Satellite terminal software intelligent adaptation method and system based on artificial intelligence

Abstract

This invention relates to the field of satellite matching technology, and particularly to an intelligent adaptation method and system for satellite terminal software based on artificial intelligence. The method includes: any satellite terminal in a satellite terminal set performing local identification of data to be processed; sorting the data to be processed according to the identification results to obtain a data table; establishing a connection channel with the satellite based on a fixed frequency band for each satellite terminal; uploading data based on the data table after successful connection channel establishment; determining the workload and urgency of each satellite terminal based on the data table; and determining the frequency band update process based on the workload and urgency. This invention determines certain fixed frequency bands based on the resource availability of each satellite terminal, enabling it to adapt to satellites only at these fixed frequency bands. The adaptation process is intermittent, and each satellite terminal uses very few resources for satellite adaptation, allowing most resources to be applied to existing basic work, resulting in extremely high resource utilization.

Description

Technical Field

[0001] This invention relates to the field of satellite matching technology, and in particular to a method and system for intelligent adaptation of satellite terminal software based on artificial intelligence. Background Technology

[0002] In satellite terminal data acquisition scenarios, existing technologies mostly adopt a blind search mode across the entire frequency band to achieve satellite adaptation. This means that all sensor terminals need to independently scan and search the entire frequency band one by one to complete satellite signal adaptation. As a result, a large amount of hardware resources are occupied by the search operation, and the resource allocation for data acquisition and processing is insufficient, which in turn affects the overall operational efficiency.

[0003] Especially in complex field environments, full-range frequency band searches are prone to problems such as signal interference and excessively long search times. Furthermore, each terminal searches independently without information sharing, and repeated search operations further waste resources. The technical problem that this invention aims to solve is how to provide a satellite-adaptive architecture suitable for satellite clusters to optimize resource utilization and enable more resources to be used for core missions. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent adaptation method and system for satellite terminal software based on artificial intelligence, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An artificial intelligence-based intelligent adaptation method for satellite terminal software, the method comprising:

[0007] The data to be processed is locally identified by any satellite terminal in the satellite terminal cluster, and sorted according to the identification results to obtain a data table; wherein, the local identification process has an built-in AI identification process.

[0008] For any satellite terminal, a connection channel with the satellite is established based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded based on a data table. The fixed frequency band is related to the number of satellite terminals in the set.

[0009] The workload and urgency of each satellite terminal are determined based on the data table, and the frequency band update process is determined based on the workload and urgency.

[0010] Among them, there are connection channels between the satellite terminals in the satellite terminal cluster. When any satellite terminal uploads data, the data frequency band is shared. When none of the satellite terminals upload data, the fixed frequency band is restored.

[0011] As a further aspect of the present invention, the step of having any satellite terminal in the satellite terminal set perform local identification of the data to be processed, and sort the data to be processed according to the identification result to obtain a data table includes:

[0012] Query the set of satellite terminals to be processed and obtain the historical uploaded data of each satellite terminal in the set.

[0013] Based on the historical uploaded data, the required identification features and their identification process are determined, and the identification process is sent to the corresponding satellite terminal, while local identification instructions are sent simultaneously; wherein, the identification process includes a process based on the feature extraction model and an AI identification process;

[0014] When any satellite terminal receives a local identification command and identification process, it evaluates the real-time acquired data based on the identification process and determines a data score; the data score is used to characterize the importance of the data at a certain moment.

[0015] The data to be processed is sorted according to the data scores to obtain a data table.

[0016] As a further aspect of the present invention, the step of establishing a connection channel with the satellite based on a fixed frequency band for any satellite terminal, and uploading data based on a data table after the connection channel is successfully established, includes:

[0017] For any satellite terminal, obtain the terminal parameters of the satellite terminal; the terminal parameters include public domain resource quantity and private domain resource quantity; the public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals;

[0018] The frequency band search quantity for each satellite terminal is determined based on the terminal parameters.

[0019] The satellite terminal is read sequentially, and sub-frequency bands are combined sequentially according to the frequency band search quantity. When the required search quantity of the combined sub-frequency bands reaches the frequency band search quantity, the combined sub-frequency band is used as the fixed frequency band of the satellite terminal.

[0020] Each satellite terminal establishes a connection channel with the satellite based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

[0021] As a further aspect of the present invention, the step of sequentially reading the satellite terminal and sequentially combining sub-frequency bands according to the frequency band search quantity includes:

[0022] A preset number of satellite terminal sequences are randomly determined; the satellite terminal sequences are used to characterize the reading order of the satellite terminals.

[0023] The distances between adjacent satellite terminals in the satellite terminal sequence are obtained sequentially to obtain the distance sequence;

[0024] The satellite terminal sequence is optimized based on the distance sequence to determine the final satellite terminal sequence;

[0025] Based on the final satellite terminal sequence, the satellite terminals are read sequentially, and the sub-frequency bands are combined sequentially according to the frequency band search volume.

[0026] As a further aspect of the present invention, the step of determining the workload and urgency of each satellite terminal based on the data table, and determining the frequency band update process based on the workload and urgency, includes:

[0027] The workload is determined based on the data table of each satellite terminal;

[0028] Obtain the data score for each data point in the data table, accumulate the data scores, and obtain the urgency level;

[0029] Establish a connection channel with the historical connection database, query the number of successful connections for each sub-frequency band within a preset time period, and determine the success probability of each sub-frequency band based on the number of successful connections.

[0030] The number of augmentation bands is determined based on the workload and urgency. Sub-bands are selected based on the success probability and merged into fixed bands to complete the band update process.

[0031] The process of selecting sub-bands involves a recursive adjustment process. Once a sub-band is selected, an additional probability is generated. This additional probability is positive and serves as the success probability of subtractive adjustment of the corresponding sub-band. The additional probability is a subtractive function of time.

[0032] As a further aspect of the present invention, the step of sharing the data frequency band when any satellite terminal uploads data, and restoring the fixed frequency band when none of the satellite terminals upload data, includes:

[0033] When any satellite terminal uploads data, its current matching frequency band is read;

[0034] Share the matching frequency band with other satellite terminals;

[0035] When all satellite terminals have not uploaded data, the duration is recorded. When the duration reaches a preset duration threshold, each satellite terminal performs a reset action. The reset action is used to adjust the frequency band to the original fixed frequency band.

[0036] The present invention also provides an intelligent adaptation system for satellite terminal software based on artificial intelligence, the system comprising:

[0037] The data table generation module is used to perform local identification of the data to be processed by any satellite terminal in the satellite terminal set, sort the data to be processed according to the identification results, and obtain a data table; wherein, the local identification process has an built-in AI identification process.

[0038] The data upload module is used to establish a connection channel with the satellite based on a fixed frequency band for any satellite terminal. Once the connection channel is successfully established, data is uploaded based on a data table. The fixed frequency band is related to the number of satellite terminals in the set.

[0039] The frequency band recursive update module is used to determine the workload and urgency of each satellite terminal based on the data table, and to determine the frequency band update process based on the workload and urgency.

[0040] Among them, there are connection channels between the satellite terminals in the satellite terminal cluster. When any satellite terminal uploads data, the data frequency band is shared. When none of the satellite terminals upload data, the fixed frequency band is restored.

[0041] As a further embodiment of the present invention, the data table generation module includes:

[0042] The historical data acquisition unit is used to query the set of satellite terminals to be processed and obtain the historical uploaded data of each satellite terminal in the set of satellite terminals.

[0043] The historical data analysis unit is used to determine the required identification features and their identification process based on the historical uploaded data, and to send the identification process to the corresponding satellite terminal and simultaneously send local identification instructions; wherein, the identification process includes a process based on the feature extraction model and an AI identification process;

[0044] The data scoring generation unit is used to evaluate the real-time acquired data based on the identification process when any satellite terminal receives a local identification instruction and identification process, and to determine the data score; the data score is used to characterize the importance of the data at a certain moment.

[0045] The data sorting unit is used to sort the data to be processed according to the data score to obtain a data table.

[0046] As a further embodiment of the present invention, the data upload module includes:

[0047] The terminal parameter acquisition unit is used to acquire the terminal parameters of any satellite terminal; the terminal parameters include public domain resource quantity and private domain resource quantity; the public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals;

[0048] The search quantity determination unit is used to determine the frequency band search quantity for each satellite terminal based on the terminal parameters.

[0049] A fixed frequency band generation unit is used to sequentially read satellite terminals, sequentially combine sub-frequency bands according to the frequency band search quantity, and when the required search quantity of the combined sub-frequency bands reaches the frequency band search quantity, the combined sub-frequency band is used as the fixed frequency band of the satellite terminal.

[0050] The sequential upload unit is used to establish a connection channel between each satellite terminal and the satellite based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

[0051] As a further embodiment of the present invention, the fixed frequency band generation unit includes:

[0052] A sequence generation subunit is used to randomly determine a preset number of satellite terminal sequences; the satellite terminal sequences are used to characterize the reading order of the satellite terminals;

[0053] The distance acquisition subunit is used to sequentially acquire the distances between adjacent satellite terminals in the satellite terminal sequence to obtain a distance sequence;

[0054] The sequence optimization subunit is used to optimize the satellite terminal sequence based on the distance sequence to determine the final satellite terminal sequence.

[0055] The combination sub-unit is used to sequentially read satellite terminals based on the final satellite terminal sequence and sequentially combine sub-frequency bands according to the frequency band search quantity.

[0056] Compared with the prior art, the beneficial effects of the present invention are:

[0057] This invention identifies and sorts the collected data through satellite terminals. Based on the resource availability of each satellite terminal, it determines certain fixed frequency bands, enabling the satellite to adapt only to these fixed frequency bands. The adaptation process is intermittent. After successful adaptation, the data is uploaded sequentially. Based on intermittent adaptation, important data can also be uploaded faster. Each satellite terminal uses very few resources for satellite adaptation, allowing most resources to be used for existing basic work, resulting in extremely high resource utilization. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0059] Figure 1 A flowchart illustrating the intelligent adaptation method for satellite terminal software based on artificial intelligence provided in this embodiment of the invention.

[0060] Figure 2 This is a block diagram illustrating the composition of an artificial intelligence-based intelligent adaptation system for satellite terminal software, provided in an embodiment of the present invention. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0062] Figure 1 This is a flowchart illustrating an artificial intelligence-based intelligent adaptation method for satellite terminal software provided in an embodiment of the present invention. The method includes:

[0063] Step S100: Any satellite terminal in the satellite terminal set performs local identification on the data to be processed, sorts the data to be processed according to the identification results, and obtains a data table; wherein, the local identification process has an built-in AI identification process.

[0064] Satellite terminals refer to terminals that need to communicate with satellites, including but not limited to information acquisition devices, such as those used in the field. These devices need to allocate limited resources to information acquisition, including accuracy and battery life. Therefore, fewer resources are needed to establish a transmission channel with the satellite. The practical application scenario of this invention is typically a cluster of intelligent acquisition devices in a field area, collectively referred to as a satellite terminal set. Any satellite terminal in the set performs local identification of the data to be processed. This process is actually offline; the data to be processed consists of data acquired at different times. Based on the identification results, the data is sorted to obtain a data table, with each satellite terminal having its own data table. It should be noted that while the data acquisition process is real-time, the data table sorting process can be set to a period, for example, a complete sorting of unuploaded data every preset time interval. For the local identification process, existing data type-based identification algorithms can be used, or an AI identification process can be built-in to identify the data and complete the sorting.

[0065] Step S200: For any satellite terminal, establish a connection channel with the satellite based on a fixed frequency band. Once the connection channel is successfully established, upload data based on the data table. The fixed frequency band is related to the number of satellite terminals in the set.

[0066] For any satellite terminal in the satellite terminal set, different frequency bands are assigned to them. Each satellite terminal will search for and establish a connection channel with the satellite in the corresponding frequency band. In this process, there is no need to perform a search process. Instead, fixed frequency bands are assigned to each satellite terminal, which reduces the resource requirements of the search process. For the satellite terminal set, the amount of resources saved is enormous. It is worth mentioning that how the fixed frequency bands are divided is related to the number of satellite terminal sets. The more satellite terminal sets there are, the more fixed frequency bands are obtained, and the smaller the fixed frequency band for each satellite terminal is. After the connection channel is successfully established, data can be uploaded sequentially based on the data table.

[0067] Step S300: Determine the workload and urgency of each satellite terminal based on the data table, and determine the frequency band update process based on the workload and urgency;

[0068] The data table refers to the data that needs to be uploaded at each satellite terminal. Analyzing this data can yield the workload and urgency of each satellite terminal. The workload indicates how much data has not yet been uploaded, and the urgency indicates whether this data needs to be uploaded urgently. Based on these two parameters, a better resource allocation process can be determined for each satellite terminal. That is, how much of the limited resources should be allocated to searching for satellites and establishing connection channels. If it is a full-band search, it will consume a lot of resources, but the success rate will be extremely high.

[0069] Based on the above, it can be understood that the technical solution of this invention is actually a cluster task processing process. There are connection channels between the satellite terminals in the satellite terminal cluster. When any satellite terminal uploads data, the data frequency band is shared. This means that if one satellite terminal successfully establishes a connection channel with the satellite, then other satellite terminals can use the same frequency band to establish a connection channel with the satellite. When all satellite terminals fail to upload data, it means that a connection channel cannot be established with the satellite in the current frequency band. At this time, it is necessary to search again. The second search still uses the original architecture, that is, to restore the fixed frequency band of each satellite terminal.

[0070] Regarding step S100, the step of having any satellite terminal in the satellite terminal set perform local identification of the data to be processed, sort the data to be processed according to the identification result, and obtain a data table includes:

[0071] Query the set of satellite terminals to be processed and obtain the historical uploaded data of each satellite terminal in the set.

[0072] Based on the historical uploaded data, the required identification features and their identification process are determined, and the identification process is sent to the corresponding satellite terminal, while local identification instructions are sent simultaneously; wherein, the identification process includes a process based on the feature extraction model and an AI identification process;

[0073] When any satellite terminal receives a local identification command and identification process, it evaluates the real-time acquired data based on the identification process and determines a data score; the data score is used to characterize the importance of the data at a certain moment.

[0074] The data to be processed is sorted according to the data scores to obtain a data table.

[0075] The above describes the data table creation process. It involves querying the set of satellite terminals to be processed, obtaining the historical uploaded data of each satellite terminal in the set, determining the data type based on the historical uploaded data, and then determining the features to be extracted based on the data type. These are called demand identification features, including but not limited to: period, mean, and peak value. Each demand identification feature has a corresponding identification process. Since the data collected by the satellite terminals is discrete data, the identification process is essentially a discrete data processing process. Many existing algorithms offer solutions for extracting different features, which will not be elaborated upon here. The identification process is then sent to the corresponding satellite terminal, and local identification instructions are sent synchronously. When any satellite terminal receives the local identification instructions and the identification process, it evaluates the real-time acquired data based on the identification process to determine a data score. The data score is used to determine the upload order of the data to be processed; the higher the data score, the earlier it appears in the data table. In other words, the process of sorting the data to be processed according to the data score to obtain the data table is a descending order sorting process.

[0076] It is worth mentioning that the identification process of the data to be processed includes the process based on the feature extraction model and the AI ​​identification process. The feature extraction model is the existing discrete data processing model used to extract features such as mean, period, and peak value. The AI ​​identification process is a comprehensive model that uses AI models to identify data with higher performance. Its actual architecture can be to set up a centralized port in the area where the satellite terminal set is located, with the AI ​​model built in, and then establish a connection channel between each satellite terminal and the centralized port. This also builds a connection channel between each satellite terminal, which fits the original architecture very well.

[0077] Regarding step S200, the step of establishing a connection channel with the satellite based on a fixed frequency band for any satellite terminal, and uploading data based on a data table after the connection channel is successfully established, includes:

[0078] For any satellite terminal, obtain the terminal parameters of the satellite terminal; the terminal parameters include public domain resource quantity and private domain resource quantity; the public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals;

[0079] The frequency band search quantity for each satellite terminal is determined based on the terminal parameters.

[0080] The satellite terminal is read sequentially, and sub-frequency bands are combined sequentially according to the frequency band search quantity. When the required search quantity of the combined sub-frequency bands reaches the frequency band search quantity, the combined sub-frequency band is used as the fixed frequency band of the satellite terminal.

[0081] Each satellite terminal establishes a connection channel with the satellite based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

[0082] In one embodiment of the technical solution of this invention, the data upload process is defined. For any satellite terminal, the terminal parameters of the satellite terminal are obtained. The terminal parameters include public domain resource quantity and private domain resource quantity. The public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals. The public domain resource quantity and private domain resource quantity are known data, and these two parameters are directly determined for each satellite terminal given that the equipment and mission are known. The frequency band search quantity of each satellite terminal is determined based on the terminal parameters. Generally, the public domain resource quantity and private domain resource quantity can be accumulated according to different weights to obtain a comprehensive resource quantity. The frequency band search quantity is determined proportionally to the comprehensive resource quantity. The search volume is calculated as follows: the total resource volume is directly proportional to both the public and private resource volumes. Its derivative (rate of change, the degree of influence of public and private resource volumes on the total resource volume) is determined by weights and is a preset value; the simplest approach is to use a weight of 0.5 for each. Furthermore, during calculation, the resource volume can be dimensionless to make the calculation process clearer. It should be noted that if the entire search range needs to be allocated to each satellite terminal so that each terminal performs a portion of the search task, the total resource volume of all satellite terminals can be accumulated. Then, the ratio of the total resource volume of each satellite terminal to the accumulated sum can be calculated to obtain a proportion. This proportion can be used to divide the entire search range, yielding the frequency band search volume (interval) for each satellite terminal.

[0083] Then, the satellite terminals are read sequentially, and sub-bands are combined sequentially according to the frequency band search quantity. A sub-band refers to a unit length within the frequency band search range. When the required search quantity of the combined sub-bands reaches the frequency band search quantity, the combined sub-band frequency is used as the fixed frequency band of the satellite terminal. This process is actually combining the unit interval into a large interval corresponding to each satellite terminal. The large interval obtained by combination is the fixed frequency band of each satellite terminal.

[0084] Finally, once each satellite terminal has a fixed frequency band, a connection channel between each satellite terminal and the satellite is established based on that fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

[0085] As a preferred embodiment of the technical solution of the present invention, the step of sequentially reading the satellite terminal and sequentially combining sub-frequency bands according to the frequency band search quantity includes:

[0086] A preset number of satellite terminal sequences are randomly determined; the satellite terminal sequences are used to characterize the reading order of the satellite terminals.

[0087] The distances between adjacent satellite terminals in the satellite terminal sequence are obtained sequentially to obtain the distance sequence;

[0088] The satellite terminal sequence is optimized based on the distance sequence to determine the final satellite terminal sequence;

[0089] Based on the final satellite terminal sequence, the satellite terminals are read sequentially, and the sub-frequency bands are combined sequentially according to the frequency band search volume.

[0090] In one example of the technical solution of this invention, the process of combining sub-frequency bands is described. The original satellite terminal reading process is performed sequentially according to a preset order, which has a certain room for expansion. The above content is one such expansion scheme. A preset number of satellite terminal sequences are randomly determined, which is equivalent to determining the sequential reading order of the satellite terminals. There are many possible numbers. Then, for any satellite terminal sequence, the distances between adjacent satellite terminals in the sequence are obtained sequentially to obtain a distance sequence. The distances are the pairwise distances, and the number of elements in the distance sequence is one less than the number of elements in the satellite terminal sequence. The satellite terminal sequence is optimized based on the distance sequence to determine the final satellite terminal sequence. Based on the final satellite terminal sequence, the satellite terminals are read sequentially, and sub-frequency bands are combined sequentially according to the frequency band search quantity.

[0091] Regarding the optimization of the satellite terminal sequence based on the distance sequence, the average distance in the distance sequence can be calculated. If the satellite terminal sequence with the maximum average distance is selected as the optimal sequence, during the sequential frequency band matching process, adjacent frequency bands will be acquired by two satellite terminals that are spatially far apart. This is equivalent to searching with close frequency bands at two different locations, which can prevent a certain degree of positional interference (a frequency band may be successful, but it is judged as unsuccessful due to the shielding of its location). Conversely, if the satellite terminal sequence with the minimum average distance is selected as the optimal sequence, during the sequential frequency band matching process, adjacent frequency bands will be acquired by two satellite terminals that are spatially close. The spatial position order and frequency band order have a higher degree of consistency and are more coordinated. The specific optimization scheme adopted depends on the needs of the staff. Generally, the satellite terminal sequence with the maximum average distance is used as the optimal sequence.

[0092] Regarding step S300, the step of determining the workload and urgency of each satellite terminal based on the data table, and determining the frequency band update process based on the workload and urgency, includes:

[0093] The workload is determined based on the data table of each satellite terminal;

[0094] Obtain the data score for each data point in the data table, accumulate the data scores, and obtain the urgency level;

[0095] Establish a connection channel with the historical connection database, query the number of successful connections for each sub-frequency band within a preset time period, and determine the success probability of each sub-frequency band based on the number of successful connections.

[0096] The number of augmentation bands is determined based on the workload and urgency. Sub-bands are selected based on the success probability and merged into fixed bands to complete the band update process.

[0097] The process of selecting sub-bands involves a recursive adjustment process. Once a sub-band is selected, an additional probability is generated. This additional probability is positive and serves as the success probability of subtractive adjustment of the corresponding sub-band. The additional probability is a subtractive function of time.

[0098] In one example of the technical solution of this invention, the frequency band update process is specifically defined. The task volume is determined based on the data table of each satellite terminal; this is a simple accumulation process and not complex. Then, the data scores of each data point in the data table are obtained, and the accumulated data scores yield the urgency level. This process can introduce a weight, which is inversely proportional to the order in the data table, so that data with lower order scores have a higher impact on urgency. Then, in an independent process, a connection channel is established with the historical connection database, and the successful connection frequency of each sub-frequency band within a preset time period is queried. The success probability of each sub-frequency band is determined based on the successful connection frequency. The augmentation band quantity is determined based on the task volume and urgency level, and the augmentation band quantity is directly proportional to both the task volume and urgency level. Sub-frequency bands are selected based on the success probability and merged into a fixed frequency band to complete the frequency band update process. The process of selecting sub-frequency bands based on the success probability is not complex; it can be by reading sub-frequency bands in descending order of success probability, or by summing the success probabilities and then normalizing each success probability to obtain the selection probability of the sub-frequency band, which is then used to randomly select a sub-frequency band.

[0099] Regarding the success probability of sub-bands, a correction term is introduced. When a sub-band is selected, an additional probability is generated. This additional probability is a positive value and is used as a subtraction to adjust the success probability of the corresponding sub-band. The additional probability is a subtractive function of time. In simple terms, if a sub-band is selected, its success probability will be reduced by a value, becoming lower. As time goes by, it will gradually recover to prevent the sub-band from being selected indefinitely.

[0100] As a preferred embodiment of the technical solution of the present invention, the step of sharing the data frequency band when any satellite terminal uploads data, and restoring the fixed frequency band when all satellite terminals have not uploaded data includes:

[0101] When any satellite terminal uploads data, its current matching frequency band is read;

[0102] Share the matching frequency band with other satellite terminals;

[0103] When all satellite terminals have not uploaded data, the duration is recorded. When the duration reaches a preset duration threshold, each satellite terminal performs a reset action. The reset action is used to adjust the frequency band to the original fixed frequency band.

[0104] The above describes the frequency band sharing process. When any satellite terminal uploads data, its current matching frequency band is read and shared with other satellite terminals. If an AI center is introduced, it can establish a connection channel with all satellite terminals as a relay to share the matching frequency band. When none of the satellite terminals upload data, the duration is recorded. When the duration is long enough, each satellite terminal performs a reset action. The reset action is used to adjust the frequency band back to the original fixed frequency band.

[0105] Figure 2 The block diagram of the composition structure of the satellite terminal software intelligent adaptation system based on artificial intelligence provided in the embodiments of the present invention, as a preferred embodiment of the technical solution of the present invention, also provides a satellite terminal software intelligent adaptation system based on artificial intelligence, the system 10 comprising:

[0106] The data table generation module 11 is used to perform local identification of the data to be processed by any satellite terminal in the satellite terminal set, and sort the data to be processed according to the identification results to obtain a data table; wherein, the local identification process has an built-in AI identification process.

[0107] The data upload module 12 is used to establish a connection channel with the satellite based on a fixed frequency band for any satellite terminal. After the connection channel is successfully established, data is uploaded based on a data table. The fixed frequency band is related to the number of satellite terminals in the set.

[0108] The frequency band recursive update module 13 is used to determine the workload and urgency of each satellite terminal according to the data table, and to determine the frequency band update process according to the workload and urgency.

[0109] Among them, there are connection channels between the satellite terminals in the satellite terminal cluster. When any satellite terminal uploads data, the data frequency band is shared. When none of the satellite terminals upload data, the fixed frequency band is restored.

[0110] Furthermore, the data table generation module 11 includes:

[0111] The historical data acquisition unit is used to query the set of satellite terminals to be processed and obtain the historical uploaded data of each satellite terminal in the set of satellite terminals.

[0112] The historical data analysis unit is used to determine the required identification features and their identification process based on the historical uploaded data, and to send the identification process to the corresponding satellite terminal and simultaneously send local identification instructions; wherein, the identification process includes a process based on the feature extraction model and an AI identification process;

[0113] The data scoring generation unit is used to evaluate the real-time acquired data based on the identification process when any satellite terminal receives a local identification instruction and identification process, and to determine the data score; the data score is used to characterize the importance of the data at a certain moment.

[0114] The data sorting unit is used to sort the data to be processed according to the data score to obtain a data table.

[0115] Specifically, the data upload module 12 includes:

[0116] The terminal parameter acquisition unit is used to acquire the terminal parameters of any satellite terminal; the terminal parameters include public domain resource quantity and private domain resource quantity; the public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals;

[0117] The search quantity determination unit is used to determine the frequency band search quantity for each satellite terminal based on the terminal parameters.

[0118] A fixed frequency band generation unit is used to sequentially read satellite terminals, sequentially combine sub-frequency bands according to the frequency band search quantity, and when the required search quantity of the combined sub-frequency bands reaches the frequency band search quantity, the combined sub-frequency band is used as the fixed frequency band of the satellite terminal.

[0119] The sequential upload unit is used to establish a connection channel between each satellite terminal and the satellite based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

[0120] Furthermore, the fixed frequency band generation unit includes:

[0121] A sequence generation subunit is used to randomly determine a preset number of satellite terminal sequences; the satellite terminal sequences are used to characterize the reading order of the satellite terminals;

[0122] The distance acquisition subunit is used to sequentially acquire the distances between adjacent satellite terminals in the satellite terminal sequence to obtain a distance sequence;

[0123] The sequence optimization subunit is used to optimize the satellite terminal sequence based on the distance sequence to determine the final satellite terminal sequence.

[0124] The combination sub-unit is used to sequentially read satellite terminals based on the final satellite terminal sequence and sequentially combine sub-frequency bands according to the frequency band search quantity.

[0125] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An artificial intelligence-based satellite terminal software intelligent adaptation method, characterized in that, The method includes: The data to be processed is locally identified by any satellite terminal in the satellite terminal cluster, and sorted according to the identification results to obtain a data table; wherein, the local identification process has an built-in AI identification process. For any satellite terminal, a connection channel with the satellite is established based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded based on a data table. The fixed frequency band is related to the number of satellite terminals in the set. The workload and urgency of each satellite terminal are determined based on the data table, and the frequency band update process is determined based on the workload and urgency. Among them, there are connection channels between the satellite terminals in the satellite terminal cluster. When any satellite terminal uploads data, the data frequency band is shared. When none of the satellite terminals upload data, the fixed frequency band is restored. 2.The AI-based satellite terminal software intelligent adaptation method of claim 1, wherein, The step of having any satellite terminal in the satellite terminal cluster perform local identification of the data to be processed, and sort the data to be processed according to the identification result to obtain a data table includes: Query the set of satellite terminals to be processed and obtain the historical uploaded data of each satellite terminal in the set. Based on the historical uploaded data, the required identification features and their identification process are determined, and the identification process is sent to the corresponding satellite terminal, while local identification instructions are sent simultaneously; wherein, the identification process includes a process based on the feature extraction model and an AI identification process; When any satellite terminal receives a local identification command and identification process, it evaluates the real-time acquired data based on the identification process and determines a data score; the data score is used to characterize the importance of the data at a certain moment. The data to be processed is sorted according to the data scores to obtain a data table. 3.The AI-based satellite terminal software intelligent adaptation method of claim 1, wherein, The steps of establishing a connection channel with the satellite based on a fixed frequency band for any satellite terminal, and uploading data based on a data table after the connection channel is successfully established, include: For any satellite terminal, obtain the terminal parameters of the satellite terminal; the terminal parameters include public domain resource quantity and private domain resource quantity; the public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals; The frequency band search quantity for each satellite terminal is determined based on the terminal parameters. The satellite terminal is read sequentially, and sub-frequency bands are combined sequentially according to the frequency band search quantity. When the required search quantity of the combined sub-frequency bands reaches the frequency band search quantity, the combined sub-frequency band is used as the fixed frequency band of the satellite terminal. Each satellite terminal establishes a connection channel with the satellite based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

4. The artificial intelligence based satellite terminal software intelligent adaptation method according to claim 3, characterized in that, The step of sequentially reading satellite terminals and sequentially combining sub-frequency bands according to the frequency band search volume includes: A preset number of satellite terminal sequences are randomly determined; the satellite terminal sequences are used to characterize the reading order of the satellite terminals. The distances between adjacent satellite terminals in the satellite terminal sequence are obtained sequentially to obtain the distance sequence; The satellite terminal sequence is optimized based on the distance sequence to determine the final satellite terminal sequence; Based on the final satellite terminal sequence, the satellite terminals are read sequentially, and the sub-frequency bands are combined sequentially according to the frequency band search volume. 5.The AI-based satellite terminal software intelligent adaptation method of claim 4, wherein, The steps of determining the workload and urgency of each satellite terminal based on the data table, and determining the frequency band update process based on the workload and urgency, include: The workload is determined based on the data table of each satellite terminal; Obtain the data score for each data point in the data table, accumulate the data scores, and obtain the urgency level; Establish a connection channel with the historical connection database, query the number of successful connections for each sub-frequency band within a preset time period, and determine the success probability of each sub-frequency band based on the number of successful connections. The number of augmentation bands is determined based on the workload and urgency. Sub-bands are selected based on the success probability and merged into fixed bands to complete the band update process. The process of selecting sub-bands involves a recursive adjustment process. Once a sub-band is selected, an additional probability is generated. This additional probability is positive and serves as the success probability of subtractive adjustment of the corresponding sub-band. The additional probability is a subtractive function of time.

6. The artificial intelligence based satellite terminal software intelligent adaptation method according to claim 1, wherein, The steps of sharing the data frequency band when any satellite terminal uploads data and restoring the fixed frequency band when none of the satellite terminals upload data include: When any satellite terminal uploads data, its current matching frequency band is read; Share the matching frequency band with other satellite terminals; When all satellite terminals have not uploaded data, the duration is recorded. When the duration reaches a preset duration threshold, each satellite terminal performs a reset action. The reset action is used to adjust the frequency band to the original fixed frequency band.

7. An artificial intelligence-based satellite terminal software intelligent adaptation system, characterized in that, The system includes: The data table generation module is used to perform local identification of the data to be processed by any satellite terminal in the satellite terminal set, sort the data to be processed according to the identification results, and obtain a data table; wherein, the local identification process has an built-in AI identification process. The data upload module is used to establish a connection channel with the satellite based on a fixed frequency band for any satellite terminal. Once the connection channel is successfully established, data is uploaded based on a data table. The fixed frequency band is related to the number of satellite terminals in the set. The frequency band recursive update module is used to determine the workload and urgency of each satellite terminal based on the data table, and to determine the frequency band update process based on the workload and urgency. Among them, there are connection channels between the satellite terminals in the satellite terminal cluster. When any satellite terminal uploads data, the data frequency band is shared. When none of the satellite terminals upload data, the fixed frequency band is restored.

8. The artificial intelligence based satellite terminal software intelligent adaptation system according to claim 7, wherein, The data table generation module includes: The historical data acquisition unit is used to query the set of satellite terminals to be processed and obtain the historical uploaded data of each satellite terminal in the set of satellite terminals. The historical data analysis unit is used to determine the required identification features and their identification process based on the historical uploaded data, and to send the identification process to the corresponding satellite terminal and simultaneously send local identification instructions; wherein, the identification process includes a process based on the feature extraction model and an AI identification process; The data scoring generation unit is used to evaluate the real-time acquired data based on the identification process when any satellite terminal receives a local identification instruction and identification process, and to determine the data score; the data score is used to characterize the importance of the data at a certain moment. The data sorting unit is used to sort the data to be processed according to the data score to obtain a data table. 9.The AI-based satellite terminal software intelligent adaptation system of claim 7, wherein, The data upload module includes: The terminal parameter acquisition unit is used to acquire the terminal parameters of any satellite terminal; the terminal parameters include public domain resource quantity and private domain resource quantity; the public domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with the satellite, and the private domain resource quantity is used to characterize the resource quantity of the satellite terminal used to establish a connection channel with other satellite terminals; The search quantity determination unit is used to determine the frequency band search quantity for each satellite terminal based on the terminal parameters. A fixed frequency band generation unit is used to sequentially read satellite terminals, sequentially combine sub-frequency bands according to the frequency band search quantity, and when the required search quantity of the combined sub-frequency bands reaches the frequency band search quantity, the combined sub-frequency band is used as the fixed frequency band of the satellite terminal. The sequential upload unit is used to establish a connection channel between each satellite terminal and the satellite based on a fixed frequency band. Once the connection channel is successfully established, data is uploaded sequentially based on the data table.

10. The artificial intelligence based satellite terminal software intelligent adaptation system according to claim 9, wherein, The fixed frequency band generation unit includes: A sequence generation subunit is used to randomly determine a preset number of satellite terminal sequences; the satellite terminal sequences are used to characterize the reading order of the satellite terminals; The distance acquisition subunit is used to sequentially acquire the distances between adjacent satellite terminals in the satellite terminal sequence to obtain a distance sequence; The sequence optimization subunit is used to optimize the satellite terminal sequence based on the distance sequence to determine the final satellite terminal sequence. The combination sub-unit is used to sequentially read satellite terminals based on the final satellite terminal sequence and sequentially combine sub-frequency bands according to the frequency band search quantity.

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