Unmanned aerial vehicle communication assisted ecological monitoring data transmission system and method

Abstract

The invention relates to the technical field of data transmission processing, and provides an unmanned aerial vehicle communication-assisted ecological monitoring data transmission system and method, and the method comprises the steps: obtaining the ecological monitoring state parameters of an unmanned aerial vehicle; calculating an ecological monitoring obstruction coefficient and a dynamic disturbance coefficient of the unmanned aerial vehicle; calculating unmanned aerial vehicle cooperative interference loss weights, obtaining an ecological monitoring unmanned aerial vehicle transmission topological graph by using the unmanned aerial vehicle cooperative interference loss weights, recording unmanned aerial vehicle cooperative interference loss weight values with a preset time slot length as a cooperative interference loss weight sequence, calculating an adaptive interval adjustment length, and calculating a node screening threshold value; acquiring an ecological monitoring transmission bearing topological graph; and calculating a Gray code adaptive bit variation value of the ecological monitoring unmanned aerial vehicle, and performing transmission adjustment on transmission data of the ecological monitoring unmanned aerial vehicle by using the Gray code adaptive bit variation value of the ecological monitoring unmanned aerial vehicle. The reliability of the ecological monitoring unmanned aerial vehicle in the data transmission process is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data transmission processing, in particular to an unmanned aerial vehicle communication assisted ecological monitoring data transmission system and method. BACKGROUND

[0002] With the continuous improvement of human science and technology, the development and utilization level of natural resources is also relatively improved, and the over-exploitation of natural resources will cause serious damage to the stability of the ecological environment, so it is necessary to monitor and manage the ecological environment of natural resources in a timely manner. However, in the process of natural resource environment monitoring, it is difficult to obtain ecological monitoring data due to the harsh natural environment and complex actual natural terrain. An unmanned aerial vehicle is a powered aircraft without human operators, which can obtain effective data by reaching the destination without endangering human safety through unmanned aerial vehicles and their loads. The main types of unmanned aerial vehicle loads are optical remote sensing, laser radar remote sensing and microwave remote sensing.

[0003] In the process of unmanned aerial vehicle ecological monitoring, the video image data of unmanned aerial vehicle ecological monitoring is easily affected by external environmental noise during transmission, resulting in a decrease in the quality of the received video image or even a signal interruption phenomenon. At this time, in order to ensure the transmission quality of the video image data in the process of unmanned aerial vehicle ecological monitoring, the video image data in the process of unmanned aerial vehicle ecological monitoring needs to be processed to enhance the transmission quality of the unmanned aerial vehicle video image. SUMMARY

[0004] The present application provides an unmanned aerial vehicle communication assisted ecological monitoring data transmission system and method to solve the problem of poor communication reliability caused by the uncertainty of the number of Gray code bits in the process of ecological monitoring unmanned aerial vehicle communication. The technical solution adopted is as follows: In a first aspect, an embodiment of the present application provides an unmanned aerial vehicle communication assisted ecological monitoring data transmission method, which comprises the following steps: Obtaining unmanned aerial vehicle ecological monitoring state parameters; Calculating the unmanned aerial vehicle ecological monitoring obstruction coefficient at different times according to the unmanned aerial vehicle ecological monitoring state parameters, and calculating the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different times according to the unmanned aerial vehicle ecological monitoring obstruction coefficient at different times; Calculating the unmanned aerial vehicle cooperative interference loss weight according to the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different times, obtaining the ecological monitoring unmanned aerial vehicle transmission topology graph using the unmanned aerial vehicle cooperative interference loss weight, recording the unmanned aerial vehicle communicating with the ground user terminal at the current time as the transmission task bearing unmanned aerial vehicle, recording the number of unmanned aerial vehicle cooperative interference loss weight values of the preset time slot length as the cooperative interference loss weight sequence, calculating the adaptive interval adjustment length according to the cooperative interference loss weight sequence, calculating the node screening threshold according to the adaptive interval adjustment length, and obtaining the ecological monitoring transmission bearing topology graph according to the node screening threshold. The ecological monitoring unmanned aerial vehicle gray code adaptive bit change value is calculated according to the ecological monitoring transmission bearing topology graph, and the ecological monitoring unmanned aerial vehicle gray code adaptive bit change value is used to adjust the transmission data of the ecological monitoring unmanned aerial vehicle.

[0005] Preferably, the unmanned aerial vehicle ecological monitoring state parameters include: unmanned aerial vehicle ecological monitoring video frame data, communication buffer capacity, spatial coordinate position, video image maximum resolution and unmanned aerial vehicle quantity. Preferably, the calculation formula of the unmanned aerial vehicle ecological monitoring obstruction coefficient at different time instants is calculated according to the unmanned aerial vehicle ecological monitoring state parameters. In the formula, the communication buffer occupation size of the ecological monitoring unmanned aerial vehicle at the i th time instant is represented. The communication buffer maximum capacity of the ecological monitoring unmanned aerial vehicle is represented. The logarithm function with the number 2 as the base is represented. The antenna gain in the unmanned aerial vehicle ecological monitoring process at the i th time instant is represented. The transmission power of the ecological monitoring unmanned aerial vehicle at the i th time instant is represented. The unmanned aerial vehicle environmental additive white Gaussian noise power at the i th time instant is represented. The unmanned aerial vehicle ecological monitoring obstruction coefficient at the i th time instant is represented. Preferably, the calculation formula of the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different time instants is calculated according to the unmanned aerial vehicle ecological monitoring obstruction coefficient at different time instants.

[0006] In the formula, the unmanned aerial vehicle ecological monitoring obstruction coefficient at the i th time instant is represented. The normalization function is represented. The ecological monitoring video image data has N different video frames in total. The maximum value and the minimum value in the k th video frame in the unmanned aerial vehicle ecological monitoring video image at the i th time instant are represented, respectively. The maximum value and the minimum value in the i th video frame at the starting position in the unmanned aerial vehicle ecological monitoring video image at the i th time instant are represented, respectively. The covariance of the k th video frame and the i th video frame at the starting position is represented. ​​​​​​​respectively represent the variance of the i-th video frame of the starting position in the unmanned aerial vehicle ecological monitoring video image at the i-th moment and the variance of the k-th video frame, The unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at the i-th moment is represented.

[0007] Preferably, the specific method for calculating the unmanned aerial vehicle cooperative interference loss weight according to the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different moments is: The Euclidean distance between the two different ecological monitoring unmanned aerial vehicles is input as a negative exponential function with a natural constant as the base, and the product of the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different moments and the function output result is recorded as the unmanned aerial vehicle cooperative interference loss weight.

[0008] Preferably, the specific method for calculating the adaptive interval adjustment length according to the sequence of cooperative interference loss weights is: The product of the preset time slot length and the number of unmanned aerial vehicles is recorded as the first product, and the ratio of the range of the sequence of cooperative interference loss weights to the first product is recorded as the adaptive interval adjustment length.

[0009] Preferably, the method for calculating the node screening threshold according to the adaptive interval adjustment length is: The adaptive interval adjustment length is used as the data interval division length of the sequence of cooperative interference loss weights, and the value of the data of the sequence of cooperative interference loss weights is used as the horizontal axis and the number of data points in each interval is used as the vertical axis to obtain the cooperative interference loss weight histogram. The node screening threshold is obtained by taking the cooperative interference loss weight histogram as the input of the triangular threshold algorithm.

[0010] Preferably, the method for obtaining the ecological monitoring transmission bearer topology graph according to the node screening threshold is: All unmanned aerial vehicle nodes in the ecological monitoring transmission topology graph whose cooperative interference loss with the transmission task bearer unmanned aerial vehicle node is less than the node screening threshold are retained, and all the nodes after retention are recorded as the ecological monitoring transmission bearer topology graph.

[0011] Preferably, the calculation formula for calculating the ecological monitoring unmanned aerial vehicle Gray code adaptive bit change value according to the ecological monitoring transmission bearer topology graph is: In the above formula, The number of nodes in the ecological monitoring transmission bearer topology graph centered at the ecological monitoring transmission task bearer unmanned aerial vehicle at moment i is represented. The total number of nodes in the ecological monitoring transmission topology graph of the ecological monitoring unmanned aerial vehicle at moment i is represented. The total number of nodes in the ecological monitoring transmission topology graph of the ecological monitoring unmanned aerial vehicle at moment i is represented. The logarithmic function with 2 as the base is represented. The maximum resolution of the ecological monitoring unmanned aerial vehicle video image is represented. The ecological monitoring unmanned aerial vehicle gray code adaptive bit change value is represented.

[0012] In a second aspect, the embodiment of the present application also provides an ecological monitoring data transmission system assisted by unmanned aerial vehicle communication, comprising a memory, a processor and a computer program stored in the memory and running on the processor, and the processor implements the steps of the method of any one of the above aspects when executing the computer program.

[0013] The beneficial effects of the present application are: firstly, the present application calculates and characterizes the noise interference influence of the unmanned aerial vehicle ecological monitoring obstruction coefficient on the unmanned aerial vehicle communication transmission in the ecological monitoring process, simultaneously considers the communication state between multiple different unmanned aerial vehicles in the ecological monitoring process, and further calculates the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient by combining the unmanned aerial vehicle ecological monitoring obstruction coefficient, so as to more accurately calculate and analyze the unmanned aerial vehicle communication interference obstruction state in the ecological monitoring process. Further, the present application obtains the ecological monitoring transmission bearing topology graph by the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient and the unmanned aerial vehicle spatial coordinate position, and dynamically adjusts the number of unmanned aerial vehicle ecological monitoring gray code bits in combination with the topology node characteristics, so as to ensure the reliability of the unmanned aerial vehicle ecological monitoring data transmission. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0015] Figure 1 A flowchart of a method for ecological monitoring data transmission assisted by unmanned aerial vehicle communication provided by an embodiment of the present application; Figure 2 A flowchart for obtaining an ecological monitoring transmission bearing topology graph. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0017] Please refer to Figure 1, which shows a flow chart of a method for ecological monitoring data transmission assisted by drone communication provided by one embodiment of the present invention, the method comprising the following steps: Step S001: Obtain the drone ecological monitoring status parameters.

[0018] During the UAV ecological monitoring process, the ground user terminal A task request is sent to the UAV equipped with image photography function, requesting the UAV to capture the video image of the ecological monitoring area in the corresponding area. Assuming that the UAV receives the task request response from the user end, the number of ecological monitoring video images obtained at the current position of the UAV is recorded as , assuming that at time The ecological monitoring video image data obtained by the UAV has a total of N different video frames, among which , , Respectively represent the drone ecological monitoring video frame data of the 1st frame, the 2nd frame and the Nth frame at time i.

[0019] In order to obtain more complete ecological monitoring data, it is necessary to use multiple different drones to coordinate monitoring. First, the spatial coordinates of all drones at different locations are obtained through the GPS global positioning system. At the same time, assuming that the total number of drones in the ecological monitoring process is The maximum resolution of the ecological monitoring video image obtained by the drone is .

[0020] Step S002: Calculate the drone ecological monitoring obstruction coefficient at different times based on the drone ecological monitoring state parameters, and calculate the drone ecological monitoring data dynamic disturbance coefficient at different times based on the drone ecological monitoring obstruction coefficient at different times.

[0021] It should be noted that during the UAV ecological monitoring process, the quality of the video image transmitted by the ecological monitoring UAV is seriously disturbed due to the interference of external noise in the natural environment. At this time, it is necessary to analyze the communication status between the UAV and the ground user terminal during the UAV ecological monitoring process.

[0022] Where, Indicates the The size of the communication buffer occupied by the ecological monitoring drone at each moment, It shows the maximum capacity of the ecological monitoring drone communication buffer. represents the logarithmic function with the base 2. It represents the antenna gain of the UAV ecological monitoring process at time i, represents the transmission power of the ecological monitoring UAV at time i, represents the UAV environmental additive white Gaussian noise power at time represents the UAV ecological monitoring obstruction coefficient at the i-th time.

[0023] When the ecological monitoring video image information obtained at each different time during the ecological environment monitoring process of the UAV can be transmitted in time, the greater the ratio between the size of the ecological monitoring UAV communication buffer occupancy and the maximum buffer capacity, the more congested the current ecological monitoring UAV communication buffer. At the same time, the greater the antenna gain and the higher the transmission power of the ecological monitoring UAV during the UAV ecological monitoring communication process, the smaller the Gaussian white noise power, and the relatively smaller the calculated UAV ecological monitoring obstruction coefficient at the i-th time. The communication monitoring obstruction occurring during the transmission of video image data information during the current time ecological monitoring UAV communication process is relatively small.

[0024] It should be noted that during the UAV ecological monitoring process, if the environmental noise interference during the flight of the ecological monitoring UAV at different times is more serious, the value of the video image obtained by the ecological monitoring UAV will be greatly affected. At this time, the abnormal value of the ecological monitoring UAV video image needs to be analyzed.

[0025] In the formula, represents the UAV ecological monitoring obstruction coefficient at the i-th time, represents the normalized function, represents that the ecological monitoring video image data has N different video frames, represents the maximum value and the minimum value of the k-th video frame in the i-th time ecological monitoring video image of the UAV, respectively, represents the maximum value and the minimum value of the i-th video frame at the starting position in the i-th time ecological monitoring video image of the UAV, respectively, represents the covariance of the k-th video frame and the i-th video frame at the starting position, represents the variance of the i-th video frame at the starting position and the variance of the k-th video frame in the i-th time ecological monitoring video image of the UAV, respectively, represents the UAV ecological monitoring data dynamic disturbance coefficient at the i-th time.

[0026] ​​​​The dynamic disturbance coefficient of the unmanned aerial vehicle ecological monitoring data at different times is calculated by the above formula. If the value of the unmanned aerial vehicle ecological monitoring obstruction coefficient calculated at time i is large, and the difference between the numerical variation range of different video frames and the video frame at the starting position in the unmanned aerial vehicle ecological monitoring video image obtained at time i is large, it means that the difference between the video frames at different positions in the unmanned aerial vehicle ecological monitoring video image obtained at time i is large, and the dynamic disturbance coefficient of the unmanned aerial vehicle ecological monitoring data at the i th moment calculated is also relatively large, which means that the numerical difference between the unmanned aerial vehicle ecological monitoring video image data obtained at time i is relatively large, and the possibility of interference of the unmanned aerial vehicle ecological monitoring video at time i is also relatively large.

[0027] Step S003, calculating the unmanned aerial vehicle cooperative interference loss weight according to the dynamic disturbance coefficient of the unmanned aerial vehicle ecological monitoring data at different times, using the unmanned aerial vehicle cooperative interference loss weight to obtain the ecological monitoring unmanned aerial vehicle transmission topology graph, recording the unmanned aerial vehicle communicating with the ground user terminal at the current moment as the transmission task bearing unmanned aerial vehicle, recording the value of the unmanned aerial vehicle cooperative interference loss weight of the preset time slot length as the cooperative interference loss weight sequence, calculating the adaptive interval adjustment length according to the cooperative interference loss weight sequence, calculating the node screening threshold according to the adaptive interval adjustment length, and obtaining the ecological monitoring transmission bearing topology graph according to the node screening threshold.

[0028] It should be noted that in order to obtain the complete state of the ecological monitoring area, multiple different unmanned aerial vehicles need to work cooperatively. When multiple different unmanned aerial vehicles monitor the ecological monitoring area at the same time, there will be communication interference in the data transmission process between multiple different ecological monitoring unmanned aerial vehicles. Therefore, the communication process state of the ecological monitoring unmanned aerial vehicle is further analyzed according to the distance between different unmanned aerial vehicles during the cooperative interference process of multiple different unmanned aerial vehicles in the ecological monitoring process.

[0029] First, the spatial coordinate position of the ecological monitoring unmanned aerial vehicle at time i is obtained by the GPS global positioning system. The Euclidean distance between two different ecological monitoring unmanned aerial vehicles can be calculated by the spatial coordinate position of the ecological monitoring unmanned aerial vehicle at time i, which is denoted as .

[0030] In the formula, indicates the dynamic disturbance coefficient of the unmanned aerial vehicle ecological monitoring data at the i th moment, indicates the Euclidean distance between two different ecological monitoring unmanned aerial vehicles and at time i, indicates the Euclidean distance between two different ecological monitoring unmanned aerial vehicles and The exp function represents an exponential function with a natural constant as the base.

[0031] The above formula can be used to calculate the two different ecological monitoring drones at time i. and The path weight value between them is the same as the value of the path weight between them. During the simultaneous monitoring process of multiple different ecological monitoring drones, if the Euclidean distance between two different ecological monitoring drones at time i is closer, and the dynamic disturbance coefficient of the drone ecological monitoring data at time i is larger, the calculated path weight between two different ecological monitoring drones at time i is and The collaborative interference loss weight value between the two different drones will be relatively large, indicating that in the process of ecological monitoring, and The interference between them is quite serious.

[0032] During the UAV ecological monitoring process, at time i, the values ​​of the collaborative interference loss weights between different UAVs can be calculated for all UAVs at different positions. The ecological monitoring UAVs and ground user terminals at different spatial positions at time i are regarded as nodes in the ecological monitoring UAV transmission topology map. The collaborative interference loss weights between two different UAVs are regarded as the weights between the nodes in the ecological monitoring UAV transmission topology map, where the ground user terminal is recorded as the end node, and the weights between all different ecological monitoring UAVs and the end node are recorded as the average values ​​of the collaborative interference loss weights of all different UAVs.

[0033] It should be noted that the priority of ecological monitoring drone missions at different times may vary. Figure 2 As shown in the figure, during the communication between different ecological monitoring UAVs and ground user terminals, the nodes of the UAV transmission topology map are first screened based on the priority emergency status of the missions carried by different ecological monitoring UAVs.

[0034] Assume that at time i, the ecological monitoring drone For the transmission task carrying drone, considering that the drone ecological monitoring video image data should have certain correlation characteristics in the short time slot segment, we take the time slot segment of length L from the current time i as the starting point, where L is an empirical value of 64. In specific applications, the implementer can set it according to the specific situation. The ecological monitoring drone at different positions at all times of the time slot segment of length L is connected with the transmission task carrying drone. The coordinated interference loss weights between them are recorded as the coordinated interference loss weight sequence .

[0035] In the above formula, respectively represent the ecological monitoring transmission task-carrying UAV at time i collusion loss weight sequence The maximum value and the minimum value in the above formula, L represents the length of the time slot segment, represents the number of ecological monitoring UAVs, represents the adaptive interval adjustment length of the ecological monitoring transmission task-carrying UAV at time i.

[0036] With the adaptive interval adjustment length as a step, the collusion loss weight between the ecological monitoring UAV and the ecological monitoring transmission task-carrying UAV at all different positions in the time slot segment with a length of L is divided into different intervals of the adaptive interval adjustment length, and the collusion loss weight histogram of the ecological monitoring transmission task-carrying UAV at time i is obtained with the numerical value of the collusion loss weight sequence data as the horizontal axis and the number of data points in each interval as the vertical axis. The node screening threshold of the collusion loss weight histogram of the UAV is obtained by using the triangular threshold algorithm.

[0037] For the ecological monitoring UAV transmission topology at time i, the ground user end node and all nodes with a collusion loss weight value greater than the node screening threshold are reserved with the ecological monitoring transmission task-carrying UAV as the center, denoted as the ecological monitoring transmission carrying topology at time i, denoted as

[0038] Step S004, calculate the Gray code adaptive bit variation value of the ecological monitoring UAV according to the ecological monitoring transmission carrying topology, and use the Gray code adaptive bit variation value of the ecological monitoring UAV to adjust the transmission data of the ecological monitoring UAV.

[0039] It should be noted that when the ecological monitoring UAV transmits video image data, in order to ensure the reliability of the transmission of the video image data of the UAV in the ecological monitoring process, the video image data needs to be encoded. Therefore, the data is optimized and encoded in combination with the ecological monitoring UAV transmission carrying topology at different times.

[0040] In the above formula, represents the ecological monitoring transmission task-carrying UAV at time i as the center, represents the total number of all nodes in the ecological monitoring UAV transmission topology at time i, represents the logarithm function with 2 as the base, ​​​The maximum resolution of the ecological monitoring unmanned aerial vehicle video image is represented, The Gray code adaptive bit change value of the ecological monitoring unmanned aerial vehicle is represented.

[0041] For the unmanned aerial vehicle carrying data transmission task in the ecological monitoring process, the number of Gray code bits in the transmission process is set as the adaptive bit change value, the number of Gray code bits of the unmanned aerial vehicle carrying data transmission task in the ecological monitoring process is dynamically adjusted, the interference error of the unmanned aerial vehicle data transmission in the ecological monitoring process is reduced, and thus the effective reliability of the data obtained by the ground user end is ensured.

[0042] Based on the same inventive concept as the above method, the embodiments of the present application also provide an ecological monitoring data transmission system assisted by unmanned aerial vehicle communication, which comprises a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of any one of the methods in the above-mentioned ecological monitoring data transmission method assisted by unmanned aerial vehicle communication when executing the computer program.

[0043] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for transmitting ecological monitoring data assisted by drone communication, characterized in that: The method comprises the following steps: Obtain UAV ecological monitoring status parameters; The obstruction coefficient of UAV ecological monitoring at different times is calculated based on the UAV ecological monitoring state parameters, and the dynamic disturbance coefficient of UAV ecological monitoring data at different times is calculated based on the obstruction coefficient of UAV ecological monitoring at different times; The UAV collaborative interference loss weight is calculated based on the dynamic disturbance coefficient of the UAV ecological monitoring data at different times. The UAV collaborative interference loss weight is used to obtain the ecological monitoring UAV transmission topology map. The UAV communicating with the ground user terminal at the current moment is recorded as the transmission task carrying UAV. The UAV collaborative interference loss weight value of the preset time slot length is recorded as the collaborative interference loss weight sequence. The adaptive interval adjustment length is calculated based on the collaborative interference loss weight sequence. The node screening threshold is calculated based on the adaptive interval adjustment length. The ecological monitoring transmission carrying topology map is obtained based on the node screening threshold. Calculate the Gray code adaptive bit change value of the ecological monitoring drone according to the ecological monitoring transmission bearer topology map, and use the Gray code adaptive bit change value of the ecological monitoring drone to adjust the transmission data of the ecological monitoring drone; The calculation formula for calculating the dynamic disturbance coefficient of the UAV ecological monitoring data at different times according to the UAV ecological monitoring obstruction coefficient at different times is: Where, It represents the obstacle coefficient of UAV ecological monitoring at the i-th moment, represents the normalization function, It indicates that there are N different video frames in the ecological monitoring video image data. , They represent the maximum and minimum values ​​in the kth video frame of the UAV ecological monitoring video image at the i-th moment, , They represent the maximum and minimum values ​​in the i-th video frame at the starting position of the UAV ecological monitoring video image at the i-th moment, respectively. represents the covariance between the kth video frame and the i-th video frame at the starting position, 、 They represent the variance of the i-th video frame and the variance of the k-th video frame at the starting position of the UAV ecological monitoring video image at the i-th moment, It represents the dynamic disturbance coefficient of the UAV ecological monitoring data at the i-th moment.

2. The method for transmitting ecological monitoring data assisted by drone communication according to claim 1, characterized in that: The UAV ecological monitoring status parameters include: UAV ecological monitoring video frame data, communication buffer capacity, spatial coordinate position, video image maximum resolution and number of UAVs.

3. The method for transmitting ecological monitoring data assisted by drone communication according to claim 1, characterized in that: The calculation formula for calculating the UAV ecological monitoring obstruction coefficient at different times based on the UAV ecological monitoring state parameters is: Where, Indicates the The size of the communication buffer occupied by the ecological monitoring drone at each moment, It shows the maximum capacity of the ecological monitoring drone communication buffer. represents the logarithmic function with the base 2. It represents the antenna gain of the UAV ecological monitoring process at time i, represents the transmission power of the ecological monitoring UAV at time i, Indicates the time The additive white Gaussian noise power of the UAV environment, It represents the obstacle coefficient of UAV ecological monitoring at the i-th moment.

4. The method for transmitting ecological monitoring data assisted by drone communication according to claim 1, characterized in that: The specific method for calculating the UAV collaborative interference loss weight based on the dynamic disturbance coefficient of the UAV ecological monitoring data at different times is: The Euclidean distance between two different ecological monitoring drones is used as the input of a negative exponential function with a natural constant as the base, and the product of the dynamic disturbance coefficient of the drone ecological monitoring data at different times and the function output result is recorded as the drone collaborative interference loss weight.

5. The method for transmitting ecological monitoring data assisted by drone communication according to claim 4, characterized in that: The specific method for calculating the adaptive interval adjustment length according to the coordinated interference loss weight sequence is: The product of the preset time slot length and the number of drones is recorded as the first product, and the ratio of the range of the cooperative interference loss weight sequence to the first product is recorded as the adaptive interval adjustment length.

6. The method for transmitting ecological monitoring data assisted by drone communication according to claim 5, characterized in that: The method for calculating the node screening threshold according to the adaptive interval adjustment length is: The adaptive interval adjustment length is used as the interval division length of the collaborative interference loss weight sequence data, the numerical value of the collaborative interference loss weight sequence data is used as the horizontal axis, and the number of data points in each interval is used as the vertical axis to obtain the collaborative interference loss weight histogram. The collaborative interference loss weight histogram is used as the input of the triangular threshold algorithm to obtain the node screening threshold.

7. The method for transmitting ecological monitoring data assisted by drone communication according to claim 6, characterized in that: The method for obtaining the ecological monitoring transmission bearer topology map according to the node screening threshold is: All drone nodes in the ecological monitoring drone transmission topology map whose collaborative interference loss with the transmission task-bearing drone nodes is less than the node screening threshold are retained, and all retained nodes are recorded as the ecological monitoring transmission carrying topology map.

8. The method for transmitting ecological monitoring data assisted by drone communication according to claim 7, characterized in that: The calculation formula for calculating the Gray code adaptive bit change value of the ecological monitoring drone based on the ecological monitoring transmission bearer topology diagram is: In the above formula, Represents the ecological monitoring transmission mission-carrying drone at time i The number of nodes in the ecological monitoring transmission topology diagram centered on represents the total number of nodes in the ecological monitoring drone transmission topology at time i, represents the logarithmic function with base 2, It represents the maximum resolution of ecological monitoring drone video images. It shows the Gray code adaptive bit change value of ecological monitoring drone.

9. An ecological monitoring data transmission system assisted by UAV communication, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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