Emergency tethered communication unmanned aerial vehicle platform

Abstract

The present application relates to the technical field of emergency mobile communication, specifically to an emergency tethered communication unmanned aerial vehicle platform, which comprises a flight attitude control module, a signal coverage optimization module, a dynamic trajectory extraction module, a communication quality quantification module and a risk state identification module.In the present application, the flight attitude of the unmanned aerial vehicle is precisely adjusted, the signal coverage and communication quality are optimized, and the reliability and coverage range of emergency communication are improved.The matching between signal strength distribution and flight path can be analyzed in real time to ensure that the stability and coverage effect of the communication equipment reach the optimal state in a sudden environment, potential risks are monitored and identified in real time, the communication quality trend is quantitatively analyzed, the security state is automatically adjusted, and efficient and stable communication services are continuously provided under complex conditions.This optimization not only improves the adaptability of the unmanned aerial vehicle and enhances the emergency response capability of emergency communication in different environments, but also ensures the timeliness and accuracy of communication support.

Description

Technical Field

[0001] This invention relates to the field of emergency mobile communication technology, and in particular to an emergency tethered communication drone platform. Background Technology

[0002] Emergency mobile communication technology refers to the technical field that provides mobile communication services to meet communication needs in emergencies and sudden events. Core technologies in this field include rapidly deployable communication equipment, high reliability assurance for emergency communications, and expanded communication coverage. To meet communication needs in specific scenarios, equipment such as emergency communication vehicles, communication satellites, and drones are widely used. The goal of this field is to achieve rapid and stable communication services in disaster, emergency, or remote environments through efficient communication methods.

[0003] Traditional emergency tethered communication drone platforms refer to equipment platforms that utilize drone technology to provide emergency communication services. By using drones as communication relays or base stations, they achieve network coverage and signal transmission. Traditional emergency tethered communication drone platforms typically employ fixed flight paths and altitudes, carrying wireless communication equipment such as satellite communication terminals and mobile communication base stations to ensure emergency communication. Their main technical measures include utilizing the drone's flight platform to enhance the coverage of communication base stations and ensure the stability of communication equipment during high-altitude operation; using batteries or solar energy to power the drones; and carrying communication equipment and data transmission for signal relay and transmission.

[0004] Existing technologies face the problem of unstable communication coverage in dynamic environments. Traditional emergency tethered communication drone platforms rely on fixed flight paths and altitudes, failing to fully consider the impact of environmental factors. This leads to fluctuations in the stability and coverage of communication equipment under complex or variable weather conditions. Furthermore, traditional methods lack real-time dynamic adaptability in adjusting flight attitude and communication quality, making them unable to effectively cope with changes in communication signals or environmental interference, thus affecting the reliability and response speed of emergency communications. For example, in strong winds or terrain changes, traditional platforms may experience signal coverage dead zones or communication interruptions, significantly limiting the effectiveness of emergency communications. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing an emergency tethered communication drone platform.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: the emergency tethered communication drone platform includes:

[0007] The flight attitude control module obtains the current wind speed influence value and load distribution status of the UAV, combines the tether cable tension range fed back by the ground control unit, selects adjustment strategies, and performs dynamic mapping according to the load distribution status to generate a flight attitude balance parameter set.

[0008] The signal coverage optimization module calls the flight attitude equalization parameter set, collects the signal strength distribution of communication equipment and the location information of the coverage area boundary, compares the degree of overlap between the two in the target area, selects the corresponding antenna angle and power configuration group, and generates a signal coverage optimization configuration group.

[0009] Based on the signal coverage optimization configuration group, the dynamic trajectory extraction module collects the altitude change time series and position offset trajectory in the UAV flight trajectory, determines the synchronous offset amplitude between trajectories, filters the stable region within the flight cycle, and generates a continuous trajectory feature set.

[0010] The communication quality quantification module calls the continuous trajectory feature set, extracts the signal strength range of each time period within the signal coverage area, and matches it with the set change segment range in the communication cycle. By analyzing the communication quality trend through segment overlay, the communication guarantee time sequence trajectory trend is obtained.

[0011] As a further aspect of the present invention, the flight attitude equalization parameter set includes wind speed mapping factor, load distribution weight, tension control range, attitude balance threshold, and flight stability index; the signal coverage optimization configuration group includes antenna angle configuration, power allocation weight, boundary matching degree, and coverage area equalization; the continuous trajectory feature set includes altitude change curve, position offset trajectory, synchronization offset marker, and stability area identifier; and the communication assurance timing trajectory trend includes signal strength segment sequence, stage evolution mode, change trend path, and timing matching result.

[0012] As a further aspect of the present invention, the flight attitude control module includes:

[0013] The wind speed and load acquisition submodule acquires the current wind speed influence value and load distribution status of the UAV. Based on the tether cable tension range fed back by the ground control unit, it extracts the state values ​​that deviate from the load reference range and the wind speed standard range, and generates the initial offset parameter set.

[0014] The adjustment strategy extraction submodule, based on the initial offset parameter set and combined with the adjustment limit under the current tension condition, filters the tension adjustment factor and load correction factor range that can control the offset state, extracts the adjustment combination that matches the current offset level, and generates flight adjustment matching parameters.

[0015] The attitude mapping submodule identifies the function mapping group of attitude and balance control based on the flight adjustment matching parameters, combined with the current load distribution state of the UAV and the wind speed influence value, determines the constraint boundary of the flight rhythm, and generates a flight attitude balance parameter set.

[0016] As a further aspect of the present invention, the signal coverage optimization module includes:

[0017] The signal response submodule calls the flight attitude equalization parameter set, collects multi-directional signal strength response values ​​and antenna angle mapping values, compares the signal response with the angle matching degree, and obtains the signal coverage overlap rate index.

[0018] The boundary positioning submodule calls the signal coverage overlap rate index, extracts the signal gradient intensity of the coverage area boundary, and jointly filters the angle set that meets the boundary clarity requirements to obtain the antenna angle selection set.

[0019] The coverage configuration submodule selects a set of combined power allocation groups based on the antenna angle, identifies the signal strength and boundary coverage density of each group, calculates the signal coverage error rate, selects the group configuration with the lowest error rate, and generates a signal coverage optimization configuration group.

[0020] As a further aspect of the present invention, the dynamic trajectory extraction module includes:

[0021] The altitude trajectory extraction submodule collects altitude change values ​​for each time period based on the signal coverage optimization configuration group, records the time series and identifies the altitude difference within consecutive time periods to obtain the altitude change time trajectory.

[0022] The position offset determination submodule extracts position coordinates based on the time period corresponding to the height change time trajectory, identifies the position change vector for each time period, matches the height and position difference, calculates the synchronization offset value, determines whether it is lower than the position change benchmark, and obtains the synchronization offset time period set.

[0023] The trajectory feature construction submodule calls the time period sequence in the synchronous offset time period set, extracts the joint vector of height and position, sorts and constructs the trajectory, judges the consistency based on the Euclidean distance between adjacent time periods, and generates a continuous trajectory feature set.

[0024] As a further aspect of the present invention, the communication quality quantification module includes:

[0025] The signal interval extraction submodule calls the time segment in the continuous trajectory feature set, extracts the signal strength value of the coverage area according to the set time window, counts the extreme signal strength of each segment, delineates the signal strength change interval, and obtains the signal distribution set of the communication period.

[0026] The segment matching and judgment submodule identifies the fitting difference between the signal amplitude deviation and the preset amplitude based on the signal strength range of each segment in the signal distribution set during the communication period, combined with the changing characteristic segments set in the communication stage, and calculates the segment offset trend value of the communication stage.

[0027] The trend trajectory generation submodule identifies segments with continuous changes in the same direction based on the communication stage segment offset trend value, accumulates the trends of adjacent segments in the same direction, classifies and identifies the trend direction, and obtains the communication guarantee time sequence trajectory trend.

[0028] As a further aspect of the present invention, the platform also includes a risk status identification module:

[0029] Based on the communication assurance time-series trajectory trend, the risk status identification module classifies the trajectory trend of UAVs in the same round, collects the environmental feature categories recorded in the environmental label information group, judges the stability of the correlation interval between them and the trajectory classification, and generates an automated communication assurance status mapping group.

[0030] The automated communication assurance status mapping group includes trajectory classification results, environmental feature correlation, classification stability interval, and assurance status label.

[0031] As a further aspect of the present invention, the risk status identification module includes:

[0032] The trajectory interval classification submodule, based on the communication guarantee time-series trajectory trend, identifies the trajectory trend vector according to the start and end points and magnitude of trajectory changes, delineates the trajectory change interval according to the adjacent inflection point positions of the time series, marks the interval number corresponding to the UAV trajectory, and generates a trajectory interval labeling table.

[0033] The category interval association submodule calls the trajectory interval label table, collects feature category items from the environmental label information, analyzes the frequency of categories by the distribution quantity between the interval number and the feature category, and filters the association combinations with a frequency higher than the category interval matching threshold to obtain the category interval corresponding relationship group;

[0034] The support status configuration submodule sets the support label mapping rules between trajectory intervals and feature categories based on the category interval correspondence group, configures the support status field for UAVs in intervals that meet the mapping rules, automatically marks the UAV support management field, and generates an automated communication support status mapping group.

[0035] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0036] In this invention, by precisely adjusting the flight attitude of the UAV, signal coverage and communication quality are optimized, thereby improving the reliability and coverage of emergency communication. Based on the dynamic adjustment of flight attitude and trajectory, the solution can analyze the matching of signal strength distribution and flight path in real time, ensuring that the stability and coverage of communication equipment reach the optimal state in emergency environments. It can also monitor and identify potential risks in real time, and automatically adjust the support status through quantitative analysis of communication quality trends, ensuring that efficient and stable communication services are continuously provided under complex conditions. This optimization not only improves the adaptability of the UAV, but also enhances the emergency response capability of emergency communication in different environments, ensuring the timeliness and accuracy of communication support. Attached Figure Description

[0037] Figure 1 This is a platform flowchart of the present invention;

[0038] Figure 2 This is a flowchart of the flight attitude control module in this invention;

[0039] Figure 3 This is a flowchart of the signal coverage optimization module in this invention;

[0040] Figure 4 This is a flowchart of the dynamic trajectory extraction module in this invention;

[0041] Figure 5 This is a flowchart of the communication quality quantification module in this invention;

[0042] Figure 6 This is a flowchart of the risk status identification module in this invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0044] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0045] Please see Figure 1 The emergency tethered communication drone platform includes:

[0046] The flight attitude control module obtains the current wind speed influence value and load distribution status of the UAV, combines the tether cable tension range fed back by the ground control unit, selects adjustment strategies, and performs dynamic mapping according to the load distribution status to generate a flight attitude balance parameter set.

[0047] The signal coverage optimization module calls the flight attitude equalization parameter set, collects the signal strength distribution of communication equipment and the location information of the coverage area boundary, compares the degree of overlap between the two in the target area, selects the corresponding antenna angle and power configuration group, and generates a signal coverage optimization configuration group.

[0048] The dynamic trajectory extraction module, based on the signal coverage optimization configuration group, collects the time series of altitude changes and position offset trajectories in the UAV flight trajectory, determines the synchronous offset amplitude between trajectories, filters the stable regions within the flight cycle, and generates a continuous trajectory feature set.

[0049] The communication quality quantification module calls the continuous trajectory feature set to extract the signal strength range of each time period within the signal coverage area and matches it with the set change segment range in the communication cycle. By overlaying the segments, the communication quality trend is analyzed to obtain the communication guarantee time sequence trajectory trend.

[0050] The risk status identification module classifies the trajectory trends of UAVs in the same round based on the time-series trajectory trends of communication support, collects environmental feature categories recorded in the environmental label information group, judges the stability of the correlation interval between them and the trajectory classification, and generates an automated communication support status mapping group.

[0051] The flight attitude balance parameter set includes wind speed mapping factor, load distribution weight, tension control range, attitude balance threshold, and flight stability index. The signal coverage optimization configuration group includes antenna angle configuration, power allocation weight, boundary matching degree, and coverage area balance. The continuous trajectory feature set includes altitude change curve, position offset trajectory, synchronization offset marker, and stability area identifier. The communication support time-series trajectory trend includes signal strength segment sequence, stage evolution pattern, change trend path, and time-series matching result. The automated communication support status mapping group includes trajectory classification result, environmental feature correlation, classification stability interval, and support status label.

[0052] Please see Figure 2 The flight attitude control module includes:

[0053] The wind speed and load acquisition submodule acquires the current wind speed influence value and load distribution status of the UAV. Based on the tether cable tension range fed back by the ground control unit, it extracts the state values ​​that deviate from the load reference range and the wind speed standard range, and generates the initial offset parameter set.

[0054] The system acquires the current wind speed impact value and load distribution status of the drone. When performing a communication relay mission in a certain area, the drone's built-in sensors monitor and record the wind speed data of the external environment in real time. For example, when the drone is at an altitude of 100 meters, the wind speed measured by the onboard anemometer is 4.5 m / s. Simultaneously, the drone's load sensors sense the weight distribution of its mounted communication equipment and battery pack. For example, with a total load of 20 kg, the distribution is 12 kg at the front and 8 kg at the rear. Based on the tether cable tension range fed back by the ground control unit, the ground control unit sets and feeds back the safe tension range of the drone's tether cable as 150 N to 200 N. Exceeding this range poses a risk to the drone's structure or tether. This tension range is determined through historical flight data analysis and structural stress testing, and deviations from the load reference range and wind speed standard range are extracted. The status values ​​and load reference range are set to [18 kg, 22 kg], where the front-end load reference value is 10 kg and the rear-end load reference value is 10 kg. The wind speed standard range is set to [2 m / s, 6 m / s]. The current total load of 20 kg is within the load reference range, but the front-end load of 12 kg deviates from the front-end load reference value by 10 kg and 2 kg, and the rear-end load of 8 kg deviates from the rear-end load reference value by 10 kg and 2 kg. The wind speed of 4.5 m / s is within the wind speed standard range, and its deviation from the midpoint of the wind speed standard range of 4 m / s is 0.5 m / s. The deviation status value is obtained by calculating the absolute difference between the current value and the reference value or the midpoint value of the range. An initial offset parameter set is generated, including a total load offset of 0 kg, a front-end load offset of 2 kg, a rear-end load offset of 2 kg, a wind speed offset of 0.5 m / s, and a mooring cable tension of 175 Newtons.

[0055] The adjustment strategy extraction submodule, based on the initial offset parameter set and combined with the adjustment limit under the current tension condition, filters out the tension adjustment factor and load correction factor range that can control the offset state, extracts the adjustment combination that matches the current offset level, and generates flight adjustment matching parameters.

[0056] The initial offset parameter set is as follows: total load offset 0 kg, front-end load offset 2 kg, rear-end load offset 2 kg, wind speed offset 0.5 m / s, and current tether cable tension of 175 N. Combined with the adjustment limits under the current tension conditions, which are dynamically calculated by the ground control unit based on the UAV model, tether cable material strength, and current flight environment (such as temperature and humidity), for example, the tension adjustment limit is ±10 N, and the load correction limit is ±1 kg. This means that, without compromising safety, the tether cable tension can be adjusted up to ±10 N, and the load distribution can be adjusted up to ±1 kg. The controllable offset state of the tension adjustment factor and load correction factor range is selected. For each parameter in the initial offset parameter set, a preset control strategy table is used for selection. This strategy table stores feasible combinations of adjustment factors under different wind speeds and load deviations. For example, for a front-end load offset of 2 kg... The feasible load correction factor range is selected as [-0.5 kg, 0.5 kg]. Simultaneously, combined with the current tension value of 175 N, the feasible tension adjustment factor range is selected as [-5 N, 5 N]. This factor range ensures that the adjustment action is within the physically feasible and safe range. Adjustment combinations matching the current offset level are extracted. Based on the current offset parameters (e.g., front load offset of 2 kg, wind speed offset of 0.5 m / s), the best-matching adjustment combination is further selected from the selected factor ranges. For example, a front load correction factor of -0.3 kg (representing a slight adjustment of 0.3 kg load to the rear end) and a tension adjustment factor of +2 N (representing an increase in mooring cable tension of 2 N) are selected. This combination aims to achieve the greatest attitude stability improvement with minimal energy consumption, generating flight adjustment matching parameters, including a tension adjustment of +2 N, a front load correction of -0.3 kg, and a rear load correction of +0.3 kg, for subsequent attitude adjustments.

[0057] The attitude mapping submodule identifies the function mapping set of attitude and balance control based on the flight adjustment matching parameters, combined with the current load distribution state of the UAV and the wind speed influence value, determines the constraint boundary of the flight rhythm, and generates a set of flight attitude balance parameters.

[0058] The flight adjustment matching parameters include tension adjustment +2 Newtons, front load correction -0.3 kg, and rear load correction +0.3 kg. Combined with the current load distribution of the UAV and the wind speed influence value, the current total load of the UAV is 20 kg, with a front load of 12 kg and a rear load of 8 kg. The wind speed influence value is 0.5 m / s (representing the deviation of the wind speed from the standard value). A set of function mappings for attitude and balance control is identified. This set of function mappings is a series of nonlinear mapping relationships pre-constructed through wind tunnel experiments and flight simulations. Through these functions, the input adjustment parameters (such as tension change and load correction) and the current environmental state (such as wind speed influence and load distribution) are mapped to specific attitude adjustment commands for the UAV. For example, a mapping function is: Pitch angle adjustment = C1 × wind speed influence value + C2 × front load correction + C3 × tension adjustment, where C1 = 0.1 (degrees / (m / s)). (degrees / kg), C3=0.02 (degrees / Newtons), then the pitch angle adjustment amount The system determines the constraint boundaries of the flight rhythm by performing safety checks on the mapped attitude adjustment commands. For example, the maximum allowable adjustment range for pitch angle is [-5 degrees, 5 degrees], and the maximum allowable adjustment range for roll angle is [-5 degrees, 5 degrees]. If the calculated adjustment amount exceeds the range, the adjustment command is restricted to the boundary value. For example, if the calculated pitch angle adjustment amount is 6 degrees, the actual adjustment amount will be restricted to 5 degrees to avoid drastic changes or instability in the UAV's attitude. A set of flight attitude equilibrium parameters is generated, including a pitch angle adjustment amount of 0.24 degrees, a roll angle adjustment amount of 0.18 degrees, a yaw angle adjustment amount of 0.05 degrees, and the corresponding execution time and execution rate.

[0059] Please see Figure 3 The signal coverage optimization module includes:

[0060] The signal response submodule calls the flight attitude equalization parameter set, collects multi-directional signal strength response values ​​and antenna angle mapping values, compares the signal response with the angle matching degree, and obtains the signal coverage overlap rate index.

[0061] The system invokes a flight attitude equalization parameter set, for example, a set with pitch adjustment of 0.24 degrees, roll adjustment of 0.18 degrees, and yaw adjustment of 0.05 degrees. It then collects multi-directional signal strength response values ​​and antenna angle mapping values. While performing attitude adjustments, the UAV's communication module, through its built-in multi-channel receiver, collects signal strength response values ​​from different directions in real time. For example, at a specific time point, the UAV receives a signal strength of -70dBm from the base station and -85dBm from the interference source. Simultaneously, through high-precision attitude... The calibration data of the sensors and antenna array is used to obtain the current elevation and azimuth angles of the antenna relative to the base station. This angle information is the antenna angle mapping value. For example, if the antenna main lobe points towards the base station at an elevation angle of 30 degrees and an azimuth angle of 120 degrees, the signal response is compared with the angle matching degree. This is done by comparing the actually measured signal strength response value with the theoretical radiation pattern of the antenna at the current angle mapping value. For example, theoretically, the antenna should receive a signal of -68 dBm at an elevation angle of 30 degrees and an azimuth angle of 120 degrees, but actually receives -70 dBm. The matching degree is calculated as the absolute value of the difference between the theoretical and actual values. This matching degree reflects the accuracy of antenna pointing and signal transmission loss. The signal coverage overlap rate index is obtained by comprehensively evaluating the signal response and angle matching degree in multiple directions and calculating the degree of overlap within the signal coverage area. For example, for a certain target coverage area, if the signal strength of more than 90% of the sub-area is higher than -80dBm, then its signal coverage overlap rate is determined to be 90%. This index reflects the reliability and coverage efficiency of the UAV communication link under a given attitude, and the index is 92%.

[0062] The boundary positioning submodule calls the signal coverage overlap rate index, extracts the signal gradient intensity of the coverage area boundary, jointly filters the angle set that meets the boundary clarity requirements, and obtains the antenna angle selection set.

[0063] The signal coverage overlap rate was set at 92%. Signal gradient strength at the coverage area boundary was extracted. The UAV conducted flight tests at the edge of the target coverage area, monitoring the rate of change of signal strength along a specific direction (e.g., from the center of the coverage area outwards). For example, when the UAV moved from an area with a signal strength of -70 dBm to an area with a signal strength of -90 dBm, and the distance traveled was 10 meters, the signal gradient strength was... A higher gradient strength (dB / m) indicates rapid signal attenuation and clear boundaries. An angle set that meets the boundary clarity requirement is jointly selected. The boundary clarity requirement refers to the signal strength change rate reaching a preset threshold within a specific distance. For example, a preset signal gradient threshold of 1.5dB / m means that when the signal strength change rate is below 1.5dB / m, the boundary is considered blurry and cannot be used for precise coverage area division. By comparing the signal gradient strength measured under different antenna angle configurations, angle configurations with gradient strength higher than 1.5dB / m are selected. For example, if antenna angle configuration A has a gradient of 2.1dB / m at the boundary, and configuration B has 1.2dB / m, then configuration A is selected, and configuration B is excluded, resulting in an antenna angle selection set containing configuration A with an antenna tilt angle of 25 degrees, an azimuth angle of 110 degrees, and a beamwidth of 30 degrees. This angle set ensures signal coverage efficiency while making the boundaries of the coverage area clearly distinguishable, facilitating subsequent precise management.

[0064] The coverage configuration submodule selects a centralized combined power allocation group based on the antenna angle, identifies the signal strength and boundary coverage density of each group, and uses the following formula:

[0065] ;

[0066] Calculate the signal coverage error rate, select the group configuration with the lowest error rate, and generate the signal coverage optimization configuration group;

[0067] in, Represents the signal coverage error rate. This represents the total number of sampling points in the current combined power allocation group to be evaluated. Representing the The average value of the combined submodule signal strength received at each sampling point. Representing the Signal strength offset at each sampling point due to antenna angle correction Representing the The boundary density weighting factor of the coverage area at each sampling point Representing the The horizontal distance between each sampling point and the central station Representing the The vertical elevation difference at each sampling point. Representing the The target signal strength value at each sampling point Represents the reference power constant;

[0068] The antenna angle selection includes two sets of combined power allocation groups. The first group has an antenna tilt angle of 25 degrees, an azimuth angle of 110 degrees, and a transmit power of 30 watts. The second group has an antenna tilt angle of 28 degrees, an azimuth angle of 115 degrees, and a transmit power of 28 watts. The signal strength and boundary coverage density of each group are identified. For the first configuration, the signal strength at multiple sampling points within the target coverage area is identified through simulation or actual testing. For example, if the signal strength at a specific sampling point is -65 dBm, the density of the signal coverage area boundary under this configuration is evaluated, along with a boundary density weighting factor. The settings are determined based on the proportion of the area within the coverage region where the signal strength is higher than a threshold (e.g., -80dBm) and the clarity of the boundary gradient. The weight values ​​range from 0 to 1; a higher value indicates that the sampling point is closer to the desired boundary and the signal strength more closely matches expectations. For example, if a sampling point is located near the boundary of the target coverage area with moderate signal strength, its... The value was set to 0.9, while another sampling point was located in the center of the coverage area. Set the value to 0.1 and use the formula: ; Calculate the signal coverage error rate;

[0069] In the formula The signal coverage error rate represents the degree of deviation between the actual received signal and the target signal. Represents the total number of sampling points in the current combined power allocation group to be evaluated, for example , Representing the The average value of the combined submodule signal strength received at each sampling point, for example , , , Representing the The signal strength offset introduced by antenna angle correction at each sampling point is obtained through experimental calibration or theoretical calculation, for example, by adjusting the antenna angle to increase signal gain. , , , Representing the The boundary density weighting factor of the coverage area at each sampling point, for example , , , Representing the The horizontal distance between each sampling point and the central station, for example , , , Representing the The vertical elevation difference at each sampling point, for example , , , Representing the The target signal strength value at each sampling point, for example , , , Represents a reference power constant used to standardize signal strength values, for example... The signal strength value needs to be converted to linear units (milliwatts), for example, -65dBm converted to... ;

[0070] This formula quantifies coverage quality by calculating the normalized deviation between the actual received signal and the target signal, taking into account the effects of boundary density and spatial distance. The denominator... This represents the spatial distance between the sampling point and the central station, used for distance attenuation compensation of signal strength, making distant sampling points comparable to nearby sampling points in error calculation. This represents the actual signal strength after antenna angle correction and boundary density weighting, while This represents the normalized target signal strength. The absolute value term measures the quality deviation of the signal coverage at a single point. Summing and averaging these terms yields the overall error rate.

[0071] The advantage of the formula lies in the introduction of... The spatial distance term allows for a more comprehensive evaluation of signal coverage quality, with a particular focus on coverage performance in boundary areas. It also corrects for signal gain caused by antenna angle adjustments, avoiding a coarse evaluation based solely on the average signal strength, thus improving the accuracy of the configuration, especially for the first set of configurations.

[0072] The calculation process is as follows:

[0073] Sampling point 1: ;

[0074] Sampling point 2: ;

[0075] Sampling point 3: ;

[0076] ;

[0077] For the second configuration, a similar calculation was performed. Select the group with the lowest error rate and compare the error rates of the first group. Error rate compared to the second group The first configuration with the smaller error rate was selected to generate a signal coverage optimization configuration group, which includes an antenna tilt angle of 25 degrees, an azimuth angle of 110 degrees, and a transmit power of 30 watts. The results show that the first configuration performs better in meeting the target signal coverage and boundary clarity requirements, providing the best communication coverage parameters for the UAV.

[0078] Please see Figure 4 The dynamic trajectory extraction module includes:

[0079] The altitude trajectory extraction submodule is based on the signal coverage optimization configuration group, collects altitude change values ​​for each time period, records the time series and identifies the altitude difference within consecutive time periods, and obtains the altitude change time trajectory.

[0080] Based on a signal coverage optimization configuration group, for example, one with an antenna tilt angle of 25 degrees, an azimuth angle of 110 degrees, and a transmit power of 30 watts, the altitude change value is collected for each time period. The UAV flies in the air according to the optimized configuration, and its onboard altimeter continuously collects the UAV's real-time altitude data at a frequency of 10 times per second (10Hz). For example, the altitude is 100.0 meters at 0 seconds, 100.5 meters at 1 second, and 101.2 meters at 2 seconds. The time series is recorded and the altitude difference within consecutive time periods is identified. The collected altitude data is then recorded. The data is arranged in chronological order to form a sequence, and the height difference between adjacent time points is calculated. For example, the height difference from 0 seconds to 1 second is 0.5 meters, and the height difference from 1 second to 2 seconds is 0.7 meters. When the height difference of multiple consecutive time points is less than 0.2 meters, it is determined to be a continuous time period with relatively stable height. The height change time trajectory is obtained, which is a sequence containing timestamps and corresponding height values. For example, the time series is: (0s, 100.0m), (1s, 100.5m), (2s, 101.2m), ..., (60s, 105.0m).

[0081] The position offset determination submodule extracts position coordinates based on the time period corresponding to the height change time trajectory, identifies the position change vector for each time period, matches the height and position difference, and uses the following formula:

[0082] ;

[0083] Calculate the synchronization offset value, determine whether it is lower than the position change reference, and obtain the synchronization offset time period set;

[0084] in, Represents the synchronization offset value. Representing the The height value at a given time point. The average height value at a given time point. The average value of the horizontal position coordinates at any given time. This represents the lateral position reference value used for reference. The dimensionless coefficient representing the moderating effect of height fluctuations. The dimensionless coefficient representing the effect of adjustment position offset. This represents the total number of time points involved in the altitude and position calculations.

[0085] Extract location coordinates based on the time period corresponding to the altitude change time trajectory. For example, based on the altitude change time trajectory... For each 1-second time interval, the GPS position coordinates of the UAV are extracted. For example, the position coordinates at 0 seconds are (longitude 116.32, latitude 39.91), and the position coordinates at 60 seconds are (longitude 116.35, latitude 39.92). The position change vector for each time interval is identified. By calculating the change in longitude and latitude between adjacent time points, the change is converted to metric units to obtain a two-dimensional position change vector. For example, from 0 seconds to 1 second, the horizontal position changes by (0.00001 longitude, 0.000005 latitude), corresponding to a horizontal displacement of 0.9 meters. The height and position difference are matched, and the height difference for each time interval is associated with the corresponding horizontal position change vector. For example, a height change of 0.5 meters within 1 second corresponds to a horizontal displacement of 0.9 meters. The synchronization offset value is calculated using the formula: In the formula This represents the synchronization offset value, which measures the combined impact of altitude fluctuations and lateral position deviations of the drone within a specific time period. rice, rice, rice, rice, rice, The average height value at a given time point, for example rice, The average value of the lateral position coordinates at any given time. For example, within the same 5-second window, the average value of the drone's lateral position (taking eastward coordinates as an example) is... rice, The lateral position reference value represents the desired hovering or cruising lateral position of the drone, for example... rice, A dimensionless coefficient representing the moderating effect of altitude fluctuations, used to balance the contribution of altitude fluctuations to synchronization offset, for example... This value was determined through extensive actual flight tests and data analysis, aiming to make the impact of a 1-meter altitude fluctuation on synchronization offset roughly equivalent to the impact of a 10-meter lateral position offset. A dimensionless coefficient representing the effect of adjusting position offset, used to balance the contribution of lateral position offset to synchronization offset, for example... This value has also been verified experimentally to ensure that the effect of position offset on the G value is reasonable. Represents the total number of time points involved in the altitude and position calculation, for example The first term of the formula The standard deviation of altitude was calculated and weighted to quantify the degree of altitude fluctuation. (Second term) The average offset of the lateral position relative to the reference was calculated and weighted. The whole formula, by comprehensively considering altitude fluctuations and lateral position offset, aims to evaluate the synchronous stability of the UAV's flight state. If the UAV remains stable at the target position and altitude, the G value approaches zero; otherwise, the G value increases.

[0086] The advantage of this formula lies in combining vertical stability with horizontal positioning accuracy, providing a quantitative assessment of the overall flight synchronization of the UAV. This is crucial for tasks requiring precise hovering or flight along a preset trajectory. For example, when a UAV needs to maintain a fixed position for an extended period during a communication relay mission, this metric effectively reflects its stability and improves communication quality. The synchronization offset value is calculated given the following:

[0087] ;

[0088] ;

[0089] ;

[0090] It determines whether the position change is below the reference threshold, which is a preset threshold. For example, the synchronization offset reference value is set to 0.25. When the calculated value... When the value is below 0.25, the synchronization offset is considered to meet the requirements. If the value is below 0.25, obtain the synchronization offset time period set. The results indicate that the drone's altitude fluctuations and lateral position shifts were within acceptable ranges during this 5-second time period, and its flight attitude remained stable.

[0091] The trajectory feature construction submodule calls the time period sequence in the synchronous offset time period set, extracts the joint vector of height and position, sorts and constructs the trajectory, judges the consistency based on the Euclidean distance between adjacent time periods, and generates a continuous trajectory feature set;

[0092] Call the synchronous offset time period set The system extracts the joint vector of altitude and position. For each synchronization offset time period, it extracts the altitude values ​​and corresponding horizontal position coordinates for all time points and combines them into a three-dimensional vector (longitude, latitude, altitude). For example, at time point 0, the joint vector is (116.32, 39.91, 100.0), and at time point 1, the joint vector is (116.32001, 39.910005, 100.5). The system then sorts and constructs the trajectory by arranging the joint vectors in ascending order of timestamps, forming a continuous data sequence describing the UAV's three-dimensional spatial motion trajectory. ,in It is a three-dimensional joint vector, and consistency is determined based on the Euclidean distance between adjacent time points. and The Euclidean distance between them, for example, after converting latitude and longitude to metric units, is calculated. If the distance is consistently below the preset consistency threshold (e.g., 0.5 meters), the trajectory segments represented by the two time points are determined to be highly consistent, indicating that the UAV is flying smoothly without violent shaking. The generated continuous trajectory feature set is: the UAV flies smoothly within a specified time period (e.g., 0 seconds to 5 seconds), and its three-dimensional spatial trajectory is composed of a series of continuous and highly consistent joint vectors.

[0093] Please see Figure 5 The communication quality quantification module includes:

[0094] The signal interval extraction submodule calls the time segment in the continuous trajectory feature set, extracts the signal strength value of the coverage area according to the set time window, counts the extreme signal strength of each segment, delineates the signal strength change interval, and obtains the signal distribution set of the communication period.

[0095] Data sequences containing time, location, and velocity information are extracted from a continuous trajectory feature set. Combined with positioning data collected per second by the device during its movement (taking a sampling frequency of 1Hz as an example), a set of feature point sequences containing latitude, longitude, timestamp, and velocity information is acquired every second. The extracted feature sequences are then segmented according to a set time window. Assuming a time window is set to 10 seconds, every 10 consecutive sampling points constitute a signal processing unit. The signal strength value within each window is extracted. This signal strength value can be derived from the Received Signal Strength Indicator (RSSI) data records of the communication device within the corresponding time period. Furthermore, extreme signal strength values ​​within each segment are statistically analyzed; specifically, the RSSI values ​​within each time window are iterated and the maximum value is selected. By comparing the minimum value with the extreme value of the previous time window, we can analyze whether the signal strength has a continuous upward or downward trend. When defining the range of signal strength changes, the RSSI range from -120dBm to -50dBm is divided into seven levels of intervals. For example, -120 to -105 is interval 1, -105 to -95 is interval 2, and so on until interval 7. If the extreme value of a certain signal falls at -85dBm, then the signal segment belongs to interval 3. Then, we summarize the results of each segment division, and count the corresponding time period, spatial location and defined interval for each segment to form a signal strength segment table with time stamps and spatial identifiers. On this basis, we reconstruct the signal distribution of the time period in the communication process, thus forming the signal distribution set of the communication time period.

[0096] The segment matching and judgment submodule identifies the fitting difference between the signal amplitude deviation and the preset amplitude based on the signal intensity range of each segment in the signal distribution concentration during the communication period, combined with the change characteristic segments set in the communication stage, and calculates the segment offset trend value of the communication stage.

[0097] Based on the signal strength range of each segment within the signal distribution during the communication period, the maximum and minimum RSSI values ​​for each time window are extracted segment by segment. Combined with the defined characteristic segments for the communication phase, these characteristic segments are predefined. For example, the communication signal should fluctuate by no more than 5 dBm during the stable phase. If a segment's fluctuation exceeds this value, it is identified as a fluctuating segment. When specifically setting these characteristic segments, it is necessary to refer to historical communication data to determine the average fluctuation range. Taking RSSI fluctuation data during a 10-minute communication period as an example, historical records show that the stable phase RSSI fluctuation is between -75 and -70 dBm. Therefore, the fluctuating segment is defined as a segment with fluctuations exceeding ±3 dBm. Then, the signal amplitude deviation value in each actual segment is identified segment by segment. This value is the extreme difference of each segment minus the reference fluctuation value of the stable segment. If the difference of a certain segment is 10dBm and the reference fluctuation is 4dBm, then the deviation value is 6dBm. This value is used as the fitting difference, reflecting whether the current segment deviates significantly from the reference segment. Then, all fitting differences are quantified, and the direction and magnitude of the change of the fitting difference of each segment on the time axis are calculated in combination with the time series relationship. That is, the offset trend value of the communication stage segment is obtained. The offset trend value is calculated by comparing the sign and change magnitude of the fitting difference between consecutive segments to obtain its trend slope. Finally, the deviation direction and value of the relatively stable characteristic baseline of each segment are constructed.

[0098] The trend trajectory generation submodule identifies segments with continuous and similar changing directions based on the segment offset trend value of the communication stage, accumulates the trends of adjacent segments with the same direction, classifies and identifies the trend direction, and obtains the communication guarantee time sequence trajectory trend.

[0099] Based on the segment offset trend values ​​of the communication phase, the signs of all offset trend values ​​are first identified. If a segment offset value is positive, the trend is considered to be strengthening; if it is negative, the trend is weakening. Segments with the same offset sign and adjacent segments are merged into a continuous trend segment. For example, if three consecutive segments have offset trend values ​​of +2, +4, and +3, they are considered as a strengthening trend segment. The trend values ​​are then summed to obtain a total trend value of +9. The trend intensity level is then calculated based on the ratio of the cumulative value to the number of segments. If the average trend value of a single segment exceeds 3dBm, it can be defined as a high-intensity trend segment; if it is below 1dBm, it is defined as a weak trend segment. Further, different intensity trend segments are marked with directions using code numbers such as "UP1", "UP2", and "DOWN1" to represent the direction of the rising or falling trend of different intensities. Finally, a trend trajectory identification sequence is formed, such as UP2-UP2-DOWN1-DOWN2, which is used to represent the continuity and intensity difference of signal changes in the communication assurance time sequence trajectory. This sequence, combined with the time axis, can intuitively display the evolution trend of signal stability throughout the communication phase, thus obtaining the communication assurance time sequence trajectory trend.

[0100] Please see Figure 6 The risk status identification module includes:

[0101] The trajectory interval classification submodule is based on the communication guarantee time-series trajectory trend. It identifies the trajectory trend vector according to the start and end points and magnitude of trajectory changes, delineates the trajectory change interval according to the adjacent inflection point positions of the time series, marks the interval number corresponding to the UAV trajectory, and generates a trajectory interval labeling table.

[0102] Based on the communication assurance time-series trajectory trend, the starting and ending points of each trajectory are first extracted from the time-series trajectory trend data. These points are defined by extreme points or inflection points in the trajectory changes. By analyzing the trend line of the trajectory changes, the transition from one state to another is identified. For example, a change from a stable state to a rapidly rising state can be considered an inflection point. Next, the magnitude of the trajectory change is used to determine the amount of change. A larger magnitude indicates a sudden or rapid change in the trajectory. This magnitude is calculated by comparing the initial value of the trajectory with the changed value. If the magnitude of the change exceeds a set threshold (e.g., a set threshold...), then... If the velocity is 5 m / s, then the trajectory segment is considered to have changed significantly and is defined as a new trajectory interval. Based on the start and end points and the magnitude, adjacent trajectory change intervals are identified through time series analysis. Using a set time threshold (e.g., every minute as an interval division unit) and the amount of position change, the trajectory is precisely divided into intervals. Finally, a unique interval number is assigned to each trajectory interval to ensure that each trajectory segment can be clearly marked, thereby generating a trajectory interval marking table. The marking table includes information such as the trajectory start and end times, position coordinates, and trajectory interval number for subsequent analysis and processing.

[0103] The category interval association submodule calls the trajectory interval label table, collects feature category items from the environmental label information, analyzes the frequency of categories by the distribution quantity between the interval number and the feature category, and filters the association combinations with a frequency higher than the category interval matching threshold to obtain the category interval corresponding relationship group;

[0104] The trajectory interval label table is invoked to extract feature category items from the environmental label information. These categories include environmental factors such as terrain, weather, and obstacle density. Each environmental feature affects the drone's trajectory changes; for example, in mountainous areas or areas with dense obstacles, trajectory changes are more complex. Next, the distribution of feature categories is analyzed based on the trajectory interval sequence number. This step requires counting the frequency of each category in each trajectory interval and using statistical methods (such as frequency analysis) to calculate the distribution of each category in each trajectory interval. For example, in a specific area, if the weather conditions are "sunny" and... The frequency of the category feature "no wind" varies across different trajectory intervals. Based on a set category frequency threshold (e.g., a frequency threshold of 30%), the association combinations of categories with a frequency higher than this threshold are filtered out. For example, if the frequency of the "sunny day" feature category in interval 1 is 40%, which is greater than the set threshold, then the category is considered to have a strong association with this interval. Based on the analysis results, a category interval correspondence group is generated, that is, each trajectory interval is recorded with its corresponding environmental feature category combination, to ensure that the UAV can adjust its trajectory strategy according to different environmental features during flight.

[0105] The support status configuration submodule sets the support label mapping rules between trajectory intervals and feature categories based on the category interval correspondence group, configures the support status field for UAVs that meet the mapping rules, automatically marks the UAV support management field, and generates an automated communication support status mapping group.

[0106] Based on the category interval correspondence group, a guarantee label mapping rule is set between trajectory intervals and feature categories. First, the mapping rule is clarified. For example, for a mountain trajectory interval, if the environment label is "mountainous" and the trajectory change range in that area is large, the interval is marked as "high-risk guarantee". If the environment label is "city" and the trajectory change is stable, it is marked as "low-risk guarantee". When setting the mapping rule, appropriate guarantee status identifiers and condition restrictions are set by considering the specific impact of environmental features. For example, the marking rule for high-risk intervals is set as follows: when the trajectory change range exceeds 5 m / s and the environment is "mountainous", it is marked as "high-risk". Then, based on the environment label and feature category of each trajectory interval, combined with the change of the trajectory interval, the guarantee status field of the UAV is automatically marked. For example, if a trajectory interval is in a mountainous area and the change range is 6 m / s, the guarantee status of the interval is automatically set to "high-risk guarantee". All intervals that meet the mapping rule are assigned the corresponding guarantee status field, thereby generating an automated communication guarantee status mapping group to ensure that each trajectory interval is accurately matched with the appropriate guarantee status.

[0107] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An emergency tethered communication drone platform, characterized in that, The platform includes: The flight attitude control module is used to obtain the current wind speed influence value and load distribution status of the UAV, combine the tether cable tension range fed back by the ground control unit, select adjustment strategies, and perform dynamic mapping according to the load distribution status to generate a flight attitude balance parameter set. The signal coverage optimization module is used to call the flight attitude equalization parameter set, collect the signal strength distribution of the communication equipment and the location information of the coverage area boundary, compare the degree of overlap between the two in the target area, select the corresponding antenna angle and power configuration group, and generate a signal coverage optimization configuration group. The dynamic trajectory extraction module is used to collect the altitude change time series and position offset trajectory in the flight trajectory of the UAV based on the signal coverage optimization configuration group, determine the synchronous offset amplitude between trajectories, filter the stable region within the flight cycle, and generate a continuous trajectory feature set. The communication quality quantification module is used to call the continuous trajectory feature set, extract the signal strength range of each time period within the signal coverage area, and match it with the set change segment range in the communication cycle. By analyzing the communication quality trend through segment superposition, the communication guarantee time sequence trajectory trend is obtained.

2. The emergency tethered communication drone platform according to claim 1, characterized in that, The flight attitude equalization parameter set includes wind speed mapping factor, load distribution weight, tension control range, attitude balance threshold, and flight stability index. The signal coverage optimization configuration group includes antenna angle configuration, power allocation weight, boundary matching degree, and coverage area equalization. The continuous trajectory feature set includes altitude change curve, position offset trajectory, synchronization offset marker, and stability area identifier. The communication guarantee time-series trajectory trend includes signal strength segment sequence, stage evolution mode, change trend path, and time-series matching result.

3. The emergency tethered communication drone platform according to claim 1, characterized in that, The flight attitude control module includes: The wind speed and load acquisition submodule is used to obtain the current wind speed influence value and load distribution status of the UAV. Based on the tether cable tension range fed back by the ground control unit, it extracts the state values ​​that deviate from the load reference range and the wind speed standard range, and generates the initial offset parameter set. The adjustment strategy extraction submodule is used to filter the tension adjustment factor and load correction factor range that can control the offset state based on the initial offset parameter group and the adjustment limit under the current tension condition, extract the adjustment combination that matches the current offset level, and generate flight adjustment matching parameters. The attitude mapping submodule is used to identify the function mapping group of attitude and balance control based on the flight adjustment matching parameters, combined with the current load distribution state of the UAV and the wind speed influence value, determine the constraint boundary of the flight rhythm, and generate a flight attitude balance parameter set.

4. The emergency tethered communication drone platform according to claim 3, characterized in that, The signal coverage optimization module includes: The signal response submodule is used to call the flight attitude equalization parameter set, collect multi-directional signal strength response values ​​and antenna angle mapping values, compare the signal response with the angle matching degree, and obtain the signal coverage overlap rate index. The boundary positioning submodule is used to call the signal coverage overlap rate index, extract the signal gradient intensity of the coverage area boundary, jointly filter the angle set that meets the boundary clarity requirements, and obtain the antenna angle selection set. The coverage configuration submodule is used to select a set of combined power allocation groups based on the antenna angle, identify the signal strength and boundary coverage density of each group, calculate the signal coverage error rate, select the group configuration with the lowest error rate, and generate a signal coverage optimization configuration group.

5. The emergency tethered communication drone platform according to claim 4, characterized in that, The dynamic trajectory extraction module includes: The altitude trajectory extraction submodule is used to collect altitude change values ​​for each time period based on the signal coverage optimization configuration group, record the time series and identify the altitude difference within consecutive time periods to obtain the altitude change time trajectory. The position offset determination submodule is used to extract position coordinates according to the time period corresponding to the height change time trajectory, identify the position change vector of each time period, match the height and position difference, calculate the synchronization offset value, determine whether it is lower than the position change benchmark, and obtain the synchronization offset time period set. The trajectory feature construction submodule is used to call the time period sequence in the synchronous offset time period set, extract the joint vector of height and position, sort and construct the trajectory, judge the consistency based on the Euclidean distance between adjacent time periods, and generate a continuous trajectory feature set.

6. The emergency tethered communication drone platform according to claim 5, characterized in that, The communication quality quantization module includes: The signal interval extraction submodule is used to call the time segments in the continuous trajectory feature set, extract the signal strength value of the coverage area according to the set time window, count the extreme signal strength of each segment, delineate the signal strength change interval, and obtain the signal distribution set of the communication period. The segment matching and judgment submodule is used to identify the fitting difference between the signal amplitude deviation and the preset amplitude based on the signal strength range of each segment in the signal distribution set of the communication period, combined with the change characteristic segment set in the communication stage, and to calculate the segment offset trend value of the communication stage. The trend trajectory generation submodule is used to identify segments with continuous changes in the same direction based on the segment offset trend value of the communication stage, accumulate the trends of adjacent segments in the same direction, classify and identify the trend direction, and obtain the communication guarantee time sequence trajectory trend.

7. The emergency tethered communication drone platform according to claim 1, characterized in that, The platform also includes a risk status identification module: The risk status identification module is used to classify the trajectory trend of UAVs in the same round based on the communication support time-series trajectory trend, collect the environmental feature categories recorded in the environmental label information group, determine the stability of the correlation interval between them and the trajectory classification, and generate an automated communication support status mapping group. The automated communication assurance status mapping group includes trajectory classification results, environmental feature correlation, classification stability interval, and assurance status label.

8. The emergency tethered communication drone platform according to claim 7, characterized in that, The risk status identification module includes: The trajectory interval classification submodule is used to identify the trajectory trend vector based on the communication guarantee time-series trajectory trend, according to the start and end points and magnitude of trajectory changes, delineate the trajectory change interval according to the adjacent inflection point positions of the time series, mark the interval number corresponding to the UAV trajectory, and generate a trajectory interval labeling table. The category interval association submodule is used to call the trajectory interval label table, collect feature category items in the environmental label information, analyze the category frequency by the distribution quantity between the interval number and the feature category, filter the association combination with the frequency higher than the category interval matching threshold, and obtain the category interval corresponding relationship group. The support status configuration submodule is used to set support label mapping rules between trajectory intervals and feature categories according to the category interval correspondence group, configure support status fields for UAVs in intervals that meet the mapping rules, automatically mark UAV support management fields, and generate automated communication support status mapping groups.

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