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

Abstract

The application discloses a transmission optimization method and system of a UAV-borne high-low orbit Ku frequency band satellite terminal, relates to the technical field of satellite communication, and comprises the following steps: monitoring the communication link of the Ku frequency band satellite terminal of the UAV, evaluating transmission stability, and generating a transmission stability evaluation result; selecting a link in combination with a satellite link coverage range, formulating a link selection decision; dynamically adjusting the satellite terminal, switching the satellite link, and performing data transmission monitoring to obtain a link quality index set; iteratively analyzing in combination with UAV flight state data, and backtracking to the Ku frequency band satellite terminal for transmission optimization according to the analysis result. The application solves the technical problems that the UAV may face unstable transmission and poor link quality when communicating with high-low orbit Ku frequency band satellites during flight, achieves stable transmission of the UAV and the high-low orbit Ku frequency band satellite, improves link quality, and meets the technical effect of efficient and reliable communication requirements.

Description

Technical Field

[0001] This invention relates to the field of satellite communication technology, and in particular to a method and system for optimizing the transmission of UAV-borne high and low orbit Ku-band satellite terminals. Background Technology

[0002] In reality, drones are widely used in various fields due to their flexibility, making the stability of their communication with satellites crucial. Currently, drones mostly communicate via single-orbit satellite terminals, employing fixed frequencies, power levels, and coding modulation methods. While these methods work in stable communication environments, their limitations become apparent as drone applications expand to more complex environments. Due to differences in the characteristics of high and low orbit satellites and variations in drone flight states, traditional methods cannot adapt to link changes, resulting in unstable and poor-quality data transmission, failing to meet the efficient and reliable satellite communication requirements of drones. Summary of the Invention

[0003] This application provides a method and system for optimizing the transmission of UAV-borne high and low orbit Ku-band satellite terminals, which is used to solve the technical problems of unstable transmission and poor link quality that UAVs may face when communicating with high and low orbit Ku-band satellites during flight.

[0004] The first aspect of this application provides a transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals. The method includes: real-time monitoring of the communication links of the UAV-borne Ku-band satellite terminal to obtain a communication dataset for transmission stability assessment, generating a transmission stability assessment result; selecting links based on the link coverage of the high and low orbit Ku-band satellites and the transmission stability assessment result, formulating a link selection decision; dynamically adjusting the Ku-band satellite terminal according to the link selection decision, performing data transmission monitoring by switching between high and low orbit Ku-band satellite links based on the adjustment result, and obtaining a set of link quality indicators; performing iterative transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminal according to the link quality indicator set and UAV flight status data, and backtracking to the Ku-band satellite terminal for transmission optimization based on the analysis results.

[0005] A second aspect of this application provides a transmission optimization system for UAV-borne high and low orbit Ku-band satellite terminals. The system includes: a transmission stability assessment result generation module, used to monitor the communication links of the UAV-borne Ku-band satellite terminal in real time, obtain a communication dataset, perform a transmission stability assessment, and generate a transmission stability assessment result; a link selection decision-making module, used to select links based on the link coverage of the high and low orbit Ku-band satellites and the transmission stability assessment result, and formulate a link selection decision; a link quality index set acquisition module, used to dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform data transmission monitoring by switching between high and low orbit Ku-band satellite links based on the adjustment result, and obtain a link quality index set; and a transmission optimization execution module, used to perform iterative transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminal according to the link quality index set and UAV flight status data, and backtrack to the Ku-band satellite terminal for transmission optimization based on the analysis results.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] This application achieves efficient switching and transmission optimization of high and low orbit Ku-band satellite links by real-time monitoring of the communication link of UAV-borne Ku-band satellite terminals, processing it through spatiotemporal alignment and spatial correlation, evaluating transmission stability, making selection decisions based on the coverage of high and low orbit satellite links, dynamically adjusting terminal parameters to execute link switching, monitoring and obtaining a set of link quality indicators, and iteratively analyzing and backtracking optimization based on UAV flight status data. This makes the communication transmission of UAV-borne satellite terminals more stable and reliable, achieving the technical effect of stable transmission of UAV-to-high and low orbit Ku-band satellite communication, improving link quality, and meeting the technical requirements of efficient and reliable communication. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a flowchart illustrating the transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals provided in this application embodiment.

[0010] Figure 2 This is a schematic diagram of the transmission optimization system for UAV-borne high and low orbit Ku-band satellite terminals provided in this application embodiment.

[0011] Figure labeling: Module 1 for generating transmission stability assessment results, Module 2 for making link selection decisions, Module 3 for obtaining link quality index set, and Module 4 for executing transmission optimization. Detailed Implementation

[0012] This application provides a method and system for optimizing the transmission of UAV-borne high and low orbit Ku-band satellite terminals, which is used to solve the technical problems of unstable transmission and poor link quality that UAVs may face when communicating with high and low orbit Ku-band satellites during flight.

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0014] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; 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 explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0015] Example 1, as Figure 1 As shown, a transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals is described, wherein the method includes:

[0016] Step A100: Monitor the communication link of the Ku-band satellite terminal carried by the UAV in real time, obtain the communication dataset, conduct a transmission stability assessment, and generate a transmission stability assessment result.

[0017] In this embodiment of the application, the Ku-band satellite terminal refers to a terminal device carried by an unmanned aerial vehicle (UAV) for establishing communication links with at least one high-orbit and low-orbit Ku-band satellite. It can optimize data transmission by real-time monitoring of the communication link, dynamic adjustment of parameters, and link switching.

[0018] Specifically, the method for obtaining the communication dataset of the UAV-borne high and low orbit Ku-band satellite terminal is as follows: real-time acquisition of multi-dimensional link dataset, interpolation and resampling to determine the time series at equal intervals and time alignment to obtain time-aligned dataset, construction of a three-dimensional matrix based on flight data for spatial correlation to obtain spatial correlation dataset, and then construction of communication dataset through spatiotemporal alignment. The specific steps are explained in detail in A110-A150.

[0019] After obtaining the communication dataset, the first step is to 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, spectral interference intensity, and link switching response time.

[0020] Next, these indicators are standardized, mapping indicators of different dimensions to a score range of 0-100. For example, the closer the signal strength is to the maximum value, the higher the score; a bit error rate below 1e-5 receives full marks. Then, a multi-dimensional weighted evaluation model is constructed. The standardized scores of these indicators (0-100) are used as input parameters. Weights are assigned based on the degree of influence of each indicator on stability, such as 30% for signal strength fluctuations, 30% for bit error rate, 20% for interruption counts, and 20% for handover response time. A weighted summation is used to calculate the basic stability score for each time point, which is the model output, thus quantitatively reflecting the stability level of the communication link at that moment.

[0021] Then, time series analysis is 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 more than one link interruption within the window, 10-20 points are deducted from the window score. Based on the score change trend of multiple consecutive windows, if the score is below 60 points for three consecutive windows, short-term stability is determined; combined with the overall score distribution within 1 hour, long-term stability is determined.

[0022] Finally, by combining short-term and long-term stability performance, a transmission stability assessment result is generated, including a stability level 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, which leads to a decrease in stability.

[0023] Through multi-indicator quantitative analysis and time series evaluation, the stability of communication link transmission was accurately determined, providing a reliable basis for subsequent link selection.

[0024] Step A200: Select links based on the link coverage of high and low orbit Ku-band satellites and the transmission stability assessment results, and formulate a link selection decision.

[0025] Optionally, the process of constructing the link coverage of Ku-band satellites in high and low orbits is as follows: generate an elevation angle score based on the satellite elevation angle, generate a link margin value based on the communication link, and generate a spatial attenuation compensation value based on the distance between high and low orbits. The three values ​​are weighted and fused to determine the link coverage. The specific steps are explained in detail in A210-A240.

[0026] Next, the coverage quality dimension is obtained based on the link coverage range mapping, and the stable 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 formulate link selection decisions. The specific steps are explained in detail in A250-A280.

[0027] Step A300: Dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform data transmission monitoring by switching between high and low orbit Ku-band satellite links based on the adjustment results, and obtain a set of link quality indicators.

[0028] In one embodiment of this application, the target link type and switching conditions are determined based on the link selection decision, their characteristics are analyzed to adjust the satellite terminal radio frequency and baseband parameters, link switching is initiated and results are generated, and then real-time transmission and user experience indicators are analyzed and integrated to construct a link quality indicator set. The specific steps are described in detail in A310-A360.

[0029] Step A400: Perform iterative transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminals according to the link quality index set and UAV flight status data, and backtrack to the Ku-band satellite terminals for transmission optimization based on the analysis results.

[0030] In this embodiment of the application, UAV flight status data refers to state information such as altitude, airspeed, and attitude angle related to UAV flight.

[0031] Specifically, the link quality index set and the UAV flight status data are spatiotemporally aligned according to timestamps to generate a spatiotemporally aligned dataset. This dataset is then mapped to a three-dimensional coordinate system of altitude-airspeed-attitude angle to draw a link quality heatmap. Transmission black areas are marked and attributed to causes. After the optimization and verification of the parameter group to be optimized, a knowledge base is built to continuously optimize the UAV-borne high and low orbit Ku-band satellite terminal. The specific steps are explained in detail in A410-A470.

[0032] Furthermore, step A100 in the method provided in this application embodiment includes:

[0033] A110: A multi-dimensional link dataset is obtained by real-time collection of communication links of UAV-borne high and low orbit Ku-band satellite terminals.

[0034] A120: The multidimensional link dataset is interpolated and resampled according to the acquisition period to determine the time series with equal intervals.

[0035] A130: Time-align the multidimensional link dataset according to the equal-interval time series to obtain a time-aligned dataset.

[0036] A140: Construct a three-dimensional trajectory association communication matrix based on UAV flight data, and spatially associate the multi-dimensional link dataset according to the three-dimensional trajectory association communication matrix to obtain a spatial association dataset.

[0037] A150: Spatiotemporally align the time-aligned dataset with the spatially associated dataset to construct the communication dataset.

[0038] Specifically, after the Ku-band satellite terminal carried by the UAV establishes communication links 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 satellite orbital position of these links in real time, forming a multi-dimensional link dataset containing multi-dimensional parameters.

[0039] Furthermore, the Ku-band satellite terminal onboard the UAV collects real-time information on signal quality, such as spectrum status, signal-to-noise ratio (SNR), and bit error rate (BER), as well as satellite orbital position, primarily through a collaborative effort of dedicated hardware modules and software algorithms integrated within the terminal. The terminal's built-in Ku-band RF front-end module receives satellite signals. Its 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 form spectrum status data. The baseband processing module demodulates and decodes the received signal, calculating the BER in real time by comparing the differences between the transmitted and received signals, and obtaining the SNR through the real-time ratio of signal power to noise power, thus completing the acquisition 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 distance. These modules work synchronously according to a set high-frequency acquisition cycle at the millisecond level, transmitting the acquired multi-dimensional parameters to the terminal's data processing unit in real time, and summarizing them to form a multi-dimensional link dataset containing timestamps, thereby realizing the real-time acquisition of various types of information.

[0040] When interpolating and resampling multidimensional link datasets, the time intervals of the collected link data may fluctuate by 1-3 seconds due to air disturbances and satellite orbit changes during UAV flight. For example, data from a low-orbit link might be collected at the 2nd and 5th seconds, with a 3-second interval; data from a high-orbit link might be collected at the 3rd and 4th seconds, with a 1-second interval. A linear interpolation method is used to calculate link parameters, such as signal strength and spectral status, for two adjacent known time points, filling in the missing time point data within the interval. For instance, if the signal strength is -70dBm at the 2nd second and -64dBm at the 5th second, it can be calculated that the signal strength is -68dBm at the 3rd second and -66dBm at the 4th second. This unifies the originally unequal time intervals to a fixed interval of 1 second, forming an equally spaced time series. This ensures that the datasets from different links are consistent in the time dimension, providing a unified benchmark for the time alignment of subsequent link data.

[0041] Next, based on the equally spaced time series, the parameters of different links in the multidimensional link dataset are time-aligned. For example, if the low-orbit link is missing data in the 2nd second, but the high-orbit link has a record in the 2nd second, the interpolated data of the low-orbit link in the 2nd second is supplemented by alignment, so that the parameters of different links correspond at the same time point, resulting in a time-aligned dataset.

[0042] Then, based on the UAV's flight data, such as altitude, latitude and longitude, and attitude angle, a three-dimensional trajectory association communication matrix is ​​constructed. Its dimensions can be set as time, spatial location, and link identifier. The parameters in the multi-dimensional link dataset are mapped to the corresponding spatial location in the matrix. For example, the low-orbit link signal strength of the UAV at 30°N, 120°E, and 500 meters altitude is associated with that spatial location to form a spatial association dataset.

[0043] Finally, the time-aligned dataset and the spatially correlated dataset are merged 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°N, 120°E, and altitude 500 meters, ultimately constructing a complete communication dataset.

[0044] 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 assessment and link selection decisions.

[0045] Furthermore, step A200 in the method provided in this application embodiment includes:

[0046] A210: Calculates the elevation angle of Ku-band satellites to generate a satellite elevation angle score.

[0047] A220: Perform margin assessment on communication links based on Ku-band satellite terminals and generate link margin values.

[0048] A230: Calculates spatial attenuation for Ku-band satellites based on their high and low orbit distances, and generates spatial attenuation compensation values.

[0049] A240: The satellite elevation angle score, the link margin value, and the spatial attenuation compensation value are weighted and fused together. Based on the fusion result, the link coverage of high and low orbit Ku-band satellites is calculated to determine the link coverage range.

[0050] Optionally, firstly, calculate the satellite elevation angle score. Based on the real-time elevation angle values ​​of the satellite and the UAV, score according to the set rules: when the elevation angle reaches or exceeds 60°, score 100 points directly; when the elevation angle is between 30° and 60°, the score is calculated linearly. For example, when the elevation angle is 45°, the score = (45-30) / (60-30)×100=50 points; when the elevation angle is below 30°, score 0 points. This is to quantify the impact of the elevation angle on the link.

[0051] Next, the link margin value is generated. By monitoring the actual signal power received by the Ku-band satellite terminal in real time and combining it with the minimum received power required by the link, the value is calculated by those skilled in the art, taking into account factors such as actual atmospheric loss and rain attenuation. The difference between the two is the link margin value. For example, if the actual received power is -50dBm and the minimum required power is -70dBm, then the link margin value is 20dB. The larger the value, the stronger the link's anti-interference and attenuation capabilities.

[0052] Then, the spatial attenuation compensation value is calculated. Based on the real-time distance between the high- and low-orbit satellites and the UAV, 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. This balances the spatial attenuation differences of satellites in different orbits.

[0053] Finally, the satellite elevation angle score (0-100 points), link margin score (e.g., 0-20dB), and spatial attenuation compensation score (0-30) are proportionally converted to a score of 0-100. A weighted fusion is then performed, assuming the weights of the three are 40%, 30%, and 30% respectively. The fusion result is calculated as: elevation angle score × 40% + link margin score × 30% + spatial attenuation compensation score × 30%. Based on the fusion result, coverage levels are determined, such as above 80 points for strong coverage, 60-80 points for medium coverage, and below 60 points for weak coverage, ultimately determining the link coverage range of the high and low orbit Ku-band satellites.

[0054] By quantifying and weighting the effects of satellite elevation angle, link margin, and spatial attenuation, the link coverage range of high and low orbit satellites was accurately constructed, providing an objective reference for coverage capability in subsequent link selection decisions.

[0055] Furthermore, step A200 in the method provided in this application embodiment includes:

[0056] A250: Perform coverage quality mapping based on the link coverage range to obtain the coverage quality dimension.

[0057] A260: Based on the transmission stability assessment results, perform state mapping to obtain the stable state dimension.

[0058] A270: Perform a two-dimensional cross-mapping between the coverage quality dimension and the stable state dimension to construct a link decision matrix.

[0059] A280: Perform dynamic link selection based on the link decision matrix and formulate link selection decisions.

[0060] Specifically, when mapping coverage quality based on the link coverage range of high and low orbit Ku-band satellites, the first step is to determine the coverage quality label based on the fusion results of the link coverage range, such as above 80 points being stable, 60-80 points being metastable, and below 60 points being unstable. Then, the label is mapped to the corresponding decision value range: stable label is mapped to [80,100], metastable label is mapped to [60,80), and unstable label is mapped to [0,60), thereby obtaining the quantitative range of the coverage quality dimension.

[0061] Next, state mapping is performed based on the transmission stability assessment results. The coverage quality index in the assessment results is used as the basis to map the decision value range of the stable state dimension according to the set rules: when the index is ≥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), thus completing the quantification of the stable state dimension.

[0062] Next, a link decision matrix is ​​constructed by performing a two-dimensional cross-mapping of the coverage quality dimension and the stable state dimension. First, the median of the two dimension intervals is taken as the representative value. For example, the median of coverage quality [80, 100] is 90, and the median of stable state [90, 100] is 95. The mean of both is calculated as (90+95) / 2 = 92.5. Then, adjustments are made according to the interval combination type: if both are in the high interval (coverage ≥ 80, 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 (e.g., coverage [80, 100], stability [70, 90)), the mean is multiplied by 1.0 to obtain the corresponding value; if a low interval exists (e.g., coverage [0, 60)), the mean is multiplied by 0.8 to obtain the corresponding value. The calculation results of all combinations are filled into the matrix to form the link decision matrix, providing a quantitative basis for dynamic link selection.

[0063] Finally, the decision output value is extracted based on the link decision matrix. When the output value is higher than the first threshold, a low-orbit single-hop link is selected. When the output value is lower than the first threshold but higher than the second threshold, a high-orbit single-hop link is activated. When the output value is lower than the second threshold, a high-low orbit multi-satellite relay link is activated. The link selection decision is formulated, and the specific steps are explained in detail in A281-A284.

[0064] By quantifying coverage quality and transmission stability into two-dimensional intervals and cross-calculating them, a link decision matrix is ​​constructed, providing a scientific and quantifiable judgment standard for link selection decisions, ensuring the accuracy and adaptability of the decisions.

[0065] Furthermore, step A280 in the method provided in this application embodiment includes:

[0066] A281: Perform dynamic link selection based on the link decision matrix and extract the decision output value.

[0067] A282: When the decision output value of the link decision matrix is ​​higher than the first threshold, a low-Earth orbit satellite single-hop link is selected as the link selection decision.

[0068] A283: When the decision output value is lower than the first threshold but higher than the second threshold, the high-orbit satellite single-hop link is enabled as the link selection decision.

[0069] A284: When the decision output value is lower than the second threshold, activate the high-low orbit multi-satellite relay link as the link selection decision.

[0070] 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-Earth orbit satellite single-hop link, the high-Earth 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.

[0071] Next, a first threshold of 80 and a second threshold of 50 are set. Those skilled in the art can divide these thresholds based on the historical best and critical intervals of link communication quality. 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-Earth orbit satellite single-hop link are both at their optimal state. In this case, the low-Earth orbit satellite single-hop link is selected as the decision, utilizing its low latency and high bandwidth characteristics to ensure efficient data transmission.

[0072] 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 deteriorated but the high-orbit link can still meet the basic communication needs. The high-orbit satellite single-hop link is activated to maintain communication continuity by relying on its wide coverage advantage.

[0073] 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-low orbit multi-satellite relay link is activated to make up for the deficiency of the single link through multi-satellite collaborative relay and avoid communication interruption.

[0074] By setting thresholds to classify and judge the decision output values, and dynamically matching the optimal link type, adaptive selection of high and low orbit satellite links is achieved, ensuring that the UAV maintains an efficient and stable communication state in complex flight environments.

[0075] Furthermore, step A300 in the method provided in this application embodiment includes:

[0076] A310: Determine the target link type based on the link selection decision and set the switching trigger conditions.

[0077] A320: Perform feature analysis according to the target link type to obtain target link features, and dynamically adjust the radio frequency parameters of the Ku-band satellite terminal based on the target link features to obtain radio frequency adjustment parameters.

[0078] A330: Based on the target link characteristics, the baseband processing parameters of the Ku-band satellite terminal are reconstructed to obtain protocol stack adjustment parameters.

[0079] A340: Initiates link switching operations for high and low orbit Ku-band satellites based on the radio frequency adjustment parameters and the protocol stack adjustment parameters, and generates link switching results.

[0080] A350: Based on the link switching results, perform real-time transmission switching analysis, set real-time transmission quality indicators, and based on the link switching results, perform user experience switching analysis, and set user experience quality indicators.

[0081] A360: The real-time transmission quality indicators and the user experience quality indicators are correlated and integrated to construct the link quality indicator set.

[0082] In this embodiment of the application, the protocol stack refers to the set of data transmission protocols used for baseband processing in the Ku-band satellite terminal. It can be reconstructed according to the characteristics of the target link to adapt to different links, thereby obtaining protocol stack adjustment parameters.

[0083] Specifically, when determining the target link type based on link selection decisions, it is first necessary to clarify whether the current switch should be to a low-Earth orbit (LEO) satellite single-hop link, a high-Earth orbit (HEO) satellite single-hop link, or a multi-satellite relay link between LEO and LEO, and then set the switching trigger conditions: for example, when the LEO link signal strength is below -85dBm for 3 consecutive seconds, a switch to a HEO link is triggered; when the single-hop link bit error rate exceeds 1e-4 and lasts for 2 seconds, a switch to a multi-satellite relay link between LEO and LEO is triggered.

[0084] Next, feature analysis is performed according to the determined target link type to extract its key characteristics: Low-Earth orbit (LEO) satellite single-hop links have high bandwidth (e.g., 10-50 Mbps) and low latency (e.g., 100-300 ms), but a relatively small coverage area; High-Earth orbit (HEO) satellite single-hop links have wide coverage but higher latency (e.g., 500-800 ms) and lower bandwidth (e.g., 2-10 Mbps); Multi-satellite relay links in both LEO and HEO achieve wide-area coverage through multi-satellite collaboration, have strong anti-interference capabilities, but complex transmission paths. Based on these characteristics, radio frequency (RF) parameters are adjusted: For example, for LEO links, the RF frequency is adjusted to 12-14 GHz, and the transmit power is set to 2W to adapt to its short-distance transmission; for HEO links, the frequency is adjusted to 10.7-12.75 GHz, and the transmit power is increased to 3W to compensate for long-distance attenuation; for relay links, frequency hopping technology is enabled, the frequency dynamically switches within the Ku band, and the power is dynamically allocated according to the number of relay nodes (e.g., 2.5W for 2 relay nodes), thus obtaining the RF adjustment parameters.

[0085] Then, based on the characteristics of the target link, the baseband processing parameters are reconstructed using a protocol stack: the low-orbit link uses a TCP / IP protocol stack with a frame length of 1500 bytes and QPSK encoding to improve transmission efficiency; the high-orbit link, due to its high latency, uses an improved TCP protocol, such as TCP-BBR, with a frame length shortened to 1000 bytes and 8PSK encoding to enhance noise immunity; the relay link is reconstructed into a multi-hop protocol stack, with a relay node synchronization field added and LDPC encoding used to reduce bit errors during relaying, thereby obtaining the protocol stack adjustment parameters.

[0086] Next, based on the target link type, the low-rail direct connection, high-rail direct connection, and high-low rail relay types are parsed out. A hierarchical handshake protocol is initiated according to the type, and corresponding requests are sent and information is received to generate the corresponding link switching results. The specific steps are explained in detail in A341-A342.

[0087] Next, based on the link switching results, real-time transmission switching analysis is performed, and real-time transmission quality indicators are set: such as throughput for low-orbit links, with a target of ≥10Mbps; bit error rate for high-orbit links, with a target of ≤1e-5; and end-to-end latency for relay links, with a target of ≤1000ms. Simultaneously, user experience switching analysis is performed, and user experience quality indicators are set: such as the number of times video transmission stutters, with a target of ≤1 time / minute; and data transmission integrity, with a target of ≥99.9%.

[0088] Finally, real-time transmission quality indicators and user experience quality indicators are linked and integrated. For example, a weighted algorithm is used to calculate a comprehensive score with transmission indicators accounting for 60% and user experience indicators accounting for 40%, forming a set of link quality indicators that intuitively reflects the communication performance of the current link.

[0089] 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 were achieved, providing a reliable basis for subsequent transmission optimization.

[0090] Furthermore, step A340 in the method provided in this application embodiment includes:

[0091] A341: Based on the target link type, analyze to obtain the low-rail direct connection type, high-rail direct connection type, and high-low rail relay type.

[0092] A342: A hierarchical handover handshake protocol is initiated to perform handover operations based on the LEO direct connection type, the HEO direct connection type, and the HEO / LEO relay type: When the target link type is the LEO direct connection type, a fast handover request is sent to receive the time slot allocation map of the LEO satellite, generating a first link handover result; when the target link type is the HEO direct connection type, an enhanced handover request is sent to receive the power adjustment value of the HEO satellite, generating a second link handover result; when the target link type is the HEO / LEO relay type, a broadcast path establishment request is sent to receive multi-terminal service flows, generating a third link handover result.

[0093] In one embodiment, the target link type determined based on the link selection decision is first analyzed to clarify the specific type: if the target is low-latency, high-bandwidth direct communication, it is determined to be a low-Earth orbit direct connection type; if the target is wide-coverage, long-distance direct communication, it is determined to be a high-Earth 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.

[0094] Based on the parsed link type, a tiered handover handshake protocol is initiated: For LEO direct connections, the terminal sends a fast handover request to the target LEO satellite, which includes the current link's radio frequency parameters and protocol stack information. The LEO satellite responds within 50ms, returning a time slot allocation map, such as allocating time slots 3 and 5, with each time slot lasting 10ms. The terminal then completes time slot synchronization accordingly, generating the first link handover result, including the handover time slot number and synchronization completion time.

[0095] For high-orbit direct connections, the terminal sends an enhanced handover request, including the current transmit power (e.g., 2W) and link margin. Due to the greater distance, high-orbit satellites require power compensation to offset attenuation. Within 300ms, they return a power adjustment value, such as +1.8W. The terminal adjusts the transmit power to 3.8W and completes the handover, generating a second link handover result, including the adjusted power value and link lock status, if the lock is successful.

[0096] For high-Earth orbit (LEO) and low-Earth orbit (HEO) relay types, the terminal broadcasts a path establishment request to available LEO and HEO satellites in the vicinity, such as LEO satellite A and HEO satellite B. The request includes the data transmission rate and the required number of relay nodes. Each satellite returns service flow allocation information within 500ms, such as A being responsible for uplink data forwarding and B being responsible for downlink data forwarding. The terminal integrates the service flows from multiple terminals to form a relay path and generates a third-link handover result, including a list of relay nodes and path transmission delay.

[0097] By designing a tiered switching mechanism for different link types, the link switching is accurately completed and corresponding results are generated, ensuring the efficiency and adaptability of high and low orbit Ku-band satellite link switching, laying the foundation for subsequent link quality monitoring.

[0098] Furthermore, step A400 in the method provided in this application embodiment includes:

[0099] A410: The link quality index set and the UAV flight status data are spatiotemporally aligned according to timestamps to generate a spatiotemporally aligned dataset.

[0100] A420: Construct a three-dimensional coordinate system of altitude-airspeed-attitude angle, map the spatiotemporal aligned dataset to the three-dimensional coordinate system, and draw a link quality heatmap.

[0101] A430: Traverse the link quality heatmap to perform transmission analysis on UAV-borne high and low orbit Ku-band satellite terminals, and mark abnormal areas as transmission black zones.

[0102] A440: Perform multi-dimensional fault attribution determination based on the aforementioned transmission black zone to generate fault root cause parameters.

[0103] A450: Based on the aforementioned root cause parameters, perform transmission iterative analysis on the UAV-borne high and low orbit Ku-band satellite terminal to determine multiple sets of parameters to be optimized.

[0104] A460: Load the multiple sets of parameters to be optimized and backtrack to the Ku-band satellite terminal to perform optimization, generate the parameter optimization effect, verify the parameter optimization effect, and when the parameter optimization effect passes the verification, construct an optimization knowledge base.

[0105] A470: Continuously optimize UAV-borne high and low orbit Ku-band satellite terminals through the aforementioned optimization knowledge base.

[0106] In this embodiment of the application, the transmission black area refers to the abnormal transmission area marked in the link quality heatmap.

[0107] Optionally, firstly, the link quality metric set, which includes real-time transmission throughput, bit error rate, and number of stutters, is spatiotemporally aligned with UAV flight status data, such as altitude, airspeed, and attitude angle, using timestamps accurate to milliseconds. For example, the link throughput of 20Mbps at 10:00:01.000 is associated with the flight altitude of 1500 meters, airspeed of 45m / s, and attitude angle of 5° at the same time, ensuring that the data correspond one-to-one in the time dimension, generating a spatiotemporally aligned dataset, and establishing a unified data foundation for subsequent analysis.

[0108] The drone's altitude can be obtained in real time through its onboard GPS or BeiDou satellite positioning modules. Its airspeed is measured by the airspeed tube on the fuselage or by the integrated wind speed sensor. Attitude angles, including roll angle, pitch angle, and yaw angle, are sensed 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 foundation for subsequent spatiotemporal alignment and analysis with the link quality index set.

[0109] Next, a three-dimensional coordinate system was constructed with altitude (Y-axis, unit: meters); airspeed (X-axis, unit: m / s); and attitude angle (Z-axis, unit: degrees). The X, Y, and Z axes were integrated into a single coordinate system. Each data point in the spatiotemporally aligned dataset was mapped to a corresponding point in this coordinate system. For example, a point with an altitude of 1500 meters, airspeed of 45 m / s, and attitude angle of 5° corresponds to a link quality score of 75. All grid points within the coordinate system were filled using an interpolation algorithm. Then, a color gradient was used (red for scores <40, yellow for 40-60, and green for >60) to create a link quality heatmap, visually representing the link quality distribution under different flight conditions.

[0110] Then, transmission analysis is performed on each grid point of the link quality heatmap. Areas with a link quality score of <30 and where three or more consecutive adjacent points meet this condition are defined as abnormal areas and marked as transmission black zones. For example, areas with an altitude of 2500-2800 meters, an airspeed of 55-60 m / s, and an attitude angle of 10°-15° that consistently have a score of 25 are marked as transmission black zones, thus identifying the flight state range that needs to be optimized.

[0111] Next, multi-dimensional fault attribution determination is performed based on the transmission black zone: fault determination is performed on satellite link, aircraft status, and high and low orbit Ku-band satellite terminals respectively. The results are used to determine the cause and generate the corresponding first, second, and third fault root cause parameters. The specific steps are explained in detail in A441-A443.

[0112] Next, the terminal's transmission was iteratively analyzed according to the root cause parameters of the fault: for insufficient elevation angle of low-orbit satellites, the frequency was iteratively adjusted, such as from 12GHz to 14GHz, and the encoding method was changed, such as from QPSK to 16QAM; for drastic fluctuations in attitude angle, the antenna pointing algorithm was iteratively optimized, such as shortening the adjustment period to 100ms; for low RF power, the power was iteratively increased, such as from 1.5W to 2.0W. Through multiple rounds of testing, 3-5 sets of parameters to be optimized were determined, each set including combinations of parameters such as frequency, power, and algorithm.

[0113] Next, the parameter set 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 increasing from 25 to 65. The effect of parameter optimization is verified: when the optimized score is >60 in 3 consecutive tests, the effect is deemed to have passed the verification. The parameter set and the corresponding black zone flight status, such as altitude 2500-2800 meters, airspeed 55-60 m / s, attitude angle 10°-15°, etc., are stored in the optimization knowledge base to form a mapping relationship between flight status and optimized parameters.

[0114] Finally, the terminal is continuously optimized by optimizing the knowledge base. The current flight status of the drone is collected in real time, such as altitude of 2600 meters and 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.

[0115] Through a closed-loop analysis and optimization of the entire process from data alignment to knowledge base construction, transmission problems were accurately located and continuously improved, enabling efficient and stable transmission of UAV-borne high and low orbit Ku-band satellite terminals in complex flight environments.

[0116] Furthermore, step A440 in the method provided in this application embodiment includes:

[0117] A441: Based on the aforementioned transmission black zone, determine the satellite link fault, attribute the cause according to the first determination result, and generate the first fault root cause parameter.

[0118] A442: Based on the transmission black zone, perform aircraft status fault determination, attribute the cause according to the second determination result, and generate second fault root cause parameters.

[0119] A443: Based on the aforementioned transmission black zone, perform fault determination for high and low orbit Ku-band satellite terminals, and attribute the cause according to the third determination result to generate third fault root cause parameters.

[0120] In one embodiment, when determining satellite link failure based on transmission black zones, the satellite communication data corresponding to the black zone is first extracted, including satellite elevation angle, link margin, and spatial attenuation value. Anomaly thresholds are set as follows: a satellite elevation angle continuously below 20°, a link margin less than 8dB, and a spatial attenuation value greater than 35dB. If the satellite data from the transmission black zone meets these conditions for more than 10 consecutive seconds, it is determined to be a satellite link failure. Based on the determination result, the cause is attributed. For example, if a low-Earth orbit satellite's elevation angle is insufficient due to its orbital position, a first root cause parameter, "low-Earth orbit satellite elevation angle continuously low," is generated; if a high-Earth orbit satellite has insufficient link margin, specific parameters such as "high-Earth orbit satellite link margin insufficient" are generated.

[0121] When determining aircraft status faults based on transmission black zones, the flight parameters of the corresponding UAVs are analyzed, including attitude angles (roll and pitch angles), airspeed rate of change, and altitude fluctuations. Anomalies are defined as attitude angle fluctuations exceeding ±15°, airspeed rate of change exceeding 10 m / s², and altitude fluctuations exceeding 50 meters. If the flight data from the transmission black zone meets these criteria and coincides perfectly with the time of link quality degradation, it is determined to be an aircraft status fault. The cause is attributed based on the determination results. For example, if drastic attitude angle fluctuations cause antenna pointing deviation, a second root cause parameter, "Drastic UAV Attitude Angle Fluctuation," is generated; if a sudden drop in altitude causes signal obstruction, parameters such as "Rapid Drop in UAV Altitude Leading to Signal Obstruction," are generated.

[0122] When performing fault determination for high and low orbit Ku-band satellite terminals in transmission black zones, the system monitors the terminal's operational data, including RF transmit power, baseband processing latency, and protocol stack synchronization status. Abnormal values ​​are defined as RF power consistently below 1.2W, baseband processing latency 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 excluded, the terminal is determined to be faulty. Based on the determination results, the system attributes the cause; for example, if the RF module power output is abnormal, a third root cause parameter, "terminal RF transmit power insufficient," is generated; if the protocol stack synchronization is abnormal, parameters such as "terminal protocol stack synchronization failure" are generated.

[0123] By identifying and attributing faults in transmission blackout areas from three dimensions—satellite link, aircraft status, and terminal—the root cause of transmission anomalies can be accurately located, providing a clear direction for subsequent targeted optimization and ensuring the efficiency and accuracy of fault resolution.

[0124] In summary, the transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals provided in this application has the following technical effects:

[0125] This application establishes a communication link by configuring a UAV 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. This optimizes the transmission of UAV-borne high and low orbit Ku-band satellite terminals, making the transmission effect more efficient and stable. It achieves stable transmission between UAVs and high and low orbit Ku-band satellites, improves link quality, and meets the technical requirements for efficient and reliable communication.

[0126] Example 2, as Figure 2 As shown, based on the same inventive concept as in Embodiment 1 above, this application provides a transmission optimization system for an unmanned aerial vehicle (UAV)-borne high and low orbit Ku-band satellite terminal, the system comprising:

[0127] 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 the communication dataset, conduct transmission stability assessment, and generate transmission stability assessment results.

[0128] Link selection decision-making module 2 is used to select links based on the link coverage of high and low orbit Ku-band satellites and the transmission stability assessment results, and to make link selection decisions.

[0129] Link quality index set acquisition module 3 is used to dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform data transmission monitoring by performing switching operations between high and low orbit Ku-band satellite links according to the adjustment results, and obtain the link quality index set.

[0130] The transmission optimization execution module 4 is used to perform transmission iterative analysis on the UAV-borne high and low orbit Ku-band satellite terminals according to the link quality index set and the UAV flight status data, and backtrack to the Ku-band satellite terminals for transmission optimization based on the analysis results.

[0131] Furthermore, the transmission stability assessment result generation module 1 is used to perform the following steps:

[0132] A multidimensional link dataset is obtained by real-time acquisition of communication links of UAV-borne high and low orbit Ku-band satellite terminals; the multidimensional link dataset is then 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 UAV 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.

[0133] Furthermore, the link selection decision-making module 2 is used to perform the following steps:

[0134] The elevation angle of Ku-band satellites is calculated to generate a satellite elevation angle score; the communication link of Ku-band satellite terminals is evaluated for margin to generate a link margin value; spatial attenuation of Ku-band satellites is calculated based on the distance between high and low orbit orbits to generate a spatial attenuation compensation value; the satellite elevation angle score, the link margin value, and the spatial attenuation compensation value are weighted and fused, and the link coverage of high and low orbit Ku-band satellites is calculated based on the fusion result to determine the link coverage range.

[0135] Furthermore, the link selection decision-making module 2 is used to perform the following steps:

[0136] Coverage quality mapping is performed based on the link coverage range to obtain the coverage quality dimension; state mapping is performed based on the transmission stability assessment results to obtain the stable state dimension; the coverage quality dimension and the stable state dimension are cross-mapped in two dimensions to construct a link decision matrix; dynamic link selection is performed based on the link decision matrix to formulate a link selection decision.

[0137] Furthermore, the link selection decision-making module 2 is used to perform the following steps:

[0138] Dynamic link selection is performed based on the link decision matrix, and the decision output value is extracted. When the decision output value of the link decision matrix is ​​higher than a first threshold, a low-Earth 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-Earth 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-low orbit multi-satellite relay link is activated as the link selection decision.

[0139] Furthermore, the link quality indicator set acquisition module 3 is used to perform the following steps:

[0140] Based on the link selection decision, the target link type is determined, and the handover triggering conditions are set. Feature analysis is performed according to the target link type to obtain target link characteristics. Based on these characteristics, the radio frequency (RF) parameters of the Ku-band satellite terminal are dynamically adjusted to obtain RF adjustment parameters. Based on the target link characteristics, the baseband processing parameters of the Ku-band satellite terminal are reconstructed using the protocol stack to obtain protocol stack adjustment parameters. According to the RF adjustment parameters and the protocol stack adjustment parameters, a link handover operation for high-Earth orbit (HEO) and low-Earth orbit (LEO) Ku-band satellites is initiated, generating a link handover result. Based on the link handover result, real-time transmission handover analysis is performed, and real-time transmission quality indicators are set. Based on the link handover result, user experience handover analysis is performed, and user experience quality indicators are set. The real-time transmission quality indicators and the user experience quality indicators are correlated and integrated to construct the link quality indicator set.

[0141] Furthermore, the link quality indicator set acquisition module 3 is used to perform the following steps:

[0142] Based on the target link type, the following are obtained: LEO direct connection type, HEO direct connection type, and HEO-LEO relay type. A hierarchical handover handshake protocol is initiated to perform the handover operation according to the LEO direct connection type, HEO direct connection type, and HEO-LEO relay type: When the target link type is the LEO direct connection type, a fast handover request is sent to receive the time slot allocation map of the LEO satellite, generating a first link handover result; when the target link type is the HEO direct connection type, an enhanced handover request is sent to receive the power adjustment value of the HEO satellite, generating a second link handover result; when the target link type is the HEO-LEO relay type, a broadcast path establishment request is sent to receive multi-terminal service flows, generating a third link handover result.

[0143] Furthermore, the transmission optimization execution module 4 is used to perform the following steps:

[0144] The link quality index set and the UAV flight status data are spatiotemporally aligned according to timestamps to generate a spatiotemporally aligned dataset. A three-dimensional coordinate system of altitude-airspeed-attitude angle is constructed, and the spatiotemporally aligned dataset is mapped to the three-dimensional coordinate system to draw a link quality heatmap. The link quality heatmap is traversed to perform transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminals, and abnormal areas are marked as transmission black zones. Multidimensional fault attribution judgment 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 terminals according to the fault root cause parameters to determine multiple sets of parameters to be optimized. The multiple sets of parameters to be optimized are loaded and backtracked to the Ku-band satellite terminals to perform optimization, generating parameter optimization effects and verifying the parameter optimization effects. When the parameter optimization effects pass the verification, an optimization knowledge base is constructed. The UAV-borne high and low orbit Ku-band satellite terminals are continuously optimized using the optimization knowledge base.

[0145] Furthermore, the transmission optimization execution module 4 is used to perform the following steps:

[0146] Satellite link fault determination is performed based on the transmission black zone, and a first fault root cause parameter is generated based on the first determination result; aircraft status fault determination is performed based on the transmission black zone, and a second fault root cause parameter is generated based on the second determination result; high and low orbit Ku-band satellite terminal fault determination is performed based on the transmission black zone, and a third fault root cause parameter is generated based on the third determination result.

[0147] The transmission optimization system for UAV-borne high and low orbit Ku-band satellite terminals provided in this embodiment of the invention can execute the transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0148] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. 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 each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0149] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for optimizing the transmission of UAV-borne high and low orbit Ku-band satellite terminals, characterized in that, The method includes: Real-time monitoring of the communication link of the Ku-band satellite terminal carried by the UAV is conducted to obtain the communication dataset for transmission stability assessment and generate transmission stability assessment results. Link selection is made based on the link coverage of high and low orbit Ku-band satellites and the transmission stability assessment results. Based on the link selection decision, the Ku-band satellite terminal is dynamically adjusted, and based on the adjustment result, the handover operation between high and low orbit Ku-band satellite links is performed to monitor data transmission and obtain a set of link quality indicators. Based on the link quality index set and UAV flight status data, the transmission iteration analysis of the UAV-borne high and low orbit Ku-band satellite terminal is performed, and the analysis results are used to backtrack to the Ku-band satellite terminal for transmission optimization. The process of constructing the link coverage area for high and low Earth orbit Ku-band satellites includes: The elevation angle of Ku-band satellites is calculated to generate a satellite elevation angle score. Based on the communication link of the Ku-band satellite terminal, a margin assessment is performed to generate a link margin value; Spatial attenuation calculations are performed on Ku-band satellites based on their high and low orbit distances to generate spatial attenuation compensation values. The satellite elevation angle score, the link margin value, and the spatial attenuation compensation value are weighted and fused. Based on the fusion result, the link coverage of high and low orbit Ku-band satellites is calculated to determine the link coverage range. The step of performing iterative transmission analysis on the UAV-borne high and low orbit Ku-band satellite terminals based on the link quality index set and UAV flight status data, and then optimizing the transmission of the Ku-band satellite terminals based on the analysis results, includes: The link quality index set and the UAV flight status data are spatiotemporally aligned according to timestamps to generate a spatiotemporally aligned dataset. Construct a three-dimensional coordinate system of altitude-airspeed-attitude angle, map the spatiotemporal aligned dataset to the three-dimensional coordinate system, and draw a link quality heatmap; The link quality heatmap is traversed to perform transmission analysis on UAV-borne high and low orbit Ku-band satellite terminals, and abnormal areas are marked as transmission black areas. Based on the aforementioned transmission black zone, perform multi-dimensional fault attribution determination to generate fault root cause parameters; Based on the aforementioned root cause parameters, a transmission iterative analysis was performed on the UAV-borne high and low orbit Ku-band satellite terminal to determine multiple sets of parameters to be optimized. Load the multiple sets of parameters to be optimized and backtrack to the Ku-band satellite terminal to perform optimization, generate the parameter optimization effect, verify the parameter optimization effect, and when the parameter optimization effect passes the verification, construct an optimization knowledge base; The optimization knowledge base is used to continuously optimize the UAV-borne high and low orbit Ku-band satellite terminals.

2. The transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals as described in claim 1, characterized in that, Real-time monitoring of the communication link of the Ku-band satellite terminal carried by the UAV to obtain communication datasets includes the following methods: A multi-dimensional link dataset was obtained by real-time acquisition of the communication links of UAV-borne high and low orbit Ku-band satellite terminals. The multidimensional link dataset is interpolated and resampled according to the acquisition period to determine the time series with equal intervals. The multidimensional link dataset is time-aligned according to the equal-interval time series to obtain a time-aligned dataset. A three-dimensional trajectory association communication matrix is ​​constructed based on UAV flight data. The multi-dimensional 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.

3. The transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals as described in claim 1, characterized in that, Link selection is made based on the link coverage of high and low orbit Ku-band satellites and the transmission stability assessment results. The method includes: Based on the link coverage range, a coverage quality mapping is performed to obtain the coverage quality dimension; Based on the transmission stability assessment results, state mapping is performed to obtain the stable state dimension; The coverage quality dimension and the stable state dimension are cross-mapped in two dimensions to construct the link decision matrix; Dynamic link selection is performed based on the link decision matrix to formulate link selection decisions.

4. The transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals as described in claim 3, characterized in that, Dynamic link selection is performed based on the link decision matrix to formulate link selection decisions. The method includes: Dynamic link selection is performed based on the link decision matrix, and the decision output value is extracted. When the decision output value of the link decision matrix is ​​higher than the first threshold, a low-Earth 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 the second threshold, the high-orbit satellite single-hop link is used as the link selection decision. When the decision output value is lower than the second threshold, the high-low orbit multi-satellite relay link is activated as the link selection decision.

5. The transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals as described in claim 1, characterized in that, Based on the link selection decision, the Ku-band satellite terminal is dynamically adjusted. Based on the adjustment result, a handover operation between high- and low-Earth orbit Ku-band satellite links is performed to monitor data transmission and obtain a set of link quality indicators. The method includes: Based on the link selection decision, the target link type is determined, and the switching trigger conditions are set; Feature analysis is performed according to the target link type to obtain target link characteristics. Based on the target link characteristics, the radio frequency parameters of the Ku-band satellite terminal are dynamically adjusted to obtain radio frequency adjustment parameters. Based on the target link characteristics, the baseband processing parameters of the Ku-band satellite terminal are reconstructed using a protocol stack to obtain protocol stack adjustment parameters; Based on the radio frequency adjustment parameters and the protocol stack adjustment parameters, initiate link handover operations for high and low orbit Ku-band satellites and generate link handover results; Based on the link switching results, perform real-time transmission switching analysis and set real-time transmission quality indicators. Based on the link switching results, perform user experience switching analysis and set user experience quality indicators. The real-time transmission quality indicators and the user experience quality indicators are correlated and integrated to construct the link quality indicator set.

6. The transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals as described in claim 5, characterized in that, Based on the radio frequency adjustment parameters and the protocol stack adjustment parameters, a link handover operation for high- and low-Earth orbit Ku-band satellites is initiated, and a link handover result is generated. The method includes: Based on the target link type, the following types are obtained: low-rail direct connection type, high-rail direct connection type, and high-low rail relay type. The handover operation is initiated based on the low-rail direct connection type, the high-rail direct connection type, and the high-low rail relay type, using a hierarchical handover handshake protocol. When the target link type is switched to the LEO direct connection type, a fast switch request is sent to receive the time slot allocation map of the LEO satellite and generate the first link switch result; When the target link type is switched to the high-orbit direct connection type, an enhanced switching request is sent to receive the power adjustment value of the high-orbit satellite and generate a second link switching result; When the target link type is switched to the high-low rail relay type, the broadcast path establishment request receives multi-terminal service streams and generates a third link switching result.

7. The transmission optimization method for UAV-borne high and low orbit Ku-band satellite terminals as described in claim 1, characterized in that, Based on the aforementioned transmission black zone, a multi-dimensional fault attribution determination is performed to generate fault root cause parameters. The method includes: Based on the aforementioned transmission black zone, satellite link faults are determined, and attribution is performed according to the first determination result to generate first fault root cause parameters. Based on the transmission black zone, the aircraft status fault determination is performed, and the cause is attributed according to the second determination result to generate the second fault root cause parameter. Based on the aforementioned transmission black zone, fault determination is performed on high and low orbit Ku-band satellite terminals. The third determination result is used to attribute the fault and generate a third fault root cause parameter.

8. A transmission optimization system for UAV-borne high and low orbit Ku-band satellite terminals, characterized in that, The system for implementing the transmission optimization method for an unmanned aerial vehicle (UAV)-borne high / low orbit Ku-band satellite terminal according to any one of claims 1-7, 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 dataset, conduct transmission stability assessment, and generate transmission stability assessment results. The link selection decision-making module is used to select links based on the link coverage of high and low orbit Ku-band satellites and the transmission stability assessment results, and to make link selection decisions. The link quality index set acquisition module is used to dynamically adjust the Ku-band satellite terminal according to the link selection decision, perform data transmission monitoring by performing switching operations between high and low orbit Ku-band satellite links according to the adjustment results, and obtain the link quality index set. The transmission optimization execution module is used to perform iterative analysis on the transmission of UAV-borne high and low orbit Ku-band satellite terminals according to the link quality index set and the UAV flight status data, and backtrack to the Ku-band satellite terminals for transmission optimization based on the analysis results.

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