A method, system and storage medium for spectrum self-monitoring for low earth mega-constellation

Abstract

The application discloses a spectrum autonomous monitoring method and system for a low-orbit giant constellation and a storage medium, relates to the fields of electromagnetic spectrum monitoring and satellite signal tracking and identification. In order to solve the problems that the existing spectrum autonomous monitoring scheme cannot realize automatic monitoring, has a large workload, is high in repetition, has data omission, is difficult to realize optimal monitoring planning in a complex multi-satellite scene and cannot cope with the demand of long-term outdoor unattended monitoring tasks, the method comprises the following steps: updating satellite parameters, calculating satellite over-the-top parameters and planning a spectrum detection task, three aspects are realized in an automatic manner, satellite over-the-top time, over-the-top angle, over-the-top direction and other parameters are autonomously calculated based on satellite parameters, a target area and monitoring time, satellite monitoring tasks in a monitoring time period are autonomously planned according to a satellite selection strategy and a monitoring threshold angle, a satellite set used for monitoring is determined, and the monitoring task of the satellite is completed.

Description

Technical Field

[0001] This invention relates to the fields of electromagnetic spectrum monitoring and satellite signal tracking and identification, and mainly to a method for autonomous spectrum monitoring of low-Earth orbit mega-constellations. Background Technology

[0002] Driven by factors such as intensified global satellite competition, ITU filing deadlines, and declining rocket launch and satellite manufacturing costs, the number of low-Earth orbit (LEO) satellites has exploded, making spectrum monitoring of these mega-constellations increasingly challenging. Due to the high speed and short transit times of LEO satellites, monitored satellites exhibit varying transit times and angles within a given timeframe. Therefore, existing autonomous spectrum monitoring schemes inevitably face the following problems when dealing with complex satellite environments:

[0003] (1) Current monitoring methods cannot achieve automated monitoring. Existing solutions require human intervention in satellite selection and monitoring mission planning when dealing with monitoring tasks, as detailed below:

[0004] 1) Existing solutions require manual simulation and selection of satellite ephemeris data, which is labor-intensive, highly repetitive, and prone to data omissions.

[0005] 2) Existing solutions require operators to plan monitoring tasks in advance based on the actual satellite overhead data obtained from simulations. When dealing with complex multi-satellite scenarios, it is difficult to achieve optimal monitoring planning.

[0006] (2) Current monitoring methods lack the convenience of monitoring. Existing schemes require manual adjustment of monitoring tasks. In outdoor experiments, dedicated personnel are needed to update and switch satellite monitoring tasks, which cannot meet the needs of long-term unattended outdoor monitoring tasks.

[0007] Existing technologies for monitoring or risk analysis of large low-Earth orbit (LEO) constellations do not address the difficulties and reasons for spectral monitoring of these constellations. For example, document CN115688996A discloses a method, system, and storage medium for analyzing collision risks of large LEO constellations. This method includes at least one of the following: short-term and long-term collision risk analyses of the LEO constellation. The short-term collision risk analysis calculates the collision probability of the LEO constellation satellites in the short term, including: analysis of the propagation curve of space target orbit prediction errors, initial screening of hazardous space targets, space target approach analysis, and calculation of the probability of collision between two space targets. The long-term collision risk analysis calculates the average collision probability of the constellation over its lifespan, including: a simplified model, calculation of space target density, calculation of space target decay rate, calculation of the number of collision debris, and calculation of the average collision probability over the constellation's lifespan. This method can analyze the collision risks of large LEO constellations in both the short and long term to ensure constellation safety.

[0008] Therefore, it is particularly important to propose satellite monitoring tasks that can be autonomously planned within a monitoring period based on relevant parameters, satellite selection strategies, and monitoring threshold angles. Summary of the Invention

[0009] The technical problem to be solved by this invention is:

[0010] This invention overcomes the shortcomings of existing technologies and proposes an autonomous spectrum monitoring method for large low-Earth orbit constellations. This method automates the process from three perspectives: satellite parameter updating, satellite overpass parameter calculation, and spectrum detection task planning. Based on satellite parameters, target area, and monitoring time, it autonomously calculates parameters such as satellite overpass time, overpass angle, and overpass direction. According to the satellite selection strategy and monitoring threshold angles, it autonomously plans satellite monitoring tasks within the monitoring period, determines the set of satellites to be monitored, and completes the satellite monitoring tasks.

[0011] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0012] The present invention provides a method for autonomous spectrum monitoring of low-Earth orbit mega-constellations, comprising the following steps:

[0013] Step 1: Automatic Ephemeris Update: Configure the URLs and data reliability priorities of ephemeris websites, and automatically download the latest ephemeris information from multiple source websites to ensure that the ephemeris information in the database is always up-to-date;

[0014] Step 2, Servo Antenna BeiDou Information Synchronization: After the field equipment is set up and the BeiDou equipment and software (within the scope of existing technology) are properly connected, the software will synchronize the BeiDou position information of the servo antenna and update the position data of the monitored area, including longitude, latitude and altitude.

[0015] Step 3: Setting monitoring mission parameters: Set the necessary parameters for the monitoring mission, including start time, end time, and satellite name, etc. Generate the parameters of the low-Earth orbit mega-constellation satellites based on the satellite's monitorable status, including overpass time, overpass direction, and overpass angle, etc., and complete the first data screening of the monitorable low-Earth orbit satellite data;

[0016] Step 3.1: Read the ephemeris data of the target satellite;

[0017] Step 3.2: Convert the corresponding ephemeris data from TLE data into latitude, longitude, and altitude data at different times (from the start time to the end time of monitoring) using the SDP4 / SGP4 model (SDP4 / SGP4 is a dedicated model, and the open-source code can be obtained from existing technologies);

[0018] Step 3.3: Calculate the visibility between the monitoring equipment and the satellite at different times based on the converted location; the visibility calculation method is as follows.

[0019] Calculate the distance D between the satellite and the monitoring equipment:

[0020]

[0021] In the above formula, x1, y1, and z1 are the position vectors of the satellite, and x2, y2, and z2 are the position vectors of the monitoring equipment;

[0022] The distance R1 from the satellite to the Earth's center is: The distance R2 from the monitoring equipment to the Earth's center is: Distance D of satellites and monitoring equipment to the horizon i :

[0023]

[0024] In the above formula, R e The radius of the Earth;

[0025] When the distance D between the satellite and the monitoring equipment is less than D1+D2, the satellite and the earth station are visible to each other.

[0026] Step 3.4: Calculate the continuous visible time between the satellite and the monitoring equipment to obtain the overpass time (last visible time T1 - first visible time T0), and analyze the motion direction during the overpass to obtain monitoring parameters such as the overpass direction and overpass angle.

[0027] Step 4: Monitoring Task Plan Generation: Based on the satellite parameters obtained in Step 3, according to the satellite selection strategy and monitoring threshold angle, a second data screening of low-orbit satellites is performed, and a task list and preprocessed files for the monitoring satellite plan within the monitoring period are automatically generated.

[0028] Satellite selection strategy: Since the transit times of different satellites overlap, the satellite selection strategy can be divided into "optimal monitoring quantity strategy" and "full cycle execution strategy" based on the execution of the monitoring mission.

[0029] 1) Optimal monitoring quantity strategy: For multiple monitoring tasks that overlap in time, the monitoring tasks will be executed in the order of their start time. Once a monitoring task is completed, the next monitoring task will be executed immediately.

[0030] 2) Complete cycle execution strategy: For multiple monitoring tasks that overlap in time, the satellite selection strategy will ensure that the monitoring task of each satellite is executed completely. After a monitoring task is completed, the monitoring tasks that overlap with that task in time will be skipped and the next complete monitoring task will be executed.

[0031] Monitoring threshold angle: The maximum angle between the satellite and the ground and antenna when the satellite passes overhead is called the monitoring angle. When the monitoring angle is lower than the threshold, the satellite signal is easily blocked by obstacles such as buildings and mountains, which affects the quality of signal monitoring.

[0032] Step 5: Monitoring Task Execution: Execute the monitoring task according to the time period of the task in the task list, read the corresponding preprocessing analysis and perform time segmentation to form fine-grained execution instructions, and issue instructions to control the servo to align with the satellite to achieve precise tracking of the satellite.

[0033] Step 5 refers to the antenna being able to accurately align with the satellite according to the instructions, thus completing the precise tracking of the satellite. Its precision is reflected in the previous steps: the precision of tracking is reflected in the precision of the antenna pointing instructions, and the precision of pointing comes from the precision of the direction calculation, which in turn comes from the accuracy of the satellite ephemeris and the accuracy of the SGP4 / SDP4 model.

[0034] Step 6: Storage and display of spectrum monitoring data: When performing satellite spectrum monitoring tasks, the control monitoring board is specified to collect monitoring spectrum information data, format the streaming data and use multi-threaded storage to store the data, and then store and display the data.

[0035] The present invention has the following beneficial technical effects:

[0036] The technology proposed in this invention effectively solves the problems of existing autonomous spectrum monitoring schemes in dealing with complex satellite environments, such as the inability to achieve automated monitoring, high workload and repetition, data omissions, difficulty in achieving optimal monitoring planning in complex multi-satellite scenarios, and inability to meet the needs of long-term unattended outdoor monitoring tasks. The method of this invention achieves automation from three aspects: "satellite parameter update - satellite overpass parameter calculation - spectrum detection task planning." Based on satellite parameters, target area, and monitoring time, it autonomously calculates parameters such as satellite overpass time, overpass angle, and overpass direction. According to the satellite selection strategy and monitoring threshold angle, it autonomously plans satellite monitoring tasks within the monitoring time period, determines the set of satellites to be monitored, and completes the satellite monitoring task.

[0037] Compared with existing technologies, this invention has the following advantages: This method achieves automatic planning of monitoring tasks. This invention autonomously updates satellite ephemeris data and calculates satellite overpass conditions; it automatically updates local database satellite ephemeris data based on a configured website, realizes satellite overpass simulation, and saves satellite overpass data. This invention autonomously plans overpass satellite monitoring tasks within the monitoring period. Based on the set satellite selection strategy and monitoring angle threshold, it constructs a satellite set within the monitoring period based on BeiDou position, satellite parameters, and monitoring time, and autonomously plans the spectrum monitoring task.

[0038] This invention and method enable long-term unattended outdoor monitoring. During long-term outdoor monitoring missions, the operator only needs to set the monitoring time period and relevant information about the monitoring target; satellite spectrum monitoring and data storage can be achieved without dedicated personnel on duty. Attached Figure Description

[0039] Figure 1 This is a flowchart of the monitoring task execution in this invention;

[0040] Figure 2 This is a schematic diagram of a star selection strategy in this invention;

[0041] Figure 3 A schematic diagram of another star selection strategy in this invention;

[0042] Figure 4 This is a schematic diagram of the included angle monitoring in this invention;

[0043] Figure 5 This is the overall block diagram of the system described in this invention. Figure 5 In the text, the software processing module describes the processing flow of the algorithm proposed in this invention, which consists of steps 1 to 5. Then, the instruction formed in step 5 is sent to the servo antenna, and the antenna feeds back the monitoring data to the software processing module corresponding to step 6. Detailed Implementation

[0044] Specific implementation method one: as follows Figures 1 to 5 As shown, the autonomous spectrum monitoring method for low-Earth orbit mega-constellations described in this invention includes the following steps:

[0045] Step 1: Automatic Ephemeris Update: Configure the URLs and data reliability priorities of ephemeris websites, and automatically download the latest ephemeris information from multiple source websites to ensure that the ephemeris information in the database is always up-to-date;

[0046] The system developed using the method of this invention can automatically download ephemeris data from the following websites: www.ucsusa.org, www.space-track.org, and CelesTrak:EOP and Space Weather Data.

[0047] Step 2, Servo Antenna BeiDou Information Synchronization: After the field equipment is set up and the BeiDou equipment and software (within the scope of existing technology) are properly connected, the software will synchronize the BeiDou position information of the servo antenna and update the position data of the monitored area, including longitude, latitude and altitude.

[0048] Step 3: Setting monitoring mission parameters: Set the necessary parameters for the monitoring mission, including start time, end time, and satellite name, etc. Generate the parameters of the low-Earth orbit mega-constellation satellites based on the satellite's monitorable status, including overpass time, overpass direction, and overpass angle, etc., and complete the first data screening of the monitorable low-Earth orbit satellite data;

[0049] Step 3.1: Read the ephemeris data of the target satellite;

[0050] Step 3.2: Convert the corresponding ephemeris data from TLE data into latitude, longitude, and altitude data at different times (from the start time to the end time of monitoring) using the SDP4 / SGP4 model (SDP4 / SGP4 is a dedicated model, and the open-source code can be obtained from existing technologies);

[0051] Step 3.3: Calculate the visibility between the monitoring equipment and the satellite at different times based on the converted location; the visibility calculation method is as follows.

[0052] Calculate the distance D between the satellite and the monitoring equipment:

[0053]

[0054] In the above formula, x1, y1, and z1 are the position vectors of the satellite, and x2, y2, and z2 are the position vectors of the monitoring equipment;

[0055] The distance R1 from the satellite to the Earth's center is: The distance R2 from the monitoring equipment to the Earth's center is: Distance D of satellites and monitoring equipment to the horizoni :

[0056]

[0057] In the above formula, R e The radius of the Earth;

[0058] When the distance D between the satellite and the monitoring equipment is less than D1+D2, the satellite and the earth station are visible to each other.

[0059] Step 3.4: Calculate the continuous visible time between the satellite and the monitoring equipment to obtain the overpass time (last visible time T1 - first visible time T0), and analyze the motion direction during the overpass to obtain monitoring parameters such as the overpass direction and overpass angle;

[0060] Step 4: Monitoring Task Plan Generation: Based on the satellite parameters obtained in Step 3, according to the satellite selection strategy and monitoring threshold angle, a second data screening of low-orbit satellites is performed, and a task list and preprocessed files for the monitoring satellite plan within the monitoring period are automatically generated.

[0061] Satellite selection strategy: Since the transit times of different satellites overlap, the satellite selection strategy can be divided into "optimal monitoring quantity strategy" and "full cycle execution strategy" based on the execution of the monitoring mission.

[0062] 1) Optimal monitoring quantity strategy: For multiple monitoring tasks that overlap in time, the monitoring tasks will be executed in the order of their start time. Once a monitoring task is completed, the next monitoring task will be executed immediately.

[0063] 2) Complete cycle execution strategy: For multiple monitoring tasks that overlap in time, the satellite selection strategy will ensure that the monitoring task of each satellite is executed completely. After a monitoring task is completed, the monitoring tasks that overlap with that task in time will be skipped and the next complete monitoring task will be executed.

[0064] Monitoring threshold angle: The maximum angle between the satellite and the ground and antenna when the satellite passes overhead is called the monitoring angle. When the monitoring angle is lower than the threshold, the satellite signal is easily blocked by obstacles such as buildings and mountains, which affects the quality of signal monitoring.

[0065] Step 5: Monitoring Task Execution: Execute the monitoring task according to the time period of the task in the task list, read the corresponding preprocessing analysis and perform time segmentation to form fine-grained execution instructions, and issue instructions to control the servo to align with the satellite to achieve precise tracking of the satellite.

[0066] Step 5 refers to the antenna being able to accurately align with the satellite according to the instructions, thus completing the precise tracking of the satellite. Its precision is reflected in the previous steps: the precision of tracking is reflected in the precision of the antenna pointing instructions, and the precision of pointing comes from the precision of the direction calculation, which in turn comes from the accuracy of the satellite ephemeris and the accuracy of the SGP4 / SDP4 model.

[0067] Step 6: Storage and display of spectrum monitoring data: When performing satellite spectrum monitoring tasks, the control monitoring board is specified to collect monitoring spectrum information data, format the streaming data and use multi-threaded storage to store the data, and then store and display the data.

[0068] To better understand this invention, the following description is in conjunction with the appendix. Figure 1-5 Examples will further illustrate the content of this invention.

[0069] Example 1: The autonomous spectrum monitoring method for giant low-Earth orbit constellations proposed in this example can complete the screening of over-the-head satellites and the planning of monitoring tasks according to requirements such as the type of monitoring satellite and the monitoring time. Taking Starlink constellation satellites as an example, it includes the following steps:

[0070] S1. Set the monitoring target type to Starlink, and the software (corresponding) Figure 5 The software processing module (which is the same software) automatically retrieves the latest Starlink ephemeris data from multiple ephemeris websites and updates the ephemeris information in the local database according to the reliability priority of the data.

[0071] S2. Complete the setup of the experimental equipment, connect the software to the Beidou positioning device, and automatically update the latitude, longitude, and altitude information of the current monitoring location to the software system for subsequent satellite overhead parameter calculations;

[0072] S3. Set the start and end times of the monitoring task, traverse the satellite list, and use multi-threaded calculation to determine the satellite overhead situation within the monitoring time range, including overhead time, overhead angle, and satellite running direction, etc., and form a set of monitorable satellites based on monitoring requirements to achieve the first screening of data;

[0073] S4. Sort the monitorable satellite tasks according to the satellite overpass time, and perform a second screening of the monitorable satellite set according to the monitoring threshold angle to remove overpass satellites whose maximum monitoring angle is lower than the threshold angle. Plan the monitoring tasks according to the satellite selection strategy, generate the final monitoring task list, and preprocess the task items to form a preprocessed file of the satellite position and servo antenna angle at the corresponding time.

[0074] S5. Execute monitoring tasks sequentially according to the time slices of the generated monitoring task list, read the corresponding preprocessing files and perform time segmentation to form fine-grained execution instructions, and control the servo antenna to achieve precise tracking of the satellite;

[0075] S6. When performing satellite tracking tasks, the system simultaneously sends a command to a designated control board to collect and monitor spectrum information data, formats the streaming data, uses multi-threaded storage, and draws a spectrum graph for real-time display based on fixed time intervals.

[0076] Example:

[0077] like Figure 1 As shown, the process of autonomous spectrum monitoring of low-Earth orbit mega-constellations by the software system developed based on the technical solution of this invention is as follows:

[0078] First, the system is initialized, then the BeiDou information is synchronized and the latitude, longitude and altitude are updated sequentially; task parameters are set and the satellite list is selected; the satellite list is traversed to obtain the TLE data of the satellites;

[0079] After traversing the satellite list to obtain the TLE data of the satellites, for each satellite, calculate the elevation angle per second within the range from the start time to the end time, and then determine whether the elevation angle is greater than or equal to the minimum angle. If so, record the current time, azimuth, antenna elevation angle and other information to the file and update the maximum angle record; otherwise, calculate the elevation angle per second within the range from the start time to the end time again until the elevation angle is greater than or equal to the minimum angle.

[0080] Record the current time, azimuth angle, antenna elevation angle, and other information to a file. After updating the maximum recorded angle, continue to check if the antenna elevation angle is less than the minimum angle. If not, stop writing to the file and plan to save the file.

[0081] If the maximum monitoring angle is less than the threshold angle, delete the file and plan the pre-stored file; if yes, the calculation of a single satellite ends and the calculation of the next satellite begins.

[0082] Simultaneously, a list of satellites that meet the satellite pairing criteria is generated from the satellite's TLE data. This list is then sorted by start time, and based on the satellite selection strategy (optimal monitoring quantity strategy, complete cycle execution strategy), monitoring tasks are assigned and executed.

[0083] Verification has shown that the method proposed in this invention solves the technical problem raised in this invention, and practical application has verified the technical effects and practicality claimed in this invention.

[0084] The method described in this invention has been verified through simulation experiments and practical applications, demonstrating the technical effects claimed by this invention.

[0085] The algorithm (method) proposed in this invention is the underlying technical core of this invention, and various products can be derived based on the algorithm.

[0086] Based on the algorithm (method) proposed in this invention, a spectrum autonomous monitoring system for low-Earth orbit mega-constellations is developed using a programming language. This system has program modules corresponding to the steps of the above-described technical solution, and executes the steps in the above-described method for autonomous spectrum monitoring of low-Earth orbit mega-constellations during runtime.

[0087] The developed system (software) computer program is stored on a computer-readable storage medium, and the computer program is configured to implement the steps of the above-described method for autonomous spectrum monitoring of a low-Earth orbit mega-constellation when invoked by a processor. In other words, the invention is materialized on a carrier, becoming a computer program product.

[0088] An autonomous spectrum monitoring device for a low-Earth orbit (LEO) mega-constellation is disclosed. The device includes at least one processor and a memory communicatively connected to the at least one processor. The memory stores instructions executable by the at least one processor. These instructions are executed by the at least one processor to enable the at least one processor to perform the aforementioned autonomous spectrum monitoring method for a LEO mega-constellation, thereby achieving autonomous spectrum monitoring of the LEO mega-constellation.

[0089] Various implementations of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, application-specific integrated circuits (ASICs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transferring data and instructions to the storage system, the at least one input device, and the at least one output device.

[0090] The computational programs (also referred to as programs, software, software applications, or code) of this invention include machine instructions of a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device PLD) for providing machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0091] It should be understood that the various processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, they are all within the protection scope of this invention.

Claims

1. A method for autonomous spectrum monitoring of low-Earth orbit mega-constellations, characterized in that, The implementation process of the method is as follows: Step 1: Automatic Ephemeris Update: Configure the URLs and data reliability priorities of ephemeris websites, and automatically download the latest ephemeris information from multiple source websites to ensure that the ephemeris information in the database is always up-to-date; Step 2, Servo Antenna BeiDou Information Synchronization: After the field equipment is set up and the BeiDou equipment is properly connected to the software, the software will synchronize the BeiDou position information of the servo antenna and update the position data of the monitored area, including longitude, latitude and altitude. Step 3: Setting monitoring mission parameters: Set the necessary parameters for the monitoring mission, including start time, end time, and satellite name, etc. Generate the parameters of the low-Earth orbit mega-constellation satellites based on the satellite's monitorable status, including overpass time, overpass direction, and overpass angle, etc., and complete the first data screening of the monitorable low-Earth orbit satellite data; Step 4: Monitoring Task Plan Generation: Based on the satellite parameters obtained in Step 3, according to the satellite selection strategy and monitoring threshold angle, a second data screening of low-orbit satellites is performed, and a task list and preprocessed files for the monitoring satellite plan within the monitoring period are automatically generated. Step 5: Monitoring Task Plan Execution: Execute the monitoring task according to the time period of the task in the task list, read the corresponding preprocessing analysis and perform time segmentation to form fine-grained execution instructions, and issue instructions to control the servo to align with the satellite to achieve precise tracking of the satellite; Step 6: Storage and display of spectrum monitoring data: When performing satellite spectrum monitoring tasks, the control monitoring board is specified to collect monitoring spectrum information data, format the streaming data and use multi-threading to store the data, and perform data storage and interface display. The specific implementation process in step 3 is as follows: Step 3.1: Read the ephemeris data of the target satellite; Step 3.2: Convert the corresponding ephemeris data from TLE data into latitude, longitude, and altitude data for different times, i.e., from the start time to the end time of monitoring, using the SDP4 / SGP4 model; Step 3.3: Calculate the visibility between the monitoring equipment and the satellite at different times based on the converted location; the visibility calculation method is as follows. Calculate the distance D between the satellite and the monitoring equipment: In the above formula, x1, y1, and z1 are the position vectors of the satellite, and x2, y2, and z2 are the position vectors of the monitoring equipment; The distance R1 from the satellite to the Earth's center is: The distance R2 from the monitoring equipment to the Earth's center is: Distance of satellites and monitoring equipment to the horizon : In the above formula, The radius of the Earth; When the distance D between the satellite and the monitoring equipment is less than D1+D2, the satellite and the earth station are visible to each other. Step 3.4: Count the continuous visible time between the satellite and the monitoring equipment to obtain the overpass time, and analyze the motion direction during the overpass to obtain monitoring parameters such as the overpass direction and overpass angle; In step 4, Satellite selection strategy: Since the transit times of different satellites overlap, the satellite selection strategy can be divided into "optimal monitoring quantity strategy" and "full cycle execution strategy" based on the execution of the monitoring task. 1) Optimal monitoring quantity strategy: For multiple monitoring tasks that overlap in time, the monitoring tasks will be executed in the order of their start time. Once a monitoring task is completed, the next monitoring task will be executed immediately. 2) Complete cycle execution strategy: For multiple monitoring tasks that overlap in time, the satellite selection strategy will ensure that the monitoring task of each satellite is executed completely. After a monitoring task is completed, the monitoring tasks that overlap with that task in time will be skipped and the next complete monitoring task will be executed.

2. The autonomous spectrum monitoring method for low-Earth orbit mega-constellations according to claim 1, characterized in that, In step 4, the monitoring threshold angle is specifically defined as the maximum angle between the satellite and the ground and antenna when the satellite passes overhead, which is called the monitoring angle. When the monitoring angle is lower than the threshold, the satellite signal is easily blocked by obstacles such as buildings and mountains, affecting the quality of signal monitoring.

3. The method for autonomous spectrum monitoring of low-Earth orbit mega-constellations according to claim 2, characterized in that, Step 5 is used to enable the antenna to be precisely aligned with the satellite according to the instructions, and to complete the precise tracking of the satellite.

4. A method and system for autonomous spectrum monitoring of low-Earth orbit mega-constellations, characterized in that: The system has a program module corresponding to the steps described in any one of claims 1-3, and executes the steps in the autonomous spectrum monitoring method for low-Earth orbit mega-constellations when it is run.

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program configured to, when invoked by a processor, implement the steps of the autonomous spectrum monitoring method for a low-Earth orbit mega-constellation according to any one of claims 1-3.

6. A spectrum autonomous monitoring device for a low-Earth orbit mega-constellation, the device comprising at least one processor and a memory communicatively connected to the at least one processor, wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the autonomous spectrum monitoring method for a low-Earth orbit mega-constellation as described in any one of claims 1-3, and to complete the satellite monitoring task.

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