Transmission optimization method and system of unmanned aerial vehicle-mounted high and low orbit Ku frequency band satellite terminal

Abstract

The invention discloses a transmission optimization method and system for an unmanned aerial vehicle-mounted high and low orbit Ku frequency band satellite terminal, and relates to the technical field of satellite communication, and the method comprises the steps: monitoring a communication link of the Ku frequency band satellite terminal of an unmanned aerial vehicle, evaluating the transmission stability, and generating a transmission stability evaluation result; link selection is carried out in combination with a satellite link coverage range, and a link selection decision is made; dynamically adjusting a satellite terminal, switching a satellite link and carrying out data transmission monitoring to obtain a link quality index set; iterative analysis is carried out by combining flight state data of the unmanned aerial vehicle, and transmission optimization is carried out by backtracking to a Ku frequency band satellite terminal according to an analysis result. The technical problems of unstable transmission and poor link quality when the unmanned aerial vehicle communicates with the high and low orbit Ku frequency band satellite in the flight process are solved, and the technical effects of stable transmission of communication between the unmanned aerial vehicle and the high and low orbit Ku frequency band satellite, improvement of the link quality and meeting of efficient and reliable communication requirements are achieved.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication technology, and in particular to a transmission optimization method and system for an unmanned aerial vehicle (UAV)-borne high-orbit and low-orbit Ku-band satellite terminal. Background Art

[0002] In reality, drones are widely used in many fields due to their flexibility, and the stability of their communication with satellites is crucial. In existing technologies, drones mostly communicate through single-orbit satellite terminals, using fixed frequency, power, and coding modulation methods. These methods can work when the communication environment is stable, but as drone application scenarios expand, their limitations are exposed in complex environments. Due to the differences in the characteristics of high- and low-orbit satellites and the changes in the flight status of drones, traditional methods are unable to adapt to link changes, resulting in unstable and poor-quality communication data transmission, making it difficult to meet the efficient and reliable satellite communication needs of drones. Summary of the Invention

[0003] This application provides a transmission optimization method and system for a UAV-mounted high-orbit Ku-band satellite terminal, which is used to solve the technical problems of unstable transmission and poor link quality that may be encountered when a UAV communicates with a high-orbit Ku-band satellite during flight.

[0004] In a first aspect, the present application provides a transmission optimization method for a high-orbit Ku-band satellite terminal carried by an unmanned aerial vehicle. The method includes: real-time monitoring of the communication link of the Ku-band satellite terminal carried by the unmanned aerial vehicle, obtaining a communication data set for transmission stability evaluation, and generating a transmission stability evaluation result; performing link selection according to the link coverage of the high-orbit Ku-band satellites and the transmission stability evaluation result, and formulating a link selection decision; dynamically adjusting the Ku-band satellite terminal according to the link selection decision, performing a switching operation between the high-orbit Ku-band satellite links and the low-orbit Ku-band satellite links according to the adjustment result to monitor data transmission and obtain a link quality indicator set; performing iterative transmission analysis on the high-orbit Ku-band satellite terminal carried by the unmanned aerial vehicle according to the link quality indicator set and combined with the flight status data of the unmanned aerial vehicle, and tracing back to the Ku-band satellite terminal according to the analysis result to perform transmission optimization.

[0005] The second aspect of the present application provides a transmission optimization system for high- and low-orbit Ku-band satellite terminals carried by unmanned aerial vehicles. The system includes: a transmission stability assessment result generation module, which is used to monitor the communication link of the Ku-band satellite terminal carried by the unmanned aerial vehicle in real time, obtain a communication data set for transmission stability assessment, and generate a transmission stability assessment result; a link selection decision-making module, which is used to select a link according to the link coverage of the high- and low-orbit Ku-band satellites in combination with the transmission stability assessment result, and make a link selection decision; a link quality indicator set acquisition module, which is used to dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform switching operations between high- and low-orbit Ku-band satellite links according to the adjustment result, perform data transmission monitoring, and obtain a link quality indicator set; a transmission optimization execution module, which is used to perform transmission iterative analysis on the high- and low-orbit Ku-band satellite terminals carried by the unmanned aerial vehicle according to the link quality indicator set combined with the flight status data of the unmanned aerial vehicle, and trace back to the Ku-band satellite terminal according to the analysis results to perform transmission optimization.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application monitors the communication link of the Ku-band satellite terminal on the drone in real time, obtains the communication data set through time-space alignment, spatial correlation and other processing, evaluates the transmission stability and makes selection decisions based on the coverage of the high- and low-orbit satellite links, dynamically adjusts the terminal parameters to perform link switching, monitors and obtains the link quality indicator set, and iteratively analyzes and retrospectively optimizes the drone's flight status data, thereby achieving efficient switching and transmission optimization of the high- and low-orbit Ku-band satellite links, making the communication transmission of the drone-mounted satellite terminal more stable and reliable, achieving stable transmission of communications between the drone and high- and low-orbit Ku-band satellites, improving link quality, and meeting the technical effects of efficient and reliable communication needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0008] Figure 1 This is a flow chart of the transmission optimization method for the UAV-mounted high-orbit and low-orbit Ku-band satellite terminal provided in the embodiment of the present application.

[0009] Figure 2 This is a structural diagram of the transmission optimization system for the UAV-mounted high- and low-orbit Ku-band satellite terminal provided in an embodiment of the present application.

[0010] Description of the accompanying drawings: transmission stability evaluation result generation module 1, link selection decision making module 2, link quality indicator set acquisition module 3, transmission optimization execution module 4. DETAILED DESCRIPTION

[0011] This application provides a transmission optimization method and system for a UAV-mounted high-orbit Ku-band satellite terminal, which is used to solve the technical problems of unstable transmission and poor link quality that may be encountered when a UAV communicates with a high-orbit Ku-band satellite during flight.

[0012] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0013] It should be noted that the terms "first", "second", etc. in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0014] Example 1, as Figure 1 As shown, a transmission optimization method for a high-orbit Ku-band satellite terminal carried by an unmanned aerial vehicle, wherein the method includes: Step A100: Monitor the communication link of the Ku-band satellite terminal carried by the UAV in real time, obtain a communication data set, perform transmission stability evaluation, and generate a transmission stability evaluation result.

[0015] In the embodiment of the present application, the Ku-band satellite terminal refers to a terminal device carried by an unmanned aerial vehicle, which is used to establish a communication link with at least one high-orbit and low-orbit Ku-band satellite and can optimize data transmission by real-time monitoring of the communication link, dynamic adjustment of parameters, link switching, and other operations.

[0016] Specifically, first, the communication dataset acquisition method for the UAV-mounted high- and low-orbit Ku-band satellite terminal is as follows: real-time acquisition of a multi-dimensional link dataset, interpolation and resampling to determine the equally spaced time series and time-align to obtain a time-aligned dataset, construct a three-dimensional matrix based on the flight data for spatial correlation to obtain a spatial correlation dataset, and then construct a communication dataset through spatiotemporal alignment. The specific steps are detailed in A110-A150.

[0017] After obtaining the communication dataset, we first extract key indicators related to transmission stability from the communication dataset, including signal strength, bit error rate, conventional threshold 1e-5, number of link interruptions per hour, spectrum interference intensity, and link switching response time.

[0018] Next, these indicators were standardized, mapping metrics of varying dimensions to a 0-100 score range. For example, the closer the signal strength is to the maximum value, the higher the score; a bit error rate below 1e-5 receives a full score. A multi-dimensional weighted evaluation model was then constructed, using the 0-100 scores obtained from these standardized indicators as input parameters. Weights were assigned based on the degree of impact of each indicator on stability, such as 30% for signal strength fluctuation, 30% for bit error rate, 20% for number of interruptions, and 20% for handover response time. A weighted summation was used to calculate a basic stability score for each time point. This score became the model output, quantitatively reflecting the stability of the communication link at that moment.

[0019] Time series analysis is then introduced, using a 10-second sliding window to calculate the average score within the window. If the signal strength fluctuation exceeds 10dB, the bit error rate exceeds 1e-5, or there is one or more link interruptions within the window, the window score is deducted by 10-20 points. Short-term stability is determined based on the trend of score changes in multiple consecutive windows, such as if the scores of three consecutive windows are below 60 points. Long-term stability is determined based on the overall score distribution within a one-hour period.

[0020] Finally, the short-term and long-term stability performances are combined to generate a transmission stability assessment result, including stability levels such as stable, basically stable, and unstable, as well as corresponding abnormal indicator details, such as a sudden increase in the bit error rate to 5e-5 during a certain period of time, resulting in a decrease in stability.

[0021] Through multi-indicator quantitative analysis and time series evaluation, accurate judgment of communication link transmission stability is achieved, providing a reliable basis for subsequent link selection.

[0022] Step A200: performing link selection according to the link coverage of high and low orbit Ku-band satellites in combination with the transmission stability evaluation result, and making a link selection decision.

[0023] Optionally, the link coverage range of high-orbit and low-orbit Ku-band satellites is constructed by generating an elevation angle score value based on the satellite elevation angle, generating a link margin value based on the communication link, and generating a spatial attenuation compensation value based on the high-orbit and low-orbit distance. The three are weighted and integrated to determine the link coverage range. The specific steps are described in detail in A210-A240.

[0024] Next, the coverage quality dimension is obtained based on the link coverage range mapping, and the stability state dimension is obtained based on the transmission stability assessment result mapping. The two are cross-mapped to construct a link decision matrix, and then dynamic link selection is performed based on the matrix to make link selection decisions. The specific steps are detailed in A250-A280.

[0025] Step A300: Dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform switching operations between high-orbit and low-orbit Ku-band satellite links according to the adjustment result, monitor data transmission, and obtain a link quality indicator set.

[0026] In one embodiment of the present application, the target link type and switching conditions are determined based on the link selection decision, its characteristics are analyzed to adjust the satellite terminal RF and baseband parameters, link switching is initiated and results are generated, and then the real-time transmission and usage experience indicators are analyzed and integrated to construct a link quality indicator set. The specific steps are described in detail in A310-A360.

[0027] Step A400: Perform iterative transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminal according to the link quality indicator set and the UAV flight status data, and perform transmission optimization back to the Ku-band satellite terminal based on the analysis results.

[0028] In the embodiment of the present application, the drone flight status data refers to status information such as altitude, airspeed, attitude angle, etc. related to the drone flight.

[0029] Specifically, the link quality indicator set and the UAV flight status data are aligned in time and space according to the timestamp to generate a time and space aligned dataset, which is then mapped to the altitude-airspeed-attitude angle three-dimensional coordinate system to draw a link quality heat map, mark the transmission black areas and attribute them, determine the parameter group to be optimized, and build a knowledge base after optimization and verification, and continuously optimize the UAV-mounted high and low orbit Ku-band satellite terminals. The specific steps are detailed in A410-A470.

[0030] Furthermore, step A100 in the method provided in the embodiment of the present application includes: A110: This system collects real-time data on the communication links of UAV-mounted Ku-band satellite terminals in high and low orbits to obtain a multi-dimensional link dataset.

[0031] A120: Interpolate and resample the multidimensional link dataset according to a collection period to determine an equally spaced time series.

[0032] A130: Time-align the multidimensional link dataset according to the equally spaced time sequence to obtain a time-aligned dataset.

[0033] A140: Construct a three-dimensional trajectory association communication matrix based on the UAV flight data, and spatially associate the multidimensional link data set according to the three-dimensional trajectory association communication matrix to obtain a spatial association data set.

[0034] A150: Perform spatiotemporal alignment on the time-aligned dataset and the spatial correlation dataset to construct the communication dataset.

[0035] Specifically, after the Ku-band satellite terminal carried by the drone establishes a communication link with at least one low-orbit satellite and at least one high-orbit satellite, it collects information such as the spectrum status, signal-to-noise ratio, bit error rate and other signal quality, satellite orbit position and other information of these links in real time to form a multi-dimensional link data set containing multi-dimensional parameters.

[0036] Furthermore, the Ku-band satellite terminal onboard the drone collects real-time information on signal quality, including spectrum status, signal-to-noise ratio (SNR), bit error rate (BER), and satellite orbital position, primarily through the collaboration of dedicated hardware modules and software algorithms integrated into the terminal. The terminal's built-in Ku-band RF front-end module is responsible for receiving satellite signals. The spectrum detection unit scans the Ku-band range covered by the link in real time, capturing information such as signal frequency distribution and interference signal strength to generate spectrum status data. The baseband processing module demodulates and decodes the received signal, calculating the BER in real time by comparing the difference between the transmitted and received signals. It also calculates the SNR by calculating the real-time ratio of signal power to noise power, completing the collection of signal quality parameters. Simultaneously, the terminal's integrated satellite navigation and orbit calculation module receives ephemeris data broadcast by high- and low-orbit satellites and combines it with the terminal's own positioning information, such as latitude, longitude, and altitude, to calculate the satellite's real-time orbital position, including parameters such as azimuth, elevation, and range. These modules work synchronously according to the set millisecond-level high-frequency acquisition cycle, transmitting the collected multi-dimensional parameters to the terminal's data processing unit in real time, and aggregating them into a multi-dimensional link data set containing timestamps, realizing real-time collection of various types of information.

[0037] When interpolating and resampling multidimensional link datasets, the time intervals between collected link data fluctuate by 1-3 seconds due to the influence of air disturbances and satellite orbit changes on Ku-band satellite links in high and low orbits during drone flight. For example, data for a low-orbit link may be collected at the 2nd and 5th seconds, with a 3-second interval; data for a high-orbit link may be collected at the 3rd and 4th seconds, with a 1-second interval. Linear interpolation is used to calculate link parameters, such as signal strength and spectrum state, at two adjacent known time points to fill in the missing time point data. For example, if the signal strength at the 2nd second is -70dBm and at the 5th second is -64dBm, the calculated values ​​at the 3rd second and the 4th second are -68dBm, respectively. This unifies the originally unequal time intervals to a fixed interval of 1 second, forming an evenly spaced time series. This ensures temporal consistency between datasets for different links and provides a unified benchmark for the time alignment of subsequent link data.

[0038] Next, we time-align the parameters of different links in the multidimensional link dataset based on equally spaced time series. For example, if the LEO link is missing data at the second second, but the HE link has data at the second second, we align and interpolate the data at the second second of the LEO link to ensure that the parameters of different links correspond to each other at the same time point, thus obtaining a time-aligned dataset.

[0039] Then, based on the UAV's flight data, such as altitude, longitude and latitude, and attitude angle, a three-dimensional trajectory correlation communication matrix is ​​constructed. Its dimensions can be set to time, spatial position, and link identification. The parameters in the multidimensional link data set are mapped to the corresponding spatial positions of the matrix. For example, the low-orbit link signal strength of the UAV at 30° north latitude, 120° east longitude, and an altitude of 500 meters is associated with this spatial position to form a spatial correlation data set.

[0040] Finally, the time-aligned dataset is fused with the spatial correlation dataset so that each data point contains both timestamp and spatial location information, such as the spectrum status and low-orbit / high-orbit signal quality corresponding to t=10 seconds, location 30° north latitude, 120° east longitude, and altitude 500 meters, to finally construct a complete communication dataset.

[0041] Through the above steps, the spatiotemporal information and signal parameters of multiple links are integrated, providing comprehensive and accurate basic data support for subsequent transmission stability evaluation and link selection decisions.

[0042] Furthermore, step A200 in the method provided in the embodiment of the present application includes: A210: Calculates the elevation angle of the Ku-band satellite and generates a satellite elevation angle score.

[0043] A220: Evaluates the communication link margin of the Ku-band satellite terminal and generates a link margin value.

[0044] A230: Calculates the spatial attenuation of Ku-band satellites based on the distance between high and low orbits and generates spatial attenuation compensation values.

[0045] A240: Perform weighted fusion on the satellite elevation angle score value, the link margin value, and the spatial attenuation compensation value, perform link coverage calculation on high and low orbit Ku-band satellites based on the fusion result, and determine the link coverage range.

[0046] Optionally, first calculate the satellite elevation angle score value, and score it according to the set rules based on the real-time elevation angle values ​​of the satellite and the drone: when the elevation angle reaches or exceeds 60°, it is directly scored as 100 points; when the elevation angle is between 30° and 60°, the score is calculated according to a linear ratio, such as when the elevation angle is 45°, the score = (45-30) / (60-30)×100=50 points; when the elevation angle is less than 30°, it is scored as 0 points, so as to quantify the impact of the elevation angle on the link.

[0047] Next, the link margin value is generated. By real-time monitoring of the actual signal power received by the Ku-band satellite terminal and combining it with the minimum received power required by the link, technicians in this field comprehensively consider actual atmospheric loss, rain attenuation and other factors to calculate the difference between the two. For example, if the actual received power is -50dBm and the minimum required power is -70dBm, the link margin value is 20dB. A larger value indicates a stronger link anti-interference and attenuation capability.

[0048] Then, the spatial attenuation compensation value is calculated. Based on the real-time distance between the high-orbit and low-orbit satellites and the drone, the attenuation value is obtained using the spatial attenuation formula (the attenuation is proportional to the square of the distance). The compensation value is then generated in reverse based on the attenuation value. For example, if the low-orbit satellite is closer, the attenuation is 10dB, and the compensation value is set to 10; if the high-orbit satellite is farther away, the attenuation is 30dB, and the compensation value is set to 30, so as to balance the spatial attenuation differences between satellites in different orbits.

[0049] Finally, the satellite elevation angle score (0-100 points), link margin (for example, 0-20dB), and spatial attenuation compensation (0-30) are proportionally converted to a score of 0-100. A weighted fusion is performed. Assuming the weights of the three are 40%, 30%, and 30%, respectively, the fusion result is = elevation angle score × 40% + link margin score × 30% + spatial attenuation compensation score × 30%. Based on the fusion result, coverage levels are assigned, such as 80 or above for strong coverage, 60-80 for medium coverage, and below 60 for weak coverage. This ultimately determines the link coverage of Ku-band satellites in both high and low orbits.

[0050] By quantifying the effects of satellite elevation angle, link margin and spatial attenuation and weighted integration, the link coverage range of high and low orbit satellites is accurately constructed, providing an objective coverage capability reference for subsequent link selection decisions.

[0051] Furthermore, step A200 in the method provided in the embodiment of the present application includes: A250: Perform coverage quality mapping based on the link coverage range to obtain a coverage quality dimension.

[0052] A260: Perform state mapping based on the transmission stability evaluation result to obtain a stable state dimension.

[0053] A270: Perform a two-dimensional cross-mapping of the coverage quality dimension and the stable state dimension to construct a link decision matrix.

[0054] A280: Perform dynamic link selection based on the link decision matrix and make a link selection decision.

[0055] Specifically, when performing coverage quality mapping based on the link coverage of high- and low-orbit Ku-band satellites, the coverage quality label is first determined based on the fusion result of the link coverage, such as 80 points or above for stable, 60-80 points for metastable, and below 60 points for unstable. The label is then mapped to the corresponding decision value interval: the stable label is mapped to [80, 100], the metastable label is mapped to [60, 80), and the unstable label is mapped to [0, 60), thereby obtaining the quantitative interval of the coverage quality dimension.

[0056] Next, state mapping is performed based on the transmission stability assessment results. Based on the coverage quality index in the assessment results, it is mapped to the decision value interval of the stable state dimension according to the set rules: when the index ≥ 85, it is mapped to [90, 100]; when 70 ≤ index < 85, it is mapped to [70, 90); when the index < 70, it is mapped to [0, 70), completing the quantization of the stable state dimension.

[0057] Next, a cross-mapping of the coverage quality and stability dimensions is performed to construct a link decision matrix. The median of the two dimensional intervals is taken as the representative value. For example, the median of the coverage quality interval [80, 100] is 90, and the median of the stability interval [90, 100] is 95. The mean of the two is calculated as (90 + 95) / 2 = 92.5. Adjustments are then made based on the interval combination type: if both are in the high interval (coverage ≥ 80 and stability ≥ 90), the mean is multiplied by 1.2 to obtain the corresponding value, with an upper limit of 100. If one is high and the other is medium (coverage [80, 100] and stability [70, 90]), the mean is multiplied by 1.0 to obtain the corresponding value. If there is a low interval (coverage [0, 60]), the mean is multiplied by 0.8 to obtain the corresponding value. The calculated results of all combinations are entered into the matrix to form the link decision matrix, providing a quantitative basis for dynamic link selection.

[0058] Finally, the decision output value is extracted based on the link decision matrix. When the output value is higher than the first threshold, the low-orbit single-hop link is selected. When the output value is lower than the first threshold but higher than the second threshold, the high-orbit single-hop link is enabled. When the output value is lower than the second threshold, the high-orbit and low-orbit multi-satellite relay link is activated, and the link selection decision is made. The specific steps are described in detail in A281-A284.

[0059] By quantifying coverage quality and transmission stability into two-dimensional intervals and cross-calculating them, a link decision matrix is ​​constructed, which provides a scientific and quantifiable judgment standard for link selection decisions, ensuring the accuracy and adaptability of decisions.

[0060] Furthermore, step A280 in the method provided in the embodiment of the present application includes: A281: Perform dynamic link selection based on the link decision matrix and extract a decision output value.

[0061] A282: When the decision output value of the link decision matrix is ​​higher than a first threshold, select a low-orbit satellite single-hop link as the link selection decision.

[0062] A283: When the decision output value is lower than the first threshold but higher than the second threshold, enable the high-orbit satellite single-hop link as the link selection decision.

[0063] A284: When the decision output value is lower than the second threshold, activate the high-orbit and low-orbit multi-satellite relay link as the link selection decision.

[0064] Specifically, when performing dynamic link selection based on the link decision matrix, the decision output values ​​corresponding to the current UAV and each candidate link, namely, the low-orbit satellite single-hop link, the high-orbit satellite single-hop link, and the high-low orbit multi-satellite relay link, are first extracted from the matrix. These values ​​are the quantitative results obtained by the two-dimensional cross-mapping calculation in step A270, reflecting the comprehensive communication quality of each link.

[0065] Next, set the first threshold to 80 and the second threshold to 50. Those skilled in the art can determine the link communication quality based on historically optimal and critical intervals. When the extracted decision output value is higher than the first threshold of 80, it indicates that the coverage quality and transmission stability of the current low-orbit satellite single-hop link are both optimal. In this case, the low-orbit satellite single-hop link is selected as the decision point, leveraging its low latency and high bandwidth to ensure efficient data transmission.

[0066] When the decision output value is between the second threshold of 50 and the first threshold of 80, it indicates that the quality of the low-orbit link has declined but the high-orbit link can still meet basic communication needs. The high-orbit satellite single-hop link is activated to maintain communication continuity by relying on its wide coverage advantage.

[0067] When the decision output value is lower than the second threshold of 50, it means that the single-hop link can no longer guarantee stable transmission. At this time, the high-orbit and low-orbit multi-satellite relay link is activated to make up for the shortcomings of the single link through multi-satellite collaborative relay and avoid communication interruption.

[0068] By setting thresholds to perform graded judgments on decision output values ​​and dynamically matching the optimal link type, adaptive selection of high- and low-orbit satellite links is achieved, ensuring that drones always maintain efficient and stable communication status in complex flight environments.

[0069] Furthermore, step A300 in the method provided in the embodiment of the present application includes: A310: Determine the target link type based on the link selection decision and set a switching trigger condition.

[0070] A320: Perform feature analysis according to the target link type to obtain target link features, and dynamically adjust radio frequency parameters of the Ku-band satellite terminal based on the target link features to obtain radio frequency adjustment parameters.

[0071] A330: Reconstruct the protocol stack of the baseband processing parameters of the Ku-band satellite terminal based on the target link characteristics to obtain protocol stack adjustment parameters.

[0072] A340: Initiate a link switching operation of a high-orbit Ku-band satellite according to the radio frequency adjustment parameter and the protocol stack adjustment parameter, and generate a link switching result.

[0073] A350: Perform real-time transmission switching analysis based on the link switching result and set a real-time transmission quality indicator. Perform user experience switching analysis based on the link switching result and set a user experience quality indicator.

[0074] A360: Correlate and integrate the real-time transmission quality indicator and the user experience quality indicator to construct the link quality indicator set.

[0075] In the embodiment of the present application, the protocol stack refers to a set of data transmission protocols used for baseband processing in the Ku-band satellite terminal, which can be reconstructed according to the characteristics of the target link to adapt to different links, thereby obtaining protocol stack adjustment parameters.

[0076] Specifically, when determining the target link type based on the link selection decision, it is first necessary to clarify whether the current switch should be to a low-orbit satellite single-hop link, a high-orbit satellite single-hop link, or a high-orbit multi-satellite relay link, and set the switching trigger conditions: for example, when the low-orbit link signal strength is lower than -85dBm for 3 consecutive seconds, the switch to the high-orbit link is triggered; when the single-hop link bit error rate exceeds 1e-4 and lasts for 2 seconds, the switch to the high-orbit multi-satellite relay link is triggered.

[0077] Next, feature analysis is performed based on the identified target link type to extract its key characteristics: single-hop links from low-orbit satellites have high bandwidth, such as 10-50 Mbps, and low latency, such as 100-300 ms, but a smaller coverage area. Single-hop links from high-orbit satellites have wide coverage but higher latency, such as 500-800 ms, and lower bandwidth, such as 2-10 Mbps. Multi-satellite relay links in both high and low orbits achieve wide-area coverage through multi-satellite collaboration and have strong anti-interference capabilities, but the transmission paths are complex. Based on these characteristics, RF parameters are adjusted: for example, for low-orbit links, the RF frequency is adjusted to 12-14 GHz and the transmit power is set to 2 W to accommodate short-range transmission. For high-orbit links, the frequency is adjusted to 10.7-12.75 GHz, and the transmit power is increased to 3 W to compensate for long-range attenuation. For relay links, frequency hopping technology is enabled, with the frequency dynamically switching within the Ku band. Power is dynamically allocated based on the number of relay nodes, such as 2.5 W for two relay nodes, thus obtaining the RF adjustment parameters.

[0078] Then, the protocol stack of the baseband processing parameters is reconstructed based on the characteristics of the target link: the low-orbit link adopts the TCP / IP protocol stack, the frame length is set to 1500 bytes, and the encoding method is QPSK to improve transmission efficiency; due to the high latency of the high-orbit link, an improved TCP protocol such as TCP-BBR is adopted, the frame length is shortened to 1000 bytes, and the encoding method is changed to 8PSK to enhance the anti-noise capability; the relay link is reconstructed into a multi-hop protocol stack, the relay node synchronization field is added, and the encoding uses LDPC code to reduce the bit error during the relay process, thereby obtaining the protocol stack adjustment parameters.

[0079] Afterwards, based on the target link type, the low-orbit direct connection, high-orbit direct connection, and high-low-orbit relay types are parsed, and a hierarchical switching handshake protocol is initiated according to the type. The corresponding requests are sent and information is received respectively to generate the corresponding link switching results. The specific steps are described in detail in A341-A342.

[0080] Next, based on the link switching results, we conducted a real-time transmission handover analysis and set real-time transmission quality metrics: for example, the throughput of the low-orbit link was targeted at ≥10Mbps; the bit error rate of the high-orbit link was targeted at ≤1e-5; and the end-to-end latency of the relay link was targeted at ≤1000ms. We also conducted a user experience handover analysis and set user experience quality metrics: for example, the number of video transmission freezes was targeted at ≤1 per minute; and the data transmission integrity was targeted at ≥99.9%.

[0081] Finally, the real-time transmission quality indicators are correlated and integrated with the usage experience quality indicators. For example, a weighted algorithm is used to calculate the comprehensive score with a weight of 60% for the transmission indicator and a weight of 40% for the experience indicator, forming a link quality indicator set that intuitively reflects the communication performance of the current link.

[0082] By dynamically adjusting terminal parameters, accurately executing link switching, and comprehensively monitoring link quality, efficient adaptation and performance evaluation of high and low orbit Ku-band satellite links are achieved, providing a reliable basis for subsequent transmission optimization.

[0083] Furthermore, step A340 in the method provided in the embodiment of the present application includes: A341: Parse the target link type to obtain a low orbit direct connection type, a high orbit direct connection type, and a high-low orbit relay type.

[0084] A342: Initiate a hierarchical switching handshake protocol to perform switching operations according to the low-orbit direct connection type, the high-orbit direct connection type, and the high-low-orbit relay type: when the target link type is the low-orbit direct connection type for switching, send a fast switching request to receive the time slot allocation map of the low-orbit satellite, and generate a first link switching result; when the target link type is the high-orbit direct connection type for switching, send an enhanced switching request to receive the power adjustment value of the high-orbit satellite, and generate a second link switching result; when the target link type is the high-low-orbit relay type for switching, broadcast a path establishment request to receive multi-terminal service flows, and generate a third link switching result.

[0085] In one embodiment, the target link type determined based on the link selection decision is first parsed to clarify the specific type: if the target is low-latency, high-bandwidth direct communication, it is determined to be a low-orbit direct connection type; if the target is wide-coverage, long-distance direct communication, it is determined to be a high-orbit direct connection type; if the target is anti-interference communication achieved through multi-satellite collaboration, it is determined to be a high-low orbit relay type.

[0086] A hierarchical handover handshake protocol is initiated based on the parsed link type. For a direct LEO connection, the terminal sends a fast handover request to the target LEO satellite, containing the RF parameters and protocol stack information for the current link. The LEO satellite responds within 50ms, returning a timeslot allocation map, such as allocating slots 3 and 5, with each slot lasting 10ms. The terminal then synchronizes the timeslots accordingly and generates the first link handover result, including the handover timeslot number and the synchronization completion time.

[0087] For high-orbit direct connections, the terminal sends an enhanced handover request, including the current transmit power (e.g., 2W) and the link margin. Due to the long distance of the high-orbit satellite, power compensation is required to offset attenuation. Within 300ms, the terminal returns the power adjustment value, such as +1.8W. The terminal adjusts the transmit power to 3.8W and completes the handover. The terminal then generates a second link handover result, including the adjusted power value and the link lock status (e.g., successful lock).

[0088] For high-orbit relay, the terminal broadcasts a path establishment request to nearby available low-orbit and high-orbit satellites, such as low-orbit satellite A and high-orbit satellite B. The request includes the data transmission rate and the required number of relay nodes. Each satellite responds within 500ms with service flow allocation information, such as A for uplink data forwarding and B for downlink data forwarding. The terminal then integrates the service flows from multiple terminals to form a relay path and generates a third-link handover result, including a relay node list and path transmission delay.

[0089] By designing a hierarchical switching mechanism for different link types, link switching is completed accurately and corresponding results are generated, ensuring the efficiency and adaptability of link switching between high and low orbit Ku-band satellites, laying the foundation for subsequent link quality monitoring.

[0090] Furthermore, step A400 in the method provided in the embodiment of the present application includes: A410: Perform spatiotemporal alignment on the link quality indicator set and the UAV flight status data according to timestamps to generate a spatiotemporal alignment data set.

[0091] A420: Construct a three-dimensional coordinate system of altitude, airspeed, and attitude angle, map the spatiotemporal alignment dataset to the three-dimensional coordinate system, and draw a link quality heat map.

[0092] A430: traverse the link quality heat map to perform transmission analysis on the UAV-mounted high-orbit and low-orbit Ku-band satellite terminals, and mark abnormal areas as transmission black zones.

[0093] A440: Perform multi-dimensional fault attribution determination based on the transmission black area to generate fault root cause parameters.

[0094] A450: Perform iterative transmission analysis on the UAV-mounted high- and low-orbit Ku-band satellite terminal according to the fault root cause parameters, and determine multiple parameter groups to be optimized.

[0095] A460: Load the multiple parameter groups to be optimized and trace back to the Ku-band satellite terminal to perform optimization, generate parameter optimization results, verify the parameter optimization results, and build an optimization knowledge base when the parameter optimization results pass the verification.

[0096] A470: Continuously optimize the UAV-mounted high and low orbit Ku-band satellite terminal through the optimization knowledge base.

[0097] In the embodiment of the present application, the transmission black zone refers to the transmission abnormal area marked in the link quality heat map.

[0098] Optionally, first, align the link quality indicator set including real-time transmission throughput, bit error rate, number of freezes, etc. with the UAV flight status data, such as altitude, airspeed, and attitude angle, according to timestamps accurate to milliseconds. For example, associate the link throughput of 20Mbps at 10:00:01.000 with the flight altitude of 1500 meters, airspeed of 45m / s, and attitude angle of 5° at the same time to ensure that the data correspond one-to-one in the time dimension, generate a spatiotemporally aligned dataset, and establish a unified data foundation for subsequent analysis.

[0099] Among them, the altitude of the drone can be obtained in real time through the onboard GPS or Beidou satellite positioning module, the airspeed is measured by the pitot tube or integrated wind speed sensor on the fuselage, and the attitude angles, including roll angle, pitch angle, and heading angle, are perceived by built-in inertial measurement units such as gyroscopes and accelerometers. These sensors work together to collect and output data in real time, providing a basis for subsequent spatiotemporal alignment and analysis with the link quality indicator set.

[0100] Next, we constructed a three-dimensional coordinate system with altitude (Y axis) in meters, airspeed (X axis) in m / s, and attitude angle (Z axis) in degrees. We integrated the X, Y, and Z axes into a coordinate system and mapped each data set in the spatiotemporal alignment dataset to a corresponding point in the coordinate system. For example, a point at an altitude of 1500 meters, an airspeed of 45 m / s, and an attitude angle of 5° corresponds to a link quality score of 75. We then used an interpolation algorithm to fill in all the grid points within the coordinate system and created a link quality heat map using a color gradient (red for a score <40, yellow for 40-60, and green for >60), visually displaying the link quality distribution under different flight conditions.

[0101] Then, we traverse each grid point of the link quality heat map to perform transmission analysis. We set the area with a link quality score of less than 30 points and where three or more consecutive adjacent points meet this condition as an abnormal area and mark it as a transmission black zone. For example, if the area with an altitude of 2500-2800 meters, an airspeed of 55-60m / s, and an attitude angle of 10°-15° continuously shows a score of 25, we mark this area as a transmission black zone and clearly identify the flight status range that needs to be optimized.

[0102] Afterwards, a multi-dimensional fault attribution determination is performed based on the transmission black zone: faults are determined for the satellite link, aircraft status, and high- and low-orbit Ku-band satellite terminals respectively. Based on the determination results, the faults are attributed and the corresponding first, second, and third root cause parameters are generated. The specific steps are described in detail in A441-A443.

[0103] Next, the terminal transmission is iteratively analyzed according to the root cause parameters of the fault: for insufficient elevation angle of low-orbit satellites, the frequency is iteratively adjusted, such as from 12GHz to 14GHz, and the coding method is changed, such as from QPSK to 16QAM; for drastic fluctuations in attitude angle, the antenna pointing algorithm is iteratively optimized, such as shortening the adjustment period to 100ms; for low RF power, the power is iteratively increased, such as from 1.5W to 2.0W. Through multiple rounds of testing, 3-5 groups of parameters to be optimized are determined, each group containing a combination of parameters such as frequency, power, and algorithm.

[0104] Next, the parameter group to be optimized is loaded into the Ku-band satellite terminal for optimization. The optimized link quality indicators are recorded, such as the black zone score improving from 25 to 65 points, to verify the parameter optimization effect. When the optimized score is greater than 60 points in three consecutive tests, the effect is determined to have passed the verification. The parameter group and the corresponding black zone flight status, such as altitude 2500-2800 meters, airspeed 55-60m / s, attitude angle 10°-15°, etc., are stored in the optimization knowledge base to form a mapping relationship between flight status and optimization parameters.

[0105] Finally, the terminal is continuously optimized by optimizing the knowledge base, collecting the current flight status of the drone in real time, such as an altitude of 2,600 meters and an airspeed of 58 m / s. The corresponding optimization parameter group is matched in the knowledge base and automatically loaded. If a new transmission black zone appears, such as an unrecorded flight status, the above analysis, optimization, and verification process is repeated to update the knowledge base and achieve dynamic improvement of terminal transmission performance.

[0106] Through closed-loop analysis and optimization of the entire process from data alignment to knowledge base construction, transmission problems are accurately located and continuously improved, achieving efficient and stable transmission of UAV-mounted high- and low-orbit Ku-band satellite terminals in complex flight environments.

[0107] Furthermore, step A440 in the method provided in the embodiment of the present application includes: A441: Determine a satellite link fault based on the transmission black zone, attribute the fault according to a first determination result, and generate a first root cause parameter of the fault.

[0108] A442: Perform aircraft status fault determination based on the transmission black area, attribute the fault according to the second determination result, and generate a second fault root cause parameter.

[0109] A443: Perform high-orbit and low-orbit Ku-band satellite terminal fault determination based on the transmission black area, attribute the fault according to the third determination result, and generate a third fault root cause parameter.

[0110] In one embodiment, when determining satellite link failures based on transmission black zones, satellite communication data corresponding to the black zones is first extracted, including satellite elevation angle, link margin, and spatial attenuation values. Abnormal thresholds are set as satellite elevation angles continuously below 20°, link margins less than 8dB, and spatial attenuation values ​​greater than 35dB. If satellite data from a transmission black zone meets these conditions for more than 10 consecutive seconds, a satellite link failure is determined. Based on the determination result, if the elevation angle of a low-orbit satellite is insufficient due to its orbital position, the first root cause parameter, "persistently low elevation angle of the low-orbit satellite," is generated. If the link margin of a high-orbit satellite is insufficient, specific parameters such as "insufficient link margin of the high-orbit satellite" are generated.

[0111] When determining aircraft status faults based on transmission black zones, the corresponding drone flight parameters are analyzed, including attitude angles (roll and pitch), airspeed rate of change, and altitude fluctuation. Abnormality criteria include attitude angle fluctuations exceeding ±15°, airspeed rate of change greater than 10m / s², and altitude fluctuations exceeding 50 meters. If the flight data from the transmission black zone meets these criteria and coincides exactly with a link quality degradation, an aircraft status fault is determined. Based on the cause of the fault, if a sharp attitude angle fluctuation causes antenna pointing deviation, the secondary root cause parameter, "Severe attitude angle fluctuations," is generated. If a sudden drop in altitude causes signal obstruction, parameters such as "Signal obstruction caused by a sharp drop in altitude" are generated.

[0112] When performing fault determination on Ku-band satellite terminals in high and low orbits based on transmission black zones, the terminal's operating data is monitored, including RF transmit power, baseband processing delay, and protocol stack synchronization status. Abnormal values ​​are defined as RF power continuously below 1.2W, baseband processing delay exceeding 400ms, and protocol stack synchronization failures exceeding 5 times per minute. If the terminal data in the transmission black zone meets these abnormal values ​​and satellite link and aircraft status factors are eliminated, the terminal is determined to be faulty. Based on the determination result, if the RF module power output is abnormal, the third root cause parameter, insufficient terminal RF transmit power, is generated. If the protocol stack synchronization is abnormal, parameters such as terminal protocol stack synchronization failure are generated.

[0113] By determining and attributing transmission black areas from three dimensions: satellite link, aircraft status, and terminal, the root cause of the transmission anomaly is accurately located, providing a clear direction for subsequent targeted optimization and ensuring efficient and accurate troubleshooting.

[0114] In summary, the transmission optimization method for a Ku-band satellite terminal onboard a drone provided in the embodiments of the present application has the following technical effects: This application establishes a communication link by configuring a drone and a satellite terminal, monitors the spectrum, signal quality, and satellite position in real time, adjusts parameters and selects the optimal communication path based on the monitoring results, continuously receives feedback and makes adjustments, and records data for optimization, thereby optimizing the transmission of high- and low-orbit Ku-band satellite terminals on drones, making the transmission effect more efficient and stable, achieving stable transmission between drones and high- and low-orbit Ku-band satellites, improving link quality, and meeting the technical effects of efficient and reliable communication needs.

[0115] Example 2, as Figure 2 As shown, based on the same inventive concept as the aforementioned embodiment 1, the embodiment of the present application provides a transmission optimization system for a high-orbit Ku-band satellite terminal onboard an unmanned aerial vehicle, the system comprising: The transmission stability assessment result generation module 1 is used to monitor the communication link of the Ku-band satellite terminal carried by the UAV in real time, obtain a communication data set to perform transmission stability assessment, and generate a transmission stability assessment result.

[0116] The link selection decision-making module 2 is used to select a link according to the link coverage of the high- and low-orbit Ku-band satellites in combination with the transmission stability assessment result, and make a link selection decision.

[0117] The link quality indicator set acquisition module 3 is used to dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform switching operations between high-orbit and low-orbit Ku-band satellite links according to the adjustment results, monitor data transmission, and obtain a link quality indicator set.

[0118] The transmission optimization execution module 4 is used to perform iterative transmission analysis on the UAV-borne high-orbit Ku-band satellite terminal according to the link quality indicator set combined with the UAV flight status data, and trace back to the Ku-band satellite terminal for transmission optimization based on the analysis results.

[0119] Furthermore, the transmission stability evaluation result generation module 1 is configured to perform the following steps: A multidimensional link dataset is obtained by real-time acquisition of the communication links of the Ku-band satellite terminals in high and low orbits carried by unmanned aerial vehicles; the multidimensional link dataset is interpolated and resampled according to the acquisition period to determine an equally spaced time series; the multidimensional link dataset is time-aligned according to the equally spaced time series to obtain a time-aligned dataset; a three-dimensional trajectory association communication matrix is ​​constructed based on the unmanned aerial vehicle flight data, and the multidimensional link dataset is spatially associated according to the three-dimensional trajectory association communication matrix to obtain a spatially associated dataset; the time-aligned dataset and the spatially associated dataset are spatiotemporally aligned to construct the communication dataset.

[0120] Furthermore, the link selection decision making module 2 is configured to perform the following steps: Calculation is performed based on the elevation angle of the Ku-band satellite to generate a satellite elevation angle score value; margin evaluation is performed based on the communication link of the Ku-band satellite terminal to generate a link margin value; spatial attenuation is calculated for the Ku-band satellite based on the high-orbit and low-orbit distance to generate a spatial attenuation compensation value; the satellite elevation angle score value, the link margin value, and the spatial attenuation compensation value are weightedly fused, and link coverage calculation of the high-orbit and low-orbit Ku-band satellites is performed based on the fusion result to determine the link coverage range.

[0121] Furthermore, the link selection decision making module 2 is configured to perform the following steps: Perform coverage quality mapping based on the link coverage range to obtain coverage quality dimensions; perform state mapping based on the transmission stability assessment result to obtain stable state dimensions; perform two-dimensional cross-mapping of the coverage quality dimension and the stable state dimension to construct a link decision matrix; perform dynamic link selection based on the link decision matrix to make link selection decisions.

[0122] Furthermore, the link selection decision making module 2 is configured to perform the following steps: Dynamic link selection is performed based on the link decision matrix, and a decision output value is extracted; when the decision output value of the link decision matrix is ​​higher than a first threshold, a low-orbit satellite single-hop link is selected as the link selection decision; when the decision output value is lower than the first threshold but higher than a second threshold, a high-orbit satellite single-hop link is enabled as the link selection decision; when the decision output value is lower than the second threshold, a high-orbit and low-orbit multi-satellite relay link is activated as the link selection decision.

[0123] Furthermore, the link quality indicator set acquisition module 3 is configured to perform the following steps: Based on the link selection decision, the target link type is determined and the switching trigger condition is set; characteristic analysis is performed according to the target link type to obtain target link characteristics, and the radio frequency parameters of the Ku-band satellite terminal are dynamically adjusted based on the target link characteristics to obtain radio frequency adjustment parameters; based on the target link characteristics, the protocol stack of the baseband processing parameters of the Ku-band satellite terminal is reconstructed to obtain protocol stack adjustment parameters; according to the radio frequency adjustment parameters and the protocol stack adjustment parameters, a link switching operation of the high-orbit and low-orbit Ku-band satellites is initiated to generate a link switching result; based on the link switching result, a real-time transmission switching analysis is performed to set a real-time transmission quality indicator; based on the link switching result, a usage experience switching analysis is performed to set a usage experience quality indicator; the real-time transmission quality indicator and the usage experience quality indicator are associated and integrated to construct the link quality indicator set.

[0124] Furthermore, the link quality indicator set acquisition module 3 is configured to perform the following steps: Based on the target link type, analysis is performed to obtain the low-orbit direct connection type, the high-orbit direct connection type, and the high-low orbit relay type; according to the low-orbit direct connection type, the high-orbit direct connection type, and the high-low orbit relay type, a hierarchical switching handshake protocol is initiated to perform a switching operation: when the target link type is the low-orbit direct connection type for switching, a fast switching request is sent to receive the time slot allocation map of the low-orbit satellite, and a first link switching result is generated; when the target link type is the high-orbit direct connection type for switching, an enhanced switching request is sent to receive the power adjustment value of the high-orbit satellite, and a second link switching result is generated; when the target link type is the high-low orbit relay type for switching, a broadcast path establishment request is sent to receive multi-terminal service flows, and a third link switching result is generated.

[0125] Furthermore, the transmission optimization execution module 4 is configured to execute the following steps: The link quality indicator set and the UAV flight status data are spatiotemporally aligned according to timestamps to generate a spatiotemporally aligned data set; a three-dimensional coordinate system of altitude, airspeed, and attitude angle is constructed, the spatiotemporally aligned data set is mapped to the three-dimensional coordinate system, and a link quality heat map is drawn; the link quality heat map is traversed to perform transmission analysis on the UAV-borne high- and low-orbit Ku-band satellite terminal, and abnormal areas are marked as transmission black zones; multi-dimensional fault attribution determination is performed based on the transmission black zones to generate fault root cause parameters; transmission iterative analysis is performed on the UAV-borne high- and low-orbit Ku-band satellite terminal according to the fault root cause parameters to determine multiple parameter groups to be optimized; the multiple parameter groups to be optimized are loaded back to the Ku-band satellite terminal for optimization, parameter optimization results are generated, and the parameter optimization results are verified. When the parameter optimization results are verified, an optimization knowledge base is constructed; and the UAV-borne high- and low-orbit Ku-band satellite terminal is continuously optimized using the optimization knowledge base.

[0126] Furthermore, the transmission optimization execution module 4 is configured to execute the following steps: A satellite link fault determination is performed based on the transmission black area, and attribution is performed according to the first determination result to generate a first root cause parameter of the fault. An aircraft status fault determination is performed based on the transmission black area, and attribution is performed according to the second determination result to generate a second root cause parameter of the fault. A high- and low-orbit Ku-band satellite terminal fault determination is performed based on the transmission black area, and attribution is performed according to the third determination result to generate a third root cause parameter of the fault.

[0127] The transmission optimization system for the unmanned aerial vehicle high-orbit Ku-band satellite terminal provided in an embodiment of the present invention can execute the transmission optimization method for the unmanned aerial vehicle high-orbit Ku-band satellite terminal provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0128] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other and are not used to limit the scope of protection of the present invention.

[0129] The above specific embodiments do not constitute a limitation to the scope of protection of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application should be included in the scope of protection of this application. In some cases, the actions or steps recorded in this application can be performed in an order different from that in the embodiments and can still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle, characterized in that: The method comprises: Real-time monitoring of the communication link of the Ku-band satellite terminal carried by the UAV, obtaining a communication data set for transmission stability assessment, and generating transmission stability assessment results; Select a link based on the link coverage of high and low orbit Ku-band satellites and the transmission stability assessment results, and make a link selection decision; Dynamically adjusting the Ku-band satellite terminal according to the link selection decision, performing a switching operation between high-orbit and low-orbit Ku-band satellite links based on the adjustment result to monitor data transmission and obtain a link quality indicator set; According to the link quality indicator set and the UAV flight status data, an iterative transmission analysis is performed on the UAV-borne high and low orbit Ku-band satellite terminal, and based on the analysis results, the transmission is optimized by tracing back to the Ku-band satellite terminal.

2. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 1, wherein: Real-time monitoring of the communication link of the Ku-band satellite terminal carried by the UAV to obtain a communication data set includes the following methods: By collecting real-time communication links of UAV-mounted high- and low-orbit Ku-band satellite terminals, a multi-dimensional link dataset is obtained. Interpolating and resampling the multidimensional link data set according to the acquisition period to determine an equally spaced time series; Time-aligning the multidimensional link dataset according to the equally spaced time sequence to obtain a time-aligned dataset; constructing a three-dimensional trajectory correlation communication matrix based on the UAV flight data, and spatially correlating the multidimensional link data set according to the three-dimensional trajectory correlation communication matrix to obtain a spatial correlation data set; The time-aligned dataset and the spatial correlation dataset are temporally and spatially aligned to construct the communication dataset.

3. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 1, wherein: The process of building link coverage for high and low orbit Ku-band satellites includes: Calculate the elevation angle of the Ku-band satellite and generate a satellite elevation angle score; Conduct margin assessment on the communication link of the Ku-band satellite terminal and generate a link margin value; Calculate the spatial attenuation of Ku-band satellites based on the distance between high and low orbits and generate spatial attenuation compensation values; The satellite elevation angle score value, the link margin value, and the spatial attenuation compensation value are weightedly fused, and link coverage calculation of high and low orbit Ku-band satellites is performed based on the fusion result to determine the link coverage range.

4. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 1, wherein: Link selection is performed based on the link coverage of high- and low-orbit Ku-band satellites in combination with the transmission stability assessment result, and a link selection decision is made, the method comprising: Perform coverage quality mapping based on the link coverage to obtain a coverage quality dimension; Performing state mapping based on the transmission stability evaluation result to obtain a stable state dimension; Performing a two-dimensional cross-mapping of the coverage quality dimension and the stable state dimension to construct a link decision matrix; Dynamic link selection is performed based on the link decision matrix to make a link selection decision.

5. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 4, wherein: Performing dynamic link selection based on the link decision matrix and making a link selection decision, the method includes: Perform dynamic link selection based on the link decision matrix and extract a decision output value; When the decision output value of the link decision matrix is ​​higher than a first threshold, selecting a low-orbit satellite single-hop link as a link selection decision; When the decision output value is lower than the first threshold but higher than the second threshold, enabling the high-orbit satellite single-hop link as the link selection decision; When the decision output value is lower than the second threshold, the high-orbit and low-orbit multi-satellite relay link is activated as the link selection decision.

6. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 1, wherein: Dynamically adjusting the Ku-band satellite terminal according to the link selection decision, performing a switching operation between high-orbit and low-orbit Ku-band satellite links based on the adjustment result to monitor data transmission, and obtaining a link quality indicator set, the method comprising: Determine the target link type based on the link selection decision and set a switching trigger condition; Performing a characteristic analysis according to the target link type to obtain target link characteristics, and dynamically adjusting radio frequency parameters of the Ku-band satellite terminal based on the target link characteristics to obtain radio frequency adjustment parameters; Reconstructing the protocol stack of the baseband processing parameters of the Ku-band satellite terminal based on the target link characteristics to obtain protocol stack adjustment parameters; Initiate a link switching operation of a high-orbit Ku-band satellite according to the radio frequency adjustment parameter and the protocol stack adjustment parameter, and generate a link switching result; Performing real-time transmission switching analysis based on the link switching result and setting a real-time transmission quality indicator; performing user experience switching analysis based on the link switching result and setting a user experience quality indicator; The real-time transmission quality indicator and the usage experience quality indicator are associated and integrated to construct the link quality indicator set.

7. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 6, wherein: The method includes initiating a link switching operation of a high-orbit Ku-band satellite according to the radio frequency adjustment parameter and the protocol stack adjustment parameter, and generating a link switching result. Parsing based on the target link type to obtain a low orbit direct connection type, a high orbit direct connection type, and a high-low orbit relay type; Initiate a hierarchical handover handshake protocol according to the low-orbit direct connection type, the high-orbit direct connection type, and the high-low-orbit relay type to perform a handover operation: When the target link type is the low-orbit direct connection type for switching, sending a fast switching request to receive a time slot allocation map of the low-orbit satellite, and generating a first link switching result; When the target link type is the high-orbit direct connection type for switching, sending an enhanced switching request to receive a power adjustment value of the high-orbit satellite, and generating a second link switching result; When the target link type is the high-orbit relay type for switching, the broadcast path establishment request receives multi-terminal service flows and generates a third link switching result.

8. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 1, wherein: According to the link quality indicator set and combined with the UAV flight status data, iterative transmission analysis is performed on the UAV-borne high-orbit and low-orbit Ku-band satellite terminals. Based on the analysis results, transmission optimization is performed backtracking to the Ku-band satellite terminals. The method includes: Performing spatiotemporal alignment on the link quality indicator set and the UAV flight status data according to timestamps to generate a spatiotemporal alignment dataset; Constructing a three-dimensional coordinate system of altitude, airspeed, and attitude angle, mapping the spatiotemporal alignment dataset to the three-dimensional coordinate system, and drawing a link quality heat map; Traversing the link quality heat map, performing transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminals, and marking abnormal areas as transmission black zones; Perform multi-dimensional fault attribution determination based on the transmission black area to generate fault root cause parameters; Performing iterative transmission analysis on the UAV-mounted high- and low-orbit Ku-band satellite terminal according to the fault root cause parameters, and determining multiple parameter groups to be optimized; Loading the multiple parameter groups to be optimized back to the Ku-band satellite terminal to perform optimization, generating parameter optimization results, verifying the parameter optimization results, and constructing an optimization knowledge base when the parameter optimization results pass the verification; The optimization knowledge base is used to continuously optimize the UAV-borne high and low orbit Ku-band satellite terminals.

9. The transmission optimization method for a Ku-band satellite terminal carried by an unmanned aerial vehicle according to claim 8, wherein: Performing multi-dimensional fault attribution determination based on the transmission black area to generate fault root cause parameters includes: Determine a satellite link fault based on the transmission black zone, attribute the fault according to a first determination result, and generate a first root cause parameter of the fault; performing aircraft status fault determination based on the transmission black area, attributing the fault according to the second determination result, and generating a second fault root cause parameter; A fault determination of a high-orbit Ku-band satellite terminal is performed based on the transmission black area, and attribution is performed according to the third determination result to generate a third fault root cause parameter.

10. A transmission optimization system for a Ku-band satellite terminal carried by an unmanned aerial vehicle (UAV), characterized in that: A method for optimizing the transmission of a Ku-band satellite terminal carried by an unmanned aerial vehicle (UAV) in a high-orbit or low-orbit manner according to any one of claims 1 to 9, the system comprising: The transmission stability assessment result generation module is used to monitor the communication link of the Ku-band satellite terminal carried by the UAV in real time, obtain the communication data set, conduct transmission stability assessment, and generate the transmission stability assessment result; a link selection decision-making module, configured to select a link based on the link coverage of high- and low-orbit Ku-band satellites and the transmission stability assessment result, and make a link selection decision; a link quality indicator set acquisition module, configured to dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform a switching operation between high-orbit and low-orbit Ku-band satellite links based on the adjustment result, perform data transmission monitoring, and obtain a link quality indicator set; The transmission optimization execution module is used to perform iterative transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminal according to the link quality indicator set combined with the UAV flight status data, and trace back to the Ku-band satellite terminal for transmission optimization based on the analysis results.

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