adapt to different needs and environmental changes. The results of the sensitivity test can guide the optimization and adjustment of the satellite constellation and improve the efficiency of the constellation design. By understanding the coverage multiplicity performance under different configurations, satellite resources can be configured more effectively to maximize coverage effects.

[0051] It is difficult for previous evaluation methods to effectively assess the specific impact of constellation changes on performance such as coverage multiplicity. The present invention provides a systematic communication performance degradation analysis method.

[0052] The present invention can dynamically measure the sensitivity of the constellation to the change in coverage multiplicity caused by the change in the number of satellites, thus filling the evaluation gap in this field.

[0053] The present invention is applied to the field of spacecraft system simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A flowchart of a method for analyzing the degradation of communication performance of the giant star constellation with respect to the sensitivity of coverage multiplicity is provided as an implementation mode 1;

[0055] Figure 2 This is a statistical calculation flow chart described in Implementation Method 2;

[0056] Figure 3 This is a flowchart of integer part calculation according to implementation mode 11;

[0057] Figure 4 This is a flowchart of calculating the decimal part according to the eleventh embodiment;

[0058] Figure 5 This is a schematic diagram of the coverage weight before processing according to the eleventh embodiment;

[0059] Figure 6 This is a graph of the time curve of reducing the coverage density after the strike according to the coverage density as described in the eleventh embodiment. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0061] Implementation method 1, see Figure 1 This embodiment describes a method for analyzing the degradation of communication performance of the giant star constellation with respect to the sensitivity of coverage multiplicity, and the method comprises:

[0062] Step 1: Count the satellite coverage of the designated location when the step length is calculated and the satellite coverage of the designated location when the geometric solution is calculated;

[0063] Step 2: The satellite set that has covered the location D within the time period T is called S. The different coverage periods corresponding to the members in the satellite set S are arranged in ascending order according to the "end coverage time", and the members corresponding to the same coverage end time are arranged in ascending order according to the start "coverage time";

[0064] Step 3: Determine the number of splicing time periods based on the average coverage density and the target average coverage density, analyze the curve relationship between the number of satellites after weight reduction and the reduction in coverage density in local areas, and complete the sensitivity test.

[0065] The method for analyzing the degradation of communication performance of the Giant Star constellation for the sensitivity of coverage multiplicity described in this embodiment further includes a step of obtaining the position of the satellite, specifically:

[0066] Step 1: According to the format of the two-line metadata record, read the parameter values ​​under different data segments and save them to the SGP4 orbit model structure variables;

[0067] Step 2: Initialize the orbit model according to the physical meaning of the SGP4 orbit model variables, and obtain the six orbital elements under the double-row metadata orbit epoch and the position and velocity in the J2000 coordinate system;

[0068] Step 3: Combine the simulation time and simulation step size to calculate the time difference between the simulation time and the orbit epoch, substitute it into the orbit model calculation function, and perform orbit recursion and data output.

[0069] In the method for analyzing the degradation of communication performance of the Giant Star constellation for sensitivity to coverage multiplicity described in this embodiment, the step-by-step calculation provides quantitative coverage data, and the geometric solution calculation takes into account the spatial characteristics of the coverage. The combination of the two can more accurately evaluate the satellite coverage. Sorting the satellite coverage time periods helps to systematically analyze the coverage situation and facilitate the detection of the changing trend of the coverage multiplicity. By adjusting the number of splicing time periods to match the target average coverage multiplicity, it is ensured that the sensitivity test can simulate the actual situation and evaluate the system performance.

[0070] Specifically, the method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity described in this embodiment uses two methods, namely, step-by-step calculation and geometric solution, to count the coverage of the satellite to the designated location. This dual calculation method ensures the accuracy and reliability of the evaluation results, takes into account the errors that may be caused by different calculation models, and thus provides a more comprehensive coverage analysis. In step 2, the coverage periods in the satellite set S are arranged in ascending order according to the end coverage time and the start coverage time. This systematic sorting method simplifies data management, facilitates subsequent analysis and processing, and improves efficiency. In step 3, the number of splicing periods is determined according to the average coverage multiplicity and the target average coverage multiplicity for sensitivity testing. This method allows researchers to accurately measure and adjust the performance of the constellation design to ensure that it meets specific coverage requirements and performance standards. By dynamically testing the sensitivity of the satellite coverage multiplicity, the test method can adapt to the impact of changes in constellation configuration on performance, and help designers optimize the satellite constellation layout to adapt to different needs and environmental changes. The results of the sensitivity test can guide the optimization and adjustment of the satellite constellation and improve the efficiency of the constellation design. By understanding the performance of coverage multiplicity under different configurations, satellite resources can be more effectively configured to maximize the coverage effect.

[0071] Implementation Method 2: See Figure 2 This embodiment further defines the method for analyzing the degradation of communication performance of the giant star constellation with respect to the sensitivity of coverage multiplicity described in the first embodiment, wherein the statistics of the satellite coverage of the designated location in the case of step-by-step calculation according to the step length in the first step include:

[0072] Step 1: Create a new table Table1, the table header includes satellite name (number), start coverage time and end coverage time;

[0073] Step 12: For each time i, read all satellite information covering location D;

[0074] Step 13: For each satellite name (number) Name_j, check whether there is a corresponding row in the table; if so, update the end coverage time of the row and add 1; if there is no corresponding row in the table, add a new row, set the start coverage time of the row to the current time i, and the end coverage time is also i;

[0075] Step 14: Repeat steps 12 and 13 until all satellite information at the current moment is processed, and then continue to the next moment i+1 until all moments in the entire period T are processed.

[0076] In step 1 of a method for analyzing the degradation of communication performance of the giant satellite constellation for sensitivity to coverage multiplicity described in this embodiment, table Table 1 is used to record the coverage information of the satellite, so that the organization and management of the data are more systematic and clear. Each row records the name of the satellite, the start and end coverage time, and this structured management helps to avoid data confusion and improve processing efficiency. By reading and updating the coverage information of the satellite at each moment i, it is ensured that the data in the table can reflect the status of the satellite in real time. This dynamic update mechanism makes the analysis of the satellite coverage more accurate and can capture the changes in the coverage time. In step 13, different processing strategies (update or add new rows) are adopted according to whether the satellite already exists in the table. This refined recording method ensures that the coverage time of each satellite is accurately recorded and updated, thereby improving the accuracy of the test. In step 14, all satellite information is processed moment by moment and the table is updated, so that the entire data processing process is carried out in an orderly manner. This structured processing method ensures that the data at any moment will not be missed, and improves the comprehensiveness and reliability of the test. By saving the satellite coverage information in a structured table form, subsequent data analysis and sensitivity testing will be more convenient. Data at the coverage moment can be quickly retrieved and processed to improve analysis efficiency.

[0077] Implementation method 3: This implementation method is a further limitation of the Superstar constellation communication performance degradation analysis method for coverage multiplicity sensitivity described in implementation method 1. The satellite coverage of a designated location calculated by geometric solution in step 1 includes:

[0078] Use geometric methods to obtain the start and end coverage times of each satellite for a specified location within a time period T;

[0079] Select a fixed time step and discretize the entire period T into multiple time points, with each time point separated by the selected step;

[0080] At each discrete time point, check whether all satellites cover the specified location and record the satellite coverage corresponding to these moments;

[0081] The coverage information of each discrete time point is organized into a table or data format to display the satellite coverage at each moment.

[0082] The method for analyzing the degradation of communication performance of the Giant Star constellation for sensitivity to coverage multiplicity described in this embodiment calculates the coverage time of the satellite through a geometric method, which can provide high accuracy and perform calculations based on the satellite orbit and viewing angle, avoiding errors caused by simple time stepping. The discretization method with a fixed time step can make the record of coverage more detailed and continuous, which is convenient for analyzing the dynamic changes of satellite coverage. Organizing the coverage information at each time point into a table or data format helps to systematically manage and view the satellite coverage, and facilitates subsequent data analysis and processing. By recording each discrete time point, the changes in coverage multiplicity during the entire period can be accurately monitored, providing real-time data support. The clear table or data format displays the coverage situation, making data analysis more intuitive and able to quickly identify and evaluate satellite coverage performance.

[0083] Embodiment 4: This embodiment further limits the method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity described in embodiment 1, and the step 2 includes:

[0084] Sort Table1 in ascending order by the End Coverage Time column;

[0085] For the sorted table, sort it in ascending order according to the start coverage time column;

[0086] Calculate the initial average coverage weight Ca1 of location D in time period T;

[0087] Calculate the average coverage weight Ca2 of site D after weight reduction;

[0088] The average coverage density Cc that needs to be reduced is obtained according to the initial average coverage density and the average coverage density;

[0089] Decompose Cc into an integer part CcI and a decimal part CcF, where the integer part CcI represents the number of complete time periods that need to be spliced, and the decimal part CcF represents the additional weight reduction that needs to be processed;

[0090] Create Table2 with the same header as Table1 to record the concatenated results;

[0091] Initialize the number of weights that have been reduced Cn = 0, which is used to track the weight of weights that have been processed currently;

[0092] According to CcI, select the time periods in Table 1 for splicing to achieve the integer part weight reduction requirement;

[0093] For the fractional part CcF, select an appropriate time period for partial splicing to meet the weight reduction requirements.

[0094] The appropriate time period described in this embodiment may be a time period with a coverage multiplicity close to CcF. The time period with a coverage multiplicity closest to CcF is selected to reduce interference with other time periods during splicing.

[0095] The appropriate time period described in this embodiment may be a time period with high splicing flexibility, and priority is given to those time periods that are easy to split or adjust, so as to achieve accurate weight reduction without affecting the overall coverage.

[0096] The appropriate time period described in this embodiment may be a continuous or overlapping time period. If a plurality of time periods overlap or are close to each other, these time periods may be spliced ​​together to more easily achieve the desired weight reduction.

[0097] The appropriate time period described in this implementation manner may be a time period that minimizes the impact, and the time period with the least impact on other coverage conditions is selected for partial splicing to avoid causing significant interference to the overall coverage quality.

[0098] Specifically, in step 2 of a method for analyzing the degradation of communication performance of the giant star constellation for sensitivity to coverage multiplicity described in this embodiment, by arranging Table 1 in ascending order of the end coverage time and the start coverage time, the order and logic of data processing are ensured. This sorting can avoid omissions and confusion and improve the accuracy of data processing. The initial average coverage multiplicity (Ca1) and the average coverage multiplicity (Ca2) after weight reduction are calculated at location D, providing a clear benchmark for evaluating weight reduction requirements. This step ensures a clear quantitative analysis of changes in coverage multiplicity. The average weight (Cc) to be reduced is decomposed into an integer part (CcI) and a decimal part (CcF), making the weight reduction target setting more refined. The integer part represents the complete period that needs to be processed, and the decimal part provides a more accurate weight reduction strategy for the additional weight reduction. The weight reduction requirements of the integer part are achieved by selecting the time periods in Table 1 for splicing, and the weight reduction of the decimal part is processed by partial splicing through appropriate time periods. This method makes the weight reduction process more efficient and flexible, and appropriate processing measures can be taken for different weight reduction requirements. Create Table2 with the same header as Table1 to record the concatenated results so that the processed data results can be clearly recorded and archived. This step helps to conduct detailed result analysis and verification after the weight reduction process. Initialize and use the weight reduction number (Cn) to track the weight reduction amount currently processed, which helps to monitor and adjust the weight reduction strategy in real time to ensure the achievement of weight reduction goals.

[0099] Embodiment 5: This embodiment further limits the method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity described in embodiment 4. The processing flow of the integer part includes:

[0100] Step 21: Initialize the current end time, find the end row S1 of the initial time Tb of the coverage period T from Table1, if there is no matching row, search downward in the order of time until the appropriate row is found; stack the S1 row into Table2, and delete the S1 row from Table1; set Ten to the value of the end coverage time column of the S1 row, and go to step 22;

[0101] Step 22: If Ten is greater than or equal to the end time Te of time period T, it means that enough time periods have been processed, the current reduced weight Cn is increased by 1, and the process goes to step 24; if Ten is less than Te, it means that not all time periods have been processed, and the process goes to step 23;

[0102] Step 23: Search for row S2 in the start coverage time column of Table1 that is equal to the current end time Ten. If no matching row is found, add or subtract the search based on Ten. Take S3 as the found row, stack S3 into Table2, and delete S3 from Table1. Update Ten to the value of the "end coverage time" column of S3, and go to step 22.

[0103] Step 24: If the currently reduced multiplicity Cn is greater than or equal to the integer part CcI, exit the loop and enter step 5; if Cn is less than CcI, return to step 21 to continue processing;

[0104] Step 25: Once Cn reaches or exceeds CcI, the entire process ends.

[0105] This embodiment is explained in conjunction with the fourth embodiment. This embodiment ensures that each processed time period accurately matches the actual coverage situation by dynamically searching for the start and end rows (S1, S2, S3) of the coverage time period in Table1. The matching rows are searched step by step, and it is ensured that each coverage time period is accurately processed, thereby reducing the possibility of missed processing. Through the step-by-step processing from step 21 to step 23, the high time complexity of the full table scan is avoided and the processing speed is improved. The data in the table is dynamically updated during the processing (for example, the processed rows are deleted), which reduces redundant calculations and improves efficiency.

[0106] Specifically, in the processing flow of the integer part described in this embodiment, steps 21 to 23 process time periods through precise matching and sorting, avoiding omissions or duplications, and improving the accuracy and completeness of data processing. Furthermore, by continuously updating the end time Ten, it is possible to dynamically adapt to the time periods in Table 1 to ensure that the processed time periods always match the current needs, thereby enhancing the flexibility of processing. By checking the relationship between Ten and the end time Te, as well as real-time tracking of the reduced weight Cn, the weight reduction can be accurately controlled to avoid excessive or insufficient weight reduction. The judgment in step 24 and the loop processing of returning to step 21 enable the process to end quickly after meeting the target, reducing unnecessary processing steps and improving efficiency. Each step clarifies the processing logic and data flow, ensuring the orderly progress of the entire weight reduction process, so that the reliability and repeatability of the results are guaranteed.

[0107] Embodiment 6: This embodiment further limits the method for analyzing the degradation of communication performance of the giant star constellation with respect to the sensitivity of coverage multiplicity described in embodiment 4. The processing flow of the decimal part includes:

[0108] Step 26: Set the current end time Ten to 0, and search for the end row S1 of the initial time Tb of the coverage period in Table1; if not found, search downward in time order and stack the found row S1 into Table2, and then delete row S1 from Table1; update Ten to the value of the end coverage time column of row S1;

[0109] Step 27: If Ten-Tb is greater than or equal to (Te-Tb)*CcF, then the process ends and goes to step 29; if Ten-Tb is less than (Te-Tb)*CcF, then go to step 28;

[0110] Step 28: Search for a row S2 equal to Ten in the start coverage time column of Table1. If not found, add or subtract from Ten to search. The last row S3 of the found row S2 is stacked into Table2, and row S3 is deleted from Table1. Ten is updated to the value of the end coverage time column of row S3. Return to step 27 and continue processing.

[0111] Step 29: If the conditions are met to end the process, then end the process.

[0112] In the processing flow of the decimal part described in this embodiment, the accuracy of the coverage multiplicity sensitivity test is ensured by gradually updating Ten and comparing the initial and end times of the coverage period. The method allows adjustment according to the actual time sequence, thereby maintaining the reliability of the test results under different dynamic change conditions. By using Table1 and Table2 to manage the data of the coverage period, the process is clear and structured, which helps to ensure the orderliness and accuracy of data processing. The conditional judgment and dynamic search mechanism involved in the steps help to effectively handle the overlap of different coverage periods and improve processing efficiency.

[0113] By dynamically processing the coverage period (such as searching, stacking, and deleting rows), this method can flexibly respond to different coverage time changes and adapt to complex constellation dynamics. By setting the end time Ten and adjusting Ten to accurately filter the coverage period, the test can effectively capture the coverage information of the key period, ensuring the efficiency of coverage detection.

[0114] By gradually checking and dynamically updating the contents of Table 1 and Table 2, it is possible to ensure that no important coverage period is missed, and the sensitivity of the coverage multiplicity can be effectively handled. The checking conditions and dynamic adjustment mechanism in the method make the test method highly scalable and can be applied to constellation dynamic change tests of different scales and complexities.

[0115] Embodiment 7: This embodiment further limits the Superstar constellation communication performance degradation analysis method for coverage multiplicity sensitivity described in Embodiment 4. The average coverage multiplicity at discrete moments is:

[0116]

[0117] Among them, T b is the coverage start time, T e is the coverage end time, δ step is the step size of discrete operation, C i T b +i*δ step The coverage multiplicity at a moment.

[0118] The average coverage multiplicity at discrete moments in this implementation takes into account the start and end times of coverage, as well as the step length, which makes the calculation of coverage multiplicity more accurate and comprehensive. By setting the discrete running step length, the coverage multiplicity changes at each moment can be analyzed in detail, thereby improving the sensitivity test capability to dynamic changes in the constellation. This method systematically integrates coverage time and multiplicity information, facilitates in-depth coverage multiplicity analysis, and optimizes the structure of the test process. Considering the characteristics of dynamic changes in the constellation, it is ensured that the test results can reflect the coverage situation in actual applications and improve the actual effectiveness of the results.

[0119] Embodiment 8: This embodiment further defines the method for analyzing the degradation of communication performance of the Giant Star constellation with respect to the sensitivity of coverage multiplicity described in Embodiment 4. The average coverage multiplicity at consecutive moments is:

[0120]

[0121] Among them, C(t) is the coverage multiplicity at time t.

[0122] Embodiment 9. A computer device described in this embodiment includes a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a method for analyzing the communication performance degradation of the Giant Star constellation for coverage multiplicity sensitivity described in any one of embodiments 1 to 8.

[0123] Embodiment 10. A computer-readable storage medium described in this embodiment stores a computer program, and when the computer program is executed by a processor, the steps of a method for analyzing the performance degradation of supergiant constellation communication for coverage multiplicity sensitivity as described in any one of embodiments 1 to 8 are performed.

[0124] Implementation Method 11: See Figures 3 to 6This embodiment is a specific example of a method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity described in the first embodiment, and is also used to explain the second to eighth embodiments, specifically:

[0125] This implementation method achieves weight reduction at a designated location D by counting and splicing the satellite coverage of the link source and destination nodes within a certain period of time T, thereby weakening the communication capability and realizing sensitivity testing. The testing method specifically includes:

[0126] Get the satellite's position, including:

[0127] Step 1: Read the parameter values ​​under different data segments according to the format of the double-line metadata record and save them to the SGP4 orbit model structure variables;

[0128] Step 2: Initialize the orbit model according to the physical meaning of the SGP4 orbit model variables, and obtain the six orbital elements under the double-row metadata orbit epoch and the position and velocity in the J2000 coordinate system;

[0129] Step 3: Combine the simulation time and simulation step size to calculate the time difference between the simulation time and the orbit epoch, substitute it into the orbit model calculation function, and perform orbit recursion and data output.

[0130] Statistics of satellite coverage, including:

[0131] 1. For the step-by-step calculation method, obtain the satellite coverage of the designated location at a series of times, including the number and name (number) of available satellite resources at the designated location D at each time, and obtain the average coverage weight Ca1 of the location within the time period. Obtain the start and end times of satellite coverage of location D in chronological order. The specific execution process is as follows: Figure 2 As shown, including:

[0132] The newly created table header Table1 includes: satellite name (number), start coverage time and end coverage time

[0133] Read the name (number) Name_j of the j-th satellite covering the location D at the i-th time;

[0134] If the table contains Name_j, find the Name_j row and increase the end coverage time of the row by one step, that is, the number of simulation steps corresponding to the end coverage time + 1; if the table does not contain the Name_j row, add a Name_j row, set the start coverage time of the row to i, and set the end coverage time to i;

[0135] Continue until j reaches the coverage multiplicity of the current moment and enter the next moment i+1; continue until i reaches the end time of time period T.

[0136] 2. For the calculation method based on geometric solution, the start and end times of the satellite coverage in the time period T can be directly obtained, and the time can be discretized according to a certain step size to obtain the satellite coverage of the specified location at a series of times, and then the above steps can be executed.

[0137] Time period splicing, including:

[0138] Considering that the target location D needs to be uniformly reduced in the specified time period T, the set of satellites that have covered the location D in the time period T is called S. In this implementation, different coverage periods corresponding to the members in S are selected according to certain rules to meet the need for uniform reduction. The specific steps are as follows:

[0139] For the statistically obtained table Table1, arrange the elements in the table in ascending order by the "end coverage time" column, and then arrange the elements in the table in ascending order by the "start coverage time" column, so as to facilitate splicing and use;

[0140] According to the weight reduction requirements, the average coverage weight Ca2 in the time period T of the location D after weight reduction is obtained, and then the average weight Cc that needs to be reduced can be obtained as Cc = Ca1-Ca2, that is, the number of time periods that need to be spliced. Generally, Cc is not an integer, and Cc needs to be decomposed into the integer part CcI and the decimal part CcF, Cc = CcI + CcF, and spliced ​​separately;

[0141] Generate the same table header Table2 as Table1, and set the current reduced multiplicity Cn = 0;

[0142] The calculation process of the integer part and the calculation process of the decimal part are as follows Figure 3 and Figure 4 As shown:

[0143] The integer part calculation process includes:

[0144]

[0145] In this embodiment, e is a preset, fixed value (which may be a few minutes, a few seconds or other units) to allow a certain degree of flexibility in the search process.

[0146] Specifically, if S2 that is exactly equal to the current end time Ten is not found in Table1, the range e can be added and subtracted from Ten to find possible rows.

[0147] In this embodiment, using range e can improve the flexibility of searching, especially when the data is not accurate enough or there may be slight errors in the time period boundaries. This ensures that when processing the time period, even if there are certain time errors, suitable covering rows can be found.

[0148] The decimal calculation process includes:

[0149]

[0150] The average coverage weight at discrete moments is calculated using the following formula:

[0151]

[0152] The average coverage weight at consecutive moments is calculated using the following formula:

[0153]

[0154] Where, T b is the coverage start time, T e is the coverage end time, δ step is the step size of discrete operation, T e -T b is δ step Integer multiples of C i T b +i*δ step The covering multiplicity at time t, C(t) is the covering multiplicity at time t.

[0155] In order to verify the test method proposed in this embodiment, this embodiment also imports two rows of metadata of the STARLINK constellation on September 18, 2023, with a total of 4729 satellites.

[0156] In order to meet the requirements of adjacent connectivity of co-orbit links and position and velocity constraints of off-orbit links, in this implementation, satellites in the same orbital plane are divided into the same domain. According to the current walker configuration of the XL constellation, there are 194 orbital planes, which can be divided into 194 domains. The number of domains contained in each sub-constellation is shown in Table 1 below.

[0157] Table 1 XL communication domain division

[0158]

[0159]

[0160] The simulation process uses the following simplifying assumptions and inferences:

[0161] Simplified Assumption 1: All nodes are allowed to connect to nodes in different domains. Since the inter-orbit forwarding settings of the XL constellation are unknown, in order to obtain all theoretically available links, it is assumed that there is a possibility of establishing links between inter-orbit satellites, that is, nodes in each domain may establish links with nodes in adjacent domains. Therefore, for any node, it is considered that it can be used as a gateway and has the "permission" to connect to nodes outside the domain.

[0162] Considering that there is no need to quantitatively describe the bandwidth and throughput of the XL constellation during the link degradation simulation, but rather qualitatively requires that the throughput be reduced to 1 / 10 of the original, the bandwidth setting of the XL constellation does not use the actual XL uplink and downlink bandwidth. In this link simulation calculation, the bandwidth of the XL satellite is uniformly set to 10Mb / s.

[0163] Simplified Assumption 2: Node bandwidth is consistent. It is assumed that the bandwidth of all nodes is the same, and the bandwidth difference between satellites is not considered.

[0164] Corollary 2-1: All available links between the source and destination only intersect at the source and destination nodes, and the other nodes do not overlap. To achieve the maximum transmission rate, each time a link is established, the node transmission rate on the link is equal to the node bandwidth. Therefore, when other available links are established at the same time, the nodes on the link are unavailable due to full-rate transmission. Ultimately, the available links are independent of each other, presenting a cluster of curves starting from the source node and ending at the destination node, with no intersection between them. For the convenience of description, the concept of "number of available links" is used instead of "throughput rate".

[0165] Corollary 2-2: The number of available links does not exceed the minimum value of the number of available nodes of the source and destination nodes. Based on the above assumptions, since the available links have no intersections with each other, it can be further concluded that the number of available links n must be less than the number of nodes n that can be connected to the source node. source The number of nodes that can be connected to the target node n dest The minimum value of ination, expressed as:

[0166] n≤min{n source n destination}

[0167] Therefore, under this assumption, the number of available links is constrained by the source and destination coverage multiplicity.

[0168] The simulation conditions are shown in Table 2 below:

[0169] Table 2 Details of simulation conditions

[0170]

[0171]

[0172] like Figure 5 and Figure 6As shown. Under normal circumstances, the average coverage density is maintained at about 23. Through statistics and calculations of the coverage of the coverage area during this period, it can be obtained that 157 satellites cover the key area. In order to keep the coverage density within 1 / 10 of the original coverage density during the entire period, the coverage period of each satellite is counted, and the period is spliced ​​to make the reduced coverage density uniform over time. After processing using this method, the same calculation is performed to obtain the coverage density change curve after processing.

[0173] The advantages of the testing method described in this embodiment are:

[0174] 1. It does not need to consider the configuration of the object. It is simple, universal, intuitive and effective.

[0175] 2. The task requirements can be met by limiting the deletion depth and reducing the impact on other links;

[0176] 3. Considering the impact of deleting satellite nodes on link connections during the entire period, ensure that the link is basically uninterrupted during the set period.

[0177] Although the preferred embodiments of the present disclosure have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present disclosure.

[0178] Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

[0179] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0180] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0181] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0182] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure rather than to limit its protection scope. Although the present disclosure has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present disclosure, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the invention, but these changes, modifications or equivalent substitutions are all within the protection scope of the disclosed claims to be approved.

Claims

1. A method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity, characterized in that: The method comprises: Step 1: Count the satellite coverage of the designated location when the step length is calculated and the satellite coverage of the designated location when the geometric solution is calculated; Step 2: The satellite set that has covered the location D within the time period T is called S. The different coverage periods corresponding to the members in the satellite set S are arranged in ascending order according to the end coverage time, and the members corresponding to the same coverage end time are arranged in ascending order according to the start coverage time; Step 3: Determine the number of splicing time periods based on the average coverage density and the target average coverage density, analyze the curve relationship between the number of satellites after weight reduction and the reduction in coverage density in local areas, and complete the sensitivity test.

2. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 1, characterized in that: The statistics of satellite coverage of the designated location in step 1 are calculated by stepping the step length, including: Step 1. Create a new table Table1, the table header includes satellite name, start coverage time and end coverage time; Step 12: For each time i, read all satellite information covering location D; Step 13: For each satellite name Name_j, check whether there is a corresponding row in the table; if so, update the end coverage time of the row and add 1; if there is no corresponding row in the table, add a new row, set the start coverage time of the row to the current time i, and the end coverage time to i; Step 14: Repeat steps 12 and 13 until all satellite information at the current moment is processed, and then continue to the next moment i+1 until all moments in the entire period T are processed.

3. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 1, characterized in that: The satellite coverage of the designated location in the geometric solution calculation in step 1 includes: Use geometric methods to obtain the start and end coverage times of each satellite for a specified location within a time period T; Select a fixed time step and discretize the entire period T into multiple time points, with each time point separated by the selected step; At each discrete time point, check whether all satellites cover the specified location and record the satellite coverage corresponding to these moments; The coverage information of each discrete time point is organized into a table or data format to display the satellite coverage at each moment.

4. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 1, characterized in that: The second step comprises: Sort Table1 in ascending order by the End Coverage Time column; For the sorted table, sort it in ascending order by the start coverage time column; Calculate the initial average coverage weight Ca1 of location D in time period T; Calculate the average coverage weight Ca2 of site D after weight reduction; The average coverage density Cc that needs to be reduced is obtained according to the initial average coverage density and the average coverage density; Decompose Cc into an integer part CcI and a decimal part CcF, where CcI represents the number of complete periods that need to be spliced, and CcF represents the additional weight that needs to be processed; Create Table2 with the same header as Table1 to record the concatenated results; Initialize the number of weights that have been reduced Cn = 0, which is used to track the weight of weights that have been processed currently; According to CcI, select the time periods in Table 1 for splicing to achieve the integer part weight reduction requirement; For the fractional part CcF, select an appropriate time period for partial splicing to meet the weight reduction requirements.

5. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 4, characterized in that: The processing flow of the integer part includes: Step 21: Initialize the current end time, find the end row S1 of the initial time Tb of the coverage period T from Table1, if there is no matching row, search downward in the order of time until the appropriate row is found; stack the S1 row into Table2, and delete the S1 row from Table1; set Ten to the value of the end coverage time column of the S1 row, and go to step 22; Step 22: If Ten ≥ the end time Te of time period T, it means that enough time periods have been processed, the current reduced weight Cn is increased by 1, and the process goes to step 24; if Ten is less than Te, it means that not all time periods have been processed, and the process goes to step 23; Step 23: Search for row S2 in the start coverage time column of Table1 that is equal to the current end time Ten. If no matching row is found, add or subtract the search based on Ten; take S3 as the found row, stack S3 into Table2, and delete S3 from Table1; update Ten to the value of the end coverage time column of S3, and proceed to step 22; Step 24: If the currently reduced multiplicity Cn ≥ integer part CcI, exit the loop and go to step 5; If Cn<CcI, return to step 21 to continue processing; Step 25: Once Cn reaches or exceeds CcI, the process ends.

6. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 4, characterized in that: The processing flow of the decimal part includes: Step 26: Set the current end time Ten to 0, and search for the end row S1 of the initial time Tb of the coverage period in Table1; if not found, search downward in time order and stack the found row S1 into Table2, and then delete row S1 from Table1; update Ten to the value of the end coverage time column of row S1; Step 27: If Ten-Tb is greater than or equal to (Te-Tb)*CcF, then the process ends and goes to step 29; if Ten-Tb<(Te-Tb)*CcF, then go to step 28; Step 28: Search for a row S2 equal to Ten in the start coverage time column of Table1. If not found, add or subtract from Ten to search. The last row S3 of the found row S2 is stacked into Table2, and row S3 is deleted from Table1. Update Ten to the value of the end coverage time column of the S3 row; return to step 27 and continue processing; Step 29: If the conditions are met to end the process, then end the process.

7. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 4, characterized in that: The average coverage weight at discrete moments is: Among them, T b is the coverage start time, T e is the coverage end time, δ step is the step size of discrete operation, C i T b +i*δ step The coverage multiplicity at a moment.

8. The method for analyzing the degradation of communication performance of the giant star constellation for the sensitivity of coverage multiplicity according to claim 4, characterized in that: The average coverage weight of the continuous moments is: Among them, C(t) is the coverage multiplicity at time t.

9. A computer device, characterized in that: The invention comprises a memory and a processor, wherein a computer program is stored in the memory, and when the processor runs the computer program stored in the memory, the processor executes a method for analyzing the degradation of communication performance of a giant star constellation for sensitivity to coverage multiplicity according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of a method for analyzing the degradation of communication performance of a giant star constellation with respect to coverage multiplicity sensitivity as claimed in any one of claims 1 to 8.

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