An unmanned aerial vehicle communication-assisted ecological monitoring data transmission system and method

Abstract

The application relates to the technical field of data transmission processing, and discloses an unmanned aerial vehicle (UAV) communication-assisted ecological monitoring data transmission system and method, which comprises the following steps: acquiring UAV ecological monitoring state parameters; calculating a UAV ecological monitoring obstruction coefficient and a dynamic disturbance coefficient; calculating a UAV cooperative interference loss weight; using the UAV cooperative interference loss weight to acquire an ecological monitoring UAV transmission topology graph; taking the UAV cooperative interference loss weight value of a preset time slot length as a cooperative interference loss weight sequence; calculating an adaptive interval adjustment length and a node screening threshold; acquiring an ecological monitoring transmission bearing topology graph; calculating an ecological monitoring UAV Gray code adaptive bit change value; and using the ecological monitoring UAV Gray code adaptive bit change value to perform transmission adjustment on ecological monitoring UAV transmission data. The application ensures the reliability of the ecological monitoring UAV data transmission process.

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 stable maintenance of the ecological environment, so it is necessary to monitor and manage the natural resource ecological environment in a timely manner. However, in the process of natural resource environment monitoring, due to the harsh natural environment and the complex actual natural terrain, it is difficult to obtain ecological monitoring data. The unmanned aerial vehicle is a powered aircraft without human operators, which can obtain effective data by unmanned aerial vehicle and its load without endangering human safety to reach the destination. The unmanned aerial vehicle load types mainly include 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, which leads to a decrease in the quality of received video image data or even signal interruption. At this time, in order to ensure the transmission quality of video image data in the process of unmanned aerial vehicle ecological monitoring, it is necessary to process the video image data in the process of unmanned aerial vehicle ecological monitoring and enhance the transmission quality of 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 uncertain number of gray code bits in the process of ecological monitoring unmanned aerial vehicle communication. The technical solution adopted is as follows:

[0005] In the 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:

[0006] Obtaining the unmanned aerial vehicle ecological monitoring state parameter;

[0007] Calculating the unmanned aerial vehicle ecological monitoring obstruction coefficient at different times according to the unmanned aerial vehicle ecological monitoring state parameter, 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;

[0008] The collaborative interference loss weight of UAVs is calculated based on the dynamic disturbance coefficient of UAV ecological monitoring data at different times. The UAV collaborative interference loss weight is used to obtain the transmission topology map of ecological monitoring UAVs. The UAVs communicating with the ground user terminal at the current time are recorded as transmission task-bearing UAVs. The UAV collaborative interference loss weight values ​​of the preset time slot length are recorded as collaborative interference loss weight sequences. 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 topology map is obtained based on the node screening threshold.

[0009] The adaptive bit variation value of the Gray code of the ecological monitoring UAV is calculated based on the topology map of ecological monitoring transmission, and the transmission data of the ecological monitoring UAV is adjusted using the adaptive bit variation value of the Gray code of the ecological monitoring UAV.

[0010] Preferably, the drone ecological monitoring status parameters include: drone ecological monitoring video frame data, communication buffer capacity, spatial coordinate position, maximum video image resolution, and number of drones;

[0011] Preferably, the formula for calculating the drone ecological monitoring obstacle coefficient at different times based on the drone ecological monitoring status parameters is as follows:

[0012]

[0013] In the formula, It indicates the first The size of the communication buffer occupied by the ecological monitoring drone at each time point. This indicates the maximum capacity of the communication buffer for ecological monitoring drones. This represents the logarithmic function with base 2. This represents the antenna gain during the UAV ecological monitoring process at time i. This indicates the transmission power of the ecological monitoring drone at time i. Indicates the time Additive white Gaussian noise power in the drone environment This represents the obstacle coefficient for drone ecological monitoring at time i.

[0014] Preferably, the formula for calculating the dynamic disturbance coefficient of UAV ecological monitoring data at different times based on the UAV ecological monitoring obstacle coefficient at different times is as follows:

[0015]

[0016] In the formula, This represents the obstacle coefficient for drone ecological monitoring at time i. This represents the normalization function. represents the maximum value and the minimum value in the kth video frame of the i th time point of the UAV ecological monitoring video image respectively, represents the maximum value and the minimum value in the i th video frame of the starting position at the i th time point of the UAV ecological monitoring video image respectively, represents the maximum value and the minimum value in the i th video frame of the starting position at the i th time point of the UAV ecological monitoring video image respectively, represents the covariance of the kth video frame and the i th video frame of the starting position, represents the variance of the i th video frame of the starting position and the variance of the kth video frame in the i th time point of the UAV ecological monitoring video image respectively, represents the dynamic disturbance coefficient of the UAV ecological monitoring data at the i th time point.

[0017] Preferably, the specific method for calculating the UAV cooperative interference loss weight according to the dynamic disturbance coefficient of the UAV ecological monitoring data at different time points is:

[0018] The Euclidean distance between two different ecological monitoring UAVs is input as a negative exponential function with a natural constant as the base, and the product of the dynamic disturbance coefficient of the UAV ecological monitoring data at different time points and the output result of the function is recorded as the UAV cooperative interference loss weight.

[0019] Preferably, the specific method for calculating the adaptive interval adjustment length according to the sequence of cooperative interference loss weights is:

[0020] The product of the preset time slot length and the number of UAVs 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.

[0021] Preferably, the method for calculating the node screening threshold according to the adaptive interval adjustment length is:

[0022] The adaptive interval adjustment length is used as the data interval division length of the sequence of cooperative interference loss weights, and the cooperative interference loss weight histogram is obtained by taking the value size of the data of the sequence of cooperative interference loss weights as the horizontal axis and the number of data points in each interval as the vertical axis, and the node screening threshold is obtained by taking the cooperative interference loss weight histogram as the input of the triangle threshold algorithm.

[0023] Preferably, the method for obtaining the ecological monitoring transmission bearing topology graph according to the node screening threshold is:

[0024] ​​​All unmanned aerial vehicle nodes in the transmission topology graph of the ecological monitoring unmanned aerial vehicle, which have a cooperative interference loss less than a node screening threshold, are reserved, and all the nodes after reservation are recorded as an ecological monitoring transmission carrying topology graph.

[0025] Preferably, a calculation formula for calculating the Gray code adaptive bit change value of the ecological monitoring unmanned aerial vehicle according to the ecological monitoring transmission carrying topology graph is as follows:

[0026]

[0027] In the above formula, indicates the ecological monitoring transmission task carrying unmanned aerial vehicle at time i the number of nodes in the ecological monitoring transmission carrying topology graph centered on the center node, indicates the total number of nodes in the transmission topology graph of the ecological monitoring unmanned aerial vehicle at time i, indicates a logarithmic function with base 2, indicates the maximum resolution of the video image of the ecological monitoring unmanned aerial vehicle, indicates the Gray code adaptive bit change value of the ecological monitoring unmanned aerial vehicle.

[0028] In a second aspect, 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 the method according to any one of the above aspects when executing the computer program.

[0029] The present application has the following beneficial effects: the present application first calculates and characterizes the noise interference influence of the unmanned aerial vehicle ecological monitoring obstruction coefficient on the communication transmission of the unmanned aerial vehicle in the ecological monitoring process, 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 communication interference obstruction state of the unmanned aerial vehicle in the ecological monitoring process. Further, the present application obtains the ecological monitoring transmission carrying topology graph by the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient and the spatial coordinate position of the unmanned aerial vehicle, and adaptively and dynamically adjusts the number of Gray code bits of the ecological monitoring unmanned aerial vehicle in combination with the topology node characteristics, thereby ensuring the reliability of the ecological monitoring data transmission of the unmanned aerial vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. 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 any creative labor.

[0031] Figure 1 A flowchart of a UAV communication-assisted ecological monitoring data transmission method provided by an embodiment of the present application is shown in FIG. 1.

[0032] Figure 2 A flowchart of a process for obtaining an ecological monitoring transmission bearing topology graph is shown in FIG. 2. DETAILED DESCRIPTION

[0033] 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 of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0034] Please refer to Figure 1 , which shows a flowchart of a UAV communication-assisted ecological monitoring data transmission method provided by an embodiment of the present application. The method includes the following steps:

[0035] Step S001: Obtain a UAV ecological monitoring state parameter.

[0036] In the process of UAV ecological monitoring, the ground user terminal sends a task request to a UAV equipped with an image shooting function at time , requesting the UAV to capture an ecological monitoring area video image at the corresponding area. Assuming that the UAV accepts the task request response from the ground user terminal, the ecological monitoring video image obtained at the current position of the UAV at this time is recorded as . Assuming that the UAV obtains N different video frames of ecological monitoring video image data at time , wherein , , respectively represent the first frame, the second frame, and the Nth frame of the UAV ecological monitoring video frame data at time i.

[0037] In order to obtain more complete ecological monitoring data, multiple different UAVs need to be used for cooperative monitoring. First, the spatial coordinate positions of all different positions of the UAVs are obtained through the GPS global positioning system. At the same time, assuming that the total number of UAVs in the process of ecological monitoring is , and the maximum resolution of the ecological monitoring video image obtained by the UAV is .

[0038] Step S002, calculating the UAV ecological monitoring obstruction coefficient at different time according to the UAV ecological monitoring state parameter, and calculating the UAV ecological monitoring data dynamic disturbance coefficient at different time according to the UAV ecological monitoring obstruction coefficient at different time.

[0039] It should be noted that, in the process of ecological monitoring of the unmanned aerial vehicle, the quality of the video image in the transmission process of the ecological monitoring unmanned aerial vehicle is seriously disturbed due to the interference of the natural environment external noise, at this time, the communication state between the unmanned aerial vehicle and the ground user terminal in the process of ecological monitoring of the unmanned aerial vehicle needs to be analyzed.

[0040]

[0041] In the formula, The communication buffer occupancy size of the ecological monitoring unmanned aerial vehicle at the i th time is represented as The maximum capacity of the communication buffer of the ecological monitoring unmanned aerial vehicle is represented as The logarithmic function with the number 2 as the base is represented as The antenna gain in the process of ecological monitoring of the unmanned aerial vehicle at time i is represented as The transmission power of the ecological monitoring unmanned aerial vehicle at time i is represented as The environmental additive white Gaussian noise power of the unmanned aerial vehicle at time i is represented as The ecological monitoring obstruction coefficient of the unmanned aerial vehicle at the i th time is represented as When the ecological monitoring video image information obtained at each different time in the process of ecological monitoring of the unmanned aerial vehicle can be transmitted in time, the larger the ratio between the communication buffer occupancy size of the ecological monitoring unmanned aerial vehicle and the maximum buffer capacity, the more congested the communication buffer of the ecological monitoring unmanned aerial vehicle, at the same time, the larger the antenna gain in the communication process of the ecological monitoring unmanned aerial vehicle, the higher the transmission power of the ecological monitoring unmanned aerial vehicle, and the smaller the Gaussian white noise power, at this time, the ecological monitoring obstruction coefficient calculated at the i th time will be relatively small, and the communication monitoring obstruction in the transmission process of the video image data information in the communication process of the ecological monitoring unmanned aerial vehicle at the current time will also be relatively small.

[0042] It should be noted that, in the process of ecological monitoring of the unmanned aerial vehicle, if the environmental noise interference in the flight process of the ecological monitoring unmanned aerial vehicle at different times is relatively serious, the value of the video image obtained by the ecological monitoring unmanned aerial vehicle will be greatly affected, at this time, the abnormal value of the video image of the ecological monitoring unmanned aerial vehicle needs to be analyzed.

[0043] It should be noted that, in the process of ecological monitoring of the unmanned aerial vehicle, if the environmental noise interference in the flight process of the ecological monitoring unmanned aerial vehicle at different times is relatively serious, the value of the video image obtained by the ecological monitoring unmanned aerial vehicle will be greatly affected, at this time, the abnormal value of the video image of the ecological monitoring unmanned aerial vehicle needs to be analyzed.

[0044]

[0045] In the formula, ​denotes the UAV ecological monitoring obstruction coefficient at the i th moment, denotes the normalization function, denotes that the ecological monitoring video image data has N different video frames, , denotes the maximum value and the minimum value in the k th video frame in the i th moment of the UAV ecological monitoring video image, , denotes the maximum value and the minimum value in the i th video frame at the starting position in the i th moment of the UAV ecological monitoring video image, denotes the covariance of the k th video frame and the i th video frame at the starting position, , denotes 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 moment of the UAV ecological monitoring video image, denotes the UAV ecological monitoring data dynamic disturbance coefficient at the i th moment.

[0046] The UAV ecological monitoring data dynamic disturbance coefficient at different moments is calculated by the above formula. If the calculated UAV ecological monitoring obstruction coefficient value at moment i is large, and the value variation range between different video frames and the video frame at the starting position in the UAV ecological monitoring video image obtained at moment i is large, it means that the difference between different video frames and the video frame at the starting position in the UAV ecological monitoring video image obtained at moment i is large, and the calculated UAV ecological monitoring data dynamic disturbance coefficient at the i th moment is also relatively large, which means that the numerical difference between the UAV ecological monitoring video image data obtained at moment i is relatively large, and the possibility of interference of the UAV ecological monitoring video at moment i is also relatively large.

[0047] Step S003, calculating the UAV cooperative interference loss weight according to the UAV ecological monitoring data dynamic disturbance coefficient at different moments, using the UAV cooperative interference loss weight to obtain the ecological monitoring UAV transmission topology graph, recording the UAV communicating with the ground user terminal at the current moment as the transmission task bearing UAV, recording the UAV cooperative interference loss weight value 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.

[0048] 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 simultaneously monitor the ecological monitoring area, communication interference of data transmission may exist between multiple different ecological monitoring unmanned aerial vehicles. Therefore, in the process of cooperation and interference between multiple different unmanned aerial vehicles in the ecological monitoring process, the communication process state of the ecological monitoring unmanned aerial vehicle is further analyzed according to the distance between different unmanned aerial vehicles.

[0049] Firstly, the spatial coordinate position of the ecological monitoring unmanned aerial vehicle at time i is obtained through the GPS global positioning system. The Euclidean distance between two different ecological monitoring unmanned aerial vehicles can be calculated through the spatial coordinate position of the ecological monitoring unmanned aerial vehicle at time i, denoted as .

[0050]

[0051] In the formula, represents the dynamic disturbance coefficient of the unmanned aerial vehicle ecological monitoring data at the i-th moment, represents the Euclidean distance between two different ecological monitoring unmanned aerial vehicles and at time i, represents the cooperative interference loss weight between two different ecological monitoring unmanned aerial vehicles and at time i. The exp function represents the exponential function with the natural constant as the base.

[0052] Through the above formula, the path weight value between two different ecological monitoring unmanned aerial vehicles and at time i can be calculated. In the process of simultaneous monitoring of multiple different ecological monitoring unmanned aerial vehicles, if the Euclidean distance between two different ecological monitoring unmanned aerial vehicles at time i is closer, and the dynamic disturbance coefficient of the unmanned aerial vehicle ecological monitoring data at the i-th moment is larger, the cooperative interference loss weight value between two different ecological monitoring unmanned aerial vehicles and at time i will be relatively large, indicating that the interference between two different unmanned aerial vehicles and in the ecological monitoring process is more serious.

[0053] In the process of UAV ecological monitoring, at time i, the value of the cooperative interference loss weight between different UAVs can be calculated for all different UAVs at different locations. The ecological monitoring UAVs and ground user terminals at different spatial locations at time i are taken as nodes in the ecological monitoring UAV transmission topology map. The cooperative interference loss weight between two different UAVs is taken as the weight between the nodes in the ecological monitoring UAV transmission topology map. The ground user terminal is recorded as the end node. The weight between all different ecological monitoring UAVs and the end node is recorded as the average value of the cooperative interference loss weight of all different UAVs.

[0054] It should be noted that the priority and emergency status of the tasks undertaken by ecological monitoring drones vary at different times, therefore, as... Figure 2 As shown, during the communication process between different ecological monitoring drones and ground users, the nodes of the drone transmission topology are first screened based on the priority and emergency status of the tasks carried by different ecological monitoring drones.

[0055] Assume an ecological monitoring drone at time i To ensure the transmission of the drone carrying the mission, and considering that the drone's ecological monitoring video image data should exhibit certain correlation within short time slots, a time slot of length L is taken forward from the current time i, where L is empirically set to 64. In specific applications, the implementer can adjust this value according to the specific circumstances. The ecological monitoring drones at different locations at all times within this time slot of length L are then compared with the drone carrying the transmission mission. The cooperative interference loss weights between them are denoted as the cooperative interference loss weight sequence. .

[0056]

[0057] In the above formula, , These represent the drones carrying the ecological monitoring and transmission task at time i. Cooperative interference loss weight sequence The maximum and minimum values, where L represents the time slot segment length. This indicates the number of ecological monitoring drones. This represents the adaptive interval adjustment length of the UAV carrying the ecological monitoring and transmission task at time i.

[0058] Using the adaptive interval adjustment length as the step size, the ecological monitoring UAVs and the ecological monitoring transmission mission carrying UAVs at all different locations in a time slot segment of length L are linked. The cooperative interference loss weight between the two is divided into different intervals with adaptive interval adjustment length, to take the numerical value of the cooperative interference loss weight sequence data as the horizontal axis, and the number of data points in each interval as the vertical axis, to obtain the cooperative interference loss weight histogram of the ecological monitoring transmission task bearing unmanned aerial vehicle at time i. The node screening threshold of the cooperative interference loss weight histogram of the unmanned aerial vehicle is obtained by using the triangular threshold algorithm.

[0059] For the ecological monitoring unmanned aerial vehicle transmission topology at time i, the ground user end node and all nodes with a cooperative interference loss weight value greater than the node screening threshold are reserved as the center of the ecological monitoring transmission task bearing unmanned aerial vehicle, denoted as the ecological monitoring transmission bearing topology at time i, denoted as .

[0060] Step S004, calculate the Gray code adaptive bit variation value of the ecological monitoring unmanned aerial vehicle according to the ecological monitoring transmission bearing topology, and use the Gray code adaptive bit variation value of the ecological monitoring unmanned aerial vehicle to adjust the transmission data of the ecological monitoring unmanned aerial vehicle.

[0061] It should be noted that when the ecological monitoring unmanned aerial vehicle transmits video image data, in order to ensure the reliability of the transmission of video image data of the unmanned aerial vehicle 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 unmanned aerial vehicle transmission bearing topology at different times.

[0062]

[0063] In the above formula, indicates the ecological monitoring transmission task bearing unmanned aerial vehicle at time i as the center of the ecological monitoring transmission bearing topology, indicates the total number of all nodes in the ecological monitoring unmanned aerial vehicle transmission topology at time i, indicates the logarithmic function with base 2, indicates the maximum resolution of the video image of the ecological monitoring unmanned aerial vehicle, indicates the Gray code adaptive bit variation value of the ecological monitoring unmanned aerial vehicle.

[0064] For the unmanned aerial vehicle bearing data transmission task in the ecological monitoring process, the number of Gray code bits in the transmission process is set to the adaptive bit variation value, the number of Gray code bits of the data transmission task bearing unmanned aerial vehicle in the ecological monitoring process is dynamically adjusted, the interference error of the data transmission of the unmanned aerial vehicle in the ecological monitoring process is reduced, and the effective reliability of the data obtained by the ground user end is ensured.

[0065] Based on the same inventive concept as the above method, the embodiments of the present application also provide an unmanned aerial vehicle communication assisted ecological monitoring data transmission system, 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 any one of the above unmanned aerial vehicle communication assisted ecological monitoring data transmission methods when executing the computer program.

[0066] The above merely describes 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 ecological monitoring data transmission assisted by UAV communication, characterized in that, The method comprises the following steps: Obtain the unmanned aerial vehicle ecological monitoring state parameters; Calculate the unmanned aerial vehicle ecological monitoring obstruction coefficient at different time according to the unmanned aerial vehicle ecological monitoring state parameters, and calculate the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different time according to the unmanned aerial vehicle ecological monitoring obstruction coefficient at different time; Take the Euclidean distance between two different ecological monitoring unmanned aerial vehicles as the input of the negative exponential function with a natural constant as the base, take the product of the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different time and the function output result as the unmanned aerial vehicle cooperative interference loss weight, obtain the ecological monitoring unmanned aerial vehicle transmission topology graph by using the unmanned aerial vehicle cooperative interference loss weight, take the unmanned aerial vehicle communicating with the ground user terminal at the current time as the transmission task bearing unmanned aerial vehicle, take the number of the unmanned aerial vehicle cooperative interference loss weight in the preset time interval as the cooperative interference loss weight sequence, take the product of the preset time interval length and the number of the unmanned aerial vehicles as the first product, take the ratio of the range of the cooperative interference loss weight sequence and the first product as the adaptive interval adjustment length, calculate the node screening threshold according to the adaptive interval adjustment length, and screen the ecological monitoring unmanned aerial vehicle transmission topology graph according to the node screening threshold to obtain the ecological monitoring transmission bearing topology graph; Calculate the ecological monitoring unmanned aerial vehicle Gray code adaptive bit variation value according to the ecological monitoring transmission bearing topology graph, and use the ecological monitoring unmanned aerial vehicle Gray code adaptive bit variation value to adjust the transmission data of the ecological monitoring unmanned aerial vehicle. The calculation formula of the unmanned aerial vehicle ecological monitoring data dynamic disturbance coefficient at different time according to the unmanned aerial vehicle ecological monitoring obstruction coefficient at different time is: In the formula, represents the UAV ecological monitoring obstruction coefficient at the i th moment, represents the normalized function, represents that the ecological monitoring video image data has N different video frames, , respectively represent the maximum value and the minimum value in the k th video frame in the i th moment of the UAV ecological monitoring video image, , respectively represent the maximum value and the minimum value in the i th video frame at the starting position in the i th moment of the UAV ecological monitoring video image, represents the covariance of the k th video frame and the i th video frame at the starting position, 、 respectively represent 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 moment of the UAV ecological monitoring video image, represents the UAV ecological monitoring data dynamic disturbance coefficient at the i th moment; The method for calculating the node screening threshold according to the adaptive interval adjustment length is: Take the adaptive interval adjustment length as the data interval division length of the cooperative interference loss weight sequence, take the value of the data of the cooperative interference loss weight sequence as the horizontal axis, and take the number of data points in each interval as the vertical axis to obtain the cooperative interference loss weight histogram, take the cooperative interference loss weight histogram as the input of the triangular threshold algorithm to obtain the node screening threshold. 2.The unmanned aerial vehicle communication-assisted ecological monitoring data transmission method of claim 1, wherein, The unmanned aerial vehicle ecological monitoring state parameters comprise: unmanned aerial vehicle ecological monitoring video frame data, communication buffer capacity, spatial coordinate position, video image maximum resolution and the number of unmanned aerial vehicles. 3.The unmanned aerial vehicle communication-assisted ecological monitoring data transmission method of claim 1, wherein, The calculation formula of the unmanned aerial vehicle ecological monitoring obstruction coefficient at different time according to the unmanned aerial vehicle ecological monitoring state parameters is: wherein, represents the communication buffer occupancy size of the ecological monitoring UAV at the i-th time instant, represents the maximum capacity of the communication buffer of the ecological monitoring UAV, represents the logarithm function with base 2, represents the antenna gain in the ecological monitoring process of the UAV at the i-th time instant, represents the transmission power of the ecological monitoring UAV at the i-th time instant, represents the UAV environmental additive white Gaussian noise power at the i-th time instant, represents the ecological monitoring obstruction coefficient of the UAV at the i-th time instant. 4.The unmanned aerial vehicle communication-assisted ecological monitoring data transmission method of claim 1, wherein, The method for obtaining the ecological monitoring transmission bearing topology graph according to the node screening threshold is: Keep all the unmanned aerial vehicle nodes in the ecological monitoring unmanned aerial vehicle transmission topology graph which have a cooperative interference loss less than the node screening threshold with the transmission task bearing unmanned aerial vehicle node, and take all the nodes after keeping as the ecological monitoring transmission bearing topology graph.

5. The method of claim 4, wherein, The calculation formula of the ecological monitoring unmanned aerial vehicle Gray code adaptive bit variation value according to the ecological monitoring transmission bearing topology graph is: In the above formula, represents the total number of nodes in the ecological monitoring transmission task-carrying UAV at time i represents the number of nodes in the central ecological monitoring transmission-carrying topology graph, represents the total number of nodes in the ecological monitoring UAV transmission topology graph at time i represents the logarithmic function with base 2, represents the maximum resolution of the video image of the ecological monitoring UAV, represents the Gray code adaptive bit change value of the ecological monitoring UAV. 6.A UAV communication-assisted ecological monitoring data transmission system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, The processor realizes the steps of the method according to any one of claims 1-5 when executing the computer program.

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