A low-orbit satellite communication shielding prediction method and system

Abstract

The application provides a low-orbit satellite communication shielding prediction method and system, and relates to the technical field of low-orbit satellite communication.The method comprises the following steps: acquiring a future trajectory sequence of a low-orbit satellite and a future trajectory sequence of a ground terminal, and topographic data and meteorological data of a region covered by the low-orbit satellite; generating a communication link space-time trajectory according to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal; performing space-time binding on the topographic data and the meteorological data to generate a space-time correlation matrix; determining the sampling point distribution and the sampling step of the topographic profile of the region covered according to the space-time correlation matrix, and combining an atmospheric refraction correction model and a meteorological attenuation model to perform dynamic shielding prediction, so as to obtain a shielding prediction result of the low-orbit satellite in a preset future time period.The application significantly improves the accuracy and timeliness of low-orbit satellite communication shielding prediction through multi-source data fusion, dynamic space-time trajectory generation, space-time binding, adaptive sampling and a comprehensive attenuation model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of low-orbit satellite communication, in particular to a low-orbit satellite communication shielding prediction method and system. BACKGROUND

[0002] Low-orbit satellite communication has been widely applied in emergency communication, Internet of Things and remote measurement and control due to its advantages of low delay, wide coverage and terminal miniaturization. However, due to the low orbit height, high moving speed and short transit time of low-orbit satellites, the communication link thereof is easily shielded by terrain (such as mountains and city buildings) and weather (such as rainfall and clouds), resulting in communication interruption or quality decline. Therefore, the prior art usually relies on static terrain data (such as digital elevation model DEM) and basic weather data to determine the shielding state through simple geometric calculation.

[0003] In the related art, for a complex scene, due to the high-speed moving characteristics of low-orbit satellites, the scene changes when the satellites pass through are accelerated, and on this basis, it is difficult to accurately reflect the dynamic relationship between the satellites and the shielding objects in real time depending on static data, so that the shielding state cannot be effectively predicted, resulting in a lagging prediction result and insufficient accuracy, which is difficult to meet the requirements of low-orbit satellite communication for real-time and accuracy. SUMMARY

[0004] The problem solved by the present application is how to improve the prediction effect of low-orbit satellite communication shielding.

[0005] To solve the above problems, the present application provides a low-orbit satellite communication shielding prediction method and system.

[0006] In a first aspect, a low-orbit satellite communication shielding prediction method of the present application comprises:

[0007] obtaining a future trajectory sequence of a low-orbit satellite and a future trajectory sequence of a ground terminal in a preset future time period, and terrain data and weather data of a region for the low-orbit satellite in the preset future time period;

[0008] generating a communication link space-time trajectory according to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal;

[0009] binding the terrain data and the weather data in space-time through the conversion relationship between the geocentric coordinate system and the topocentric coordinate system to generate a space-time correlation matrix;

[0010] determining the sampling point distribution of the terrain profile of the region and the sampling step length of the terrain profile of the region according to the space-time correlation matrix in combination with the communication link space-time trajectory;

[0011] According to the sampling point distribution and the sampling step, dynamic occlusion prediction is performed in combination with an atmospheric refraction correction model and a meteorological attenuation model to obtain an occlusion prediction result of the low-orbit satellite in the preset future time period.

[0012] Optionally, the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal in a preset future time period, and the topographic data and meteorological data of the low-orbit satellite for a region in the preset future time period are obtained by:

[0013] Real-time orbit parameters of the low-orbit satellite are obtained.

[0014] According to the real-time orbit parameters of the low-orbit satellite, attitude data of the low-orbit satellite in the preset future time period is obtained by prediction through an SGP4 orbit model.

[0015] According to the attitude data, the future trajectory sequence of the low-orbit satellite is generated.

[0016] According to the path data file of the ground terminal, discrete trajectory points corresponding to each time point of the ground terminal in the preset future time period are determined by integral operation and attitude solution.

[0017] According to the discrete trajectory points corresponding to each time point, the future trajectory sequence of the ground terminal is generated.

[0018] Optionally, the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal in a preset future time period, and the topographic data and meteorological data of the low-orbit satellite for a region in the preset future time period are obtained by:

[0019] According to the DEM data of the low-orbit satellite for the region, height information of the region is obtained by extraction.

[0020] The city building white model data of the ground terminal is spatially superimposed with the DEM data to generate a comprehensive topographic height of the region.

[0021] The comprehensive topographic height is taken as the topographic data.

[0022] A plurality of meteorological parameters in the preset future time period are obtained, and the meteorological parameters are spatially interpolated according to the same grid resolution as the DEM data to obtain the meteorological data.

[0023] Optionally, the communication link space-time trajectory is generated according to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal, comprising:

[0024] time aligning, according to the same time step, the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal, to obtain a relative position vector of the low-orbit satellite and the ground terminal;

[0025] converting the relative position vector to a topocentric coordinate system to obtain an elevation angle, an azimuth angle and a straight-line distance of the low-orbit satellite relative to the ground terminal;

[0026] geometrically correcting the straight-line distance by the curvature of the earth, in combination with the elevation angle and the azimuth angle, to obtain a space-time trajectory of the communication link.

[0027] Optionally, the space-time binding of the topographic data and the meteorological data to generate a space-time correlation matrix comprises:

[0028] unifying the topographic data, the meteorological data and the future trajectory sequence of the low-orbit satellite to the geocentric coordinate system based on WGS-84 ellipsoid parameters;

[0029] converting the topographic data, the meteorological data and the future trajectory sequence of the low-orbit satellite in the geocentric coordinate system to the topocentric coordinate system with the ground terminal as the origin by a rotation matrix to obtain real-time attitude data of the low-orbit satellite relative to the ground terminal, the real-time attitude data comprising real-time height, real-time elevation angle and real-time azimuth angle;

[0030] establishing a global time axis based on the time stamp of the future trajectory sequence, and generating a satellite orbit time sequence of the low-orbit satellite by linear interpolation of the meteorological data through the global time axis;

[0031] obtaining the space-time correlation matrix according to the satellite orbit time sequence in combination with the real-time attitude data.

[0032] Optionally, the determination of the sampling point distribution and the sampling step length of the topographic profile of the region according to the space-time correlation matrix in combination with the space-time trajectory of the communication link comprises:

[0033] determining a horizontal projection direction of a real-time line connecting the low-orbit satellite and the ground terminal in a horizontal plane according to the real-time elevation angle and the real-time azimuth angle of the low-orbit satellite in combination with the space-time trajectory of the communication link;

[0034] determining a sampling direction of the topographic profile according to the horizontal projection direction;

[0035] determining a sampling range by a radius constraint formula according to the real-time height and the real-time elevation angle;

[0036] divide the real-time elevation angles according to a preset rule, and assign each of the real-time elevation angles with a corresponding sampling step length according to a division result;

[0037] generate sampling points in the sampling range along the sampling direction according to the sampling step length, to obtain a sampling point distribution.

[0038] Optionally, the dynamic occlusion prediction is performed according to the sampling point distribution and the sampling step length, in combination with an atmospheric refraction correction model and a meteorological attenuation model, to obtain an occlusion prediction result of the low-orbit satellite in the preset future time period, including:

[0039] According to the sampling point distribution, the integrated terrain height and the meteorological parameter of each sampling point are obtained along the sampling direction;

[0040] According to the integrated terrain height, the line-of-sight height of each sampling point is determined in combination with the communication link space-time trajectory;

[0041] According to the meteorological parameter of the sampling point, a meteorological parameter signal attenuation amount is determined through the meteorological attenuation model and the atmospheric refraction correction model;

[0042] According to the line-of-sight height and the meteorological parameter signal attenuation amount, it is judged whether there is an occlusion in the preset future time period, and the judgment result is taken as the occlusion prediction result.

[0043] Optionally, according to the line-of-sight height and the meteorological parameter signal attenuation amount, it is judged whether there is an occlusion in the preset future time period, and the judgment result is taken as the occlusion prediction result, including:

[0044] According to the size relationship between the meteorological parameter signal attenuation amount and a preset link margin, it is judged whether there is a meteorological occlusion in the preset future time period;

[0045] If the meteorological parameter signal attenuation amount is greater than or equal to the preset link margin, it is determined that there is the meteorological occlusion in the preset future time period;

[0046] If the meteorological parameter signal attenuation amount is less than the preset link margin, it is determined that there is no meteorological occlusion in the preset future time period.

[0047] Optionally, according to the line-of-sight height and the meteorological parameter signal attenuation amount, it is judged whether there is an occlusion in the preset future time period, and the judgment result is taken as the occlusion prediction result, including:

[0048] According to the size relationship between the line-of-sight height of each sampling point and the integrated terrain height of the sampling point, it is judged whether there is a terrain occlusion in the preset future time period.

[0049] If the line-of-sight height of each sampling point is greater than or equal to the corresponding integrated terrain height, it is determined that the terrain occlusion does not exist in the preset future time period;

[0050] If the line-of-sight height of any sampling point is less than the corresponding integrated terrain height, it is determined that the terrain occlusion exists in the preset future time period.

[0051] In a second aspect, the present application provides a low-orbit satellite communication occlusion prediction system, comprising:

[0052] A data acquisition module is configured to acquire a future trajectory sequence of a low-orbit satellite and a future trajectory sequence of a ground terminal in a preset future time period, as well as terrain data and meteorological data of a region of interest of the low-orbit satellite in the preset future time period;

[0053] A link generation module is configured to generate a communication link space-time trajectory according to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal;

[0054] A space-time binding module is configured to bind the terrain data and the meteorological data in space-time through a conversion relationship between a geodetic coordinate system and a topocentric coordinate system, and generate a space-time correlation matrix;

[0055] A sampling decision module is configured to determine a sampling point distribution of a terrain profile of the region of interest and a sampling step of the terrain profile of the region of interest according to the space-time correlation matrix and in combination with the communication link space-time trajectory;

[0056] An occlusion prediction module is configured to perform dynamic occlusion prediction according to the sampling point distribution and the sampling step in combination with an atmospheric refraction correction model and a meteorological attenuation model, and obtain an occlusion prediction result of the low-orbit satellite in the preset future time period.

[0057] The low-orbit satellite communication shielding prediction method and system of the present application improves the accuracy and timeliness of low-orbit satellite communication shielding prediction through multi-source data fusion and dynamic analysis. First, by obtaining the trajectory sequence of low-orbit satellites and ground terminals in the future time period, as well as the terrain and weather data of the region, a comprehensive data foundation is provided for prediction, which takes into account the dynamic characteristics of the satellite and also considers the mobility of the ground terminal, making the prediction adaptable to various complex motion scenarios. According to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal, the communication link space-time trajectory is generated, which can accurately track the relative position changes between the satellite and the ground terminal. By generating the space-time trajectory, combined with the conversion between the geocentric coordinate system and the station-centered coordinate system, the accuracy and consistency of the data in different coordinate systems are ensured. Especially for low-orbit satellites, the rapid movement of low-orbit satellites will cause rapid changes in the signal propagation path, and accurate space-time trajectory can reflect the changes in real time. Through the space-time binding generated by the space-time correlation matrix, the terrain and weather data are further integrated, so that the analysis can be carried out in a unified space-time framework.

[0058] By integrating, the deviation of data in the space-time dimension is eliminated, which can more accurately predict the signal reception under different terrain and weather conditions in low-orbit satellite communication, so as to make adjustments in advance and reduce the risk of signal interruption. Then, based on the space-time correlation matrix, the sampling point distribution and sampling step of the terrain profile are determined, which embodies the dynamic and adaptive nature of the present application. Among them, the sampling strategy is dynamically adjusted according to the space-time correlation matrix and the communication link space-time trajectory to adapt to different terrain complexity and satellite elevation angles. Through adaptive sampling, not only the accuracy of the prediction is improved, but also the calculation efficiency is optimized, which can quickly respond to the dynamic changes of the satellite and the terminal while ensuring the accuracy, and timely capture the signal shielding caused by terrain changes (such as entering a valley or a city canyon) or weather changes (such as rain or heavy fog), so as to make early warning and ensure the continuity of communication.

[0059] Finally, combined with the atmospheric refraction correction model and the weather attenuation model, dynamic shielding prediction is carried out, considering the influence of various factors on signal propagation. Not only the accuracy of the prediction is improved, but also potential shielding events can be predicted in advance, so as to provide the optimal communication window suggestion for the communication system, reduce the possibility of signal interruption, and improve the reliability and stability of communication.

[0060] In summary, through multi-source data fusion, dynamic space-time trajectory generation, space-time binding, adaptive sampling and the application of comprehensive attenuation model, the accuracy and timeliness of low-orbit satellite communication shielding prediction are significantly improved, the risk of signal interruption is effectively reduced, and the continuity and stability of communication are improved. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1A flowchart of a low-orbit satellite communication shielding prediction method of an embodiment of the present application is shown in FIG. 1.

[0062] Figure 2 A shielding prediction result diagram of an embodiment of the present application is shown in FIG. 2.

[0063] Figure 3 A shielding analysis effect diagram of an embodiment of the present application is shown in FIG. 3.

[0064] Figure 4 A structure diagram of a low-orbit satellite communication shielding prediction system of an embodiment of the present application is shown in FIG. 4. DETAILED DESCRIPTION

[0065] In order to make the above objectives, features and advantages of the present application more apparent, specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms, and should not be interpreted as being limited to the embodiments set forth herein, but rather, these embodiments are provided so as to more thoroughly and completely understand the present application. It should be understood that the drawings and embodiments of the present application are for illustrative purposes only, and are not intended to limit the scope of protection of the present application.

[0066] It should be understood that each of the steps recited in the method embodiments of the present application can be executed in different orders, and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the execution of the steps shown. The scope of the present application is not limited in this respect.

[0067] The term "comprising" and variations thereof as used in the present application are open-ended, that is, "including but not limited to"; the term "based on" is "based, at least in part, on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; the term "optional" means "optional in at least some embodiments". Related definitions will be given in the description below. It should be noted that the concepts of "first", "second", etc. mentioned in the present application are only used to distinguish different devices, modules or units, and are not intended to limit the order or interdependence of the functions performed by these devices, modules or units.

[0068] It should be noted that the modification of "one" or "multiple" mentioned in the present application is illustrative and not limiting, and those skilled in the art should understand that, unless otherwise explicitly indicated in the context, it should be understood as "one or more".

[0069] The names of the messages or information exchanged between the multiple devices in the embodiments of the present application are only for illustrative purposes, and are not intended to limit the scope of these messages or information.

[0070] It should be noted that the information (including but not limited to user equipment information, user personal information, etc.), data (including but not limited to data for analysis, stored data, displayed data, etc.) and signals involved in the present application are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

[0071] In combination Figure 1 The low-orbit satellite communication shielding prediction method provided by the embodiment of the present application includes:

[0072] Obtaining a future trajectory sequence of a low-orbit satellite and a future trajectory sequence of a ground terminal in a preset future time period, and topographic data and meteorological data of a region covered by the low-orbit satellite in the preset future time period.

[0073] Specifically, the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal in the preset future time period, and the topographic data and meteorological data of the region covered by the low-orbit satellite in the preset future time period are obtained, so as to construct a full-dimensional basic data set required for shielding prediction, covering four core elements of satellite, terminal, topography and meteorology. The satellite future trajectory sequence is obtained by taking real-time orbit parameters in a satellite orbit database as input, and through the orbit extrapolation capability of the SGP4 orbit model, dynamic trajectory data in the preset future time period is generated, which is suitable for the high-speed moving characteristics of the low-orbit satellite. The future trajectory sequence of the ground terminal is generated in combination with the terminal motion characteristics, which is suitable for the position change requirements of mobile scenarios such as vehicle-mounted and ship-mounted. The topographic data fuses the natural terrain height of high-precision DEM and the artificial building height of urban building white model, forming comprehensive data that can reflect the real ground form. In the preferred embodiment of the present application, the topographic data can be obtained from a topographic database, and the storage precision of the topographic database reaches 12.5-meter topographic digital elevation (DEM) data, and three-dimensional building white model of main cities is also included, and the model includes building height parameters and accurate contour coordinate information. In addition, the database also stores characteristic data of main mountains, covering key information such as mountain slope, strike and vertex coordinates. The above-mentioned topographic related data are standardized stored in Shapefile or GeoTIFF format, ensuring the compatibility and reusability of the data. The meteorological data focuses on key parameters affecting communication, and through spatial interpolation processing, it is ensured that the spatial resolution matches the topographic data, laying a foundation for subsequent multi-source data fusion.

[0074] In another preferred embodiment of the present application, the ITU atmospheric model is used as the basic model for meteorological data processing. By connecting the public data interface of the meteorological department, real-time meteorological information in a specific future time period is obtained and stored. These information are mainly used for atmospheric refraction correction calculation in satellite communication and rainfall condition prediction, providing accurate data support for meteorological factors for communication shielding prediction. The whole data acquisition process realizes full coverage of dynamic and static data.

[0075] According to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal, a communication link space-time trajectory is generated.

[0076] Specifically, the space-time path of the communication link between the low-orbit satellite and the ground terminal is generated based on the future predicted trajectories of the two, and the signal propagation direction and range at different times are determined. By establishing the correspondence between the positions of the satellite and the ground terminal, the spatial positions of the satellite and the terminal at different times are connected in time dimension to form the space-time trajectory of the communication link. Specifically, by time aligning the future trajectory sequence of the satellite and the terminal, the synchronization deviation of the two in time dimension is eliminated, and the relative position vectors at different times are obtained. Based on the relative position vectors, the key attitude parameters of the satellite relative to the terminal, such as elevation angle and azimuth angle, can be further calculated to determine the spatial direction of signal propagation. Considering the long-distance scenario that may be involved in low-orbit satellite communication, the earth curvature correction mechanism is introduced to geometrically correct the straight-line distance to ensure that the trajectory calculation conforms to the real geophysical model. The finally generated space-time trajectory of the communication link fully presents the space-time changes of the signal propagation path in the preset future time period, providing accurate path reference for subsequent shielding analysis.

[0077] The topographic data and the meteorological data are spatio-temporally bound through the conversion relationship between the geocentric coordinate system and the station-centered coordinate system to generate a spatio-temporal correlation matrix.

[0078] Specifically, the time and space of topographic, meteorological, and satellite orbit data are unified and standardized to ensure data availability. Therefore, through coordinate unification and time alignment, the spatio-temporal fragmentation problem of multi-source data can be solved to realize collaborative processing of data. First, the topographic, meteorological, and satellite trajectory data are converted to the geocentric coordinate system to eliminate the spatial reference deviation of different data sources; then, they are converted to the station-centered coordinate system through a rotation matrix to adapt to the analysis requirements of the local view of the terminal and facilitate direct calculation of the attitude parameters of the satellite relative to the terminal. Time alignment constructs a global time axis based on the satellite trajectory timestamp to convert the quasi-static meteorological data into high-frequency data synchronized with the satellite trajectory. The finally formed spatio-temporal correlation matrix deeply binds the spatial dimension topographic height and meteorological parameters with the time dimension satellite dynamic parameters.

[0079] According to the space-time correlation matrix, in combination with the space-time trajectory of the communication link, a sampling point distribution of the topographic profile of the pair of regions and a sampling step length of the topographic profile of the pair of regions are determined.

[0080] Specifically, the determination of the sampling point distribution is guided by the space-time trajectory of the communication link, and a sampling profile is drawn along the azimuth direction of the satellite relative to the terminal, ensuring that the sampling range focuses on the area that the signal propagation path may pass through. The sampling range is controlled by dynamic radius constraints, combined with satellite height, elevation angle and other parameters for adjustment, to avoid redundant calculation; the sampling step length adopts an adaptive strategy, which is adjusted according to dynamic parameters such as satellite elevation angle, and small step length is used in low elevation angle and other scenarios sensitive to terrain details, and large step length is used in high elevation angle and other scenarios; through dynamic optimization of the sampling point distribution and the step length, the topographic profile sampling can accurately capture the topographic features of the potential blocking area, while taking into account the real-time performance of the calculation.

[0081] According to the sampling point distribution and the sampling step length, in combination with an atmospheric refraction correction model and a meteorological attenuation model, a dynamic blocking prediction is performed to obtain a blocking prediction result of the low-orbit satellite in the preset future time period.

[0082] Specifically, the comprehensive determination of terrain and meteorological blocking is realized by multi-model fusion. The terrain blocking determination is based on the physical blocking principle, and the integrated terrain height of the sampling point is compared with the line-of-sight height of the communication link. If the terrain height exceeds the line-of-sight height, it is determined that there is a block, which directly reflects the physical blocking of the signal by the terrain and buildings. The meteorological blocking determination focuses on the signal attenuation effect, and quantifies the signal attenuation amount caused by meteorological factors such as precipitation and cloud layer through the meteorological attenuation model, and compares it with the preset link margin to determine whether the meteorological conditions cause communication interruption. The entire determination process combines the two blocking mechanisms of physical blocking and signal attenuation, realizes comprehensive prediction of the blocking state in complex scenarios, and the final output prediction result covers the core conclusion of whether there is a block in the preset future time period.

[0083] The low-orbit satellite communication shielding prediction method of the embodiment improves the accuracy and timeliness of low-orbit satellite communication shielding prediction through multi-source data fusion and dynamic analysis. First, by obtaining the trajectory sequence of low-orbit satellites and ground terminals in the future time period, as well as the terrain and weather data of the region, a comprehensive data foundation is provided for prediction. The dynamic characteristics of the satellite are considered, and the mobility of the ground terminal is also taken into account, so that the prediction can adapt to various complex motion scenarios. According to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal, a communication link space-time trajectory is generated, which can accurately track the relative position changes between the satellite and the ground terminal. By generating the space-time trajectory, combined with the conversion between the geocentric coordinate system and the station-centered coordinate system, the accuracy and consistency of the data in different coordinate systems are ensured. Especially for low-orbit satellites, the rapid movement of low-orbit satellites will cause rapid changes in the signal propagation path, and accurate space-time trajectories can reflect the changes in real time. Through the space-time binding generated by the space-time correlation matrix, the terrain and weather data are further integrated, so that the analysis can be carried out in a unified space-time framework.

[0084] By integrating, the deviation of data in the space-time dimension is eliminated. In low-orbit satellite communication, eliminating the deviation can more accurately predict the signal reception under different terrain and weather conditions, so as to make adjustments in advance and reduce the risk of signal interruption. Then, based on the space-time correlation matrix, the sampling point distribution and sampling step of the terrain profile are determined, which embodies the dynamic and adaptive nature of the embodiment. Among them, the sampling strategy is dynamically adjusted according to the space-time correlation matrix and the communication link space-time trajectory to adapt to different terrain complexity and satellite elevation angles. Through adaptive sampling, not only the accuracy of the prediction is improved, but also the calculation efficiency is optimized, which can quickly respond to the dynamic changes of the satellite and the terminal while ensuring the accuracy, and timely capture the signal shielding caused by terrain changes (such as entering a valley or a city canyon) or weather changes (such as rain or heavy fog), so as to make early warning and ensure the continuity of communication.

[0085] Finally, combined with the atmospheric refraction correction model and the weather attenuation model, dynamic shielding prediction is carried out, considering the influence of multiple factors on signal propagation. Not only the accuracy of the prediction is improved, but also potential shielding events can be predicted in advance, so as to provide the optimal communication window suggestion for the communication system, reduce the possibility of signal interruption, and improve the reliability and stability of communication.

[0086] In summary, through multi-source data fusion, dynamic space-time trajectory generation, space-time binding, adaptive sampling and the application of comprehensive attenuation models, the accuracy and timeliness of low-orbit satellite communication shielding prediction are significantly improved, the risk of signal interruption is effectively reduced, and the continuity and stability of communication are improved.

[0087] Optionally, the acquiring the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal in a preset future time period, and the topographic data and meteorological data of the low-orbit satellite to a region in the preset future time period comprises:

[0088] acquiring real-time orbit parameters of the low-orbit satellite;

[0089] predicting, by an SGP4 orbit model, the real-time orbit parameters of the low-orbit satellite to obtain attitude data of the low-orbit satellite in the preset future time period;

[0090] generating the future trajectory sequence of the low-orbit satellite according to the attitude data;

[0091] determining, by integral operation and attitude solution, discrete trajectory points corresponding to each time point of the ground terminal in the preset future time period according to a path data file of the ground terminal;

[0092] generating the future trajectory sequence of the ground terminal according to the discrete trajectory points corresponding to each time point.

[0093] Specifically, first, real-time orbit parameters of the low-orbit satellite are acquired, and an SGP4 orbit model is used for prediction to obtain attitude data of the satellite in a preset future time period. This process ensures the accuracy and timeliness of the satellite trajectory, and provides a reliable basis for subsequent communication link analysis. The SGP4 model is an orbit propagation model that can accurately predict the position and velocity of the satellite in the future time period, thereby generating an accurate future trajectory sequence. Secondly, for the future trajectory sequence of the ground terminal, discrete trajectory points corresponding to each time point are determined according to a path data file of the ground terminal by integral operation and attitude solution, so that the position change of the ground terminal in the future time period can be accurately tracked even if the terminal is in a dynamic moving state.

[0094] In this way, the future trajectory sequence of the ground terminal is generated, ensuring that the position information of the ground terminal is updated synchronously with the satellite trajectory, and providing accurate ground terminal data for the space-time analysis of the communication link. For example, two-line element (TLE) data of the satellite is acquired from an international satellite orbit database and a domestic measurement and control mechanism, and the acquired orbit parameters are calculated based on the SGP4 algorithm model to generate position information of the satellite in a future period of time. The time interval for calculation is 10 seconds, thereby ensuring the timeliness and accuracy of the satellite orbit data, and providing reliable orbit basis for satellite communication shielding prediction.

[0095] In a preferred embodiment of the present application, the database stores in real time the satellite position , velocity and the elevation angle of the satellite relative to the ground terminal in the geodetic coordinate system azimuth angle and other core parameters. Satellite position information is obtained by analyzing two-line elements, and calculated by combining the SGP4 orbit model. In view of the characteristics that the low-orbit satellite moves at a high speed (about 7.8 km / s), which causes the elevation angle to change more than 1° per second, the database implements high-frequency updates of at least once per second for the elevation angle and the azimuth angle, to ensure that the relative spatial relationship between the satellite and the ground terminal can be accurately reflected, and to provide a real-time and dynamic basis for subsequent occlusion analysis.

[0096] Based on real-time orbit parameters, the satellite trajectory time-space sequence in the next 15 minutes is generated by extrapolation using the SGP4 model , and the time interval is set to 10 seconds. The sequence contains predicted elevation angles , azimuth angles and other parameters at each time in the future, which can be combined with the ground terminal position to calculate the line-of-sight height at the corresponding time in advance, as follows:

[0097] ;

[0098] , where is the line-of-sight height between the satellite and the ground terminal at time t (unit: m), is the altitude of the ground terminal (unit: m), is the horizontal distance between the satellite and the ground terminal at time t (unit: m), is the elevation angle of the satellite relative to the ground terminal at time t (unit: rad).

[0099] The ground terminal trajectory prediction needs to be selected in different ways according to the actual situation: if the terminal moves along a specified path, the key node coordinates are obtained by analyzing the path data file, and the position at each time is calculated by combining the motion speed and the 10-second time interval; if it relies on inertial navigation data, the data collected by accelerometers, gyroscopes and other devices are used to calculate the terminal position and attitude in real time through integral operation and attitude solution, to obtain a discrete trajectory point sequence every 10 seconds. Combined with the above parameters, the terrain profile sampling range can be further determined, and the start / end time and duration of future terrain occlusion can be accurately predicted. After spatiotemporal alignment of the trajectory sequence with the future 15-minute weather data trend prediction (such as precipitation intensity change), the possibility of future weather occlusion can be simultaneously predicted, to provide a time dimension decision basis for communication window planning (such as selecting an unoccluded period for data transmission). The design of a 10-second time interval balances the calculation efficiency and accuracy, avoids prediction errors caused by too large intervals (controlled within 10 seconds), and adapts to the characteristics of short transit time (5-10 minutes) of low-orbit satellites, to ensure the practicality of the prediction results. At the same time, the configurability of the sampling frequency can accurately capture the parameter mutations caused by the high-speed movement of the satellite, avoid misjudgment of instantaneous occlusion caused by data lag, and ensure the sampling accuracy of terrain occlusion calculation and the calculation efficiency of the overall algorithm software simulation.

[0100] In this optional embodiment, by accurately obtaining the future trajectory sequence of the low-orbit satellite and the ground terminal, as well as the topographic and meteorological data of the region, the accuracy and timeliness of the low-orbit satellite communication blockage prediction are significantly improved. By using the SGP4 orbit model to predict the satellite trajectory, the position change of the satellite in the future time period can be accurately tracked, ensuring the accuracy and timeliness of the satellite trajectory. For the ground terminal, through integral operation and attitude solution, the position change of the ground terminal in the future time period can be accurately tracked.

[0101] Optionally, the obtaining of the future trajectory sequence of the low-orbit satellite in the preset future time period and the future trajectory sequence of the ground terminal, as well as the topographic data and meteorological data of the region of the low-orbit satellite in the preset future time period, comprises:

[0102] extracting the DEM data of the region according to the DEM data of the low-orbit satellite to obtain height information of the region;

[0103] spatially superimposing the city building white model data of the ground terminal and the DEM data to generate a comprehensive terrain height of the region;

[0104] taking the comprehensive terrain height as the topographic data;

[0105] obtaining a plurality of meteorological parameters in the preset future time period, and spatially interpolating the meteorological parameters according to the same grid resolution as the DEM data to obtain the meteorological data.

[0106] Specifically, first, by extracting the DEM data of the region, the height information of the region is obtained, wherein the DEM data is used to provide the basic height profile of the terrain, which serves as the basis for analyzing the influence of the terrain on the communication link. Then, the city building white model data of the ground terminal is spatially superimposed with the DEM data to generate a comprehensive terrain height. In addition, a plurality of meteorological parameters in the preset future time period are obtained, and spatially interpolated according to the same grid resolution as the DEM data to obtain the meteorological data; meteorological parameters such as precipitation intensity, temperature and air pressure have a significant impact on signal propagation, especially precipitation will cause signal attenuation. By spatial interpolation, the meteorological data is aligned with the topographic data in space, ensuring the consistency and accuracy of the two in analysis, so that the meteorological data can be seamlessly combined with the topographic data to provide comprehensive environmental information for blockage prediction.

[0107] In a preferred embodiment of the present application, for the acquisition of terrain data, the natural terrain is first acquired, including 12.5m resolution DEM data, and the natural height h of each sampling point of the terrain profile is extracted; through grid division and elevation value reading of the DEM data, the height information of each position on the terrain surface can be accurately acquired. In the data reading process, parallel computing technology is used to improve the data processing speed, especially for large-area terrain data regions, and then building is supplemented, wherein according to the high-precision building white model data of the main city, the building height increment Δh_build is superimposed in the urban area to generate the integrated terrain height h_total(x, y) = h_DEM(x, y) + Δh_build(x, y) (the sum of the terrain height and the building height at the current position), wherein h_total(x, y) represents the integrated terrain height, that is, the total height of the terrain and the building after superposition at the coordinate point (x, y); h_DEM(x, y) represents the height of the digital elevation model (DEM), that is, the natural terrain height at the coordinate point (x, y); Δh_build(x, y) represents the building height increment, that is, the height of the building at the coordinate point (x, y); the high-precision building white model data contains the three-dimensional geometric shape and height information of the building, which can accurately reflect the actual terrain undulation of the urban area through spatial matching and superposition calculation with DEM data. Finally, efficiency optimization is performed, and the terrain data is loaded in pyramid layers (divided into 5m precision and 12.5m precision): 5m high-precision data is loaded in low elevation (15°≤θ<30°) of satellite communication link, and 12.5m low-precision data is loaded in high elevation (30°≤θ<90°), balancing precision and calculation speed. In the case of low elevation, the signal propagation path is more easily affected by terrain details, so loading 5m precision data can more accurately analyze the shielding condition. When the elevation is high, the terrain has a relatively small impact on signal shielding, and the use of 12.5m precision data can reduce the data processing amount and improve the calculation efficiency. In the data loading process, by establishing a data index and cache mechanism, the data reading speed is accelerated, and repeated loading of the same area of data is avoided. The terrain data of different precisions is stored in blocks according to the region, and the corresponding index file is established, and when the data needs to be loaded, the corresponding block data is quickly located according to the position of the satellite and the ground terminal.

[0108] For the acquisition of meteorological data, through the accurate collection, storage and processing of key meteorological parameters in the meteorological database, multi-dimensional meteorological influence evaluation support is provided for low-orbit satellite communication shielding prediction. The database mainly stores real-time and future 15-minute core meteorological parameters such as precipitation intensity (R), ground temperature (T), air pressure (P), altitude (H), and cloud height, which directly affect the satellite signal propagation process: precipitation intensity (R) can cause rain attenuation effect of the signal, resulting in signal energy attenuation; ground temperature (T) and air pressure (P) change the refraction characteristics of the signal propagation path by affecting the atmospheric density distribution; cloud height is directly related to whether the signal is blocked by the cloud layer, and all parameters are obtained in real time through a network interface to ensure the timeliness and authority of the data.

[0109] In this optional embodiment, by accurately obtaining and processing terrain and meteorological data, the accuracy and reliability of low-orbit satellite communication shielding prediction are significantly improved. By extracting DEM data and generating a comprehensive terrain height, the impact of terrain on communication links is more comprehensively considered, including natural terrain and artificial structures such as urban buildings. The prediction results are more accurate through comprehensive terrain data, especially for urban environments, which can more accurately predict the shielding of signals by buildings.

[0110] Optionally, the communication link space-time trajectory is generated according to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal, comprising:

[0111] The future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal are time-aligned according to the same time step to obtain a relative position vector of the low-orbit satellite and the ground terminal;

[0112] The relative position vector is converted to a geocentric coordinate system to obtain an elevation angle, an azimuth angle, and a straight-line distance of the low-orbit satellite relative to the ground terminal;

[0113] The straight-line distance is geometrically corrected by the curvature of the Earth in combination with the elevation angle and the azimuth angle to obtain the communication link space-time trajectory.

[0114] Specifically, by time-aligning the future trajectory sequences of the low-orbit satellite and the ground terminal according to the same time step, a relative position vector between the satellite and the terminal is obtained. Since the motion speed and direction of the satellite and the terminal can change at any time, the relative position vector is obtained through accurate time alignment in a dynamic environment, ensuring the synchronization of the position information of the satellite and the terminal in time, and providing an accurate space-time reference for subsequent analysis.

[0115] Next, the relative position vector is converted to the station-centered coordinate system to obtain the elevation angle, azimuth angle and straight-line distance of the satellite relative to the terminal. The station-centered coordinate system is a local coordinate system with the ground terminal as the origin. This conversion makes the analysis more close to the perspective of the ground terminal, facilitating subsequent occlusion analysis. Through this conversion, the relative position relationship between the satellite and the terminal can be more intuitively understood, providing a more intuitive perspective for the analysis of the communication link.

[0116] Finally, through the earth curvature correction, the straight-line distance is geometrically corrected in combination with the elevation angle and the azimuth angle to obtain the space-time trajectory of the communication link. The earth curvature correction considers the influence of the curvature of the earth on the signal propagation path. Through this correction, the actual propagation path of the signal can be more accurately simulated, and the accuracy of the prediction can be improved.

[0117] In a preferred embodiment of the present application, considering the straight-line assumption of signal propagation and the influence of the earth curvature, when calculating the long-distance communication link, the earth radius (taking 6378 km) parameter is introduced to correct the propagation path, and the correction formula is:

[0118] ;

[0119] wherein, is the straight-line distance (unit: km) between the satellite and the ground terminal after the earth curvature correction, R is the earth radius (value 6378 km, calculated based on the ellipsoid parameters of the WGS-84 coordinate system), is the orbital height (unit: km, calculated from the satellite orbit data, i.e. the vertical distance of the satellite from the earth ellipsoid) of the satellite at time t, is the altitude (unit: km, taken from the DEM data of the terrain database, i.e. the vertical distance of the terminal from the earth ellipsoid) of the ground terminal, is the elevation angle (unit: rad, calculated from the spatial coordinates of the satellite and the terminal) of the satellite relative to the ground terminal at time t,

[0120] In this optional embodiment, by accurately generating the space-time trajectory of the communication link, the accuracy and reliability of the low-orbit satellite communication occlusion prediction are significantly improved, thereby improving the accuracy and reliability of the low-orbit satellite communication occlusion prediction.

[0121] Optionally, the space-time binding of the terrain data and the meteorological data through the conversion relationship between the geodetic coordinate system and the station-centered coordinate system generates a space-time correlation matrix, comprising:

[0122] unify the terrain data, the weather data and the future trajectory sequence of the low earth orbit satellite to the geocentric coordinate system based on WGS-84 ellipsoid parameters;

[0123] convert the terrain data, the weather data and the future trajectory sequence of the low earth orbit satellite in the geocentric coordinate system to the station-centered coordinate system with the ground terminal as the origin through a rotation matrix, to obtain real-time attitude data of the low earth orbit satellite relative to the ground terminal, the real-time attitude data including real-time altitude, real-time elevation angle and real-time azimuth angle;

[0124] establish a global time axis based on the time stamp of the future trajectory sequence, and perform linear interpolation on the weather data through the global time axis to generate a satellite orbit time sequence of the low earth orbit satellite;

[0125] obtain the space-time correlation matrix according to the satellite orbit time sequence in combination with the real-time attitude data.

[0126] Specifically, the multi-source data space-time fusion is precisely aligned with the coordinate system and the time axis, eliminates the deviation of terrain, weather and satellite orbit data in the space-time dimension, and provides a consistent data basis for occlusion prediction. First, based on the WGS-84 ellipsoid parameters, the terrain data, the weather data and the future trajectory sequence of the low earth orbit satellite are unified to the geocentric coordinate system. The geocentric coordinate system is a global unified coordinate system that can accurately describe the position and motion of the earth's surface. Next, the data in the geocentric coordinate system is converted to the station-centered coordinate system with the ground terminal as the origin through a rotation matrix, to obtain real-time attitude data of the low earth orbit satellite relative to the ground terminal, including real-time altitude, real-time elevation angle and real-time azimuth angle. The station-centered coordinate system is a local coordinate system with the ground terminal as the origin, which is more convenient for analyzing the relative position relationship between the satellite and the terminal. Through the conversion operation, the data is closer to the perspective of the ground terminal, which is convenient for subsequent occlusion analysis and can more intuitively understand the relative position relationship between the satellite and the terminal, providing a more intuitive perspective for communication link analysis. In addition, a global time axis is established based on the time stamp of the future trajectory sequence, and the weather data is linearly interpolated through the global time axis to generate a satellite orbit time sequence of the low earth orbit satellite, ensuring the synchronization of weather data and satellite trajectory data in time, and providing an accurate time reference for subsequent space-time analysis.

[0127] By linear interpolation, the time resolution of meteorological data can be aligned with the time resolution of satellite trajectories, ensuring the synchronization of both in time. Finally, according to the time series of satellite orbits, combined with real-time attitude data, a spatio-temporal correlation matrix is obtained. As a three-dimensional matrix, the spatio-temporal correlation matrix contains information of spatial dimensions (terrain and meteorological data) and time dimensions (satellite trajectories and meteorological data).

[0128] In a preferred embodiment of the present application, for the conversion of the terrestrial coordinate system, the geodetic coordinates (latitude φ, longitude λ, height h) of all data are converted into three-dimensional Cartesian coordinates (X, Y, Z) based on the WGS-84 ellipsoid model, and the conversion formula is as follows:

[0129] (the colure radius of curvature);

[0130] ;

[0131] ;

[0132] ;

[0133] wherein, represents the colure radius of curvature, e is the first eccentricity of the ellipsoid, a is the long semi-axis of the ellipsoid, the long semi-axis a = 6378137 m, the flattening of the ellipsoid f = 1 / 298.257223563; for converting the geodetic coordinates (latitude φ, longitude λ, height h) into three-dimensional Cartesian coordinates (X, Y, Z), through the conversion, the terrain DEM data (containing altitude h), the three-dimensional coordinates of the building model, the grid center coordinates of the meteorological data and the ECEF coordinates of the satellite orbit are unified to the same coordinate system, and the influence of the earth flattening on the spatial positioning is corrected.

[0134] In another preferred embodiment of the present application, in order to adapt to the local visual angle analysis of the ground terminal, the ECEF coordinates are converted into the station-centered coordinate system (eastward E, northward N, skyward U) where the terminal is located by a rotation matrix, and the conversion matrix is as follows:

[0135] ;

[0136] wherein, λ is the terminal longitude, φ is the terminal latitude, and the units are rad; after conversion, the real-time elevation angle θ(t) and azimuth angle φ(t) of the satellite relative to the terminal can be directly calculated:

[0137] ;

[0138] ;

[0139] Wherein, E(t), N(t), U(t) are coordinate components of satellite in ENU coordinate system at time t.

[0140] In another preferred embodiment of the present application, for time alignment, first, the establishment of the reference time sequence is carried out, second, the time matching of multi-source data is carried out, and finally, the space-time correlation matrix is constructed. Specifically, taking the timestamp of satellite orbit data as the reference (sampling interval 10 seconds, high-frequency update up to 1 second level), the global time axis is constructed (k=0, 1,..., n, and Δt is the sampling interval).

[0141] The static terrain data is bound to the global time axis because its spatial characteristics do not change with time, that is:

[0142] ;

[0143] The weather data linearly interpolates the quasi-static weather parameters (such as precipitation intensity R, temperature T) updated every minute to generate high-frequency data matching the satellite orbit time sequence:

[0144] ;

[0145] Finally, the obtained space-time correlation matrix is The matrix elements contain spatial dimensions and time dimensions. The spatial dimension is the integrated terrain height at (x, y) The time dimension is the weather parameter at time The terrain, weather, and satellite orbit data of any spatial point (x, y) can be called synchronously to provide space-time consistent input for the occlusion prediction algorithm.

[0146] In this optional embodiment, through the accurate space-time binding and conversion relationship, the accuracy and reliability of the low-orbit satellite communication occlusion prediction are significantly improved. By uniformly converting the terrain data, weather data, and satellite trajectory to the geostationary coordinate system, the consistency and comparability of all data in the same coordinate system are ensured, which provides a solid foundation for subsequent space-time analysis.

[0147] Optionally, the determining, according to the space-time correlation matrix and in combination with the space-time trajectory of the communication link, of the sampling point distribution of the terrain profile of the region and the sampling step length of the terrain profile of the region comprises:

[0148] According to the real-time elevation angle and the real-time azimuth angle of the low-orbit satellite, in combination with the space-time trajectory of the communication link, the horizontal projection direction of the real-time connecting line of the low-orbit satellite and the ground terminal in the horizontal plane is determined.

[0149] According to the horizontal projection direction, the sampling direction of the terrain profile is determined.

[0150] determine a sampling range by a radius constraint formula according to the real-time height and the real-time elevation angle;

[0151] divide the real-time elevation angle according to a preset rule, and assign a corresponding sampling step to each real-time elevation angle according to a division result;

[0152] generate sampling points in the sampling range according to the sampling step along the sampling direction, to obtain a sampling point distribution.

[0153] Specifically, first, the real-time elevation angle and the real-time azimuth angle of the low-orbit satellite are utilized, combined with the communication link space-time trajectory, to determine the horizontal projection direction of the real-time connecting line between the satellite and the ground terminal in the horizontal plane, to ensure the accuracy of the sampling direction, so that the subsequent topographic profile analysis can accurately reflect the topographic changes on the signal propagation path. The determination of the horizontal projection direction is based on the relative position relationship between the satellite and the terminal, and is obtained through geometric calculation, providing clear direction guidance for the sampling of the topographic profile. Then, the sampling direction of the topographic profile is determined according to the horizontal projection direction.

[0154] Specifically, the analysis direction of the topographic profile needs to be aligned with the signal propagation path to ensure that the sampling points can cover the key topographic features on the signal propagation path. In this way, the topographic changes that may affect signal propagation, such as mountains, valleys, buildings, etc., can be more accurately captured. Then, according to the real-time height and the real-time elevation angle, the sampling range is determined by the radius constraint formula. The radius constraint formula takes into account the height and elevation angle of the satellite, dynamically adjusts the sampling range, and ensures that potential obstructions can be effectively captured under different elevation angles. This dynamic adjustment mechanism enables the sampling range to adapt to the motion changes of the satellite and the terminal, improving the flexibility and accuracy of the prediction. Next, the real-time elevation angle is divided according to a preset rule, and a corresponding sampling step is assigned to each real-time elevation angle. According to different intervals of the elevation angle, the sampling step is adjusted to adapt to the changes of different topographic complexities and signal propagation paths. For example, at low elevation angles, the sampling step can be smaller to capture more topographic details; at high elevation angles, the sampling step can be larger to improve computational efficiency. This adaptive sampling strategy not only improves the accuracy of the prediction, but also optimizes the computational efficiency. Finally, along the sampling direction, sampling points are generated in the sampling range according to the sampling step, to obtain a sampling point distribution. The sampling point distribution generated in this process provides specific data points for the analysis of the topographic profile, enabling the system to accurately analyze the influence of the topography on signal propagation.

[0155] In the preferred embodiment of the present application, to solve the problem of dynamic change of the topographic profile calculation range caused by the high-speed movement (about 7.8 km / s) of the low-orbit satellite, the effective sampling area is limited by a dynamic radius constraint, balancing accuracy and efficiency:

[0156] The dynamic radius calculation formula is:

[0157] ;

[0158] wherein, is the maximum radius of the terrain profile sampling at time t (unit: km), and the upper limit is set to 10 km to avoid redundant calculation; is the satellite orbit height at time t (unit: km, provided by satellite orbit data), is the elevation angle of the satellite relative to the ground terminal at time t (unit: rad), is a terrain coefficient, which is dynamically valued according to the region type: 1.5 for urban areas (buildings are densely populated and the range needs to be expanded), 1.2 for mountainous areas (terrain undulates and the range needs to be moderately expanded), and 1.0 for plains (terrain is flat and the range can be contracted).

[0159] The dynamic radius constraint limits the sampling range of the terrain profile by setting the maximum calculation radius , which reduces unnecessary calculation while ensuring the accuracy of the occlusion analysis, adapts to the characteristics of the low-orbit satellite moving at a speed of about 7.8 km / s, and ensures the timeliness of the prediction.

[0160] Based on the satellite height and the elevation angle , the calculation range is limited to optimize efficiency:

[0161] ;

[0162] wherein, is a terrain coefficient, which is 1.5 for urban areas, 1.2 for mountainous areas, and 1.0 for plains.

[0163] This constraint dynamically adjusts the sampling radius based on the real-time position parameters of the satellite, ensuring that only the terrain areas that may cause occlusion are calculated. In low elevation angles (15°<θ<30°), the range is expanded to capture distant occluders, and in high elevation angles (90°>θ>60°), the range is contracted to reduce invalid operations, adapting to the characteristics of the satellite moving at high speed.

[0164] The terrain profile is generated along the real-time azimuth angle φ(t) of the satellite, and through dynamic adjustment of the sampling direction and step, the terrain occlusion features are accurately captured. Among them, with the change of the satellite azimuth angle φ(t) (updated every second), the sampling direction of the terrain profile is adjusted in real time to ensure that the sampling path is always consistent with the horizontal projection direction of the satellite-terminal line of sight, and the formula is as follows:

[0165] ;

[0166] wherein, Δφ is an angular offset within ±5°, which is used to cover the possible occlusion areas on both sides of the line of sight.

[0167] According to the satellite elevation angle dynamic optimization sampling step, a low elevation angle scene (θ(t) < 30°) adopts a 10m fine step to capture long-distance low barriers (such as building group edges, low mountains); a medium elevation angle scene (30°≤θ(t)≤60°) adopts a 50m medium step to balance accuracy and efficiency; and a high elevation angle scene (θ(t)>60°) adopts a 100m coarse sampling step to focus on the near-field high barrier risk area. The step switching is automatically triggered through threshold judgment to ensure that the sampling density under different elevations matches the barrier risk.

[0168] The sampling density is dynamically adjusted through the rugged terrain coefficient to realize accurate barrier analysis of complex terrain, wherein the rugged coefficient k is defined to evaluate the terrain complexity on the sampling path:

[0169] ;

[0170] wherein h i is the terrain height (unit: m) of the i th sampling point, is the sampling step (unit: m); When k≥0.3 (high rugged area, such as mountainous area, dense building group): the current step is automatically halved (minimum 5m) to encrypt sampling to capture steep terrain changes; when 0.1≤k<0.3 (medium rugged area, such as hilly area, suburban area), the current step is maintained; and when k<0.1 (low rugged area, such as plain, open land), the step can be expanded to 1.5 times of the original step (maximum 150m). Through this mechanism, the algorithm can adapt to the terrain features, ensure the barrier judgment accuracy in complex areas, improve the calculation efficiency in flat areas, and provide reliable support for real-time barrier prediction.

[0171] In the preferred embodiment of the present application, the sampling step can be set to 10 meters at low elevation to capture more terrain details, and the sampling step can be set to 100 meters at high elevation to improve calculation efficiency. The adaptive sampling strategy of this embodiment not only improves the prediction accuracy, but also optimizes the calculation efficiency.

[0172] In this optional embodiment, by determining the sampling point distribution and sampling step of the terrain profile, the accuracy and efficiency of the low-orbit satellite communication barrier prediction are improved, so that it can adapt to the changes of different elevations and terrain complexities, and ensure that potential barriers can be accurately captured under various conditions. Not only improves the accuracy of prediction, but also optimizes the calculation efficiency, ensures the accuracy while quickly responding to the dynamic changes of satellites and terminals.

[0173]

[0174] ​Optionally, the dynamic occlusion prediction is performed according to the sampling point distribution and the sampling step size, in combination with an atmospheric refraction correction model and a meteorological attenuation model, to obtain an occlusion prediction result of the low-orbit satellite in the preset future time period, including:

[0175] According to the sampling point distribution, the integrated terrain height and the meteorological parameter of each sampling point are obtained along the sampling direction;

[0176] In combination with the communication link space-time trajectory, the line-of-sight height of each sampling point is determined according to the integrated terrain height;

[0177] According to the meteorological parameter of the sampling point, a meteorological parameter signal attenuation amount is determined through the meteorological attenuation model and the atmospheric refraction correction model;

[0178] According to the line-of-sight height and the meteorological parameter signal attenuation amount, it is judged whether there is occlusion in the preset future time period, and the judgment result is taken as the occlusion prediction result.

[0179] Specifically, the dynamic occlusion prediction algorithm realizes the rapid determination of the low-orbit satellite communication occlusion by adapting the satellite motion state and the terrain features in real time, while ensuring the occlusion analysis accuracy and optimizing the calculation efficiency. In the data extraction link, key information is accurately obtained from the sampling point distribution along the preset sampling direction, for example, the integrated terrain height integrates the natural terrain height of the 12.5-meter precision DEM and the building height increment of the urban high-precision building model, which truly reflects the ground shape of complex scenes such as urban valleys and mountains; the meteorological parameters include the core indexes such as precipitation intensity, ground temperature, air pressure, and cloud height, which provide quantitative input for subsequent attenuation calculation. The determination of the line-of-sight height takes the communication link space-time trajectory as the benchmark, combines the integrated terrain height and the geometric optics principle, and performs geometric operation on parameters such as the ground terminal altitude, the horizontal distance between the sampling point and the terminal, and the satellite elevation angle, to superimpose the earth curvature correction amount (calculated based on the WGS-84 ellipsoid long semi-axis) and the atmospheric refraction correction amount (using the ITU-RP.453 model, using the ground temperature, air pressure, and water vapor pressure to calculate the refraction index, and integrating along the propagation path to obtain the elevation angle correction amount, which significantly reduces the line-of-sight height error in low-elevation scenarios), to form a corrected line-of-sight height that fits the real propagation path, solving the determination deviation problem caused by the neglect of earth curvature and atmospheric refraction in traditional models. The calculation of the meteorological parameter signal attenuation amount is based on the meteorological attenuation model adapted to Ku / Ka frequency bands, and different calculation formulas are used for different precipitation types such as rain and snow according to the intensity, in combination with the satellite elevation angle to calculate the precipitation layer propagation path length, to realize the accurate quantization of the attenuation amount; at the same time, cloud layer attenuation calculation is included, further improving the meteorological influence evaluation.

[0180] In combination with Figure 2As shown, in a preferred embodiment of the present application, the final output of the pre-judgment result is a list of shielding events, shielding probability timing, spatial dimension, key shielding parameters, decision suggestions and early warning threshold; wherein the shielding event list contains the start time , end time , duration of each shielding period , and labels the shielding type (terrain / weather / mixed); the shielding probability timing includes an integrated shielding probability output every 10 seconds (terrain shielding probability is calculated based on the shielding ratio of the sampling point, and weather shielding probability is calculated based on the decay threshold probability); the spatial dimension includes a shielding area heat map: showing the shielding frequency (unit: times / 15min) of each area within the next 15 minutes in a 30m grid; the key shielding parameters include the first shielding point coordinates (latitude and longitude), the maximum shielding height difference , shielding angle change curve ; the optimal communication window includes filtering the period with continuous unshielded duration ≥60 seconds and decay ≤5dB, and sorting by communication quality; the early warning threshold is triggered when the prediction is that there will be shielding within 10 seconds (probability ≥90%).

[0181] In another preferred embodiment of the present application, the low-orbit satellite communication terminal performs shielding pre-judgment for the next 10 minutes in the mountain rain and fog area, and the sampling direction has been determined to be along the satellite azimuth (120°), and the sampling point distribution is 100 discrete points with a 10m step in the low elevation (25°) scenario. Along this direction, the integrated terrain height (DEM elevation 320-580m superimposed with no building increment) and weather parameters (precipitation intensity 15mm / h, ground temperature 18℃, cloud height 1.2km) of each sampling point are extracted; combined with the space-time trajectory of the communication link, the corrected line-of-sight height of each point (ground terminal elevation 300m + horizontal distance × tan25° + earth curvature correction + atmospheric refraction correction) is calculated; the rain attenuation (0.3+0.015×15)×1.2 / sin25°≈8.2dB) and cloud layer attenuation (1.2 / sin25°×0.15≈0.43dB) are calculated by the weather attenuation model, and finally the total attenuation 8.63dB is obtained.

[0182] In this optional embodiment, by constructing a standardized dynamic shielding pre-judgment process, the limitations of the existing technology in terrain and weather shielding analysis are effectively broken through, and the precision is insufficient. The introduction of integrated terrain height solves the problem of missed shielding of urban buildings and other artificial facilities, and the corrected line-of-sight height significantly reduces the geometric error in the low-elevation scenario. The differential weather attenuation calculation model is sensitive to the precipitation characteristics of high-frequency satellite communication, avoiding the problem of poor adaptability of a single attenuation model.

[0183] Optionally, the judging whether the preset future time period exists the blockage according to the line-of-sight height and the meteorological parameter signal attenuation amount, and taking the judging result as the blockage pre-judging result, comprises:

[0184] According to the size relationship between the meteorological parameter signal attenuation amount and a preset link margin, it is judged whether the preset future time period exists meteorological blockage;

[0185] If the meteorological parameter signal attenuation amount is greater than or equal to the preset link margin, it is determined that the preset future time period exists the meteorological blockage;

[0186] If the meteorological parameter signal attenuation amount is less than the preset link margin, it is determined that the preset future time period does not exist the meteorological blockage.

[0187] Specifically, first, the abstract meteorological parameter is converted into a quantifiable signal attenuation index, and the blockage state is determined by comparing with the key threshold in the communication link design. The calculation of the meteorological parameter signal attenuation amount is based on a hierarchical refinement model framework. For the Ku / Ka high frequency band commonly used by low-orbit satellites, first, the rain and snow types are distinguished. When it rains, the differentiated coefficient formula is used according to light rain / medium rain (≤10mm / h) and heavy rain / heavy rain (>10mm / h). When it snows, 60% of the rain attenuation of the same intensity is taken, and the cloud layer height and the cloud and fog attenuation calculated by the elevation angle are also taken into account to form a comprehensive evaluation of the total attenuation. The preset link margin is used as the determination reference, which is dynamically valued based on the communication link design standard (default 10dB, with 2 times of redundancy reserved). It not only considers the basic loss of signal transmission, but also reserves a buffer space for sudden meteorological changes. The determination logic adopts a clear binary comparison rule, which directly outputs the conclusion of whether there is meteorological blockage through the size relationship between the attenuation amount and the link margin, avoiding the uncertainty brought by fuzzy determination. At the same time, the determination logic is parallel and independent with the terrain blockage determination logic, ensuring that the influence of meteorological factors on the communication link can be identified separately and accurately, and adapting to the blockage analysis needs in complex weather scenarios such as rain, fog and snow.

[0188] In this optional embodiment, by establishing a standardized meteorological blockage determination rule, the problem of fuzzy meteorological blockage evaluation and poor adaptability to link design in the prior art is effectively solved. Through the hierarchical refinement attenuation calculation model, accurate quantification is realized for different types and intensities of precipitation, which significantly improves the accuracy of meteorological influence evaluation. Through the threshold determination method of link margin, the deep adaptation of meteorological blockage determination and communication system design is realized, avoiding false positives or false negatives caused by deviating from the actual carrying capacity of the link.

[0189] Optionally, the judging whether the preset future time period exists the blockage according to the line-of-sight height and the meteorological parameter signal attenuation amount, and taking the judging result as the blockage pre-judging result, comprises:

[0190] determine whether the terrain occlusion exists in the preset future time period according to a size relationship between the line-of-sight height of each sampling point and the integrated terrain height of the sampling point;

[0191] If the line-of-sight height of each sampling point is greater than or equal to the integrated terrain height corresponding to the sampling point, it is determined that the terrain occlusion does not exist in the preset future time period.

[0192] If the line-of-sight height of any sampling point is less than the integrated terrain height corresponding to the sampling point, it is determined that the terrain occlusion exists in the preset future time period.

[0193] Specifically, the occlusion determination is completed through the quantitative comparison of the line-of-sight height and the integrated terrain height. The integrated terrain height is used as an occlusion quantitative index, and is not a direct reference of single terrain data, but is a fusion of the natural terrain height of digital elevation data and the building height increment of high-precision building white model in the city. It can completely reflect the composite occlusion characteristics of natural terrain and artificial buildings in urban canyons, mountainous areas and other scenes, and solve the problem of missed judgment of building occlusion caused by traditional reliance on digital elevation data.

[0194] In the preferred embodiments of the present application, the terrain occlusion is determined by combining Figure 3 As shown in the figure, the terrain occlusion can be presented in the form of an occlusion analysis effect diagram based on a single-point building white model. The line-of-sight height, as a geometric reference of signal propagation path, is calculated based on the space-time trajectory of the communication link, combined with the ground terminal altitude, the horizontal distance between the sampling point and the terminal, the satellite elevation angle and other parameters, and implicitly includes the double correction of the earth curvature and the atmospheric refraction. That is, the path deviation caused by the earth surface is corrected by the WGS-84 ellipsoid radius, and the influence of atmospheric refraction in low-elevation-angle scenarios is corrected by the ITU-RP.453 model, to ensure that the line-of-sight height calculation conforms to the real physical propagation law. The determination logic adopts the full-point coverage standard, that is, if the terrain height of any sampling point exceeds the line-of-sight height, it is determined that there is an occlusion. The above determination process not only adapts to the straight-line characteristics of low-orbit satellite signal propagation, but also accurately captures any occlusion on the path, including long-distance low-mountain ranges, dense building groups and other easily overlooked occlusion sources. At the same time, it cooperates with the dynamically adjusted sampling point distribution (step adaptation based on elevation angle, density encryption based on terrain ruggedness coefficient), to further improve the accuracy and comprehensiveness of the determination.

[0195] In summary, in the embodiments of the present application, for each sampling time in the future (interval 10 seconds), the occlusion state can be determined by the following logic:

[0196] If the following conditions are met, it is determined that there is an occlusion at time:

[0197] ;

[0198] ;

[0199] where, is the natural terrain height of the ith sampling point, taken from 12.5m precision DEM data, and bound to the geodetic coordinate system after coordinate conversion. is the building height increment of the point (if there is a building, bridge, etc.), taken from the three-dimensional building white model data, and the value is 0 when there is no building.

[0200] The corrected line-of-sight height is:

[0201] ;

[0202] where the basic line-of-sight height is where is the ground terminal altitude (taken from DEM), is the horizontal distance between the sampling point and the terminal (calculated from ECEF coordinates), is the satellite elevation angle (taken from the orbit database); the earth curvature correction amount is (R=6378137m is the WGS-84 ellipsoid long semi-axis).

[0203] The atmospheric refraction correction amount is calculated based on the ITU-R P.453 recommendation model, and the calculation formula is:

[0204] ;

[0205] where the refraction coefficient 0.157 corresponds to the equivalent earth radius 8490km, and is suitable for low elevation angle <30° scene.

[0206] The weather shielding judgment is based on the signal attenuation threshold, and the core parameter calculation is as follows:

[0207] ;

[0208] where the rain attenuation is calculated according to the Ku / Ka frequency band segmented formula (light rain or moderate rain ; when it is heavy rain or heavy rain, .), the snow attenuation is 60% of the same intensity rain attenuation, and the cloud and fog attenuation is calculated based on the cloud height and the elevation angle to calculate the path length, and the attenuation coefficient is 0.15dB / km. The link margin threshold is dynamically valued, and the default is 10dB (according to the Ku / Ka frequency band communication link design standard, 2 times of redundancy is reserved).

[0209] In the optional embodiment, the determination criterion and execution logic of explicit terrain occlusion are used to effectively break through the limitation of low analysis accuracy and high omission rate of complex terrain occlusion in the prior art.

[0210] In combination with Figure 4 As shown in the drawings, the low-orbit satellite communication occlusion pre-judgment system provided by the embodiment of the application comprises:

[0211] A data acquisition module is configured to acquire a future trajectory sequence of a low-orbit satellite and a future trajectory sequence of a ground terminal in a preset future time period, and terrain data and meteorological data of a region of interest of the low-orbit satellite in the preset future time period.

[0212] A link generation module is configured to generate a communication link space-time trajectory according to the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal.

[0213] A space-time binding module is configured to bind the terrain data and the meteorological data in space-time by a conversion relationship between a geodetic coordinate system and a topocentric coordinate system, and generate a space-time correlation matrix.

[0214] A sampling decision module is configured to determine a sampling point distribution of a terrain profile of the region of interest and a sampling step length of the terrain profile of the region of interest according to the space-time correlation matrix in combination with the communication link space-time trajectory.

[0215] An occlusion pre-judgment module is configured to perform dynamic occlusion pre-judgment according to the sampling point distribution and the sampling step length in combination with an atmospheric refraction correction model and a meteorological attenuation model, and obtain an occlusion pre-judgment result of the low-orbit satellite in the preset future time period.

[0216] The low-orbit satellite communication occlusion pre-judgment system of the embodiment has the same advantages as the low-orbit satellite communication occlusion pre-judgment method of the prior art, and thus will not be described here.

[0217] Although the above disclosure is made, the protection scope of the present application is not limited to this. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present application, and these changes and modifications will fall within the protection scope of the present application.

Claims

1. A method for predicting low-Earth orbit satellite communication obstruction, characterized in that, include: Acquire the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal within a preset future time period, as well as the terrain data and meteorological data of the low-orbit satellite over the local area within the preset future time period; Based on the future trajectory sequence of the low-Earth orbit satellite and the future trajectory sequence of the ground terminal, a spatiotemporal trajectory of the communication link is generated; specifically, this includes: aligning the future trajectory sequence of the low-Earth orbit satellite and the future trajectory sequence of the ground terminal with the same time step to obtain the relative position vector between the low-Earth orbit satellite and the ground terminal; The relative position vector is transformed to the station center coordinate system to obtain the elevation angle, azimuth angle and straight-line distance of the low-orbit satellite relative to the ground terminal; By correcting for Earth curvature and combining the elevation angle and azimuth angle, the straight-line distance is geometrically corrected to obtain the spatiotemporal trajectory of the communication link; By transforming the Earth-fixed coordinate system and the station-centered coordinate system, the terrain data and the meteorological data are spatiotemporally bound to generate a spatiotemporal correlation matrix; specifically, this includes: based on the WGS-84 ellipsoid parameters, uniformly transforming the terrain data, the meteorological data, and the future trajectory sequence of the low-orbit satellite to the Earth-fixed coordinate system; The terrain data, meteorological data, and future trajectory sequence of the low-orbit satellite in the Earth-fixed coordinate system are transformed to the station-centered coordinate system with the ground terminal as the origin by a rotation matrix, so as to obtain the real-time attitude data of the low-orbit satellite relative to the ground terminal. The real-time attitude data includes real-time altitude, real-time elevation angle, and real-time azimuth angle. A global timeline is established based on the timestamps of the future trajectory sequence, and the meteorological data is linearly interpolated using the global timeline to generate the satellite orbit timeline of the low-orbit satellite. Based on the satellite orbit time series and the real-time attitude data, the spatiotemporal correlation matrix is ​​obtained; Based on the spatiotemporal correlation matrix and the spatiotemporal trajectory of the communication link, the sampling point distribution of the terrain profile of the region and the sampling step size of the terrain profile of the region are determined. Based on the sampling point distribution and the sampling step size, dynamic occlusion prediction is performed by combining the atmospheric refraction correction model and the meteorological attenuation model to obtain the occlusion prediction result of the low-orbit satellite in the preset future time period.

2. The low-orbit satellite communication obstruction prediction method according to claim 1, characterized in that, The acquisition of the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal within a preset future time period, as well as the terrain data and meteorological data of the low-orbit satellite over the local area within the preset future time period, includes: Obtain the real-time orbital parameters of the low-Earth orbit satellite; Using the SGP4 orbit model, the attitude data of the low-Earth orbit satellite within the preset future time period is obtained by predicting the real-time orbit parameters of the low-Earth orbit satellite. Based on the attitude data, the future trajectory sequence of the low-Earth orbit satellite is generated; By performing integral calculations and attitude calculations, and based on the path data file of the ground terminal, the discrete trajectory points corresponding to each time point within the preset future time period are determined. The future trajectory sequence of the ground terminal is generated based on the discrete trajectory points corresponding to each time point.

3. The low-orbit satellite communication obstruction prediction method according to claim 1, characterized in that, The acquisition of the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal within a preset future time period, as well as the terrain data and meteorological data of the low-orbit satellite over the local area within the preset future time period, includes: The altitude information of the ground region is obtained by extracting the DEM data of the ground region from the low-orbit satellite. The urban building white model data of the ground terminal is spatially overlaid with the DEM data to generate the comprehensive terrain height of the region. The comprehensive terrain height is used as the terrain data; Multiple meteorological parameters within the preset future time period are obtained, and the meteorological parameters are spatially interpolated according to the same grid resolution as the DEM data to obtain the meteorological data.

4. The low-orbit satellite communication obstruction prediction method according to claim 3, characterized in that, The step of determining the sampling point distribution and sampling step size of the terrain profile of the region based on the spatiotemporal correlation matrix and the spatiotemporal trajectory of the communication link includes: Based on the real-time elevation angle and real-time azimuth angle of the low-orbit satellite, and in conjunction with the spatiotemporal trajectory of the communication link, the horizontal projection direction of the real-time connection between the low-orbit satellite and the ground terminal on the horizontal plane is determined. The sampling direction of the terrain profile is determined based on the horizontal projection direction. Based on the real-time altitude and the real-time elevation angle, the sampling range is determined using the radius constraint formula; The real-time elevation angle is divided according to a preset rule, and a corresponding sampling step size is assigned to each real-time elevation angle according to the division result; Along the sampling direction, sampling points are generated within the sampling range according to the sampling step size, thus obtaining the sampling point distribution.

5. The low-orbit satellite communication obstruction prediction method according to claim 4, characterized in that, The step of dynamically predicting occlusion based on the sampling point distribution and the sampling step size, combined with the atmospheric refraction correction model and the meteorological attenuation model, to obtain the occlusion prediction result of the low-orbit satellite within the preset future time period includes: Along the sampling direction, the comprehensive terrain height and meteorological parameters of each sampling point are obtained according to the distribution of the sampling points; Based on the spatiotemporal trajectory of the communication link and the comprehensive terrain elevation, the line-of-sight height of each sampling point is determined; The attenuation of meteorological parameter signals is determined based on the meteorological parameters at the sampling points using the meteorological attenuation model and the atmospheric refraction correction model. Based on the line-of-sight height and the attenuation of the meteorological parameter signal, it is determined whether there is obstruction in the preset future time period, and the determination result is used as the obstruction prediction result.

6. The low-orbit satellite communication obstruction prediction method according to claim 5, characterized in that, The step of determining whether there is obstruction in the preset future time period based on the line-of-sight height and the attenuation of the meteorological parameter signal, and using the determination result as the obstruction prediction result, includes: Based on the relationship between the attenuation of the meteorological parameter signal and the preset link margin, it is determined whether there is meteorological obstruction in the preset future time period; If the attenuation of the meteorological parameter signal is greater than or equal to the preset link margin, then it is determined that the meteorological obstruction exists in the preset future time period. If the attenuation of the meteorological parameter signal is less than the preset link margin, it is determined that there is no meteorological obstruction in the preset future time period.

7. The low-orbit satellite communication obstruction prediction method according to claim 6, characterized in that, The step of determining whether there is obstruction in the preset future time period based on the line-of-sight height and the attenuation of the meteorological parameter signal, and using the determination result as the obstruction prediction result, includes: Based on the relationship between the line-of-sight height of each sampling point and the overall terrain height of the sampling point, it is determined whether there is terrain occlusion in the preset future time period; If the line-of-sight height of each sampling point is greater than or equal to the comprehensive terrain height corresponding to the sampling point, then it is determined that there is no terrain occlusion in the preset future time period. If the line-of-sight height of any of the sampling points is less than the overall terrain height corresponding to the sampling point, then it is determined that the terrain occlusion exists in the preset future time period.

8. A low-orbit satellite communication obstruction prediction system, characterized in that, include: The data acquisition module is used to acquire the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal within a preset future time period, as well as the terrain data and meteorological data of the low-orbit satellite over the local area within the preset future time period. The link generation module is used to generate a communication link spatiotemporal trajectory based on the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal; specifically, it includes: aligning the future trajectory sequence of the low-orbit satellite and the future trajectory sequence of the ground terminal with the same time step to obtain the relative position vector between the low-orbit satellite and the ground terminal; The relative position vector is transformed to the station center coordinate system to obtain the elevation angle, azimuth angle and straight-line distance of the low-orbit satellite relative to the ground terminal; By correcting for Earth curvature and combining the elevation angle and azimuth angle, the straight-line distance is geometrically corrected to obtain the spatiotemporal trajectory of the communication link; The spatiotemporal binding module is used to spatiotemporally bind the terrain data and the meteorological data through the transformation relationship between the ground-fixed coordinate system and the station-centered coordinate system, and generate a spatiotemporal correlation matrix; specifically, it includes: based on the WGS-84 ellipsoid parameters, uniformly converting the terrain data, the meteorological data and the future trajectory sequence of the low-orbit satellite to the ground-fixed coordinate system; The terrain data, meteorological data, and future trajectory sequence of the low-orbit satellite in the Earth-fixed coordinate system are transformed to the station-centered coordinate system with the ground terminal as the origin by a rotation matrix, so as to obtain the real-time attitude data of the low-orbit satellite relative to the ground terminal. The real-time attitude data includes real-time altitude, real-time elevation angle, and real-time azimuth angle. A global timeline is established based on the timestamps of the future trajectory sequence, and the meteorological data is linearly interpolated using the global timeline to generate the satellite orbit timeline of the low-orbit satellite. Based on the satellite orbit time series and the real-time attitude data, the spatiotemporal correlation matrix is ​​obtained; The sampling decision module is used to determine the sampling point distribution and sampling step size of the terrain profile of the region based on the spatiotemporal correlation matrix and the spatiotemporal trajectory of the communication link. The occlusion prediction module is used to perform dynamic occlusion prediction based on the sampling point distribution and the sampling step size, combined with the atmospheric refraction correction model and the meteorological attenuation model, to obtain the occlusion prediction result of the low-orbit satellite in the preset future time period.

Images