Satellite-ground integrated unmanned aerial vehicle communication channel management method and system based on AI

Abstract

The invention is suitable for the technical field of satellite communication, and provides an AI-based satellite-ground integrated unmanned aerial vehicle communication channel management method and system, and the method comprises the steps: obtaining the real-time temperature of a radio frequency front-end module of a current unmanned aerial vehicle satellite communication terminal under the condition of determining that a reference temperature node exists, and when the real-time temperature exceeds the reference temperature node, cooling measures of the unmanned aerial vehicle are controlled based on the temperature node, so that the temperature of the radio frequency front-end module is adjusted to be below the reference temperature node in a future time period. According to the method, existing communication links and cooling hardware structures are not changed, the communication stability and reliability after low-orbit satellite link switching can be improved only through control strategy optimization, the risks of short-time link falling and performance degradation are reduced, finer and more intelligent satellite-ground integrated unmanned aerial vehicle communication channel management is achieved, and the method has remarkable engineering practical value.

Description

Technical Field

[0001] This invention belongs to the field of satellite communication technology, and in particular relates to an AI-based method and system for managing communication channels of unmanned aerial vehicles (UAVs) integrating space and ground. Background Technology

[0002] With the widespread application of drones in surveying and inspection, emergency communications, and maritime operations, their communication capabilities are gradually evolving from single-ground communication to a combined ground-satellite communication mode. In existing technologies, drones typically possess both ground and satellite communication links. When the ground communication link is obstructed, has weak coverage, or is unstable, it can switch to a low-Earth orbit satellite communication link to ensure communication continuity. Related technologies are now able to predict and determine whether a communication link switch is necessary by monitoring communication quality, flight position, or combining map information, and execute the switch from the ground communication link to the satellite communication link when the switching conditions are met, thus maintaining the drone's data transmission and control capabilities.

[0003] However, in existing integrated satellite-ground UAV communication systems, communication channel management primarily focuses on external link conditions and network resource status. Handover decisions are typically based on macroscopic indicators such as signal strength, bit error rate, or coverage, with less consideration given to the impact of the internal state of individual UAV terminals on the handover effect. In practical applications, especially in scenarios where multiple UAVs perform the same or similar tasks, even under the same communication link handover conditions, different UAVs may still exhibit significant differences in communication performance after switching from the ground link to the satellite link. This can manifest as short-term link drops, communication quality fluctuations, or data transmission performance degradation. Existing technologies struggle to effectively explain these differences and lack targeted control measures, typically resorting only to passive responses such as increasing handover redundancy or relaxing communication performance requirements.

[0004] Research has revealed that a key reason for the aforementioned problems lies in the failure of existing technologies to identify and utilize the impact of the temperature state of the satellite communication terminal's radio frequency (RF) front-end module on the effectiveness of communication link handover. Temperature variations in the RF front-end module affect frequency offset compensation, transmit power, and phase stability, thus significantly impacting low-Earth orbit (LEO) satellite communication access and handover stability. However, existing communication channel management schemes do not incorporate this factor into the handover decision-making and execution process, resulting in a lack of proactive adjustment capabilities for terminal status before handover. Therefore, identifying the impact of terminal temperature on handover benefits without altering the existing communication link structure and hardware configuration, and proactively adjusting the status when a satellite-to-ground communication link handover is predicted to be necessary, to improve post-handover communication stability and reliability, has become a critical technical problem that urgently needs to be addressed by existing technologies. Summary of the Invention

[0005] The purpose of this invention is to provide an AI-based method and system for managing communication channels of unmanned aerial vehicles (UAVs) that integrates space and ground systems, in order to solve the problems mentioned in the background art.

[0006] This invention is implemented as follows: an AI-based method for managing communication channels of integrated space-ground unmanned aerial vehicles (UAVs), the method comprising:

[0007] In the event that the drone will switch from a terrestrial communication link to a low-Earth orbit satellite communication link in the future, historical communication operation data of the drone is obtained.

[0008] Based on historical communication operation data, multiple sets of historical handover control sample groups were extracted. Each set of historical handover control sample groups includes samples that performed channel handover and samples that did not perform channel handover under the same handover conditions and operating conditions, and the same temperature of the radio frequency front-end module of the satellite communication terminal. The radio frequency front-end module temperature is different for different historical handover control sample groups.

[0009] Analyze each historical switching control sample group to obtain the communication performance improvement index of performing channel switching compared to not performing channel switching; determine whether there is a reference temperature node of the RF front-end module that causes the communication performance improvement index to be lower than a preset threshold;

[0010] If a reference temperature node is identified, the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal is obtained. When the real-time temperature exceeds the reference temperature node, the cooling measures of the UAV are controlled based on the temperature node to adjust the temperature of the radio frequency front-end module below the reference temperature node in the future.

[0011] As a further limitation of the technical solution of the present invention, the historical switching comparison sample group includes at least two historical samples. The two historical samples correspond to the UAV in the past when it was performing a mission. Under the same conditions as the current situation, the communication link switching situation and the temperature of the satellite communication terminal radio frequency front-end module are the same. One historical sample performed a communication channel switching, and the other historical sample did not perform a communication channel switching.

[0012] As a further limitation of the technical solution of the present invention, the sample is consistent with the current communication link switching situation and working conditions, specifically referring to the sample and the current UAV being in the same or equivalent communication link switching trigger conditions, flight status parameters and communication service load conditions when performing the task.

[0013] As a further limitation of the technical solution of this embodiment of the invention, the calculation process of the communication effect improvement index includes:

[0014] Each historical sample in the historical handover control sample group is analyzed to distinguish between samples that have performed communication channel handover and samples that have not performed communication channel handover.

[0015] Using the moment when the communication link switching conditions are met as the time reference, and the moment after the same preset time interval from the time reference as the reference time point, at least one communication performance indicator is obtained for the sample that performs communication channel switching and the sample that does not perform communication channel switching within a preset period after the reference time point; the communication performance indicator includes signal-to-noise ratio, bit error rate, and data transmission delay.

[0016] Based on the communication performance indicators, the communication effect of performing communication channel switching and the communication effect of not performing communication channel switching are calculated respectively, and the communication effect improvement index is determined according to the improvement of the communication effect of performing communication channel switching relative to the communication effect of not performing communication channel switching.

[0017] As a further limitation of the technical solution of this invention, the step of determining whether there is a radio frequency front-end module reference temperature node that causes the communication performance improvement index to be lower than a preset threshold includes:

[0018] Several historical switching control sample groups are sorted from smallest to largest according to the corresponding radio frequency front-end module temperature to obtain a sample group sequence, and the corresponding communication performance improvement index change curve is extracted based on the sample group sequence.

[0019] The communication effect improvement index change curve is analyzed to identify whether there is a temperature node, such that in the sample group before the temperature node, the corresponding communication effect improvement index is higher than the preset threshold, while after the temperature node, the communication effect improvement index is lower than the preset threshold in more than a preset number of consecutive sample groups.

[0020] If a temperature node that meets the above conditions is identified, the temperature node is determined to be the reference temperature node of the radio frequency front-end module.

[0021] As a further limitation of the technical solution of this embodiment of the invention, when a reference temperature node is determined to exist, the steps of obtaining the real-time temperature of the radio frequency front-end module of the current UAV satellite communication terminal, and controlling the cooling measures of the UAV based on the temperature node when the real-time temperature exceeds the reference temperature node, so as to adjust the temperature of the radio frequency front-end module to below the reference temperature node in the future include:

[0022] Obtain the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal, and determine whether the real-time temperature exceeds the reference temperature node;

[0023] If it is determined that the real-time temperature exceeds the reference temperature node, a cooling control command is generated based on the temperature difference between the real-time temperature and the reference temperature node and the current load of the UAV.

[0024] The cooling control command is sent to the drone's cooling measures to adjust the temperature of the drone's radio frequency front-end module to below the reference temperature node during the future time period.

[0025] An AI-based integrated space-ground UAV communication channel management system, the system comprising:

[0026] The prediction and data acquisition module is used to acquire historical communication operation data of the UAV when it is predicted that the UAV will switch from a ground communication link to a low-Earth orbit satellite communication link in the future.

[0027] The sample construction module is used to extract multiple sets of historical handover control sample groups based on historical communication operation data. Each set of historical handover control sample groups includes samples that have undergone channel handover and samples that have not undergone channel handover, under the same handover conditions and operating conditions and the same temperature of the radio frequency front-end module of the satellite communication terminal. The radio frequency front-end module temperature is different for different historical handover control sample groups.

[0028] The effect analysis and temperature node determination module is used to analyze each historical handover control sample group, obtain the communication effect improvement index of performing channel handover relative to not performing channel handover, and determine whether there is a reference temperature node of the radio frequency front-end module that makes the communication effect improvement index lower than a preset threshold.

[0029] The cooling control module is used to obtain the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal when a reference temperature node is determined to exist, and to control the UAV's cooling measures based on the temperature node when the real-time temperature exceeds the reference temperature node, so as to adjust the temperature of the radio frequency front-end module below the reference temperature node in the future.

[0030] As a further limitation of the technical solution of the present invention, the historical switching comparison sample group includes at least two historical samples. The two historical samples correspond to the UAV in the past when it was performing a mission. Under the same conditions as the current situation, the communication link switching situation and the temperature of the satellite communication terminal radio frequency front-end module are the same. One historical sample performed a communication channel switching, and the other historical sample did not perform a communication channel switching.

[0031] As a further limitation of the technical solution of the present invention, the sample is consistent with the current communication link switching situation and working conditions, specifically referring to the sample and the current UAV being in the same or equivalent communication link switching trigger conditions, flight status parameters and communication service load conditions when performing the task.

[0032] As a further limitation of the technical solution of this embodiment of the invention, the calculation process of the communication effect improvement index includes:

[0033] Each historical sample in the historical handover comparison sample group is analyzed to distinguish between samples that have performed communication channel handover and those that have not. The moment when the communication link handover conditions are met is used as a time base, and the moment after the same preset time interval from the time base is used as a reference time point. At least one communication performance indicator is obtained for both the samples that performed communication channel handover and those that did not, within a preset time period after the reference time point. The communication performance indicators include signal-to-noise ratio, bit error rate, and data transmission delay. Based on the communication performance indicators, the communication effect of performing communication channel handover and the communication effect of not performing communication channel handover are calculated respectively. The communication effect improvement index is determined based on the improvement of the communication effect of performing communication channel handover relative to the communication effect of not performing communication channel handover.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] By introducing an AI-based historical communication operation data analysis mechanism, this invention, for the first time, correlates the temperature status of the satellite communication terminal's RF front-end module with the communication link switching effect through modeling. It identifies and determines reference temperature nodes affecting switching benefits, and proactively implements temperature regulation and continuous temperature control for the RF front-end module of individual UAVs in anticipation of future satellite-to-ground communication link switching. This avoids fluctuations in communication performance after switching due to differences in terminal status. This invention does not alter existing communication links or cooling hardware structures; it improves communication stability and reliability after low-Earth orbit satellite link switching solely through control strategy optimization, reducing the risk of short-term link drops and performance degradation. It achieves more refined and intelligent integrated satellite-to-ground UAV communication channel management, demonstrating significant engineering practical value. Attached Figure Description

[0036] Figure 1 A flowchart of the method provided in the embodiments of the present invention;

[0037] Figure 2 This is a flowchart illustrating the method for determining the presence of a reference temperature node for the radio frequency front-end module in the embodiments of the present invention.

[0038] Figure 3This is a flowchart illustrating the cooling measures for controlling a drone based on temperature nodes in the method provided in this embodiment of the invention;

[0039] Figure 4 The application architecture diagram of the system provided in the embodiments of the present invention. Detailed Implementation

[0040] 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.

[0041] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0042] Specifically, an AI-based method for managing communication channels of integrated space-ground unmanned aerial vehicles (UAVs) includes the following steps:

[0043] Step S100: If it is predicted that the currently flying UAV will switch from a ground communication link to a low-orbit satellite communication link in the future, acquire the historical communication operation data of the UAV.

[0044] Step S200: Based on historical communication operation data, extract multiple sets of historical handover comparison sample groups. Each set of historical handover comparison sample groups includes samples that have performed channel handover and samples that have not performed channel handover, under the conditions of consistent handover scenarios and operating conditions and the same temperature of the radio frequency front-end module of the satellite communication terminal. The radio frequency front-end module temperatures of different historical handover comparison sample groups are different.

[0045] The historical switching comparison sample group includes at least two historical samples. These two samples correspond to instances where, during a previous mission, the communication link switching conditions, operating conditions, and satellite communication terminal RF front-end module temperature were identical to the current conditions. One historical sample performed a communication channel switch, while the other did not. The consistency of communication link switching conditions and operating conditions between the sample and the current UAV specifically means that the sample and the current UAV were under the same or equivalent communication link switching trigger conditions, flight status parameters, and communication service load conditions during the mission.

[0046] In this embodiment of the invention, the UAV is a UAV with integrated space-ground communication capabilities, simultaneously equipped with a terrestrial communication link and a low-Earth orbit satellite communication link, capable of switching between the two communication links during flight based on communication conditions. The UAV is equipped with a satellite communication terminal, including a satellite communication terminal radio frequency front-end module. This RF front-end module is used to transmit and receive radio frequency signals with the low-Earth orbit satellite, as well as related frequency and power processing. The UAV's internal structure is also equipped with cooling measures, which may include, but are not limited to, fans, heat sinks, heat pipes, liquid cooling structures, or active cooling methods based on power consumption regulation. These cooling measures not only dissipate heat from the UAV's battery, motors, and other components, but also provide directional or coordinated cooling for the satellite communication terminal RF front-end module to regulate its operating temperature.

[0047] The prediction described in step S100 is a technical means that can already be implemented in the prior art. During the data transmission or flight control operations of a UAV, it is usually necessary to continuously monitor the environmental and communication status, such as monitoring the signal strength, bit error rate, and latency changes of the ground communication link, and combining this with information such as the UAV's flight path and geographical location to determine whether there is a need to switch from the ground communication link to a low-Earth orbit (LEO) satellite communication link. In the prior art, considering the advantages of ground communication links such as low communication cost, low access threshold, and low latency, UAVs usually prioritize maintaining ground communication links when no significant communication risks occur. Only when it is predicted that a UAV may enter a ground communication link obstruction area or weak coverage area in the future will a decision to switch to a LEO satellite communication link be triggered. This prediction process can be based on pre-stored map data, terrain information, historical communication fluctuation maps, or flight trajectory planning results to make judgments a certain period in advance, and is a conventional technical means that has already been implemented in this field.

[0048] The core research point of this invention originates from the observations of those skilled in the art in long-term practical applications. In team-based operations such as island surveying and forest patrols, multiple drones often fly collaboratively under the same operation type, similar operating time, and similar communication load conditions. In existing technologies, when these drones meet the communication link switching conditions, they typically adopt a consistent switching strategy, i.e., switching from a ground communication link to a low-Earth orbit satellite communication link at the same time. However, actual operational results show that within the preset time period after the switch, the communication performance of different drones fluctuates to some extent. For example, the stability and continuity of the video data and surveying data obtained by the receiving end differ; some drones exhibit better communication performance, while the communication performance of others, although still acceptable, is significantly lower.

[0049] Analysis of extensive operational data revealed that the aforementioned differences are not caused by the communication link conditions themselves, but rather by the individual state of the UAVs. Specifically, different UAVs operate in different local environments, such as whether they are in shady areas, whether ventilation is good, or whether they are exposed to direct sunlight for extended periods. These factors lead to varying heat dissipation conditions for each UAV, resulting in differences in the operating temperature of the RF front-end module of the satellite communication terminal. Temperature variations in the RF front-end module significantly affect critical performance during low-Earth orbit (LEO) satellite communication handover. For example, LEO satellite handover involves significant Doppler frequency shift and frequency offset compensation, and frequency offset is closely related to the temperature drift of the local oscillator or clock. Higher temperatures increase the likelihood of link instability shortly after handover. Simultaneously, in the Ka or Ku bands, the temperature of the RF power amplifier affects the equivalent isotropic radiated power, thus impacting whether the satellite access threshold can be met. For terminals using phased array antennas, temperature drift can also cause deterioration in beam pointing and phase consistency, making handover failure more likely. Therefore, even under equally favorable satellite link conditions, different UAVs may exhibit different communication performance after handover due to differences in the temperature of their RF front-end modules.

[0050] Based on the above findings, those skilled in the art propose that the present invention can further refine the research object to the operation process of individual UAVs. By analyzing historical communication operation data, the influence of the temperature of the radio frequency front-end module on the communication link switching effect can be identified. In the event that communication link switching is required in the future, targeted temperature adjustment measures can be taken in advance to improve the communication stability and overall communication effect after switching, thereby achieving better UAV communication channel management.

[0051] The historical communication operation data can originate from operational logs automatically recorded by the UAV during past missions or from data aggregated and stored by the ground control system and cloud management platform. This historical communication operation data includes at least communication link type information, communication link switching records, signal-to-noise ratio, bit error rate, and data transmission latency, as well as UAV flight status parameters, communication service load, and temperature data of the satellite communication terminal's radio frequency front-end module. All of this data is already collected and stored by existing UAV systems during operation and can be directly obtained without incurring additional hardware costs.

[0052] In step S200, multiple sets of historical switching control samples are extracted based on the historical communication operation data. These samples are used to characterize the differences in communication performance between the same UAV performing channel switching and not performing channel switching under different RF front-end module temperature conditions. Each set of historical switching control samples includes at least two historical samples. Under identical communication link switching conditions, operating conditions, and RF front-end module temperatures, one historical sample performed a communication channel switch, while the other did not. By setting this control relationship, the impact of channel switching behavior itself on communication performance can be highlighted, excluding other influencing factors.

[0053] In actual operation, even when the UAV meets the conditions for communication link switching, it may not actually perform the switching due to system policy configuration, satellite resource occupancy status, or operational constraints. This naturally creates a historical comparison sample of switching actions and non-switching actions. This invention utilizes this objectively existing operational phenomenon to construct a historical switching comparison sample group for analysis.

[0054] The samples described are consistent with the current conditions in terms of communication link switching scenarios and operating conditions, but this does not mean they are exactly the same; rather, it means they are within the same or equivalent range of conditions. For example, the communication link switching trigger conditions can be consistent within a preset tolerance range, and flight status parameters and communication service load conditions can also remain equivalent within a reasonable deviation range. In addition to the above conditions, screening conditions such as flight altitude range, mission type, or ambient temperature range can be introduced as needed. By setting relatively strict screening conditions, the interference of non-target factors on the analysis results can be minimized, allowing the obtained analysis conclusions to more accurately reflect the impact of RF front-end module temperature on the communication link switching effect, thereby providing a decision-making basis with practical guidance for the currently flying UAV.

[0055] Therefore, step S200, by constructing and screening a historical switching control sample group, directly serves the core research point proposed in step S100, namely, under the premise of predicting that future communication link switching is needed, it provides a reliable data foundation for subsequent identification of temperature influence patterns and the formulation of forward-looking temperature regulation strategies.

[0056] Furthermore, the AI-based space-ground integrated UAV communication channel management method also includes the following steps:

[0057] Step S300: Analyze each historical handover control sample group to obtain the communication performance improvement index of performing channel handover compared to not performing channel handover. The calculation process of the communication performance improvement index includes:

[0058] Each historical sample in the historical handover control sample group is analyzed to distinguish between samples that have performed communication channel handover and samples that have not performed communication channel handover.

[0059] Using the moment when the communication link switching conditions are met as the time reference, and the moment after the same preset time interval from the time reference as the reference time point, at least one communication performance indicator is obtained for the sample that performs communication channel switching and the sample that does not perform communication channel switching within a preset period after the reference time point; the communication performance indicator includes signal-to-noise ratio, bit error rate, and data transmission delay.

[0060] Based on the communication performance indicators, the communication effect of performing communication channel switching and the communication effect of not performing communication channel switching are calculated respectively, and the communication effect improvement index is determined according to the improvement of the communication effect of performing communication channel switching relative to the communication effect of not performing communication channel switching.

[0061] After calculating the communication performance improvement index for each sample group based on AI, it is determined whether there is a reference temperature node for the RF front-end module that causes the communication performance improvement index to fall below a preset threshold.

[0062] Specifically, Figure 2 A flowchart is shown to determine whether a reference temperature node for the radio frequency front-end module exists.

[0063] Determining whether there is a reference temperature node for the radio frequency front-end module that causes the communication performance improvement index to fall below a preset threshold specifically includes the following steps:

[0064] Step S301: Sort several historical switching control sample groups according to the corresponding radio frequency front-end module temperature from small to large to obtain a sample group sequence, and extract the corresponding communication effect improvement index change curve based on the sample group sequence.

[0065] Step S302: Analyze the communication effect improvement index change curve to identify whether there is a temperature node, such that in the sample group before the temperature node, the corresponding communication effect improvement index is higher than the preset threshold, while after the temperature node, the communication effect improvement index is lower than the preset threshold in more than a preset number of consecutive sample groups.

[0066] Step S303: If a temperature node that meets the above conditions is identified, the temperature node is determined to be the reference temperature node of the radio frequency front-end module.

[0067] In this embodiment of the invention, step S300 is used to analyze and interpret the multiple historical switching control sample groups extracted in step S200 to quantify the changes in communication performance resulting from performing communication channel switching compared to not performing communication channel switching under different RF front-end module temperature conditions. Since each historical switching control sample group maintains consistency in communication link switching scenarios and operating conditions, and is equivalent to the corresponding conditions of the currently flying UAV, with differences only in the temperature of the satellite communication terminal's RF front-end module, the differences in the communication performance improvement index between different sample groups can be directly attributed to the differences in RF front-end module temperature, thereby verifying the impact of temperature factors on the communication link switching performance.

[0068] When calculating the communication performance improvement index, the historical samples in each historical handover control sample group are first analyzed to clearly distinguish between samples that performed communication channel handover and those that did not. To ensure temporal consistency in the comparison between the two types of samples, the moment when the communication link handover conditions were met is used as a unified time reference for both samples that performed and did not perform the handover. The reference time point is the time after the same preset time interval from the time reference. Only at this same reference time point do samples that performed the handover begin to perform the handover, while samples that did not perform the handover maintain their original communication link. This method avoids introducing additional interference factors due to inconsistent time alignment.

[0069] Within a preset time period following the reference time point, communication performance indicators are acquired for samples that underwent communication channel switching and those that did not. These performance indicators may include signal-to-noise ratio, bit error rate, and data transmission latency, used to characterize communication performance from multiple dimensions such as communication quality, reliability, and real-time performance. Subsequently, based on these performance indicators, the communication effects of both the switched and unswitched communication channels are calculated. Furthermore, the communication performance improvement index for the corresponding sample group is obtained based on the difference or relative change between the two. This calculation method visually reflects the actual improvement in communication performance brought about by communication channel switching under the same external conditions.

[0070] After obtaining the communication performance improvement index for each historical handover control sample group, further analysis is conducted to determine if there are any RF front-end module reference temperature nodes that cause the communication performance improvement index to fall below a preset threshold. To this end, such as... Figure 2As shown, in step S301, several historical switching control sample groups are first sorted according to the corresponding RF front-end module temperature from low to high to form a sample group sequence, and the corresponding communication performance improvement index change curve is extracted based on the sample group sequence. This change curve is used to describe the overall trend of the communication performance improvement index as the RF front-end module temperature increases.

[0071] In step S302, the communication performance improvement index change curve is analyzed to identify whether there is a temperature node such that in the sample groups before this temperature node, the corresponding communication performance improvement index is higher than a preset threshold, while after this temperature node, the communication performance improvement index is lower than the preset threshold in more than a preset number of consecutive sample groups. The preset number is used to avoid misjudging the temperature node due to occasional fluctuations in individual samples. By requiring that multiple consecutive sample groups after the temperature node meet the condition of being lower than the preset threshold, the stability and reliability of the identified temperature node can be improved, making it more realistically reflect the long-term impact of RF front-end module temperature on communication performance.

[0072] The preset threshold is used to characterize the minimum communication performance improvement required to be achieved in practical applications when performing communication channel switching. It can be set based on the statistical results of historical communication operation data, the communication performance requirements of existing systems, or service quality standards. It is used to distinguish whether communication channel switching still has significant practical application value under different RF front-end module temperature conditions.

[0073] In step S303, when a temperature node that meets the above conditions is identified, it is determined as the reference temperature node for the RF front-end module. The reference temperature node indicates that within the temperature range at or below this range, performing communication channel switching can reliably achieve a relatively ideal improvement in communication performance. However, once the temperature of the RF front-end module exceeds the reference temperature node, the improvement in communication performance will decrease significantly, and the benefits brought by communication channel switching will begin to deteriorate.

[0074] By determining the reference temperature node of the radio frequency front-end module, this invention transforms the statistical patterns obtained from the analysis of historical samples into specific control criteria that can be used for real-time decision-making. This echoes the core research point of this invention, which is that, under the premise of predicting that communication link switching will be required in the future, it no longer relies solely on the communication link conditions themselves, but combines the temperature status of the individual UAV's radio frequency front-end module to take forward-looking adjustment measures in advance to ensure that the communication channel switching can achieve stable and excellent communication results within a preset period after execution.

[0075] Furthermore, the AI-based space-ground integrated UAV communication channel management method also includes the following steps:

[0076] Step S400: If a reference temperature node is determined to exist, the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal is obtained. When the real-time temperature exceeds the reference temperature node, the cooling measures of the UAV are controlled based on the temperature node to adjust the temperature of the radio frequency front-end module to below the reference temperature node in the future.

[0077] Specifically, Figure 3 A flowchart illustrating the cooling measures for a drone based on temperature nodes is shown.

[0078] The process, which involves obtaining the real-time temperature of the UAV satellite communication terminal's radio frequency front-end module when a reference temperature node is identified, and controlling the UAV's cooling measures based on the temperature node when the real-time temperature exceeds the reference temperature node, aims to adjust the temperature of the radio frequency front-end module below the reference temperature node in the future. Specifically, this includes the following steps:

[0079] Step S401: Obtain the real-time temperature of the radio frequency front-end module of the current UAV satellite communication terminal, and determine whether the real-time temperature exceeds the reference temperature node;

[0080] Step S402: If it is determined that the real-time temperature exceeds the reference temperature node, a cooling control command is generated based on the temperature difference between the real-time temperature and the reference temperature node and the current load of the UAV.

[0081] Step S403: Send the cooling control command to the cooling measures of the UAV so that the temperature of the UAV's radio frequency front-end module is adjusted to below the reference temperature node during the future time period.

[0082] In this embodiment of the invention, step S400 is used to apply the analysis conclusions obtained in step S300 to the actual flight process of the UAV when a reference temperature node is determined to exist. This allows for proactive regulation of the temperature of the satellite communication terminal's radio frequency front-end module before a future switch from a ground communication link to a low-Earth orbit satellite communication link is predicted, reducing the risk of communication performance degradation after the switch due to excessively high radio frequency front-end module temperature. This step represents the practical application stage of the invention and is one of the core steps in optimizing communication channel management. Step S300 confirms that historical samples show a pattern where the communication performance improvement exponentially decreases after the radio frequency front-end module temperature exceeds the reference temperature node. Therefore, under the same or equivalent communication link switching conditions and operating conditions, the real-time temperature of the radio frequency front-end module should be managed to ensure that subsequent switches consistently achieve the expected communication performance improvement.

[0083] In the prior art, the airframe of a drone is usually equipped with cooling measures to control the heat dissipation of heat-generating components such as batteries, ESCs, motors, and onboard computing units. These cooling measures are not specially added for the satellite communication terminal radio frequency front-end module described in this invention, but are based on existing cooling structures or cooling capabilities. By adjusting the control strategy, the radio frequency front-end module is cooled in a coordinated manner, thereby reducing the modification cost and facilitating implementation.

[0084] like Figure 3 As shown, step S400 specifically includes steps S401 to S403. In step S401, the real-time temperature of the current UAV satellite communication terminal radio frequency front-end module is obtained, and it is determined whether the real-time temperature exceeds the reference temperature node. The real-time temperature can be obtained by a temperature sensor installed on the radio frequency front-end module, or output by a temperature detection unit inside the radio frequency front-end module and read by the UAV's control system. By comparing the real-time temperature with the reference temperature node, it is possible to quickly determine whether the current radio frequency front-end module is in a risky state that may lead to an exponential decrease in the communication performance improvement after switching.

[0085] In step S402, if the real-time temperature exceeds the reference temperature node, a cooling control command is generated based on the temperature difference between the real-time temperature and the reference temperature node, as well as the current load of the UAV. The cooling control command indicates the intensity or mode of the cooling measures. Its generation process can be based on an existing UAV cooling control model. Under the premise of meeting the current load conditions, the cooling measures are controlled at an appropriate power level, ensuring that the temperature of the RF front-end module remains stable and below the reference temperature node throughout the entire future time period. Simultaneously, the generation of the cooling control command also comprehensively considers factors such as ambient temperature, heat dissipation efficiency, and energy consumption constraints to avoid a significant increase in energy consumption or impact on the UAV's endurance due to excessive cooling. The current load can include the UAV's power load, onboard computing load, and communication load, reflecting the available power margin for cooling at different times, thus ensuring that the cooling control command meets both the cooling objective and the overall energy management requirements of the UAV.

[0086] In step S403, the cooling control command is sent to the UAV's cooling measures to adjust the temperature of the UAV's RF front-end module below the reference temperature node within the future time period. In specific implementations, the cooling control command can be sent from the flight control system or thermal management control unit to the cooling measures' actuators, such as a fan drive unit, liquid cooling pump control unit, or heat dissipation channel control mechanism, thereby adjusting the intensity of the cooling measures to gradually reduce the RF front-end module temperature below the reference temperature node. Furthermore, after the communication link is switched from a terrestrial communication link to a low-Earth orbit satellite communication link, the cooling measures can continue to perform closed-loop control based on real-time temperature feedback, maintaining the RF front-end module temperature below the reference temperature node during satellite communication link operation. This ensures stable operation of the satellite communication terminal's RF front-end module, reducing short-term link drops, increased bit error rate, or latency jitter after the switch.

[0087] The significance of step S400 lies in transforming the "correlation pattern between RF front-end module temperature and communication channel switching effect" summarized from historical samples into an executable real-time control strategy. This strategy, through proactive cooling and continuous temperature control, reduces the probability of decreased switching benefits for individual UAVs due to excessively high RF front-end module temperatures when predicting future communication link switching needs. This process echoes the core research point of this invention: incorporating the temperature factor of the individual UAV's RF front-end module into the communication link switching decision, enabling communication channel management to not only focus on link coverage conditions but also proactively eliminate the impact of terminal state differences on switching effects.

[0088] The overall beneficial effects of this invention are reflected in the following aspects: By constructing a historical switching comparison sample group using historical communication operation data, calculating the communication effect improvement index, and identifying reference temperature nodes, the system can determine in advance whether performing communication channel switching under specific temperature conditions still has sufficient communication effect improvement value. Furthermore, when predicting the need to switch from a ground communication link to a low-Earth orbit satellite communication link in the future, it implements proactive cooling and continuous temperature control of the satellite communication terminal's RF front-end module based on the reference temperature node, thereby improving the communication stability and quality after the switch, reducing the risk of switching failure and short-term link drop, and better leveraging the access value of the low-Earth orbit satellite communication link while meeting communication effect requirements. Therefore, this invention effectively addresses the core research point involved in step S100, namely, solving the problem of communication effect fluctuations after switching due to temperature differences in the RF front-end module under the same or equivalent communication link switching scenarios and operating conditions, achieving better integrated space-ground UAV communication channel management.

[0089] This invention has promising applications and is suitable for UAV missions requiring switching between terrestrial and low-Earth orbit satellite communication links, such as island surveying, forest patrols, disaster emergency response, and offshore wind power inspection. Especially in applications with high requirements for the stability of video and mapping data transmission, and where there is a risk of terrestrial link obstruction or weak coverage, this invention can improve the overall benefits and reliability of communication link switching without adding complex hardware by optimizing the control strategy of existing cooling measures. It has high engineering and promotional value.

[0090] The prediction, construction of historical switching control sample groups, calculation of communication effect improvement index, and identification of reference temperature nodes in the above steps can all be completed by data analysis or learning models based on artificial intelligence (AI). Through training and reasoning on historical communication operation data, intelligent analysis and decision support can be achieved for the switching effect of communication links and the influence of temperature.

[0091] Furthermore, Figure 4 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0092] In another preferred embodiment of the present invention, an AI-based integrated space-ground UAV communication channel management system includes:

[0093] The prediction and data acquisition module 100 is used to acquire historical communication operation data of the UAV when it is predicted that the UAV will switch from a ground communication link to a low-orbit satellite communication link in the future.

[0094] Furthermore, the AI-based integrated space-ground UAV communication channel management system also includes:

[0095] The sample construction module 200 is used to extract multiple sets of historical handover control sample groups based on historical communication operation data. Each set of historical handover control sample groups includes samples that have performed channel handover and samples that have not performed channel handover under the same handover conditions and working conditions and the same temperature of the radio frequency front-end module of the satellite communication terminal. The radio frequency front-end module temperature is different for different historical handover control sample groups.

[0096] The historical switching comparison sample group includes at least two historical samples. The two historical samples correspond to the UAV in the past when it was performing a mission. Under the same conditions as the current situation, the communication link switching situation and the temperature of the satellite communication terminal radio frequency front-end module are the same. One historical sample performed a communication channel switching, and the other historical sample did not perform a communication channel switching.

[0097] The sample is consistent with the current one in terms of communication link switching conditions and operating conditions. Specifically, the sample and the current UAV are in the same or equivalent communication link switching trigger conditions, flight status parameters and communication service load conditions when performing the mission.

[0098] Furthermore, the AI-based integrated space-ground UAV communication channel management system also includes:

[0099] The effect analysis and temperature node determination module 300 is used to analyze each historical switching control sample group, obtain the communication effect improvement index of performing channel switching relative to not performing channel switching, and determine whether there is a radio frequency front-end module reference temperature node that makes the communication effect improvement index lower than a preset threshold.

[0100] The calculation process for the communication performance improvement index includes:

[0101] Each historical sample in the historical handover comparison sample group is analyzed to distinguish between samples that have performed communication channel handover and those that have not. The moment when the communication link handover conditions are met is used as a time base, and the moment after the same preset time interval from the time base is used as a reference time point. At least one communication performance indicator is obtained for both the samples that performed communication channel handover and those that did not, within a preset time period after the reference time point. The communication performance indicators include signal-to-noise ratio, bit error rate, and data transmission delay. Based on the communication performance indicators, the communication effect of performing communication channel handover and the communication effect of not performing communication channel handover are calculated respectively. The communication effect improvement index is determined based on the improvement of the communication effect of performing communication channel handover relative to the communication effect of not performing communication channel handover.

[0102] Furthermore, the AI-based integrated space-ground UAV communication channel management system also includes:

[0103] The cooling control module 400 is used to obtain the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal when a reference temperature node is determined to exist, and to control the cooling measures of the UAV based on the temperature node when the real-time temperature exceeds the reference temperature node, so as to adjust the temperature of the radio frequency front-end module below the reference temperature node in the future.

[0104] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0105] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0106] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0107] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0108] 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 AI-based method for managing communication channels of integrated space-ground unmanned aerial vehicles (UAVs), characterized in that, The method includes: In the event that the drone will switch from a terrestrial communication link to a low-Earth orbit satellite communication link in the future, historical communication operation data of the drone is obtained. Based on historical communication operation data, multiple sets of historical handover control sample groups were extracted. Each set of historical handover control sample groups includes samples that performed channel handover and samples that did not perform channel handover under the same handover conditions and operating conditions, and the same temperature of the radio frequency front-end module of the satellite communication terminal. The radio frequency front-end module temperature is different for different historical handover control sample groups. Analyze each historical switching control sample group to obtain the communication performance improvement index of performing channel switching compared to not performing channel switching; determine whether there is a reference temperature node of the RF front-end module that causes the communication performance improvement index to be lower than a preset threshold; If a reference temperature node is identified, the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal is obtained. When the real-time temperature exceeds the reference temperature node, the cooling measures of the UAV are controlled based on the temperature node to adjust the temperature of the radio frequency front-end module below the reference temperature node in the future.

2. The AI-based space-ground integrated UAV communication channel management method according to claim 1, characterized in that, The historical switching comparison sample group includes at least two historical samples. The two historical samples correspond to the UAV in the past when it was performing a mission. Under the same conditions as the current situation, the communication link switching situation and the temperature of the satellite communication terminal radio frequency front-end module are the same. One historical sample performed a communication channel switching, and the other historical sample did not perform a communication channel switching.

3. The AI-based space-ground integrated UAV communication channel management method according to claim 2, characterized in that, The sample is consistent with the current one in terms of communication link switching conditions and operating conditions. Specifically, the sample and the current UAV are in the same or equivalent communication link switching trigger conditions, flight status parameters and communication service load conditions when performing the mission.

4. The AI-based space-ground integrated UAV communication channel management method according to claim 1, characterized in that, The calculation process for the communication performance improvement index includes: Each historical sample in the historical handover control sample group is analyzed to distinguish between samples that have performed communication channel handover and samples that have not performed communication channel handover. Using the moment when the communication link switching conditions are met as the time reference, and the moment after the same preset time interval from the time reference as the reference time point, at least one communication performance indicator is obtained for the sample that performs communication channel switching and the sample that does not perform communication channel switching within a preset period after the reference time point; the communication performance indicator includes signal-to-noise ratio, bit error rate, and data transmission delay. Based on the communication performance indicators, the communication effect of performing communication channel switching and the communication effect of not performing communication channel switching are calculated respectively, and the communication effect improvement index is determined according to the improvement of the communication effect of performing communication channel switching relative to the communication effect of not performing communication channel switching.

5. The AI-based space-ground integrated UAV communication channel management method according to claim 1, characterized in that, The steps to determine whether there is an RF front-end module reference temperature node that causes the communication performance improvement index to fall below a preset threshold include: Several historical switching control sample groups are sorted from smallest to largest according to the corresponding radio frequency front-end module temperature to obtain a sample group sequence, and the corresponding communication performance improvement index change curve is extracted based on the sample group sequence. The communication effect improvement index change curve is analyzed to identify whether there is a temperature node, such that in the sample group before the temperature node, the corresponding communication effect improvement index is higher than the preset threshold, while after the temperature node, the communication effect improvement index is lower than the preset threshold in more than a preset number of consecutive sample groups. If a temperature node that meets the above conditions is identified, the temperature node is determined to be the reference temperature node of the radio frequency front-end module.

6. The AI-based space-ground integrated UAV communication channel management method according to claim 5, characterized in that, Given the existence of a reference temperature node, the steps of acquiring the real-time temperature of the current UAV satellite communication terminal RF front-end module, and controlling the UAV's cooling measures based on the temperature node when the real-time temperature exceeds the reference temperature node, to adjust the temperature of the RF front-end module below the reference temperature node in the future, include: Obtain the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal, and determine whether the real-time temperature exceeds the reference temperature node; If it is determined that the real-time temperature exceeds the reference temperature node, a cooling control command is generated based on the temperature difference between the real-time temperature and the reference temperature node and the current load of the UAV. The cooling control command is sent to the drone's cooling measures to adjust the temperature of the drone's radio frequency front-end module below the reference temperature node during the future time period.

7. An AI-based integrated space-ground UAV communication channel management system, characterized in that, The system includes: The prediction and data acquisition module is used to acquire historical communication operation data of the UAV when it is predicted that the UAV will switch from a ground communication link to a low-Earth orbit satellite communication link in the future. The sample construction module is used to extract multiple sets of historical handover control sample groups based on historical communication operation data. Each set of historical handover control sample groups includes samples that have undergone channel handover and samples that have not undergone channel handover, under the same handover conditions and operating conditions and the same temperature of the radio frequency front-end module of the satellite communication terminal. The radio frequency front-end module temperature is different for different historical handover control sample groups. The effect analysis and temperature node determination module is used to analyze each historical handover control sample group, obtain the communication effect improvement index of performing channel handover relative to not performing channel handover, and determine whether there is a reference temperature node of the radio frequency front-end module that makes the communication effect improvement index lower than a preset threshold. The cooling control module is used to obtain the real-time temperature of the radio frequency front-end module of the UAV satellite communication terminal when a reference temperature node is determined to exist, and to control the UAV's cooling measures based on the temperature node when the real-time temperature exceeds the reference temperature node, so as to adjust the temperature of the radio frequency front-end module below the reference temperature node in the future.

8. The AI-based space-ground integrated UAV communication channel management system according to claim 7, characterized in that, The historical switching comparison sample group includes at least two historical samples. The two historical samples correspond to the UAV in the past when it was performing a mission. Under the same conditions as the current situation, the communication link switching situation and the temperature of the satellite communication terminal radio frequency front-end module are the same. One historical sample performed a communication channel switching, and the other historical sample did not perform a communication channel switching.

9. The AI-based space-ground integrated UAV communication channel management system according to claim 8, characterized in that, The sample is consistent with the current one in terms of communication link switching conditions and operating conditions. Specifically, the sample and the current UAV are in the same or equivalent communication link switching trigger conditions, flight status parameters and communication service load conditions when performing the mission.

10. The AI-based space-ground integrated UAV communication channel management system according to claim 9, characterized in that, The calculation process for the communication performance improvement index includes: Each historical sample in the historical handover comparison sample group is analyzed to distinguish between samples that have performed communication channel handover and those that have not. The moment when the communication link handover conditions are met is used as a time base, and the moment after the same preset time interval from the time base is used as a reference time point. At least one communication performance indicator is obtained for both the samples that performed communication channel handover and those that did not, within a preset time period after the reference time point. The communication performance indicators include signal-to-noise ratio, bit error rate, and data transmission delay. Based on the communication performance indicators, the communication effect of performing communication channel handover and the communication effect of not performing communication channel handover are calculated respectively. The communication effect improvement index is determined based on the improvement of the communication effect of performing communication channel handover relative to the communication effect of not performing communication channel handover.

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