Unmanned aerial vehicle ground communication relay data transmission method

Abstract

The invention discloses an unmanned aerial vehicle ground communication relay data transmission method, and the method comprises the specific steps: building a related element model: constructing an unmanned aerial vehicle-ground terminal data transmission model, an unmanned aerial vehicle channel distribution model and an unmanned aerial vehicle flight model, and simplifying the complexity of unmanned aerial vehicle ground data transmission; and communication relay problem modeling: converting a communication relay problem into a plane geometry problem, processing direct communication and indirect communication conditions, and converting the direct communication and indirect communication conditions into a multi-traveler problem. And solving a genetic algorithm problem: optimizing a flight path and a data transmission strategy of the unmanned aerial vehicle by adopting the genetic algorithm, and finding an optimal or satisfactory solution by simulating natural selection and a genetic mechanism. The method can improve the communication relay efficiency, is suitable for a complex communication environment, guarantees the flight safety, achieves the intelligent path planning, and improves the energy utilization efficiency. The flight path of the unmanned aerial vehicle can be effectively planned, interactive communication of the ground data terminal under a certain bandwidth is ensured, and effectiveness and practicability of the method are proved.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle communication, and in particular relates to a method for relaying data transmission in unmanned aerial vehicle-to-ground communication. Background Art

[0002] With the development of drone technology, drones are increasingly used in the civil field, especially in the field of communications. Due to their flexibility and mobility, drones are widely used in the construction of temporary communication networks, disaster emergency communications, remote monitoring and other scenarios. In these applications, drones need to have stable data transmission with ground terminals to ensure the real-time and accuracy of information.

[0003] However, existing drone-to-ground communication systems face multiple challenges. First, the communication distance and signal quality between drones and ground terminals are affected by many factors, including the drone's flight altitude, weather conditions, ground obstacles, etc. These factors cause signal attenuation and affect communication quality. Second, the drone's flight path and speed have a direct impact on data transmission efficiency. Drones need to optimize their flight paths as much as possible while ensuring safety to reduce transmission delays and increase data transmission rates.

[0004] In practical applications, the communication between drones and ground terminals often requires relay support to expand the communication coverage. However, existing relay solutions often lack flexibility and intelligence, and are difficult to adapt to complex and changing communication environments. For example, in emergency situations such as disaster relief, ground communication infrastructure may be damaged, and drones need to be quickly deployed and establish temporary communication links. Existing relay solutions often require pre-planning and cannot meet the needs of rapid response.

[0005] In addition, with the increase in the number of drones, air traffic management has become another challenge. When performing communication relay tasks, drones need to avoid conflicts with other aircraft to ensure flight safety. Although existing drone flight control systems have certain obstacle avoidance capabilities, in a complex air traffic environment, how to efficiently plan flight paths, avoid conflicts, and ensure the completion of communication tasks is still a technical problem.

[0006] In terms of data transmission, existing drone communication systems often use a fixed power transmission mode, which results in weak signals when the drone is far away from the ground terminal and wastes energy when the distance is close. Therefore, a method for dynamically adjusting the transmission power is needed to adapt to different communication distances and environmental conditions and improve energy efficiency.

[0007] In summary, the existing UAV-to-ground communication relay technology has problems such as low communication efficiency, poor adaptability, and insufficient security. Summary of the invention

[0008] In order to overcome the shortcomings of the prior art, the present invention provides a method for UAV-to-ground communication relay data transmission, and the specific steps include: establishment of relevant element models: constructing a UAV-ground terminal data transmission model, a UAV channel allocation model and a UAV flight model to simplify the complexity of UAV-to-ground data transmission. Communication relay problem modeling: converting the communication relay problem into a plane geometry problem, dealing with direct communication and indirect communication situations, and converting it into a multi-traveling salesman problem. Genetic algorithm problem solving: using genetic algorithms to optimize the flight path and data transmission strategy of the UAV, and finding the optimal or satisfactory solution by simulating natural selection and genetic mechanisms. The present invention can improve the efficiency of communication relay, adapt to complex communication environments, ensure flight safety, intelligent path planning and improve energy utilization efficiency. It can effectively plan the UAV trajectory and ensure that the ground data terminal can communicate interactively under a certain bandwidth, which proves the effectiveness and practicality of the method.

[0009] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0010] Step 1: Establishment of relevant factor model;

[0011] Step 1-1: UAV-ground terminal data transmission model;

[0012] Assume that the data transmission from the UAV to the ground terminal is the maximum tangent transmission mode, that is, a UAV can only transmit data to one ground terminal at a time at the limit distance; the moving range of the ground terminal is a circular area with a radius of d = a1km, and the information transmission range of the UAV to the ground mobile terminal is the diameter range of the circular area on the ground. The data transmission time t between the UAV and the ground terminal is only related to the flight speed V of the UAV. uav Related, that is:

[0013]

[0014] Step 1-2: UAV information sending rate model;

[0015] Assume that the communication distance of each drone is a2 meters. The communication range of a drone is expressed as a spherical area with the drone as the center. When communicating with another drone, it only needs the communication sphere areas of the two drones to overlap, that is, the communication between the drones can be completed. Therefore, a drone-drone communication model is constructed. If there is a communicable area between the two drones, it is considered that the communication between the two drones is successful.

[0016] According to the UAV-ground data terminal transmission model, the UAV only transmits data to one ground data terminal at a time, so the UAV channel transmission is full power transmission, that is, p i(t) = a3; the rate at which user i receives information sent by the drone at time t is:

[0017]

[0018] Among them, ρ0 is the channel characteristic parameter, which is taken as 4.314×10 -10 , d(u,i) represents the Euclidean distance between the UAV and i at time t. According to the constructed UAV-ground data terminal transmission model, d(u,i)=a2; B i represents the channel width of user i;

[0019] Step 1-3: Drone flight model;

[0020] The drone is considered as a spherical particle with a diameter of r1 and a center of mass of (x, y, z). There is an obstacle avoidance safety distance of r2 meters around it. All obstacle point sets O cannot enter this area, that is, we must ensure that:

[0021]

[0022] When the UAV is transmitting data to the user terminal while passing over the user terminal, the speed is set to the minimum flight speed V of the UAV. min ; When the UAV is flying in other areas without performing information transmission tasks, set the UAV to fly at the maximum speed V max to conduct a flight;

[0023] Step 2: Modeling of communication relay problem;

[0024] Define the i-th ground mobile terminal and its moving range as area A i , i=1,2,3,…,a4, the jth drone and its signal communication range area is B j There are two situations for communication between two mobile terminals on the ground:

[0025] (1) Direct communication: that is, if two ground mobile terminals are within the signal transmission range of a drone, they can communicate directly through the drone;

[0026] (2) Indirect communication: two ground mobile terminals need to pass through the signal relay of the drone to achieve mutual communication;

[0027] If uninterrupted communication is to be achieved between any two ground terminals k and l, it is necessary to ensure that n>0 UAVs are passed between terminal k and terminal l for communication transfer, that is, to ensure: A k ∪B1∪B2∪…∪B n ∪A lIt is geometrically connected, so the communication relay problem is transformed into the problem of solving the connected domain of plane geometric figures;

[0028] The communication relay problem is abstracted into a multi-traveling salesman problem: use three drones to traverse all ground terminal areas and meet the number of traversals required for each ground terminal; according to the three-subscript equation proposed by the multi-traveling salesman problem, define the variables as follows:

[0029]

[0030]

[0031] The time it takes for a drone to complete a task is divided into two parts, namely, data transmission time t1 and flight time t2; the time taken for the nth drone is:

[0032]

[0033] where d X is the distance that the nth UAV passes the ith user terminal for the mth time, d Y is the distance from user terminal j to the next terminal during the mth flight of the nth UAV;

[0034] The requirement is to make the total time for the drone to complete all tasks as short as possible, so the objective function is constructed as follows:

[0035]

[0036] The M-TSP model for establishing communication relay is as follows:

[0037]

[0038] Step 3: Genetic algorithm problem solving;

[0039] (1) Population initialization;

[0040] The individual coding methods include binary coding and real number coding. In the process of solving the TSP problem, the individual coding method is real number coding. For the TSP problem, the real number coding is a random arrangement of real numbers from 1 to n. The initialization parameters are: the population size M, i.e. the number of drones in the air communication relay, the number of chromosome genes N, i.e. the number of ground data terminals, the number of iterations C, the crossover probability Pc, and the mutation probability P.

[0041] (2) Fitness function;

[0042] In the TSP problem, if the distance D(i,j) between any two data communication terminals is known, the total distance can be calculated by random permutation of each chromosome, i.e., n data communication terminals. Therefore, the inverse of the total distance of a random full permutation can be used as the fitness function, i.e., the shorter the distance, the better the fitness function, which meets the TSP requirements.

[0043] (3) Select operation;

[0044] Adopt a selection strategy based on fitness ratio, that is, the individuals with better fitness have a greater probability of being selected, and at the same time, the individuals with the highest fitness are preserved in the selection;

[0045] (4) Crossover operation;

[0046] Randomly select two individuals and exchange several gene fragments at the corresponding positions, while ensuring that each individual is still a 1-n random arrangement to prevent local convergence;

[0047] (5) Mutation operation;

[0048] An individual is randomly selected, and two genes of the individual are randomly selected to be exchanged to achieve mutation operation.

[0049] The optimal strategy for UAV-to-ground communication relay is obtained based on the genetic algorithm, and the optimal data transmission solution is obtained.

[0050] Preferably, a1=2, a2=3000, a3=5, and a4=72.

[0051] A computer program, which enables a computer to execute the above data transmission method.

[0052] An electronic device comprises: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the above-mentioned data transmission method.

[0053] A computer-readable storage medium stores a computer program, which implements the above-mentioned data transmission method when executed by a processor.

[0054] A chip includes: a processor, which is used to call and run a computer program from a memory, so that a device equipped with the chip executes the above-mentioned data transmission method.

[0055] A computer program product comprises a computer storage medium storing a computer program, wherein the computer program comprises instructions executable by at least one processor, and the above-mentioned data transmission method is implemented when the instructions are executed by the at least one processor.

[0056] The beneficial effects of the present invention are as follows:

[0057] High-efficiency communication relay: By optimizing the flight path and data transmission strategy of the UAV, the present invention can significantly improve the efficiency of UAV-to-ground communication and reduce data transmission delay.

[0058] Strong adaptability: The present invention can adapt to complex and changing communication environments, including dynamically changing distances between drones and ground terminals and the number of users.

[0059] High safety: By considering the safe flight distance and obstacle avoidance strategy of the UAV, the present invention ensures the flight safety of the UAV when performing communication relay tasks.

[0060] Intelligent path planning: Using genetic algorithms, the present invention can intelligently plan the flight path of the UAV to avoid conflicts with other aircraft while completing communication tasks.

[0061] Energy efficiency: The present invention improves energy utilization efficiency and reduces energy waste by dynamically adjusting the transmission power of the UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 The UAV-ground terminal data transmission model is shown;

[0063] Figure 2 A UAV-UAV communication model is shown;

[0064] Figure 3 The UAV-ground terminal communication model is shown;

[0065] Figure 4 Showing the safety boundary model of drones;

[0066] Figure 5 A simulated flight model of a UAV is shown;

[0067] Figure 6 A simplified model of UAV flight is shown;

[0068] Figure 7 Schematic diagrams showing two terminal communication situations, (a) direct communication schematic diagram, (b) indirect communication schematic diagram;

[0069] Figure 8 A schematic diagram of a continuous communication relay is shown;

[0070] Fig. 9 Show the genetic algorithm flow chart;

[0071] Fig.10 The overall map of the routes of the three drones is shown;

[0072] Fig.11 The route diagrams of three drones are shown: (a) drone route 1, (b) drone route 2, and (c) drone route 3. DETAILED DESCRIPTION

[0073] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0074] The existing UAV-to-ground communication relay technology has problems such as low communication efficiency, poor adaptability, and insufficient security. In order to solve these problems, the present invention proposes a new UAV-to-ground communication relay data transmission method, which establishes a data transmission model, a channel allocation model, and a UAV flight model between the UAV and the ground terminal, and uses a genetic algorithm to optimize the flight path and data transmission strategy of the UAV, so as to achieve efficient and reliable UAV-to-ground communication.

[0075] The present invention aims to improve the continuity and efficiency of UAV-to-ground communications through technological innovation, especially to ensure the stability and security of communications in complex and changeable communication environments, and to provide technical support for the widespread application of UAVs in the civilian field.

[0076] The technical solution of the present invention mainly includes the following key steps:

[0077] Establishment of relevant element models: First, the present invention establishes a data transmission model between the UAV and the ground terminal, a UAV channel allocation model, and a UAV flight model. These models simplify the complexity of the UAV-to-ground data transmission process and provide a basis for modeling subsequent communication relay problems. Specifically, the UAV-ground terminal data transmission model takes into account the flight speed and communication range of the UAV, while the UAV flight model takes into account the safe flight distance and route planning of the UAV.

[0078] Communication relay problem modeling: The present invention transforms the communication relay problem into a plane geometry problem, and ensures the connectivity between the UAV and the ground terminal through the concept of "connected domain". By defining the moving range of the ground mobile terminal and the signal communication range of the UAV, the present invention can handle both direct communication and indirect communication, and transform it into a multiple traveling salesman problem (M-TSP problem).

[0079] Genetic algorithm problem solving: The present invention uses a genetic algorithm to solve the communication relay model, and continuously iterates and improves the solution by simulating natural selection and genetic mechanisms until the optimal or satisfactory solution is found. The genetic algorithm includes steps such as population initialization, fitness function definition, selection operation, crossover operation, and mutation operation. Through these steps, the present invention can find the optimal flight path and data transmission strategy of the drone.

[0080] Embodiment 1:

[0081] A UAV-to-ground communication relay data transmission method mainly includes three steps: establishing UAV-ground terminal data transmission model, UAV channel allocation model, UAV flight model and other related factor models, modeling communication relay problems, and solving genetic algorithm problems.

[0082] Step 1: Establishment of relevant factor model.

[0083] In the process of UAV-to-ground data transmission, there are too many variables that are difficult to predict (such as the distance between the UAV and the ground terminal, the number of current users of the UAV, etc. are constantly changing), so it is necessary to first simplify the model of related element models to facilitate the construction of the UAV-to-ground data transmission model. The element models mainly include: UAV-ground terminal data transmission model, UAV channel allocation model, and UAV flight model.

[0084] Step 1: UAV-ground terminal data transmission model;

[0085] In order to simplify the model, it is assumed that the UAV transmits data to the ground terminal in the maximum tangent transmission mode ( Figure 1 ), that is, a UAV can only transmit data to one ground terminal at a time. The mobile range of the ground terminal is a circular area with a radius of d = 2km. In order to maximize the reception of UAV information by ground mobile terminals, it is assumed that the information transmission range of the UAV to the ground mobile terminal is the diameter of the circular area on the ground. At this time, it can be obtained that the UAV-ground terminal data transmission time t is only related to the flight speed V of the UAV. uav Related, that is:

[0086]

[0087] Step 2: UAV information sending rate model;

[0088] Assume that the drone can communicate with mobile terminals within 3,000 meters when flying. In order to make it easier to write programs and establish models, assume that the communication distance of each drone is 3,000 meters. The communication range of the drone can be expressed as a spherical area with the drone as the center. When communicating with another drone, it only needs the communication spheres of the two drones to overlap to complete the communication between the drones. Therefore, the drone-drone communication model can be constructed as follows: Figure 2 As shown, if the two drones are in the yellow communicable area in the figure, it is considered that the communication between the two drones is successful.

[0089] Similarly, the communication model between the drone and the ground terminal is as follows Figure 3 shown.

[0090] According to the UAV-ground data terminal transmission model, the UAV only transmits data to one ground data terminal at a time, so the UAV channel transmission is full power transmission, that is, p i (t) = 5 (unit: w (watt)). The rate at which user i receives information sent by the drone at time t is:

[0091]

[0092] ρ0 is the channel characteristic parameter, which is taken as 4.314×10 -10 (Units omitted). d(u,i) represents the Euclidean distance between the UAV and i at time t. It is easy to know from the constructed UAV-ground data terminal transmission model that d(u,i) = 3000, unit: meter.

[0093] The UAV information sending rate model can be simplified to a model that is only related to the bandwidth of user i (bits / second):

[0094]

[0095] Step 3: Drone flight model;

[0096] During the flight of the drone, it is necessary to consider the safe flight distance of the drone (50 meters) and build a safety boundary model for the drone. Figure 4 shown.

[0097] The drone is considered as a spherical particle with a diameter of r1 and a center of mass of (x, y, z). There is an obstacle avoidance safety distance of r2 = 50 meters outside it. When considering the route planning of the drone, all obstacle points O cannot enter this area, that is, it is necessary to ensure that:

[0098]

[0099] Build a UAV simulation flight model in Simulink Figure 5 As shown in the figure, CollisionAvoidance, UAV_autopilot and UAV_Constrain represent the obstacle avoidance module, autonomous flight module and conditional constraint module of the UAV respectively. In order to simplify the route planning model of the UAV and enable it to fly the planned route quickly, the input of the UAV adopts the waypoint navigation method of (X, Y, Z) three-dimensional coordinate points.

[0100] All route planning algorithms for UAV flight must take into account the actual flight performance of the UAV, that is, the route planned by the algorithm must be a feasible route for the UAV (for example, due to the minimum turning radius of the UAV, the route cannot have a zigzag turn). The UAV's own constraints are restricted in Simulink ( Figure 5 The UAV_Constrain module in the , is used to facilitate the subsequent calling and adjustment of the UAV model.

[0101] It is necessary to design an appropriate UAV speed so that the total time for the UAV to complete all tasks is as short as possible, while also allowing the ground user terminal to receive a large amount of data. Figure 6 The simplified model shown.

[0102] That is, when the UAV is transmitting data to the user terminal while passing over the user terminal, the speed is set to the minimum flight speed V of the UAV. min =60 km / h (for unified measurement units, set as V min =16.67 m / s); when the UAV is flying in other areas without performing information transmission tasks, the UAV is set to fly at the maximum flight speed, that is, V max =100km / h=27.78m / s.

[0103] Step 2: Modeling the communication relay problem.

[0104] The communication relay problem can be transformed into a plane geometry problem for processing. By borrowing the idea of ​​"connected domain" from mathematical graphics, that is, ensuring that the connected domain between the UAV and the ground terminal remains connected at all times during the flight of the UAV, uninterrupted communication in the disaster area can be guaranteed.

[0105] Define the i-th ground mobile terminal and its moving range as area A i (i=1,2,3,…,72), the jth UAV and its signal communication range area is B j ,There are two situations for communication between two mobile terminals on the ground.

[0106] (1) Direct communication: If two ground mobile terminals are within the signal transmission range of a UAV, they can communicate directly through the UAV. Figure 7 a);

[0107] (2) Indirect communication: two ground mobile terminals need to pass through the signal relay of the drone to achieve mutual communication ( Figure 7 b).

[0108] If uninterrupted communication is to be achieved between any two ground terminals (terminal k, terminal l), it is necessary to ensure that n (n>0) UAVs are connected between terminal k and terminal l for communication transfer, that is, to ensure that A k ∪B1∪B2∪…∪B n ∪A l is geometrically connected ( Figure 8). Therefore, the communication relay problem can be transformed into the problem of solving the connected domain of plane geometric figures.

[0109] Assume that the drone needs n times to send the total amount of 500M (1M is calculated as 10 6 According to the simplified UAV information transmission rate model, it is easy to get: 0.301B i tn i =500×10 6 , that is, n i =3.46×10 6 / B i For user i, the drone needs to pass through n i (n i It takes 72 user terminals to receive the data.

[0110] Through the above transformation, the communication relay problem can be transformed into a multi-traveling salesman problem (M-TSP problem). The Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem. The classic TSP can be described as: a salesman is going to several cities to sell goods. The salesman starts from one city and needs to pass through all cities before returning to the starting point. How to choose the route to make the total journey shortest? The communication relay problem is abstracted into a multi-traveling salesman problem: use three drones to traverse 72 ground terminal areas and meet the number of traversals required for each ground terminal. According to the three-subscript equation proposed by the TSP problem, the variables are defined as follows:

[0111]

[0112] It is necessary to make the drone complete all tasks in the shortest possible time. The time it takes for a drone to complete a task can be divided into three parts, namely data transmission time t1 and flight time t2. The time taken for the nth drone is:

[0113]

[0114] where d X is the distance that the nth UAV passes the ith user terminal for the mth time, d Y is the distance from user terminal j to the next terminal during the mth flight of the nth UAV.

[0115] If the total time required for the drone to complete all tasks is as short as possible, the objective function can be constructed as follows:

[0116]

[0117] For the jth user terminal, it is necessary to traverse the n i times (i.e. ), there are 72 user terminals (i.e. ).

[0118] Based on the above considerations, the M-TSP model for establishing communication relay is as follows:

[0119]

[0120] Step 3: Genetic algorithm problem solving.

[0121] Genetic algorithms have a wide range of applications. They combine the ideas and principles of biological evolution with computer science and have been widely used in solving practical problems. Genetic algorithms are generally composed of selection, crossover, and mutation. They gradually improve the current solution through continuous iteration until the optimal solution or satisfactory solution is finally found. The algorithm flow chart is as follows:

[0122] There are five basic steps to solve the communication relay model constructed by genetic algorithm:

[0123] (1) Population initialization. Individual coding methods include binary coding and real number coding. In the process of solving the TSP problem, the individual coding method is real number coding. For the TSP problem, the real number coding is a random arrangement of real numbers from 1 to n. The initialization parameters are: the population size M (i.e., the number of drones in the air communication relay), the number of chromosome genes N (i.e., the number of ground data terminals), the number of iterations C, the crossover probability Pc, and the mutation probability P.

[0124] (2) Fitness function. In the TSP problem, if the distance D(i, j) between any two data communication terminals is known, the total distance can be calculated for each chromosome (i.e., the random arrangement of n data communication terminals). Therefore, the inverse of the total distance of a random full arrangement can be used as the fitness function. That is, the shorter the distance, the better the fitness function, which meets the TSP requirements.

[0125] (3) Selection operation. There are many methods for genetic algorithm selection operation, such as roulette method and tournament method. This program adopts a selection strategy based on fitness ratio, that is, the better the fitness of the individual, the greater the probability of being selected, and the individual with the highest fitness is saved in the selection.

[0126] (4) Crossover operation. There are many methods for crossover operation in genetic algorithms. In this program, two individuals are randomly selected for each individual, and several gene fragments are exchanged at the corresponding positions, while ensuring that each individual is still a 1-n random arrangement to prevent local convergence.

[0127] (5) Mutation operation. In this program, for the mutation operation, an individual is randomly selected, and two genes of the individual are randomly selected to be exchanged to realize the mutation operation.

[0128] Based on the genetic algorithm, the optimal strategy for UAV-to-ground communication relay can be solved and the optimal data transmission plan can be obtained.

[0129] Embodiment 2:

[0130] Assuming the number of drones is 3, the number of ground terminals is 72, the number of iterations is 100, the elimination index is 2, the crossover probability and mutation probability are 0.4 and 0.2 respectively, the optimal drone-to-ground communication relay data transmission scheme can be calculated, that is, the total time for drones to complete all tasks is 159.65 hours, and the overall route map of the three drones is as follows: Fig.10 .

[0131] In order to more clearly express the simulation results, the routes of the three drones, the users they serve, and the time of task completion are shown in Fig.11 (a)- Fig.11 (c) It can be seen that by rationally planning the flight paths of the three UAVs, it is possible to ensure that the ground data terminals can communicate interactively with each other under certain bandwidth conditions. This confirms the effectiveness of the proposed UAV-to-ground communication relay data transmission method.

Claims

1. A method for transmitting data via relay in UAV-to-ground communication, characterized in that: The steps include: Step 1: Establishment of relevant factor model; Step 1-1: UAV-ground terminal data transmission model; Assume that the data transmission from the UAV to the ground terminal is the maximum tangent transmission mode, that is, a UAV can only transmit data to one ground terminal at a time at the limit distance; the moving range of the ground terminal is a circular area with a radius of d = a1km, and the information transmission range of the UAV to the ground mobile terminal is the diameter range of the circular area on the ground. The data transmission time t between the UAV and the ground terminal is only related to the flight speed V of the UAV. uav Related, that is: Step 1-2: UAV information sending rate model; Assume that the communication distance of each drone is a2 meters. The communication range of a drone is expressed as a spherical area with the drone as the center. When communicating with another drone, it only needs the communication sphere areas of the two drones to overlap, that is, the communication between the drones can be completed. Therefore, a drone-drone communication model is constructed. If there is a communicable area between the two drones, it is considered that the communication between the two drones is successful. According to the UAV-ground data terminal transmission model, the UAV only transmits data to one ground data terminal at a time, so the UAV channel transmission is full power transmission, that is, p i (t) = a3; the rate at which user i receives information sent by the drone at time t is: Among them, ρ0 is the channel characteristic parameter, which is taken as 4.314×10 -10 , d(u,i) represents the Euclidean distance between the UAV and i at time t. According to the constructed UAV-ground data terminal transmission model, d(u,i)=a2; B i represents the channel width of user i; Step 1-3: Drone flight model; The drone is considered as a spherical particle with a diameter of r1 and a center of mass of (x, y, z). There is an obstacle avoidance safety distance of r2 meters around it. All obstacle point sets O cannot enter this area, that is, we must ensure that: When the UAV is transmitting data to the user terminal while passing over the user terminal, the speed is set to the minimum flight speed V of the UAV. min ; When the UAV is flying in other areas without performing information transmission tasks, set the UAV to fly at the maximum speed V max to conduct a flight; Step 2: Modeling of communication relay problem; Define the i-th ground mobile terminal and its moving range as area A i , i=1,2,3,…,a4, the jth drone and its signal communication range area is B j There are two situations for communication between two mobile terminals on the ground: (1) Direct communication: that is, if two ground mobile terminals are within the signal transmission range of a drone, they can communicate directly through the drone; (2) Indirect communication: two ground mobile terminals need to pass through the signal relay of the drone to achieve mutual communication; If uninterrupted communication is to be achieved between any two ground terminals k and l, it is necessary to ensure that n>0 UAVs are passed between terminal k and terminal l for communication transfer, that is, to ensure: A k ∪B1∪B2∪…∪B n ∪A l It is geometrically connected, so the communication relay problem is transformed into the problem of solving the connected domain of plane geometric figures; The communication relay problem is abstracted into a multi-traveling salesman problem: use three drones to traverse all ground terminal areas and meet the number of traversals required for each ground terminal; according to the three-subscript equation proposed by the multi-traveling salesman problem, define the variables as follows: The time it takes for a drone to complete a task is divided into two parts, namely, data transmission time t1 and flight time t2; the time taken for the nth drone is: where d X is the distance that the nth UAV passes the ith user terminal for the mth time, d Y is the distance from user terminal j to the next terminal during the mth flight of the nth UAV; The requirement is to make the total time for the drone to complete all tasks as short as possible, so the objective function is constructed as follows: The M-TSP model for establishing communication relay is as follows: Step 3: Genetic algorithm problem solving; (1) Population initialization; The individual coding methods include binary coding and real number coding. In the process of solving the TSP problem, the individual coding method is real number coding. For the TSP problem, the real number coding is a random arrangement of real numbers from 1 to n. The initialization parameters are: the population size M, i.e. the number of drones in the air communication relay, the number of chromosome genes N, i.e. the number of ground data terminals, the number of iterations C, the crossover probability Pc, and the mutation probability P. (2) Fitness function; In the TSP problem, if the distance D(i,j) between any two data communication terminals is known, the total distance can be calculated for each chromosome, i.e., the random arrangement of n data communication terminals. Therefore, the inverse of the total distance of a random full arrangement can be used as the fitness function, i.e., the shorter the distance, the better the fitness function, which meets the TSP requirements; (3) Select operation; Adopt a selection strategy based on fitness ratio, that is, the individuals with better fitness have a greater probability of being selected, and at the same time, the individuals with the highest fitness are preserved in the selection; (4) Crossover operation; Randomly select two individuals and exchange several gene fragments at the corresponding positions, while ensuring that each individual is still a 1-n random arrangement to prevent local convergence; (5) Mutation operation; Randomly select individuals and randomly select two genes of individuals to exchange to achieve mutation operation; The optimal strategy for UAV-to-ground communication relay is obtained based on the genetic algorithm, and the optimal data transmission solution is obtained.

2. The method for transmitting data via relay of UAV-to-ground communication according to claim 1, characterized in that: Said a1=2, a2=3000, a3=5, a4=72.

3. A computer program, characterized in that The computer program enables a computer to execute the method according to any one of claims 1 to 2.

4. An electronic device, characterized in that: include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method as claimed in any one of claims 1 to 2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 2 is implemented.

6. A chip, characterized in that: include: A processor, configured to call and run a computer program from a memory, so that a device equipped with the chip executes a method as claimed in any one of claims 1 to 2.

7. A computer program product, characterized in that The computer program product comprises a computer storage medium storing a computer program, wherein the computer program comprises instructions executable by at least one processor, and when the instructions are executed by the at least one processor, the method according to any one of claims 1 to 2 is implemented.

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