Optimized Transmission Method and System for Ephemeris Information in Low Earth Orbit Satellite Communication

Abstract

The present application 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 includes: obtaining satellite type information and orbital altitude information of a target satellite; analyzing the dynamic characteristics of ephemeris data update based on the orbital altitude information and collecting ephemeris data to generate a data set; discriminating the synchronicity of ephemeris data types based on the satellite type information to generate a first data type and a second data type; analyzing the change rate of adjacent sampling points of the ephemeris data set, matching a polynomial interpolation model according to the result, and performing interpolation after dividing by data type to generate first and second polynomial interpolation coefficients; obtaining the communication link state between the satellite and the ground measurement and control station, adjusting the transmission protocol parameters, and then transmitting the polynomial interpolation coefficients to the ground measurement and control station for reconstruction, so as to solve the technical problems of insufficient real-time performance of ephemeris information and inability of data reliability to meet the dynamic application requirements due to differences in satellite orbital altitude and type.

Description

Technical Field

[0001] This application relates to the technical field of data transmission, and specifically to an optimized transmission method and system for ephemeris information in low-earth orbit satellite communication. Background Art

[0002] Due to their low orbital altitude, wide coverage, short communication delay and other characteristics, low-earth orbit satellites have become an important part of modern communication systems. However, during the process of low-earth orbit satellite communication, as the key data to ensure communication accuracy and reliability, the transmission process of ephemeris information faces many challenges. 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 the condition of limited communication bandwidth, it is easy to cause transmission delay and data packet loss problems. In addition, due to the diverse orbital altitudes and mission types of low-earth orbit satellites, there are significant differences in the dynamic update rate of their ephemeris information. A single transmission method is difficult to meet the requirements of different satellite types and orbital characteristics, thus affecting the timeliness and reliability of ephemeris data. On the other hand, in the communication link of low-earth orbit satellites, the communication environment between the ground measurement 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 state and are 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 classify and process ephemeris information according to satellite missions and data characteristics and optimize the transmission order is also a problem that the existing technology cannot effectively solve. Summary of the Invention

[0003] This application provides an optimized transmission method and system for ephemeris information in low-earth orbit satellite communication, aiming to solve the technical problems of insufficient timeliness of ephemeris information and inability to meet the dynamic application requirements of data reliability due to differences in satellite orbital altitude and type, and to achieve dynamic acquisition and hierarchical interpolation processing of ephemeris information based on orbital altitude and satellite type, optimize the configuration of communication link parameters, improve the efficiency and reliability of ephemeris information transmission, and ensure the real-time and accurate transmission of ephemeris information in low-earth orbit satellite communication.

[0004] In view of the above problems, this application provides an optimized transmission method and system for ephemeris information in low-earth orbit satellite communication.

[0005] In the first aspect disclosed in this application, an optimized transmission method for ephemeris information in low-earth orbit satellite communication is provided. The method includes: obtaining the satellite type information and orbital altitude information of a target satellite; analyzing the update dynamic characteristics of ephemeris data based on the orbital altitude information, and collecting ephemeris data based on the update dynamic characteristics to generate an ephemeris data set; determining 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, where the synchronous priority of the first data type is higher than that of the second data type; analyzing the change rate of adjacent sampling points for the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and performing interpolation on 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; obtaining the communication link state 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.

[0006] In another aspect disclosed in this application, an optimized transmission system for ephemeris information in low-earth orbit satellite communication is provided. The system includes: an information acquisition unit: obtaining the satellite type information and orbital altitude information of a target satellite; an ephemeris data collection unit: analyzing the update dynamic characteristics of ephemeris data based on the orbital altitude information, and collecting ephemeris data based on the update dynamic characteristics to generate an ephemeris data set; a synchronous transmission determination unit: determining 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, where the synchronous priority of the first data type is higher than that of the second data type; a data interpolation unit: analyzing the change rate of adjacent sampling points for the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and performing interpolation on 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: obtaining the communication link state 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:

[0008] The above-mentioned optimized transmission method for ephemeris information in low-earth orbit satellite communication obtains the type and orbital altitude information of the target satellite, analyzes the dynamic update characteristics of ephemeris data based on the orbital altitude, and collects corresponding data to generate an ephemeris data set. Subsequently, it discriminates the transmission synchronization of ephemeris data according to the satellite type, dividing it into a first data type with a higher synchronization priority and a second data type with a lower priority. Then, it analyzes the change rate of adjacent sampling points in the ephemeris data set, selects an appropriate polynomial interpolation model based on the analysis results, and divides and interpolates the ephemeris data for different data types to generate corresponding polynomial interpolation coefficients. Finally, according to the communication link status between the satellite and the ground control station, it dynamically adjusts the parameters of the transmission protocol and transmits the generated polynomial interpolation coefficients to the ground control station for reconstructing ephemeris data. This method realizes the efficient compression and transmission of ephemeris data, improving communication efficiency and reliability.

[0009] The above description is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of this application more obvious and understandable, the following specifically illustrates the specific embodiments of this application. Brief Description of the Drawings

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0011] Figure 1 It is a schematic flowchart of the optimized transmission method for ephemeris information in low-earth orbit satellite communication in an embodiment.

[0012] Figure 2 It is an architecture diagram of the optimized transmission system for ephemeris information in low-earth orbit satellite communication in an embodiment.

[0013] Description of the reference numerals: Information acquisition unit 11, ephemeris data acquisition unit 12, synchronization transmission discrimination unit 13, data interpolation unit 14, coefficient reconstruction unit 15. Detailed Embodiments

[0014] Embodiments of the present application provide an optimized transmission method and system for ephemeris information in low-earth orbit satellite communication, which solve the technical problems of insufficient real-time performance of ephemeris information and inability of data reliability to meet the requirements of dynamic applications caused by differences in satellite orbital altitude and type. It realizes dynamic acquisition and hierarchical interpolation processing of ephemeris information based on orbital altitude and satellite type, optimizes the configuration of communication link parameters, improves the efficiency and reliability of ephemeris information transmission, and ensures the real-time and accurate transmission of ephemeris information in low-earth orbit satellite communication.

[0015] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0016] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules not clearly listed or inherent to these processes, methods, products or devices.

[0017] Embodiment 1, as Figure 1 shown, the present application provides an optimized transmission method for ephemeris information in low-earth orbit satellite communication, and the method includes:

[0018] Obtain the satellite type information and orbital altitude information of the target satellite.

[0019] In the embodiments of the present application, first, relevant information of the target satellite is obtained from the satellite management terminal, including the type of the satellite (such as remote sensing satellite, communication satellite, navigation satellite, etc.) and its operating orbital altitude. These information can be queried through satellite orbit design parameters, satellite mission planning files, etc. in the terminal database. The satellite type information is mainly used to judge the characteristics of the tasks performed by the satellite. For example, whether it has high requirements for the real-time performance of data transmission or whether it needs to prioritize the processing of certain specific data types, while the orbital altitude information reflects the operating position and dynamic characteristics of the satellite. For example, the changes in the perigee and apogee may affect the frequency of ephemeris data update and transmission requirements. The acquisition of these basic information lays a data foundation for the subsequent analysis of the dynamic update characteristics of ephemeris data and transmission optimization.

[0020] Analyze the dynamic update characteristics of ephemeris data based on the orbital altitude information, and collect ephemeris data based on the update dynamic characteristics to generate an ephemeris data set.

[0021] In one embodiment, based on the orbital altitude information of the target satellite (such as perigee altitude and apogee altitude) and the orbital category (such as circular orbit, elliptical orbit, etc.), the satellite orbit is preliminarily classified. The orbital altitude reflects the operating speed and orbital change characteristics of the satellite. Low-orbit satellites usually have a high operating speed and frequent orbital changes, while high-orbit satellites have a low operating speed and small changes; based on the orbital altitude information, directly evaluate the change characteristics of the main parameters related to the orbit. For example, the change range of the orbital altitude, the length of the orbital period, the average motion rate, etc. during the on-orbit operation of the satellite (which can be based on orbital mechanics formulas such as Kepler's third law, etc.). Through the analysis of these parameters, the speed and law of orbital change can be obtained to evaluate the impact of its orbital change on the update frequency and dynamic characteristics of the ephemeris data. For example, for satellites with a lower orbital altitude, their operating speed is faster and the change of orbital parameters is more frequent, so the ephemeris data requires a higher update frequency. For satellites with a higher orbit, the change of orbital parameters is slower 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, determine the acquisition parameters of the ephemeris data, including sampling interval, data capture accuracy, acquisition period, etc.; then, according to the acquisition parameters determined by updating the dynamic characteristics, start the acquisition process of the ephemeris data, record the orbital parameters of the satellite in real time (such as position, speed, time stamp, etc.), and organize these data according to the time sequence and parameter category to generate a complete ephemeris data set. This data set provides a basis for subsequent data processing (such as classification, interpolation, and transmission optimization), and can reflect the dynamic change law of the satellite orbit characteristics, ensuring that the subsequent steps can be operated based on accurate and complete data.

[0022] Based on the satellite type information, perform the synchronization transmission discrimination of multiple ephemeris data types to generate a first data type and a second data type, where the synchronization priority of the first data type is higher than that of the second data type.

[0023] In this embodiment, based on the type information of the target satellite (such as navigation satellite, remote sensing satellite, communication satellite, etc.), the synchronization and real-time requirements of different types of ephemeris data for mission requirements are analyzed. For example, the ephemeris information of navigation satellites plays a crucial role in precise positioning. Therefore, it is necessary to prioritize 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 requirements for the timeliness of mission execution and can be transmitted with appropriate delays. Based on the above analysis, the types of ephemeris data are classified to generate a first data type and a second data type. Among them, the first data type mainly includes ephemeris information and high-priority data (such as satellite attitude data, etc.) that are crucial for mission execution. These data need to be transmitted in real time to ensure the normal execution of satellite missions. The second data type includes auxiliary or non-critical data with lower priorities (such as detailed environmental monitoring data or some telemetry information). These data can be sent with delays when the transmission conditions permit. Finally, through this classification method, a transmission mechanism for data priorities is established to ensure that critical ephemeris information is preferentially transmitted in the communication link, while non-critical data can be sent later, thereby optimizing data transmission in limited communication bandwidth, improving the overall communication efficiency and the reliability of mission execution.

[0024] Furthermore, the present application provides a discriminant for synchronous transmission of multiple types of ephemeris data based on the satellite type information, generating a first data type and a second data type, where the synchronization priority of the first data type is higher than that of the second data type, including:

[0025] Determine the satellite mission based on the satellite type information; perform an application priority analysis of multiple types of ephemeris data based on the satellite mission to generate a priority analysis result; according to the priority analysis result, determine the data type with a priority greater than or equal to the preset priority as the first data type, and determine the data type with a priority less than the preset priority as the second data type.

[0026] Preferably, according to the satellite type information (such as navigation satellites, remote sensing satellites, communication satellites, etc.), combined with the mission requirement document (from the satellite management terminal), clarify the main tasks performed by the satellite. For example, the main task of a navigation satellite is to provide high-precision positioning and timing services, the task of a remote sensing satellite may be to conduct surface monitoring or resource exploration, and the task of a communication satellite focuses on signal relaying or data transmission. On this basis, extract the core data requirements directly related to the satellite mission, such as timing information, data transfer volume, etc.; then, extract the minimum real-time standard set for all data types by the satellite mission from the timing information, which reflects the overall requirement of the satellite mission for time sensitivity, and then extract the maximum tolerable delay set for a specific data type from the timing information, which represents the upper limit of the time delay acceptable during the transmission of this data type. By calculating the ratio of the minimum real-time standard to the time delay upper limit of the current data type, obtain the real-time factor for each data type. This real-time factor quantifies the real-time requirement of the ephemeris data type for mission execution, and the closer the value is to 1, the higher the real-time requirement; extract the single transmission data volume of the current data type and the maximum data volume supported by the current communication link from the data transfer volume, and by combining these data with the transmission cost factor formula Combine to calculate the transmission cost factor for each data type. This transmission cost factor represents the transmission cost of the ephemeris data type, and the closer the value is to 1, the higher the transmission cost. Among them, is the transmission cost factor, is the single transmission data volume of the current data type, is the maximum data volume supported by the current communication link, k is the weight of the link quality factor, ranging from 0 to 1, used to balance the influence 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, which can be determined based on the signal-to-noise ratio; then, perform a weighted calculation on the real-time factor and the transmission cost factor to obtain the priority value for each ephemeris data type, and add these priority values to the priority analysis result in sequence. By comparing the size of each priority value in the priority analysis result with the preset priority, classify the ephemeris data types with priority values greater than or equal to the preset priority as the first data type. For example, for a navigation satellite, orbital parameters and time stamps may be classified as the first data type because these data have the highest real-time requirements. Classify the ephemeris data types with priority values lower than the preset priority as the second data type. For example, the detailed environmental monitoring data or lower-precision status information of a navigation satellite 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 at the same time.

[0027] Perform a rate-of-change analysis on adjacent sampling points of the ephemeris data set, match a target polynomial interpolation model according to the analysis results, and perform interpolation on the ephemeris data set after data partitioning according to the first data type and the second data type to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient.

[0028] In this embodiment, by traversing the ephemeris data set, key parameters (such as orbital position, velocity, etc.) and their time stamps of each sampling point are extracted, and the rate of change between adjacent sampling points is calculated, so as to obtain characteristics such as the change amplitude and fluctuation frequency. These analysis results are used to determine the dynamic characteristics of the ephemeris data change and provide a basis for the subsequent selection of the polynomial interpolation model; subsequently, according to the rate-of-change analysis results, a suitable polynomial interpolation model is matched. Data with large dynamic changes requires a higher-order polynomial to ensure fitting accuracy, while data with stable changes selects a lower-order polynomial model to achieve efficient utilization of computing resources; after the polynomial model is matched, the ephemeris data set is classified according to the first data type and the second data type. The first data type includes key data with high priority and strict synchronization requirements, such as orbital parameters and time stamps, and the second data type includes auxiliary data with lower priority and lower real-time requirements, such as environmental monitoring information. The classified data is fitted by the matched polynomial model to generate a first polynomial interpolation coefficient and a second polynomial interpolation coefficient respectively. These coefficients characterize the change characteristics of the original data in a highly compressed form. During 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 reliable execution of the task, while the interpolation coefficient corresponding to the low-priority data, that is, the second polynomial interpolation coefficient, can be sent later when the link conditions permit, thereby optimizing the communication bandwidth utilization and improving the transmission efficiency.

[0029] Furthermore, the present application provides a method for performing a rate-of-change analysis on adjacent sampling points of the ephemeris data set, matching a target polynomial interpolation model according to the analysis results, and performing interpolation on the ephemeris data set after data partitioning 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:

[0030] Traverse the ephemeris data set, record the time stamps and orbital parameters of each sampling point; based on the time stamps, calculate the change rate of the orbital parameters between adjacent sampling points, and identify the dynamic fluctuation index according to the change rate; match the target polynomial interpolation model in the preset polynomial interpolation model based on the dynamic fluctuation index; partition the ephemeris data set according to the first data type and the second data type to generate the first type of data and the second type of data; interpolate the first type of data and the second type of data respectively with the target polynomial interpolation model to generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient.

[0031] Preferably, after obtaining the ephemeris data set, traverse the ephemeris data set, and record the time mark of each sampling point and the corresponding orbit parameters (such as position, velocity, attitude, etc.) one by one. These data are used to analyze the variation law of the orbit parameters with time. By extracting the data of adjacent sampling points, calculate the variation rate of the orbit parameters. The calculation method is to subtract the orbit parameters of the current sampling point from the orbit parameters of the subsequent sampling point, and then calculate the ratio of the obtained difference to the time difference between the two sampling points to obtain the variation rate of each orbit parameter. Through the analysis and calculation of the variation rate, the dynamic fluctuation characteristics of the orbit parameters can be identified. For example, by calculating the mean value of the variation rate of the orbit parameters, the average rate of each orbit parameter can be obtained. By calculating the difference between the maximum value and the minimum value of the variation rate, the variation amplitude of each orbit parameter can be obtained. By counting the number of times of rate change (defining a threshold, and recording it as a fluctuation when the difference between the subsequent variation rate and the current variation rate is greater than this threshold), the fluctuation frequency of each orbit parameter can be obtained; According to the calculated dynamic fluctuation characteristics (average rate, variation amplitude, fluctuation frequency), calculate the ratio of the average rate to the maximum rate to obtain the rate smoothness, and then perform weighted calculation on the rate smoothness, variation amplitude, and fluctuation frequency to generate a dynamic fluctuation index, indicating the complexity of the change of the orbit parameters, providing a basis for selecting a suitable polynomial interpolation model to ensure the accuracy of model selection; Subsequently, based on the dynamic fluctuation index, select a matching model from the preset polynomial interpolation models as the target polynomial interpolation model. The preset polynomial interpolation models include polynomials of different orders, such as second-order, third-order or higher-order polynomials. According to the size of the dynamic fluctuation index, select an interpolation model suitable for describing the current data change characteristics. 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, classify the ephemeris data set according to the category to which the previously determined ephemeris data type belongs, and obtain specific first data type and second data type. The first data type includes key data with high requirements for real-time and synchronization, such as orbit parameters and time marks, and the second data type includes auxiliary data with low requirements for real-time, such as environmental monitoring information; Then, for the divided data sets, apply the target polynomial interpolation model to perform interpolation calculations respectively. Through interpolation processing, corresponding polynomial interpolation coefficients are generated for each type of data. Among them, the interpolation results of the first data type and the second data type generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient respectively. These coefficients are used for subsequent data transmission and reconstruction; Finally, the whole process realizes the dynamic change analysis and unified polynomial interpolation processing of the ephemeris data. Through the evaluation of the dynamic fluctuation index and unified model matching, the fitting accuracy of the data is ensured, and at the same time, the transmission efficiency and real-time performance are optimized through data classification and interpolation coefficient generation.

[0032] Further, the present application provides for matching the target polynomial interpolation model in a preset polynomial interpolation model based on the dynamic fluctuation index, including:

[0033] Construct the preset polynomial interpolation model, which includes multiple interpolation models corresponding to multiple interpolation orders. Among them, the multiple interpolation models have optimal matching dynamic characteristic marks; in the multiple interpolation models, match the interpolation model whose optimal matching dynamic characteristic mark meets the dynamic fluctuation index to generate the target polynomial interpolation model.

[0034] Optionally, when constructing the preset polynomial interpolation model according to the Lagrange polynomial, first determine the applicable polynomial order range according to the dynamic characteristics of the ephemeris data. For example, for Lagrange polynomials from the second order to the fifth order, each model is represented 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 data of the ephemeris, including the change characteristics of high-fluctuation and low-fluctuation orbit parameters, for subsequent fitting and testing; through Lagrange polynomial fitting of the sample data, calculate the fitting error of the interpolation models at different orders point by point in combination with the mean square error (MSE) to quantify the fitting performance of the model. For each order model, under the condition that the error meets the preset threshold, determine its applicable dynamic fluctuation range. For example, low-order models are applicable to data with small fluctuations, and high-order models are applicable to data with large fluctuations; after the preset model is constructed, calculate the dynamic fluctuation index according to the analysis result of the change rate of the ephemeris data during operation. This index quantifies the change characteristics of the data. By traversing the preset Lagrange polynomial models, retrieve the interpolation model within the applicable dynamic fluctuation index range 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, preferentially select the model with a lower order and a smaller fitting error to balance the fitting accuracy and calculation efficiency; the finally determined model is the target Lagrange polynomial interpolation model, which can provide the best fitting effect and calculation performance in the subsequent fitting process of the ephemeris data. In this way, not only the dynamic matching of the model and data characteristics is realized, but also the accuracy and efficiency of the ephemeris data processing are ensured.

[0035] Further, the present application provides for constructing the preset polynomial interpolation model, including:

[0036] Construct the multiple interpolation models corresponding to the multiple interpolation orders based on the Lagrange polynomial; collect ephemeris data samples with gradually increasing fluctuation indexes, and perform interpolation tests through the multiple interpolation models. Calculate the mean square error between the reconstructed ephemeris data and the ephemeris data samples, and determine the fluctuation indexes corresponding to the samples when the mean square error of the multiple interpolation models meets the preset error threshold to generate the optimal matching dynamic characteristic marks.

[0037] Optionally, multiple interpolation models are constructed based on Lagrange polynomials, and each model corresponds to a different interpolation order (such as second order, third order, fourth order, fifth order, etc.). The form of the Lagrange polynomial of each order is: ; where is the Lagrange polynomial of order n, and n is the interpolation order. and are respectively the time mark and the orbital parameter value of the i-th data point. is the time mark of the j-th data point except for the time mark of the i-th data point; Subsequently, sample data with different fluctuation characteristics are collected from the historical data of the ephemeris. The fluctuation indexes of these samples gradually increase, covering the data range from stable change to violent fluctuation. Each sample contains a time mark and an orbital parameter value, which can reflect the dynamic change characteristics of the data; Then, each set of collected sample data is input into the Lagrange polynomial models of different orders for interpolation calculation. The fitting results generated by the interpolation models are compared with the original ephemeris data samples, and the mean square error MSE between the reconstructed data and the real data is calculated. For each interpolation model, when the mean square error of a certain set of sample data meets the preset error threshold, record the order of the model and the fluctuation index of the corresponding sample, and use it 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 this set of sample data 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 requirement is determined, and these fluctuation indexes are recorded as the optimal matching dynamic characteristic marks of the models. These marks will be used for subsequent dynamic fluctuation index matching to ensure that the most suitable interpolation model can be selected for fitting processing for each ephemeris data set.

[0038] Obtain the communication link state between the target satellite and the ground measurement and control station. After adjusting the parameters of the transmission protocol, transmit the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground measurement and control station for reconstruction.

[0039] In this embodiment, it is first necessary to evaluate the communication link status between the target satellite and the ground TT&C station. By detecting the key parameters of the communication link (such as the signal-to-noise ratio), comprehensively analyzing the current status of the link, the communication link status is obtained. According to this communication link status, the parameters of the transmission protocol are dynamically adjusted. These parameters include the transmission rate, error correction coding method, etc. For example, in the case of good link quality, the transmission rate can be increased and redundant coding can be reduced to improve data throughput. When the link quality is poor, the transmission rate can be reduced and the error correction coding intensity can be increased to ensure data reliability. After the adjustment of the transmission protocol is completed, the first polynomial interpolation coefficient (high-priority data) and the second polynomial interpolation coefficient (low-priority data) are sent to the ground TT&C station through the optimized communication link. After the data reaches the ground, according to the transmitted polynomial interpolation coefficients, the ephemeris data is reconstructed 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 orbit 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 the dynamic adjustment of the link status, while improving the efficiency and reliability of the entire data transmission process.

[0040] Furthermore, the present application provides obtaining the communication link status between the target satellite and the ground TT&C station and performing parameter regulation of the transmission protocol, including:

[0041] Performing a fusion analysis of the link quality and the signal-to-noise ratio degradation degree of the communication link between the target satellite and the ground TT&C station to generate the communication link status; adjusting the transmission rate and error correction coding of the communication link based on the communication link status to complete the parameter regulation of the transmission protocol.

[0042] Optionally, key performance indicators of the communication link are collected in real time through the communication link between the ground measurement and control station and the target satellite, including but not limited to signal-to-noise ratio, bit error rate, latency, and packet loss rate. By normalizing these key performance indicators and performing weighted calculations on the normalized results, the link quality score of the communication link is quantified to represent the overall health status of the communication link. Then, the difference between the signal-to-noise ratio collected last time and the current signal-to-noise ratio is calculated, and the ratio of the calculated difference to the signal-to-noise ratio collected last time is calculated to obtain the signal-to-noise ratio degradation. Subsequently, a fusion analysis of the communication link state is performed based on the link quality score and the signal-to-noise ratio degradation, that is, the link quality score and the signal-to-noise ratio degradation are weighted and fused, and then compared with the corresponding range to determine the current state of the communication link. For example, the state of a communication link with a link state score greater than or equal to 0.8 is a first-level communication link. At this time, the link state is stable, the signal-to-noise ratio degradation is small, and the overall quality is good. The state of a communication link with a link state score greater than or equal to 0.5 and less than 0.8 is a second-level communication link. At this time, the link state is medium, and there are certain signal degradation or quality problems. The state of a communication link with a link state score less than 0.5 is a third-level communication link. At this time, the link state is unstable, the signal-to-noise ratio degradation is significant, and the bit error rate is high. After that, 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 the data transmission performance and reliability. After the adjustment is completed, the adjusted parameter values are recorded and applied to the subsequent data transmission process, and the link state is continuously monitored for dynamic optimization. The regulated communication protocol ensures to improve the transmission efficiency when the link is good and enhance the transmission reliability when the link is poor, so as to achieve the stable and reliable transmission of ephemeris data.

[0043] Furthermore, the present application provides an adjustment of the transmission rate and error correction coding of the communication link based on the communication link state, including:

[0044] Configure a link parameter adjustment module, where 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; input the communication link state into the link parameter adjustment module, traverse and match in the multiple adjustment mode trigger conditions to generate a matching adjustment mode; adjust the transmission rate and error correction coding in the matching adjustment mode.

[0045] Optionally, when configuring the link parameter adjustment module, it is first necessary to connect it to a preset adjustment database, which stores various adjustment modes and their corresponding triggering conditions (such as link status score ranges or communication link status levels). Each mode is designed and named with a clear operation plan according to the different characteristics of the link status. For example, the high-efficiency transmission mode is applicable to the case of excellent link status. When the signal-to-noise ratio is high and the bit error rate is low, this mode will significantly increase the transmission rate and adopt low-redundancy coding (such as LDPC coding) to maximize data transmission efficiency. The balanced transmission mode is applicable to the case of medium link status. When the signal-to-noise ratio slightly decreases but the link quality is still acceptable, this mode appropriately reduces the transmission rate and adopts error correction coding with medium redundancy (such as medium-rate convolutional coding) to balance transmission efficiency and reliability. The robust transmission mode is applicable to the case of poor link status. When the signal-to-noise ratio is low and the bit error rate is high, this mode significantly reduces the transmission rate and adopts high-redundancy strong error correction coding (such as BCH coding or high-efficiency convolutional coding) to enhance data reliability and reduce bit errors. Subsequently, the calculated link status score or communication link status level is input into the link parameter adjustment module. The link parameter adjustment module will automatically traverse the triggering conditions of all adjustment modes in the preset adjustment database and match the adjustment mode corresponding to the current link status. For example, when the link status score is greater than or equal to 0.8 or the communication link status level is a first-level communication link, the high-efficiency transmission mode is matched. At this time, the transmission rate will be automatically adjusted to a higher level and the low-redundancy LDPC coding scheme will be adopted. After the matching is completed, the parameters of the transmission protocol are dynamically adjusted according to the selected adjustment mode. This includes optimizing the adjustment of the transmission rate to make full use of the bandwidth under good link conditions and avoiding data loss when the link is poor, switching the strategy of error correction coding from low redundancy to high redundancy to adapt to the transmission requirements under different link conditions, and at the same time optimizing the data packet splitting strategy, using large data packets under good links to reduce the overhead of the packet header, and adopting small data packets under poor links to reduce the impact of packet loss. Through this series of dynamic adjustments, it is ensured that the link can maintain the efficiency and reliability of data transmission under various conditions, realizing the adaptive optimization of the transmission protocol and the maximization of resource utilization.

[0046] In summary, the embodiments of the present application have at least the following technical effects:

[0047] In the embodiments of the present application, by obtaining the type information and orbital altitude information of the target satellite and combining with the analysis of the dynamic characteristics of the orbital altitude, efficient acquisition and classification of ephemeris data are realized; based on the importance of satellite missions, the synchronization priority of ephemeris data is judged, and it 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 and using the dynamic fluctuation index to match the optimal Lagrangian polynomial interpolation model, the polynomial interpolation coefficients of the data are respectively generated to achieve high-precision compression and reconstruction; in addition, by obtaining the communication link state between the target satellite and the ground TT&C station in real time and based on the fusion analysis of the signal-to-noise ratio and link quality, the parameters of the transmission protocol, including the transmission rate and the error correction coding strategy, are dynamically adjusted to optimize the data transmission performance; finally, in the case of changes in the link conditions, by configuring the link parameter adjustment module and matching the adjustment mode, the reliability, real-time performance, and efficiency of the ephemeris data transmission are ensured. These technical effects jointly solve the technical problems of insufficient real-time performance of ephemeris information and inability of data reliability to meet the dynamic application requirements due to the differences in satellite orbital altitude and type, realize the dynamic acquisition and hierarchical interpolation processing of ephemeris information based on orbital altitude and satellite type, optimize the configuration of communication link parameters, improve the efficiency and reliability of ephemeris information transmission, and ensure the real-time and accurate transmission of ephemeris information in low-earth orbit satellite communication.

[0048] Embodiment 2, based on the same inventive concept as the method for optimizing the transmission of ephemeris information in low-earth orbit satellite communication in the foregoing embodiment, as Figure 2 shown, the present application provides a system for optimizing the transmission of ephemeris information in low-earth orbit satellite communication, and the system includes: an information acquisition unit 11: acquiring the satellite type information and orbital altitude information of the target satellite; an ephemeris data acquisition unit 12: analyzing the update dynamic characteristics of ephemeris data based on the orbital altitude information, and acquiring ephemeris data based on the update dynamic characteristics to generate an ephemeris data set; a synchronization transmission discrimination unit 13: discriminating the synchronization 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; a data interpolation unit 14: analyzing the change rate of adjacent sampling points for the ephemeris data set, matching a target polynomial interpolation model according to the analysis result, and performing interpolation on 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 state between the target satellite and the ground TT&C 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 TT&C station for reconstruction.

[0049] Further, the synchronization transmission discrimination unit 13 is further configured to execute the following method:

[0050] Determine a satellite mission based on the satellite type information; perform an application priority analysis on various ephemeris data types according to the satellite mission to generate a priority analysis result; according to the priority analysis result, determine the data types with a priority greater than or equal to a preset priority as the first data type, and determine the data types with a priority less than the preset priority as the second data type.

[0051] Further, the data interpolation unit 14 is further configured to execute the following method:

[0052] Traverse the ephemeris data set, record the time marks and orbital parameters of each sampling point; based on the time marks, calculate the orbital parameter change rate between adjacent sampling points, and identify the dynamic fluctuation index according to the change rate; based on the dynamic fluctuation index, match the target polynomial interpolation model in a preset polynomial interpolation model; divide the ephemeris data set into first-type data and second-type data according to the first data type and the second data type; perform interpolation on the first-type data and the second-type data respectively with the target polynomial interpolation model to generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient.

[0053] Further, the data interpolation unit 14 is further configured to execute the following method:

[0054] Construct the preset polynomial interpolation model, where the preset polynomial interpolation model includes multiple interpolation models corresponding to multiple interpolation orders, and among them, the multiple interpolation models have an optimal matching dynamic characteristic mark; in the multiple interpolation models, match the interpolation model whose optimal matching dynamic characteristic mark meets the dynamic fluctuation index to generate the target polynomial interpolation model.

[0055] Further, the data interpolation unit 14 is further configured to execute the following method:

[0056] Construct the multiple interpolation models corresponding to the multiple interpolation orders based on the Lagrange polynomial; collect ephemeris data samples with gradually increasing fluctuation indexes, perform interpolation tests through the multiple interpolation models, calculate the mean square error between the reconstructed ephemeris data and the ephemeris data samples, and determine the fluctuation index corresponding to the samples when the mean square error of the multiple interpolation models meets a preset error threshold to generate the optimal matching dynamic characteristic mark.

[0057] Further, the coefficient reconstruction unit 15 is further configured to execute the following method:

[0058] Perform a fusion analysis of the link quality and signal-to-noise ratio degradation degree of the communication link between the target satellite and the ground measurement and control station to generate the communication link state; based on the communication link state, adjust the transmission rate and error correction coding of the communication link to complete the parameter regulation of the transmission protocol.

[0059] Further, the coefficient reconstruction unit 15 is further configured to perform the following method:

[0060] Configure a link parameter adjustment module, where 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; input the communication link state into the link parameter adjustment module, traverse and match among the multiple adjustment mode trigger conditions to generate a matching adjustment mode; adjust the transmission rate and error correction coding with the matching adjustment mode.

[0061] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the advantages or disadvantages of the embodiments. And the above describes specific embodiments of this specification. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0062] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0063] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications 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 equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. An optimized transmission method for ephemeris information in low-earth orbit satellite communication, characterized in that Including: Obtain the satellite type information and orbital altitude information of the target satellite; Conduct an analysis on the update dynamic characteristics of ephemeris data based on the orbital altitude information, and collect ephemeris data based on the update dynamic characteristics to generate an ephemeris data set; Conduct a discrimination on 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 synchronous priority of the first data type is higher than that of the second data type; Conduct an analysis on the change rate of adjacent sampling points for the ephemeris data set, match a target polynomial interpolation model according to the analysis result, and perform interpolation on the ephemeris data set after data partitioning 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 change rate refers to the change rate of the orbital parameters of adjacent sampling points in the ephemeris data set over time; Obtain the communication link state between the target satellite and the ground measurement and control station, and after adjusting the parameters of the transmission protocol, transmit the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground measurement and control station for reconstruction.

2. The optimized transmission method of ephemeris information in low-earth orbit satellite communication according to claim 1, wherein, Conduct an analysis on the change rate of adjacent sampling points for the ephemeris data set, match a target polynomial interpolation model according to the analysis result, and perform interpolation on the ephemeris data set after data partitioning 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: Traverse the ephemeris data set and record the time marks and orbital parameters of each sampling point; Based on the time marks, calculate the change rate of the orbital parameters of adjacent sampling points, and identify the dynamic fluctuation index according to the change rate; Match the target polynomial interpolation model in the preset polynomial interpolation model based on the dynamic fluctuation index; Partition the ephemeris data set according to the first data type and the second data type to generate a first type of data and a second type of data; Perform interpolation on the first type of data and the second type of data respectively with the target polynomial interpolation model to generate the first polynomial interpolation coefficient and the second polynomial interpolation coefficient.

3. The optimized transmission method of ephemeris information in low-earth orbit satellite communication according to claim 2, characterized in that, Matching the target polynomial interpolation model in the preset polynomial interpolation model based on the dynamic fluctuation index includes: Construct the preset polynomial interpolation model, which includes multiple interpolation models corresponding to multiple interpolation orders, wherein the multiple interpolation models have optimal matching dynamic characteristic marks; Among the multiple interpolation models, match the interpolation model whose optimal matching dynamic characteristic mark meets the dynamic fluctuation index to generate the target polynomial interpolation model.

4. The optimized transmission method of ephemeris information in low-earth orbit satellite communication according to claim 3, characterized in that, Constructing the preset polynomial interpolation model includes: Construct the multiple interpolation models corresponding to the multiple interpolation orders based on the Lagrange polynomial; Collect ephemeris data samples with gradually increasing acquisition 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 when the mean square error of the multiple interpolation models meets the preset error threshold, and generate the optimal matching dynamic characteristic markers.

5. The optimized transmission method for ephemeris information in low-earth orbit satellite communication according to claim 1, characterized in that, Based on the satellite type information, perform synchronization transmission discrimination for multiple ephemeris data types, and generate a first data type and a second data type, where the synchronization priority of the first data type is higher than that of the second data type, including: Determine the satellite mission based on the satellite type information; Perform application priority analysis for multiple ephemeris data types according to the satellite mission, and generate a priority analysis result; According to the priority analysis result, determine the data types with priorities greater than or equal to the preset priority as the first data type, and determine the data types with priorities less than the preset priority as the second data type.

6. The optimized transmission method of ephemeris information in low-earth orbit satellite communication according to claim 1, characterized in that, Obtain the communication link status between the target satellite and the ground measurement and control station, and perform parameter regulation of the transmission protocol, including: Perform a fusion analysis of the link quality and the signal-to-noise ratio degradation degree of the communication link between the target satellite and the ground measurement and control station, and generate the communication link status; Based on the communication link status, adjust the transmission rate and error correction coding of the communication link to complete the parameter regulation of the transmission protocol.

7. The optimized transmission method of ephemeris information in low-earth orbit satellite communication according to claim 6, wherein Based on the communication link status, adjust the transmission rate and error correction coding of the communication link, including: Configure a link parameter adjustment module, where 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; Input the communication link status into the link parameter adjustment module, perform traversal matching among the multiple adjustment mode trigger conditions, and generate a matching adjustment mode; Adjust the transmission rate and error correction coding according to the matching adjustment mode.

8. An optimized transmission system for ephemeris information in low-earth orbit satellite communication, characterized in that, Steps for implementing the optimized transmission method of ephemeris information in low-earth orbit satellite communication according to any one of claims 1 to 7, including: Information acquisition unit: Acquire the satellite type information and orbital altitude information of the target satellite; Ephemeris data acquisition unit: Based on the orbital altitude information, perform updated dynamic characteristic analysis of ephemeris data, and acquire ephemeris data based on the updated dynamic characteristics to generate an ephemeris data set; Synchronization transmission discrimination unit: Based on the satellite type information, perform synchronization transmission discrimination for multiple ephemeris data types, and generate a first data type and a second data type, where the synchronization priority of the first data type is higher than that of the second data type; Data interpolation unit: Analyze the change rate of adjacent sampling points for the ephemeris data set, match the target polynomial interpolation model according to the analysis result, and perform interpolation on 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: Obtain the communication link status between the target satellite and the ground TT&C station. After adjusting the parameters of the transmission protocol, transmit the first polynomial interpolation coefficient and the second polynomial interpolation coefficient to the ground TT&C station for reconstruction.

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