Optimized transmission method and system for ephemeris information in low earth orbit satellite communication

Abstract

The invention relates to the technical field of data transmission, and provides an optimized transmission method and system for ephemeris information in low earth orbit satellite communication. The method comprises the following steps: acquiring satellite type information and orbit height information of a target satellite; analyzing ephemeris data based on the orbit height information, updating dynamic characteristics, and collecting the ephemeris data to generate a data set; judging ephemeris data type synchronism based on the satellite type information, and generating a first data type and a second data type; performing adjacent sampling point change rate analysis on the ephemeris data set, matching a polynomial interpolation model according to a result, performing interpolation after data type division, and generating a first polynomial interpolation coefficient and a second polynomial interpolation coefficient; after the state of a communication link between a satellite and a ground measurement and control station is obtained and a transmission protocol parameter is regulated and controlled, a polynomial interpolation coefficient is transmitted to the ground measurement and control station for reconstruction, so that the technical problems that the ephemeris information real-time performance is insufficient and the data reliability cannot meet the dynamic application requirement due to the difference of the satellite orbit height and type are solved.

Description

Technical Field

[0001] The present application relates to the technical field of data transmission, and in particular to a method and system for optimizing transmission of ephemeris information in low-orbit satellite communications. Background Art

[0002] Low-orbit satellites have become an important part of modern communication systems due to their low orbital altitude, wide coverage, and short communication delay. However, in the process of low-orbit satellite communication, ephemeris information, as key data to ensure communication accuracy and reliability, faces many challenges in its transmission process. In traditional methods, ephemeris information is usually transmitted at a high sampling frequency and a fixed transmission interval, resulting in a large amount of data and low transmission efficiency. Especially under limited communication bandwidth conditions, it is easy to cause transmission delays and data packet loss problems. In addition, due to the diversity of orbital altitudes and mission types of low-orbit satellites, there are large differences in the dynamic update rate of their ephemeris information. A single transmission method is difficult to adapt to the needs of different satellite types and orbital characteristics, thus affecting the real-time and reliability of ephemeris data. On the other hand, in the low-orbit satellite communication link, the communication environment between the ground tracking and control station and the satellite is usually affected by factors such as channel conditions, signal-to-noise ratio changes, and bit error rate. Traditional transmission protocols lack a dynamic adjustment mechanism for the communication link status, making it difficult to achieve efficient and stable transmission of ephemeris information under complex link conditions. In addition, different types of ephemeris data have different requirements for synchronization and transmission priority. How to hierarchically process ephemeris information and optimize the transmission order according to satellite missions and data characteristics is also a problem that is difficult to effectively solve with existing technologies. Summary of the invention

[0003] The present application provides a method and system for optimizing the transmission of ephemeris information in low-orbit satellite communications, aiming to solve the technical problems of insufficient real-time performance of ephemeris information and inability of data reliability to meet dynamic application requirements due to differences in satellite orbit altitudes and types, thereby realizing dynamic collection and hierarchical interpolation processing of ephemeris information based on orbit altitude and satellite type, optimizing the configuration of communication link parameters, improving the efficiency and reliability of ephemeris information transmission, and ensuring the technical effect of real-time and accurate transmission of ephemeris information in low-orbit satellite communications.

[0004] In view of the above problems, the present application provides a method and system for optimizing the transmission of ephemeris information in low-orbit satellite communications.

[0005] The first aspect disclosed in the present application provides an optimized transmission method for ephemeris information in low-orbit satellite communications, the method comprising: acquiring satellite type information and orbital height information of a target satellite; analyzing the dynamic characteristics of ephemeris data update based on the orbital height information, and collecting ephemeris data based on the update dynamic characteristics to generate an ephemeris data set; distinguishing the synchronous transmission of multiple ephemeris data types based on the satellite type information to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type; analyzing the change rate of adjacent sampling points of the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient; acquiring the communication link status between the target satellite and a ground measurement and control station, and after adjusting the parameters of the transmission protocol, transmitting the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground measurement and control station for reconstruction.

[0006] Another aspect disclosed in the present application provides an optimized transmission system for ephemeris information in low-orbit satellite communications, the system comprising: an information acquisition unit: acquiring satellite type information and orbital height information of a target satellite; an ephemeris data acquisition unit: performing an update dynamic characteristic analysis of ephemeris data based on the orbital height information, and performing ephemeris data acquisition based on the update dynamic characteristic to generate an ephemeris data set; a synchronization transmission discrimination unit: performing synchronization transmission discrimination of multiple ephemeris data types based on the satellite type information to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type; a data interpolation unit: performing a change rate analysis of adjacent sampling points on the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient; a coefficient reconstruction unit: acquiring the communication link status between the target satellite and the ground measurement and control station, and after adjusting the parameters of the transmission protocol, transmitting the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground measurement and control station for reconstruction.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The above-mentioned optimized transmission method of ephemeris information in low-orbit satellite communication obtains the type and orbital height information of the target satellite, analyzes the dynamic update characteristics of the ephemeris data according to the orbital height, and collects the corresponding data to generate an ephemeris data set; then, the transmission synchronization of the ephemeris data is judged according to the satellite type, and divided into a first data type with a higher synchronization priority and a second data type with a lower priority; then, the change rate of adjacent sampling points in the ephemeris data set is analyzed, and an adaptive polynomial interpolation model is selected according to the analysis result, and the ephemeris data is divided and interpolated for different data types to generate corresponding polynomial interpolation coefficients; finally, according to the communication link status between the satellite and the ground measurement and control station, the parameters of the transmission protocol are dynamically adjusted, and the generated polynomial interpolation coefficients are transmitted to the ground measurement and control station for reconstructing the ephemeris data. This method realizes the efficient compression and transmission of ephemeris data, and improves the communication efficiency and reliability.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0010] Figure 1 The figure is a flow chart of a method for optimizing transmission of ephemeris information in low-orbit satellite communications in one embodiment.

[0011] Figure 2 This is a diagram of the architecture of an optimized transmission system for ephemeris information in low-orbit satellite communications in one embodiment.

[0012] Description of the reference numerals: information acquisition unit 11 , ephemeris data acquisition unit 12 , synchronous transmission determination unit 13 , data interpolation unit 14 , coefficient reconstruction unit 15 . DETAILED DESCRIPTION

[0013] The embodiments of the present application provide a method and system for optimizing the transmission of ephemeris information in low-orbit satellite communications, thereby solving the technical problems of insufficient real-time performance of ephemeris information and inability of data reliability to meet dynamic application requirements due to differences in satellite orbit altitudes and types. The method realizes dynamic collection and hierarchical interpolation processing of ephemeris information based on orbit altitude and satellite type, optimizes the configuration of communication link parameters, improves the efficiency and reliability of ephemeris information transmission, and ensures the technical effect of real-time and accurate transmission of ephemeris information in low-orbit satellite communications.

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0015] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0016] Embodiment 1, as Figure 1 As shown, the present application provides a method for optimizing transmission of ephemeris information in low-orbit satellite communications, the method comprising: Get the satellite type information and orbit altitude information of the target satellite.

[0017] In an embodiment of the present application, first, relevant information of the target satellite is obtained from the satellite management terminal, including the type of satellite (such as remote sensing satellite, communication satellite, navigation satellite, etc.) and the orbital altitude of its operation. This information can be obtained by querying the satellite orbit design parameters and satellite mission planning files in the terminal database. The satellite type information is mainly used to determine the characteristics of the mission performed by the satellite, for example, whether there are high requirements for the real-time performance of data transmission or whether certain specific data types need to be processed first, while the orbital altitude information reflects the operating position and dynamic characteristics of the satellite. For example, changes in the perigee and apogee may affect the frequency of updating the ephemeris data and the transmission requirements. The acquisition of these basic information lays a data foundation for the subsequent dynamic update characteristics analysis and transmission optimization of the ephemeris data.

[0018] An update dynamic characteristic analysis of the ephemeris data is performed based on the orbital altitude information, and ephemeris data is collected based on the update dynamic characteristic to generate an ephemeris data set.

[0019] In one embodiment, the satellite orbit is preliminarily classified according to the orbital altitude information of the target satellite (such as the perigee altitude and the apogee altitude) and the orbital type (such as circular orbit, elliptical orbit, etc.). The orbital altitude reflects the satellite's operating speed and orbital change characteristics. Low-orbit satellites usually have a fast operating speed and frequent orbital changes, while high-orbit satellites have a slow operating speed and small changes. Based on the orbital altitude information, the change characteristics of the main parameters related to the orbit are directly evaluated, such as the range of orbital altitude changes, the length of the orbital period, the average motion rate, etc. during the satellite's in-orbit operation (which can be based on orbital mechanics formulas, such as Kepler's third law, etc.). By analyzing these parameters, the speed and regularity of the orbital changes can be obtained to evaluate the impact of its orbital changes on the update frequency and dynamic characteristics of the ephemeris data. For example, for a satellite with a lower orbital altitude, its operating speed is faster and its orbital parameters are smaller. The number of changes is also more frequent, so the ephemeris data needs a higher update frequency. For satellites with higher orbits, the orbital parameters change slowly, and the update frequency of the ephemeris data can be appropriately reduced. Subsequently, based on these dynamic characteristics, combined with the corresponding relationship between the preset change interval and the acquisition parameters, the acquisition parameters of the ephemeris data are determined, including the sampling interval, data capture accuracy, and acquisition period. After that, according to the acquisition parameters determined by updating the dynamic characteristics, the ephemeris data acquisition process is started to record the orbital parameters of the satellite (such as position, speed, time stamp, etc.) in real time, and these data are sorted in chronological order and parameter category to generate a complete ephemeris data set, which provides a basis for subsequent data processing (such as classification, interpolation, and transmission optimization), and can reflect the dynamic changes of satellite orbital characteristics, ensuring that subsequent steps can be operated based on accurate and complete data.

[0020] Based on the satellite type information, synchronous transmission of multiple ephemeris data types is judged to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type.

[0021] In this embodiment, the synchronization and real-time requirements of different types of ephemeris data for task requirements are analyzed through the type information of the target satellite (such as a navigation satellite, a remote sensing satellite or a communication satellite, etc.). For example, the ephemeris information of the navigation satellite plays a vital role in accurate positioning, so it is necessary to give priority to ensuring the real-time and synchronization of its transmission, while other non-critical data (such as status information or low-priority telemetry data) have lower timeliness requirements for task execution and can be appropriately delayed in transmission; based on the above analysis, the ephemeris data type is classified to generate a first data type and a second data type, wherein the first data type mainly includes ephemeris information and high-priority data that is critical to task execution (such as satellite attitude data, etc.), which need to be transmitted in real time to ensure the normal execution of the satellite mission, and the second data type includes auxiliary or non-critical data with lower priority (such as detailed environmental monitoring data or part of telemetry information), which can be delayed in transmission when transmission conditions permit; finally, through this classification method, a data priority transmission mechanism is established to ensure that critical ephemeris information is transmitted first in the communication link, while non-critical data can be sent later, thereby optimizing data transmission in a limited communication bandwidth and improving overall communication efficiency and reliability of task execution.

[0022] Further, the present application provides synchronous transmission discrimination of multiple ephemeris data types based on the satellite type information to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type, including: Determine a satellite mission based on the satellite type information; perform application priority analysis on multiple ephemeris data types based on the satellite mission to generate a priority analysis result; and determine a data type with a priority greater than or equal to a preset priority as the first data type, and determine a data type with a priority less than the preset priority as the second data type based on the priority analysis result.

[0023] Preferably, according to the satellite type information (such as navigation satellite, remote sensing satellite, communication satellite, etc.), combined with the mission requirement document (derived from the satellite management terminal), the main task performed by the satellite is clarified. For example, the main task of the navigation satellite is to provide high-precision positioning and timing services, the task of the remote sensing satellite may be to conduct surface monitoring or resource surveying, and the task of the communication satellite is concentrated on signal relay or data transmission. On this basis, the core data requirements directly related to the satellite mission are extracted, such as timing information, data transfer volume, etc.; then, the minimum real-time standard set for all data types by the satellite mission is extracted from the timing information, reflecting the overall requirements of the satellite mission for time sensitivity, and then the maximum tolerable delay set for a specific data type is extracted from the timing information, indicating the upper limit of the acceptable time delay of the data type during transmission. The real-time factor of each data type is obtained by calculating the ratio of the minimum real-time standard to the upper limit of the time delay of the current data type. This real-time factor quantifies the real-time requirement of the ephemeris data type for task execution. The closer the value is to 1, the higher the real-time requirement; the single transmission data volume of the current data type and the maximum data volume that the current communication link can support are extracted from the data transfer volume, and these data are compared with the transmission cost factor formula Combined, the transmission cost factor of each data type is calculated. This transmission cost factor represents the transmission cost of the ephemeris data type. The closer the value is to 1, the higher the transmission cost is. is the transmission cost factor, The single transmission data volume of the current data type. is the maximum amount of data that the current communication link can support, k is the weight of the link quality factor, ranging from 0 to 1, which is used to balance the impact of data volume and link quality. is the quality factor of the communication link, ranging from 0 to 1, indicating the quality of the link. The higher the value, the better the link. It can be determined based on the signal-to-noise ratio. After that, the real-time factor and the transmission cost factor are weighted to obtain the priority value of each ephemeris data type, and these priority values ​​are added to the priority analysis result in turn. By comparing each priority value in the priority analysis result with the preset priority, the ephemeris data type with a priority value greater than or equal to the preset priority is classified as the first data type. For example, for navigation satellites, orbital parameters and time stamps may be classified as the first data type because these data have the highest real-time requirements. The ephemeris data type with a priority value lower than the preset priority is classified as the second data type. For example, the detailed environmental monitoring data of the navigation satellite or the lower-precision status information may be classified as the second data type. The first data type and the second data type obtained through the above classification process will be used in the subsequent data transmission strategy to ensure the priority transmission of key data and improve the utilization efficiency of the communication bandwidth.

[0024] Perform a change rate analysis of adjacent sampling points on the ephemeris data set, match a target polynomial interpolation model according to the analysis result, and interpolate the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient.

[0025] In this embodiment, by traversing the ephemeris data set, extracting key parameters (such as orbital position, speed, etc.) and time tags of each sampling point, and calculating the change rate between adjacent sampling points, characteristics such as change amplitude and fluctuation frequency are obtained. These analysis results are used to determine the dynamic characteristics of the ephemeris data change and provide a basis for the subsequent polynomial interpolation model selection; then, according to the change rate analysis results, a suitable polynomial interpolation model is matched. Data with large dynamic changes require a higher-order polynomial to ensure fitting accuracy, while data with stable changes selects a lower-order polynomial model to achieve efficient use of computing resources; after completing the polynomial model matching, the ephemeris data set is classified into a first data type and a second data type, and the first data type includes an optimal The second data type includes key data with higher priority and strict synchronization requirements, such as orbital parameters and time stamps, and auxiliary data with lower priority and lower real-time requirements, such as environmental monitoring information. The classified data are fitted by a matching polynomial model to generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient, which characterize the changing characteristics of the original data in an efficient and compressed form. In the subsequent transmission process, the interpolation coefficient corresponding to the high-priority data, that is, the first polynomial interpolation coefficient will be sent first to ensure the real-time and reliability of task execution, while the interpolation coefficient corresponding to the low-priority data, that is, the second polynomial interpolation coefficient can be sent after a delay allowed by the link conditions, thereby optimizing the communication bandwidth utilization and improving the transmission efficiency.

[0026] Further, the present application provides performing a change rate analysis of adjacent sampling points on the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient, including: The ephemeris data set is traversed to record the time stamp and orbital parameters of each sampling point; based on the time stamp, the orbital parameter change rate of adjacent sampling points is calculated, and the dynamic fluctuation index is identified according to the change rate; based on the dynamic fluctuation index, the target polynomial interpolation model is matched in a preset polynomial interpolation model; the ephemeris data set is divided according to the first data type and the second data type to generate the first type of data and the second type of data; the first type of data and the second type of data are interpolated respectively by using the target polynomial interpolation model to generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient.

[0027] Preferably, after obtaining the ephemeris data set, the ephemeris data set is traversed, and the time stamp of each sampling point and the corresponding orbital parameters (such as position, speed, attitude, etc.) are recorded one by one. These data are used to analyze the change law of the orbital parameters over time. By extracting the data of adjacent sampling points, the change rate of the orbital parameters is calculated. The calculation method is to use the orbital parameter of the next sampling point to subtract the orbital parameter of the current sampling point, and then calculate the ratio of the obtained difference to the time difference between the two sampling points to obtain the change rate of each orbital parameter. By analyzing and calculating the change rate, the dynamic fluctuation characteristics of the orbital parameters can be identified. For example, by calculating the mean of the change rate of the orbital parameters, the average rate of each orbital parameter can be obtained. By calculating the change rate The difference between the maximum and minimum values ​​of the change rate can be used to obtain the change amplitude of each orbital parameter. By counting the number of rate changes (a threshold is defined, and when the difference between the next change rate and the current change rate is greater than this threshold, it is recorded as a fluctuation), the fluctuation frequency of each orbital parameter can be obtained. According to the calculated dynamic fluctuation characteristics (average rate, change amplitude, and fluctuation frequency), the average rate is calculated to be proportional to the maximum rate to obtain the rate stability. The rate stability is then weighted with the change amplitude and the fluctuation frequency to generate a dynamic fluctuation index, which indicates the complexity of the orbital parameter changes and provides a basis for selecting a suitable polynomial interpolation model to ensure the accuracy of the model selection. Subsequently, based on the dynamic fluctuation index, the preset The matched model is selected as the target polynomial interpolation model in the polynomial interpolation model. The preset polynomial interpolation model includes polynomials of different orders, such as second-order, third-order or higher-order polynomials. According to the size of the dynamic fluctuation index, an interpolation model suitable for describing the current data change characteristics is selected. For example, data with large fluctuations may require a higher-order model to ensure the fitting accuracy, while data with small fluctuations can use a low-order model to improve the calculation efficiency. After matching the target polynomial interpolation model, the ephemeris data set is classified according to the category to which the ephemeris data type previously determined belongs, and a specific first data type and a second data type are obtained. The first data type includes key data with high real-time and synchronization requirements, such as orbital parameters and time stamps. Note that the second data type includes auxiliary data with lower real-time requirements, such as environmental monitoring information; then, the target polynomial interpolation model is applied to the divided data sets for interpolation calculation, and the corresponding polynomial interpolation coefficients are generated for each type of data through interpolation processing, wherein the interpolation results of the first data type and the second data type generate the first polynomial interpolation coefficients and the second polynomial interpolation coefficients, respectively, which are used for subsequent data transmission and reconstruction; finally, the whole process realizes the dynamic change analysis of ephemeris data and unified polynomial interpolation processing, ensures the fitting accuracy of the data through the evaluation of dynamic fluctuation indicators and unified model matching, and optimizes the transmission efficiency and real-time performance through data classification and interpolation coefficient generation.

[0028] Furthermore, the present application provides matching the target polynomial interpolation model in a preset polynomial interpolation model based on the dynamic fluctuation index, including: Construct the preset polynomial interpolation model, the preset polynomial interpolation model includes multiple interpolation models corresponding to multiple interpolation orders, wherein the multiple interpolation models have optimal matching dynamic characteristic labels; among the multiple interpolation models, match the interpolation model with the optimal matching dynamic characteristic label that satisfies the dynamic fluctuation index to generate the target polynomial interpolation model.

[0029] Optionally, when constructing a preset polynomial interpolation model based on the Lagrangian polynomial, first determine the applicable polynomial order range based on the dynamic characteristics of the ephemeris data, for example, from the second to the fifth order Lagrangian polynomials, each model is expressed in a standard form, and can adapt to ephemeris data with different dynamic fluctuation characteristics. At the same time, select representative sample data from the historical ephemeris data, including orbital parameter change characteristics with high and low fluctuations, for subsequent fitting and testing; perform Lagrangian polynomial fitting on the sample data, and calculate the fitting error of the interpolation model of different orders point by point in combination with the mean square error (MSE) to quantify the fitting performance of the model. For each order of the model, determine its applicable dynamic fluctuation range under the condition that the error meets the preset threshold. For example, a low-order model is suitable for models with smaller fluctuations. Data, high-order models are suitable for data with large fluctuations; after the preset model is built, the dynamic fluctuation index is calculated according to the change rate analysis results of the ephemeris data during runtime. This index quantifies the change characteristics of the data. By traversing the preset Lagrangian polynomial model, the interpolation model applicable to the dynamic fluctuation index range is retrieved to ensure that the matched interpolation model can reflect the fluctuation characteristics of the data. When multiple models meet the conditions at the same time, the model with lower order and smaller fitting error is preferred to balance the fitting accuracy and calculation efficiency; the final model is the target Lagrangian polynomial interpolation model, which can provide the best fitting effect and calculation performance in the subsequent ephemeris data fitting processing. In this way, not only the dynamic matching of the model and data characteristics is achieved, but also the accuracy and efficiency of ephemeris data processing are ensured.

[0030] Furthermore, the present application provides a method for constructing the preset polynomial interpolation model, including: Based on Lagrange polynomials, the multiple interpolation models corresponding to the multiple interpolation orders are constructed; ephemeris data samples with successively increasing fluctuation indicators are collected, and interpolation tests are performed through the multiple interpolation models, the mean square error between the reconstructed ephemeris data and the ephemeris data samples is calculated, the fluctuation indicators corresponding to the samples of the multiple interpolation models when the mean square error meets a preset error threshold are determined, and the optimal matching dynamic characteristic mark is generated.

[0031] Optionally, multiple interpolation models are constructed based on Lagrange polynomials, each model corresponds to a different interpolation order (such as second order, third order, fourth order, fifth order, etc.), and the Lagrange polynomial form of each order is: ;in, is the nth-order Lagrange polynomial, n is the interpolation order, and are the time stamp and orbital parameter value of the ith data point, respectively. is the time mark of the jth data point in addition to the time mark of the i-th data point; then, sample data with different fluctuation characteristics are collected from the historical data of the ephemeris, and the fluctuation index of these samples gradually increases, which can cover the data range from stable changes to violent fluctuations. Each sample contains a time mark and an orbital parameter value, which can reflect the dynamic change characteristics of the data; then, each group of sample data collected is input into the Lagrangian polynomial model of different orders for interpolation calculation, and the fitting result generated by the interpolation model is compared with the original ephemeris data sample to calculate the mean square error MSE between the reconstructed data and the real data. For each interpolation model, when the mean square error of a group of sample data meets the preset error threshold, the order of the model and the corresponding sample are recorded. The fluctuation index is used as the optimal matching dynamic characteristic mark of the model. For example, when the second-order interpolation model meets the error threshold, the maximum fluctuation index of the sample data set is 0.3. At this time, the optimal matching dynamic characteristic mark of the second-order interpolation model is greater than 0 and less than or equal to 0.3. Similarly, the third-order interpolation model corresponds to greater than 0.3 and less than or equal to 0.6, the fourth-order interpolation model corresponds to greater than 0.6 and less than or equal to 0.8, and the fifth-order model corresponds to greater than 0.8. In this way, the fluctuation applicable range of each interpolation model when meeting the error requirements is determined, and these fluctuation indexes are recorded as the optimal matching dynamic characteristic marks of the model. These marks will be used for subsequent dynamic fluctuation index matching to ensure that each ephemeris data set can select the most suitable interpolation model for fitting processing.

[0032] The communication link status between the target satellite and the ground measurement and control station is obtained, and after adjusting the parameters of the transmission protocol, the first polynomial interpolation coefficient and the second polynomial interpolation coefficient are transmitted to the ground measurement and control station for reconstruction.

[0033] In this embodiment, it is first necessary to evaluate the state of the communication link between the target satellite and the ground control station. By detecting the key parameters of the communication link (such as the signal-to-noise ratio), the current state of the link is comprehensively analyzed to obtain the communication link state. According to the communication link state, the parameters of the transmission protocol are dynamically adjusted. These parameters include the transmission rate, error correction coding method, etc. For example, when the link quality is good, the transmission rate can be increased and the redundant coding can be reduced to improve the data throughput. When the link quality is poor, the transmission rate can be reduced and the error correction coding strength can be increased to ensure the reliability of the data. After completing the adjustment of the transmission protocol, the first polynomial interpolation system is used. The first polynomial interpolation coefficient (high priority data) and the second polynomial interpolation coefficient (low priority data) are sent to the ground tracking and control station through the optimized communication link. After the data arrives at the ground, the ephemeris data is reconstructed according to the transmitted polynomial interpolation coefficients using the standard polynomial form corresponding to the matching polynomial interpolation model, that is, these coefficients are substituted and calculated, so as to restore the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to complete orbital parameters, time stamps and other information. This process ensures the timely transmission of high-priority data and the reliable transmission of low-priority data through dynamic adjustment of the link status, while improving the efficiency and reliability of the entire data transmission process.

[0034] Furthermore, the present application provides a method for obtaining the communication link status between the target satellite and the ground measurement and control station and performing parameter adjustment of the transmission protocol, including: A fusion analysis of link quality and signal-to-noise ratio degradation is performed on the communication link between the target satellite and the ground measurement and control station to generate the communication link status; based on the communication link status, the transmission rate and error correction coding of the communication link are adjusted to complete parameter control of the transmission protocol.

[0035] Optionally, through the communication link between the ground tracking and control station and the target satellite, key performance indicators of the communication link are collected in real time, including but not limited to signal-to-noise ratio, bit error rate, delay, and packet loss rate. These key performance indicators are normalized and the normalized results are weighted to quantify the link quality score of the communication link, which represents the overall health status of the communication link. The difference between the signal-to-noise ratio collected last time and the current signal-to-noise ratio is then calculated, and the calculated difference is compared with the signal-to-noise ratio collected last time to obtain the signal-to-noise ratio reduction degree. Subsequently, the communication link status is fused and analyzed according to the link quality score and the signal-to-noise ratio reduction degree, that is, the link quality score and the signal-to-noise ratio reduction degree are weightedly fused and then compared with the corresponding range to determine the status of the current communication link. For example, the status of a communication link with a link status score greater than or equal to 0.8 is a first-level communication link. At this time, the link The link state is stable, the signal-to-noise ratio decreases slightly, and the overall quality is good. The state of the communication link with a link state score greater than or equal to 0.5 and less than 0.8 is a secondary communication link. At this time, the link state is medium, and there are certain signal degradation or quality problems. The state of the communication link with a link state score less than 0.5 is a tertiary communication link. At this time, the link state is unstable, the signal-to-noise ratio deteriorates significantly, and the bit error rate is high. Afterwards, according to the communication link state, the key parameters of the transmission protocol are dynamically adjusted through the link parameter adjustment module, such as transmission rate, error correction coding, etc., to optimize data transmission performance and reliability. After the adjustment is completed, the adjusted parameter values ​​are recorded and applied to subsequent data transmission processes, and the link state is continuously monitored for dynamic optimization. The regulated communication protocol ensures that the transmission efficiency is improved when the link is good, and the transmission reliability is enhanced when the link is poor, thereby achieving stable and reliable transmission of ephemeris data.

[0036] Further, the present application provides adjusting the transmission rate and error correction coding of the communication link based on the communication link state, including: A link parameter adjustment module is configured, wherein the link parameter adjustment module is connected to a preset adjustment database, wherein the preset adjustment database includes multiple adjustment modes and corresponding multiple adjustment mode trigger conditions; the communication link state is input into the link parameter adjustment module, traversal matching is performed among the multiple adjustment mode trigger conditions to generate a matching adjustment mode; and the transmission rate and error correction coding are adjusted with the matching adjustment mode.

[0037] Optionally, when configuring the link parameter adjustment module, it is first necessary to connect it to a preset adjustment database, which stores a variety of adjustment modes and their corresponding trigger conditions (such as link status score range or communication link status level). Each mode is designed and named as a clear operation plan according to the different characteristics of the link status. For example, the efficient transmission mode is suitable for situations where the link status is excellent. When the signal-to-noise ratio is high and the bit error rate is low, this mode will significantly increase the transmission rate and use low-redundancy coding (such as LDPC coding) to maximize data transmission efficiency. The balanced transmission mode is suitable for situations where the link status is medium. When the signal-to-noise ratio decreases slightly but the link quality is acceptable, this mode appropriately reduces the transmission rate and uses medium-redundancy error correction coding (such as medium-rate convolutional code) to achieve a balance between transmission efficiency and reliability. The robust transmission mode is suitable for situations where the link status is poor. When the signal-to-noise ratio is low and the bit error rate is high, this mode significantly reduces the transmission rate and uses high-redundancy strong error correction coding (such as BCH coding or efficient convolutional coding). To enhance data reliability and reduce bit errors; then, the calculated link state score or communication link state level is input into the link parameter adjustment module, which will automatically traverse the trigger conditions of all adjustment modes in the preset adjustment database and match the adjustment mode corresponding to the current link state. For example, when the link state score is greater than or equal to 0.8 or the communication link state level is a first-level communication link, the efficient transmission mode is matched. At this time, the transmission rate is automatically adjusted to a higher level and a low-redundancy LDPC coding scheme is adopted; after the matching is completed, the parameters of the transmission protocol are dynamically adjusted according to the selected adjustment mode, which includes optimizing the transmission rate to make full use of the bandwidth under excellent link conditions, avoiding data loss when the link is poor, switching the error correction coding strategy from low redundancy to high redundancy, adapting to the transmission requirements under different link conditions, and optimizing the data packetization strategy, using large data packets to reduce header overhead when the link is good, and using small data packets to reduce the impact of packet loss when the link is poor. Through this series of dynamic adjustments, it is ensured that the link can maintain the efficiency and reliability of data transmission under various conditions, and realize the adaptive optimization of the transmission protocol and the maximum utilization of resources.

[0038] In summary, the embodiments of the present application have at least the following technical effects: The embodiment of the present application achieves efficient collection and classification of ephemeris data by acquiring type information and orbital altitude information of the target satellite, combined with dynamic characteristics analysis of the orbital altitude; based on the importance of the satellite mission, the ephemeris data is prioritized for synchronization, and is divided into a first data type with a higher priority and a second data type with a lower priority; by analyzing the change rate of adjacent sampling points of the ephemeris data, the optimal Lagrangian polynomial interpolation model is matched using a dynamic fluctuation index, and polynomial interpolation coefficients of the data are generated respectively to achieve high-precision compression and reconstruction; in addition, by acquiring the communication link status between the target satellite and the ground measurement and control station in real time, the parameters of the transmission protocol, including the transmission rate and the error correction coding strategy, are dynamically adjusted based on a fusion analysis of the signal-to-noise ratio and the link quality to optimize the data transmission performance; finally, in the case of changing link conditions, the reliability, real-time nature and efficiency of ephemeris data transmission are ensured by configuring a link parameter adjustment module and matching the adjustment mode. These technical effects jointly solve the technical problems of insufficient real-time performance of ephemeris information and inability of data reliability to meet dynamic application needs due to differences in satellite orbit altitudes and types, realize dynamic collection and hierarchical interpolation processing of ephemeris information based on orbit altitude and satellite type, optimize communication link parameter configuration, improve the efficiency and reliability of ephemeris information transmission, and ensure the real-time and accurate transmission of ephemeris information in low-orbit satellite communications.

[0039] Embodiment 2 is based on the same inventive concept as the method for optimizing transmission of ephemeris information in low-orbit satellite communication in the above embodiment. Figure 2 As shown, the present application provides an optimized transmission system for ephemeris information in low-orbit satellite communications, the system comprising: an information acquisition unit 11: acquiring satellite type information and orbital height information of a target satellite; an ephemeris data acquisition unit 12: performing an update dynamic characteristic analysis of ephemeris data based on the orbital height information, and performing ephemeris data acquisition based on the update dynamic characteristics to generate an ephemeris data set; a synchronization transmission discrimination unit 13: performing synchronization transmission discrimination of multiple ephemeris data types based on the satellite type information, generating a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type; a data interpolation unit 14: performing a change rate analysis of adjacent sampling points for the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient; a coefficient reconstruction unit 15: acquiring the communication link status between the target satellite and the ground measurement and control station, and after adjusting the parameters of the transmission protocol, transmitting the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground measurement and control station for reconstruction.

[0040] Furthermore, the synchronous transmission determination unit 13 is also used to execute the following method: Determine a satellite mission based on the satellite type information; perform application priority analysis on multiple ephemeris data types based on the satellite mission to generate a priority analysis result; and determine a data type with a priority greater than or equal to a preset priority as the first data type, and determine a data type with a priority less than the preset priority as the second data type based on the priority analysis result.

[0041] Furthermore, the data interpolation unit 14 is also used to perform the following method: The ephemeris data set is traversed to record the time stamp and orbital parameters of each sampling point; based on the time stamp, the orbital parameter change rate of adjacent sampling points is calculated, and the dynamic fluctuation index is identified according to the change rate; based on the dynamic fluctuation index, the target polynomial interpolation model is matched in a preset polynomial interpolation model; the ephemeris data set is divided according to the first data type and the second data type to generate the first type of data and the second type of data; the first type of data and the second type of data are interpolated respectively by using the target polynomial interpolation model to generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient.

[0042] Furthermore, the data interpolation unit 14 is also used to perform the following method: Construct the preset polynomial interpolation model, the preset polynomial interpolation model includes multiple interpolation models corresponding to multiple interpolation orders, wherein the multiple interpolation models have optimal matching dynamic characteristic labels; among the multiple interpolation models, match the interpolation model with the optimal matching dynamic characteristic label that satisfies the dynamic fluctuation index to generate the target polynomial interpolation model.

[0043] Furthermore, the data interpolation unit 14 is also used to perform the following method: Based on Lagrange polynomials, the multiple interpolation models corresponding to the multiple interpolation orders are constructed; ephemeris data samples with successively increasing fluctuation indicators are collected, and interpolation tests are performed through the multiple interpolation models, the mean square error between the reconstructed ephemeris data and the ephemeris data samples is calculated, the fluctuation indicators corresponding to the samples of the multiple interpolation models when the mean square error meets a preset error threshold are determined, and the optimal matching dynamic characteristic mark is generated.

[0044] Furthermore, the coefficient reconstruction unit 15 is also used to perform the following method: A fusion analysis of link quality and signal-to-noise ratio degradation is performed on the communication link between the target satellite and the ground measurement and control station to generate the communication link status; based on the communication link status, the transmission rate and error correction coding of the communication link are adjusted to complete parameter control of the transmission protocol.

[0045] Furthermore, the coefficient reconstruction unit 15 is also used to perform the following method: A link parameter adjustment module is configured, wherein the link parameter adjustment module is connected to a preset adjustment database, wherein the preset adjustment database includes multiple adjustment modes and corresponding multiple adjustment mode trigger conditions; the communication link state is input into the link parameter adjustment module, traversal matching is performed among the multiple adjustment mode trigger conditions to generate a matching adjustment mode; and the transmission rate and error correction coding are adjusted with the matching adjustment mode.

[0046] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0047] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0048] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A method for optimizing transmission of ephemeris information in low-orbit satellite communications, characterized in that: include: Obtain satellite type information and orbital altitude information of the target satellite; Performing an update dynamic characteristic analysis of the ephemeris data based on the orbital altitude information, and collecting the ephemeris data based on the update dynamic characteristic to generate an ephemeris data set; Based on the satellite type information, synchronous transmission judgment of multiple ephemeris data types is performed to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type; Performing a change rate analysis of adjacent sampling points on the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient; The communication link status between the target satellite and the ground measurement and control station is obtained, and after adjusting the parameters of the transmission protocol, the first polynomial interpolation coefficient and the second polynomial interpolation coefficient are transmitted to the ground measurement and control station for reconstruction.

2. The method for optimizing transmission of ephemeris information in low-orbit satellite communication according to claim 1, characterized in that: The method includes: performing a change rate analysis of adjacent sampling points on the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient, including: Traversing the ephemeris data set, recording the time stamp and orbital parameters of each sampling point; Based on the time stamp, calculating the change rate of the orbital parameters of adjacent sampling points, and identifying the dynamic fluctuation index according to the change rate; Matching the target polynomial interpolation model in a preset polynomial interpolation model based on the dynamic volatility index; Dividing the ephemeris data set according to the first data type and the second data type to generate first type data and second type data; The first type of data and the second type of data are interpolated respectively using the target polynomial interpolation model to generate the first polynomial interpolation coefficients and the second polynomial interpolation coefficients.

3. The method for optimizing transmission of ephemeris information in low-orbit satellite communication according to claim 2, characterized in that: Matching the target polynomial interpolation model in a preset polynomial interpolation model based on the dynamic fluctuation index includes: Constructing the preset polynomial interpolation model, wherein the preset polynomial interpolation model includes a plurality of interpolation models corresponding to a plurality of interpolation orders, wherein the plurality of interpolation models have optimal matching dynamic characteristic marks; Among the multiple interpolation models, the interpolation model whose best matching dynamic characteristic mark satisfies the dynamic fluctuation index is matched to generate the target polynomial interpolation model.

4. The method for optimizing transmission of ephemeris information in low-orbit satellite communication according to claim 3, characterized in that: Constructing the preset polynomial interpolation model includes: Constructing the plurality of interpolation models corresponding to the plurality of interpolation orders based on Lagrange polynomials; Collect ephemeris data samples with successively increasing fluctuation indicators, perform interpolation tests through the multiple interpolation models, calculate the mean square error between the reconstructed ephemeris data and the ephemeris data samples, determine the fluctuation indicators corresponding to the samples of the multiple interpolation models when the mean square error meets a preset error threshold, and generate the optimal matching dynamic characteristic mark.

5. The method for optimizing transmission of ephemeris information in low-orbit satellite communication according to claim 1, characterized in that: Based on the satellite type information, synchronous transmission judgment of multiple ephemeris data types is performed to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type, including: determining a satellite mission based on the satellite type information; Performing application priority analysis on multiple ephemeris data types based on the satellite mission to generate a priority analysis result; According to the priority analysis result, a data type having a priority greater than or equal to a preset priority is determined as the first data type, and a data type having a priority less than the preset priority is determined as the second data type.

6. The method for optimizing transmission of ephemeris information in low-orbit satellite communication according to claim 1, characterized in that: Acquiring the communication link status between the target satellite and the ground control station and adjusting the parameters of the transmission protocol include: Performing a fusion analysis of link quality and signal-to-noise ratio degradation on the communication link between the target satellite and the ground tracking and control station to generate the communication link status; The transmission rate and error correction coding of the communication link are adjusted based on the communication link status to complete the parameter control of the transmission protocol.

7. The method for optimizing transmission of ephemeris information in low-orbit satellite communication according to claim 6, characterized in that: Adjusting the transmission rate and error correction coding of the communication link based on the communication link state includes: Configure a link parameter adjustment module, wherein the link parameter adjustment module is connected to a preset adjustment database, and the preset adjustment database includes multiple adjustment modes and corresponding multiple adjustment mode trigger conditions; Inputting the communication link state into the link parameter adjustment module, performing traversal matching on the multiple adjustment mode triggering conditions, and generating a matching adjustment mode; The transmission rate and the error correction coding are adjusted in the matching adjustment mode.

8. An optimized transmission system for ephemeris information in low-orbit satellite communications, characterized in that: The steps for implementing the method for optimizing transmission of ephemeris information in low-orbit satellite communications as described in any one of claims 1 to 7 include: Information acquisition unit: obtains satellite type information and orbital height information of the target satellite; An ephemeris data acquisition unit: performs an update dynamic characteristic analysis of the ephemeris data based on the orbital altitude information, and performs ephemeris data acquisition based on the update dynamic characteristic to generate an ephemeris data set; A synchronous transmission determination unit: based on the satellite type information, performs synchronous transmission determination of multiple ephemeris data types to generate a first data type and a second data type, wherein the synchronization priority of the first data type is higher than that of the second data type; A data interpolation unit: performing a change rate analysis of adjacent sampling points on the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and interpolating the ephemeris data set after data division according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient; Coefficient reconstruction unit: obtains the communication link status between the target satellite and the ground measurement and control station, and after adjusting the parameters of the transmission protocol, transmits the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground measurement and control station for reconstruction.

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