CN110673481A - Method and device for determining attribute data of unmanned aerial vehicle, electronic equipment and storage medium - Google Patents

Abstract

The present application relates to a method, device, electronic device and storage medium for determining attribute data of an unmanned aerial vehicle. The method establishes a non-convex non-convex based on the range of flight speed, the range of flight height, the beam width of the drone, the coverage conditions and the data transmission rate of the sub-time period. The problem model converts the non-convex problem model into multiple target time-based convex problem models to determine the UAV's flight trajectory and beamwidth. The method for determining the attribute data of the UAV provided in this application can minimize the unmanned aerial vehicle by adjusting the flight trajectory and antenna beam width of the UAV under the condition that the flight speed, height and antenna beam width of the UAV are limited. The completion time of the machine transfer task.

Description

Method, device, electronic device and storage medium for determining attribute data of unmanned aerial vehicle

technical field

The present application relates to the technical field of unmanned aerial vehicle communication, and in particular, to a method, device, electronic device and storage medium for determining attribute data of an unmanned aerial vehicle.

Background technique

In recent years, drones have been widely used in military and civilian fields, and are expected to bring rich business opportunities in the next decade. In various applications of UAVs, UAV-assisted wireless communication has evolved into a very promising technology. Compared with traditional ground communication, UAV communication mainly has the following three advantages. First, drones can be deployed on demand with high flexibility and low operating costs. Second, compared to terrestrial channels, UAV-ground channels typically experience less scattering and thus have a higher probability of forming line-of-sight links, providing a more reliable communication link for user scheduling and resource allocation. Finally, UAVs can dynamically adjust their position in 3D space to improve communication quality, or avoid interference through proper trajectory design. The above advantages have given rise to a large number of new applications, such as cellular data offloading in hotspots, service restoration after infrastructure failures, mobile data relaying or customized communications in emergencies, etc. However, many challenges need to be addressed before the full potential of drone communications can be realized.

According to the mobility of UAV, the research of UAV-assisted communication system can be roughly divided into two categories. In the first category, UAVs serve as stationary aerial communication platforms, providing ubiquitous wireless coverage for ground users. In this scenario, the UAV deployment problem has been extensively studied. These work by optimizing the altitude or horizontal position of the drone to achieve different design goals, such as maximizing outage probability, coverage area, number of users served, throughput, etc. In the second category, UAVs serve as mobile aerial platforms to serve ground users. Several typical applications include UAV-assisted relay, information dissemination/data collection. Compared with the first type of research, this type of work further improves the system performance by optimizing the trajectory of the UAV to obtain better channel quality.

However, in most of the UAV communication work, the UAV's height is fixed, and its flight trajectory is limited to a horizontal plane, which does not fully utilize the UAV's mobility in the vertical direction. In addition, most work on UAV trajectory optimization assumes that UAVs are equipped with omnidirectional antennas, i.e., they can radiate signals of equal intensity in all directions in three-dimensional space. However, in practice, isoradiation can be achieved only in two-dimensional space (ie, the horizontal direction), thereby realizing an omnidirectional antenna. In modern communication systems, directional antennas with tunable beamwidths have been widely used in various scenarios. Therefore, it is of practical significance to study the trajectory design of UAVs equipped with directional antennas.

SUMMARY OF THE INVENTION

The embodiments of the present application provide a method, device, electronic device and storage medium for determining attribute data of an unmanned aerial vehicle, which can adjust the unmanned aerial vehicle by adjusting the flying speed, height, and antenna beam width of the unmanned aerial vehicle under the condition that the flying speed, height, and antenna beam width of the unmanned aerial vehicle are limited. The flight trajectory and antenna beamwidth are optimized to minimize the completion time of the UAV transmission mission.

On the one hand, an embodiment of the present application provides a method for determining attribute data of an unmanned aerial vehicle, including:

Determine the flight speed range, flight height range, and beam width of the UAV; determine the coverage conditions of the UAV based on the user corresponding to the UAV and the data transmission rate of the sub-time period; based on the flight speed range, the flight The height range, the beam width of the UAV, the coverage conditions and the data transmission rate of the sub-time period establish a non-convex problem model; convert the non-convex problem model into multiple target time-based convex problem models; The flight trajectory and beam width of the man-machine; wherein, the sub-time period is a time period within the preset time, and the target time is less than the preset time.

On the other hand, an embodiment of the present application provides a device for determining attribute data of an unmanned aerial vehicle, including:

The first determination module is used to determine the flight speed range of the UAV, the flight height range, and the beam width of the UAV; the second determination module is used to determine the coverage conditions of the UAV based on the user corresponding to the UAV and The data transmission rate of the sub-period; the third determination module is used to establish a non-convex problem model based on the flight speed range, the flight height range, the beam width of the UAV, the coverage conditions and the data transmission rate of the sub-period; the fourth determination module , which is used to convert the non-convex problem model into multiple convex problem models based on target time; the fifth determination module is used to determine the flight trajectory and beam width of the UAV based on the multiple convex problem models; wherein, the sub-time period is A time period within the preset time, the target time is less than the preset time.

On the other hand, an embodiment of the present application provides an electronic device, the electronic device includes a processor and a memory, and the memory stores at least one instruction, at least one segment of program, code set or instruction set, at least one instruction, at least one segment of program, code The set or instruction set is loaded and executed by the processor to implement the above-mentioned method for determining the attribute data of the drone.

On the other hand, an embodiment of the present application provides a computer-readable storage medium, in which the storage medium stores at least one instruction, at least one piece of program, code set or instruction set, at least one instruction, at least one piece of program, code set or instruction set Loaded and executed by the processor to realize the above-mentioned method for determining the attribute data of the drone.

The method, device, electronic device, and storage medium for determining attribute data of an unmanned aerial vehicle provided by the embodiments of the present application have the following beneficial effects:

By determining the flight speed range of the drone, the flight height range, and the beam width of the drone, determine the coverage conditions of the drone based on the user corresponding to the drone and the data transmission rate of the sub-time period, and based on the flight speed range , the flight height range, the beam width of the UAV, the coverage conditions and the data transmission rate of the sub-time period to establish a non-convex problem model, convert the non-convex problem model into multiple convex problem models based on target time, so as to determine the UAV's flight path and beamwidth. The method for determining the attribute data of the UAV provided by this application can minimize the unmanned aerial vehicle by adjusting the flight trajectory and antenna beam width of the UAV under the condition that the flight speed, height and antenna beam width of the UAV are limited. The completion time of the machine transfer task.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the drawings that are used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained from these drawings without creative effort.

1 is a schematic diagram of an application scenario provided by an embodiment of the present application;

2 is a schematic flowchart of a method for determining attribute data of an unmanned aerial vehicle provided by an embodiment of the present application;

3 is a simulation diagram of a UAV flight trajectory provided by an embodiment of the present application;

4 is a simulation diagram of the height and beam width of a UAV provided by an embodiment of the present application;

Fig. 5 is a kind of algorithm convergence curve diagram provided by the embodiment of the present application;

6 is a simulation diagram of the task completion time of a different scheme provided by an embodiment of the present application;

FIG. 7 is a schematic structural diagram of an apparatus for determining attribute data of an unmanned aerial vehicle provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present application.

It should be noted that the terms "first", "second", etc. in the description and claims of the present application and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that data so used may be interchanged under appropriate circumstances so that the embodiments of the application described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having" and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

Please refer to FIG. 1 . FIG. 1 is a schematic diagram of an application scenario provided by an embodiment of the present application, including a drone 101 and a user 102 . For example, in a multicast system assisted by the drone 101 , the drone 101 acts as an air base station to provide file transmission services for a plurality of ground users 102 .

By determining the flight speed range of the UAV 101, the flight height range, and the beam width of the UAV 101; secondly, determine the coverage conditions of the UAV 101 and the data transmission rate of the sub-time period, and the sub-time period is a preset time A time period within the target time is less than the preset time. Based on the flight speed range, flight height range, the beam width of the UAV 101, the coverage conditions and the data transmission rate of the sub-time period, a non-convex problem model is established, and the non-convex problem model is converted into multiple target time-based convex problem models. It is ensured that the user 102 is always within the coverage of the UAV 101, so that the optimal flight trajectory and beam width of the UAV 101 can be determined.

A specific embodiment of a method for determining attribute data of an unmanned aerial vehicle of the present application is introduced below. FIG. 2 is a schematic flowchart of a method for determining attribute data of an unmanned aerial vehicle provided by an embodiment of the present application. The method operation steps of the flowchart, but may include more or less operation steps based on routine or non-creative work. The sequence of steps enumerated in the embodiments is only one of the execution sequences of many steps, and does not represent the only execution sequence. When an actual system or server product is executed, it can be executed sequentially or in parallel (for example, in a parallel processor or multi-threaded processing environment) according to the embodiments or the methods shown in the accompanying drawings. Specifically, as shown in Figure 2, the method may include:

S201: Determine the flight speed range of the UAV, the flight height range, and the beam width of the UAV.

其中w_k∈R^{2 ×1}为水平坐标。为了便于说明，采用离散化方法将飞行时间T分为N个步长为δ_t的等间隔子时间段，即T＝Nδ_t。这里δ_t必须足够小，以确保在每个子时间段内无人机位置几乎不变。因此，无人机轨迹可以近似表示为

其中，q[n]∈R^2×1为无人机的水平坐标；h[n]为无人机的高度。确定无人机的最大水平飞行速度V_L和最大垂直飞行速度V_D，以及飞行最大高度h_max、最小高度h_min，则无人机飞行的限制条件可以根据公式(1)(2)(3)确定：In the embodiment of the present application, a specific application function scenario is used for description. The application scenario is a downlink multicast system. In this application scenario, the drone acts as a flying base station to transmit D-bit files to a group of ground users. The three-dimensional Cartesian coordinate system is used here, assuming that the coordinates of each user are

where w _k ∈ R ^{2 ×1} is the horizontal coordinate. For the convenience of description, the time of flight T is divided into N equally spaced sub-time segments with a step size of δ _t by using a discretization method, that is, T=Nδ _t . Here _δt must be small enough to ensure that the UAV position is almost unchanged in each sub-period. Therefore, the UAV trajectory can be approximately expressed as

Among them, q[n]∈R ^2×1 is the horizontal coordinate of the UAV; h[n] is the height of the UAV. Determine the maximum horizontal flight speed _VL and the maximum vertical flight speed V _D of the UAV, as well as the maximum flight height h _max and the minimum height h _min , then the restrictions on the flight of the UAV can be based on formula (1)(2)(3 )Sure:

In addition, in order to periodically serve ground users, the UAV needs to return to the initial position after the task is completed, that is, the horizontal coordinate of the UAV needs to satisfy the formula (4):

q[1]=q[N], h[1]=h[N]. …(4)

(θ[n],ψ[n])方向上相应的天线增益可以根据公式(5)确定：In the embodiment of the present application, the UAV is equipped with a directional antenna with adjustable beam width, and θ[n] and ψ[n] represent the azimuth and elevation angles of the antenna, respectively. The half-power beamwidths are assumed to be equal in azimuth and elevation, i.e. 2Θ[n], where

The corresponding antenna gain in the (θ[n],ψ[n]) direction can be determined according to formula (5):

和g分别代表主瓣和副瓣的天线增益。in,

and g represent the antenna gain of the main lobe and side lobe, respectively.

因此假设g＝0；波束宽度受最小和最大波束宽度限制，且

则无人机的波束宽度可以根据公式(6)确定：because

So assume g = 0; the beamwidth is limited by the minimum and maximum beamwidths, and

Then the beam width of the UAV can be determined according to formula (6):

S203: Determine the coverage condition of the drone based on the user corresponding to the drone and the data transmission rate of the sub-time period; the sub-time period is a time period within a preset time, and the target time is less than the preset time.

An optional implementation manner of determining the coverage conditions of the drone based on the user corresponding to the drone includes determining the user position of the user corresponding to the drone; determining the flight level position of the drone; Horizontal position, flight altitude range, and beamwidth determine coverage conditions.

In an optional implementation manner of determining the data transmission rate of the sub-time period, it includes determining the channel power gain under the first reference distance; The channel power gain of the user; the data transmission rate of the sub-period is determined according to the channel bandwidth, the channel power gain, the transmission power of the UAV and the power of the Gaussian white noise.

Based on the above application scenario, it is assumed that each ground user is equipped with an omnidirectional antenna with unity gain. As shown in Figure 1, the ground area covered by the main lobe of the UAV antenna is a circular area with a radius of rc[n]=h[n] _tanΘ [n] centered on the horizontal projection of the UAV. In order to ensure that all ground users are always within the coverage of the UAV, the coverage conditions of the UAV based on the user corresponding to the UAV can be determined according to formula (7):

It is assumed that the air-to-ground communication channel is a line-of-sight link, and the Doppler effect caused by the movement of the UAV can be perfectly compensated. According to the free space path loss model, the channel power gain from the UAV to the user can be determined according to formula (8):

Among them, β ₀ represents the channel power gain at the reference distance d ₀ =1.

The data transmission rate of the user in the sub-period of time n can be determined according to formula (9):

P表示无人机传输功率；σ²表示接收处加性高斯白噪声的功率。Among them, B is the channel bandwidth;

P represents the transmission power of the UAV; σ ² represents the power of the additive white Gaussian noise at the receiver.

S205: Establish a non-convex problem model based on the flight speed range, the flight height range, the beam width of the UAV, the coverage conditions and the data transmission rate of the sub-time period.

S207: Convert the non-convex problem model into multiple target time-based convex problem models.

S209: Determine the flight trajectory and beam width of the UAV based on multiple convex problem models.

An optional implementation of converting a non-convex problem model into multiple target time-based convex problem models includes determining multiple target times based on the non-convex problem model; converting the non-convex problem model into multiple target time-based model of the convex problem.

In the embodiment of the present application, the flight trajectory of the drone includes the flight trajectory in the horizontal direction and the flight trajectory in the vertical direction of the drone.

In the embodiment of the present application, the non-convex problem model is converted into a new non-convex problem model based on target time and a monotonic problem based on the new non-convex problem. Using dichotomy for a monotonic problem can determine multiple target times and transform a non-convex problem model based on target time into multiple convex problem models based on target time until the monotonic problem is optimally solved. In this way, the optimal UAV flight trajectory and beam width can be determined, that is, when the UAV is closer to the user, the UAV flies at a lower altitude and the antenna beam width is large. The target time required to transfer a file of the same size is shorter compared to the prior art.

In this embodiment of the present application, establishing a non-convex problem model may be formula (10):

In order to solve the formula (10), the embodiments of the present application introduce two easier-to-handle problems, and then prove that the optimal solution of the formula (10) can be obtained by solving these two new problems. Based on the above application scenario, the ratio of the left-hand throughput to the file data of formula (10) is defined as the ratio, then the first introduced problem is to maximize the minimum ratio between users, which can be expressed as the formula ( 11):

For a given N, let η ^* (N) be the optimal value of equation (11). For any given N, if and only if η ^* (N) ≥ 1, the task is completed, then the target time can be determined according to formula (12):

Obviously N only appears in the upper limit of the summation of formula (11b), so η ^* (N) increases monotonically with respect to N. By using the bisection method, multiple target times are determined until the constraint formula (12b) takes an equal sign.

In order to solve the flight trajectory and beam width of the UAV, formula (11) is equivalently transformed into formula (13):

是关于Θ²[n]和h²[n]+||q[n]-w_k||²的凸函数，如此可以获得该函数在{q_r[n],h_r[n],Θ_r[n]}处的一阶泰勒展开作为下界，即公式(14)：Since Equation (13) is still a non-convex problem, the SCA technique is used here to replace the non-concave term with a global concave lower bound. because

is a convex function with respect to Θ ² [n] and h ² [n]+||q[n]-w _k || ² , so that the function can be obtained in {q _r [n],h _r [n],Θ The first-order Taylor expansion at _r [n]} serves as the lower bound, which is Equation (14):

in,

For a given point {h _r [n],Θ _r [n]}, the global lower bound of (h[n]tanΘ[n]) ² can be determined according to equation (15) as:

in,

According to the SCA principle, formula (13b) is replaced by formula (16):

Further, Equation (16) is transformed into the following SOC constraints:

Therefore, given the points {q _r [n], h _r [n], Θ _r [n]}, Equation (13) can be approximated as Equation (18):

In this way, converting the non-convex problem model into a target time-based convex problem model, Equation (18) is a convex problem, and using a standard convex optimization toolkit such as CVX, the UAV's flight trajectory and beamwidth can be determined.

Simulation experiments are performed below based on the methods proposed in the embodiments of the present application and specific experimental data.

最小波束宽度

无人机最大发射功率P＝0.01W，带宽B＝10MHZ，噪声功率σ²＝2×10^-11W，距离为1时的信道增益β₀＝-50，子时间段间隔δ_t＝0.2s。初始化轨迹q₀[n]为以用户几何中心w_c为圆心，

为半径的圆，其中

初始化高度为h₀[n]∈[h_min,h_max]，初始化波束宽度

For a UAV-assisted multicast communication system, set the number of users to K=6, the maximum UAV flight height _{h max} =250m, the minimum flight height hmin =70m, and the maximum horizontal flight speed _VL =50m/s , the maximum vertical flight speed V _D =20m/s, the maximum beam width

Minimum beam width

The maximum transmit power of the UAV is P=0.01W, the bandwidth B=10MHZ, the noise power σ ² =2×10 ^-11 W, the channel gain β ₀ =-50 when the distance is 1, and the sub-time interval δ _t =0.2s . The initialized trajectory q ₀ [n] takes the user geometric center w _c as the center of the circle,

is a circle of radius, where

Initialize the height as h ₀ [n]∈[h _min ,h _max ], initialize the beam width

Please refer to FIG. 3, FIG. 3(a) is a simulation diagram of the flight trajectory of an unmanned aerial vehicle provided by an embodiment of the present application under D=42Mbits, and FIG. 3(b) is an unmanned aerial vehicle provided by an embodiment of the present application. The simulation diagram of the flight trajectory of the aircraft under D=315Mbits. It can be seen that as D increases, the flight trajectory of the flight expands, and it flies close to the top of the user for better communication quality. Compared with the prior art OMA solution, the UAV in the SO solution proposed in this application dynamically adjusts the height to balance the horizontal trajectory and the beam width, making full use of the spatial freedom.

Please refer to FIG. 4, FIG. 4(a) is a simulation diagram of the height and beam width of a UAV provided by an embodiment of the present application at D=42Mbits, and FIG. 4(b) is a simulation diagram of a drone provided by an embodiment of the present application. Simulation diagram of height and beam width of man-machine at D=315Mbits. It can be seen that when the drone is flying close to some users, the drone is flying at a lower altitude, and the antenna beam width is larger at this time. Otherwise, the drone dynamically adjusts its height and beam width to meet the coverage. Require.

Please refer to FIG. 5. FIG. 5 is a convergence curve diagram of an algorithm provided by an embodiment of the present application. When T=50s, the algorithm based on the method provided by the embodiment of the present application converges after about 9 times, and the speed is fast.

Please refer to FIG. 6. FIG. 6 is a simulation diagram of a task completion time of a different scheme provided by an embodiment of the present application. As shown in FIG. 6 , when files of different sizes are transmitted, the method provided by the embodiment of the present application has different task completion time from the existing solution. It can be seen that the method SO provided by the embodiment of the present application has the fastest time to complete the task.

An embodiment of the present application further provides a device for determining attribute data of an unmanned aerial vehicle. FIG. 7 is a schematic structural diagram of a device for determining attribute data of an unmanned aerial vehicle provided by an embodiment of the present application. As shown in FIG. 7 , the device includes: :

a first determination module 701, used to determine the flight speed range of the UAV, the flight height range, and the beam width of the UAV;

The second determination module 702 is used for determining the coverage conditions of the drone based on the user corresponding to the drone and the data transmission rate of the sub-time period;

The third determination module 703 is configured to establish a non-convex problem model based on the flight speed range, the flight height range, the beam width of the UAV, the coverage conditions and the data transmission rate of the sub-time segment;

a fourth determination module 704, configured to convert the non-convex problem model into a plurality of target time-based convex problem models;

The fifth determination module 705 is used for determining the flight trajectory and beam width of the UAV based on the multiple convex problem models; the sub-time period is a time period within a preset time, and the target time is less than the preset time.

The apparatus and method embodiments in the embodiments of the present application are based on the same concept of the application.

The embodiments of the present application also provide an electronic device, the electronic device includes a processor and a memory, and the memory stores at least one instruction, at least one program, code set or instruction set, at least one instruction, at least one program, code set or The instruction set is loaded and executed by the processor to realize the above determination method of the attribute data of the drone.

Embodiments of the present application further provide a storage medium, where the storage medium can be set in a server to store at least one instruction, at least one section of program, at least one instruction, at least one piece of program, A code set or instruction set, the at least one instruction, the at least one piece of program, the code set or the instruction set is loaded and executed by the processor to implement the above method for determining the attribute data of the drone.

Optionally, in this embodiment, the above-mentioned storage medium may be located in at least one network server among multiple network servers of a computer network. Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic Various media that can store program codes, such as discs or optical discs.

It can be seen from the above-mentioned embodiments of the method, device, electronic device or storage medium for determining the attribute data of the UAV provided by the present application that in the present application, the range of the flight speed, the range of the flight altitude, and the beam of the UAV is determined. Width, determine the coverage conditions of the drone based on the user's coverage conditions and the data transmission rate of the sub-time period, and based on the flight speed range, flight height range, the beam width of the drone, coverage conditions and data transmission in the sub-time period The rate establishes a non-convex problem model, converts the non-convex problem model into a target time-based convex problem model, and determines the UAV's flight trajectory and beam width. The method for UAV attribute data provided in this application can minimize the UAV by adjusting the UAV's flight trajectory and antenna beam width under the condition that the UAV's flight speed, height, and antenna beam width are limited. The completion time of the transfer task.

It should be noted that: the above-mentioned order of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that in the embodiments and still achieve desirable results. Additionally, the processes depicted in the figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and reference may be made to the partial descriptions of the method embodiments for related parts.

Those of ordinary skill in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. The storage medium mentioned may be a read-only memory, a magnetic disk or an optical disk, etc.

The above descriptions are only preferred embodiments of the present application, and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection of the present application. within the range.

Claims (10)

1. a determination method of UAV attribute data, is characterized in that, comprises: Determining the flight speed range of the UAV, the flight altitude range, and the beam width of the UAV; Determine the data transmission rate of the drone based on the coverage conditions of the user corresponding to the drone and the sub-time period; Establish a non-convex problem model based on the flight speed range, the flight height range, the beam width of the UAV, the coverage conditions and the data transmission rate of the sub-time period; converting the non-convex problem model into a plurality of target time-based convex problem models; determining the flight path and beam width of the UAV based on a plurality of the convex problem models; The sub-time period is a time period within a preset time period, and the target time period is less than the preset time period. 2. The method according to claim 1, wherein the determining of the UAV is based on the coverage conditions of the user corresponding to the UAV, comprising: determining the user location of the user corresponding to the drone; determining the flight level position of the drone; The coverage condition is determined based on the user position, the flight level position, the flight altitude range, and the beamwidth. 3. The method according to claim 2, wherein the determining the data transmission rate of the sub-time period comprises: determining the channel power gain at the first reference distance; determining channel power gains for the UAV and the user based on the channel power gain, the user position, the flight level position, and the flight altitude range; The data transmission rate of the sub-period is determined according to the channel bandwidth, the channel power gain, the transmission power of the UAV and the power of white Gaussian noise. 4. The method according to claim 1, wherein the converting the non-convex problem model into a plurality of target time-based convex problem models comprises: determining a plurality of the target times based on the non-convex problem model; Transforming the non-convex problem model into a plurality of convex problem models based on the target time. 5. A device for determining the attribute data of an unmanned aerial vehicle, comprising: a first determination module, used to determine the flight speed range of the UAV, the flight height range, and the beam width of the UAV; a second determining module, configured to determine the data transmission rate of the drone based on the coverage conditions of the user corresponding to the drone and the sub-time period; A third determination module, configured to establish a non-convex problem model based on the flight speed range, the flight height range, the beam width of the UAV, the coverage condition and the data transmission rate of the sub-time period; a fourth determination module for converting the non-convex problem model into a plurality of target time-based convex problem models; a fifth determination module, configured to determine the flight trajectory and beam width of the UAV based on the plurality of convex problem models; The sub-time period is a time period within a preset time period, and the target time period is less than the preset time period. 6. The device of claim 5, wherein: The second determining module is further configured to determine the user position of the user corresponding to the drone; determine the flight level position of the drone; based on the user position, the flight level position, the flight height range and the The beamwidth determines the coverage condition. 7. The device of claim 5, wherein The second determination module is further configured to determine the channel power gain at the first reference distance; determine the UAV based on the channel power gain, the user position, the flight level position and the flight altitude range and the channel power gain of the user; the data transmission rate of the sub-period is determined according to the channel bandwidth, the channel power gain, the transmission power of the UAV and the power of white Gaussian noise. 8. The device of claim 5, wherein: The fourth determination module is further configured to determine a plurality of the target times based on the non-convex problem model; and convert the non-convex problem model into a plurality of convex problem models based on the target time. 9. An electronic device, characterized in that the electronic device comprises a processor and a memory, and the memory stores at least one instruction, at least a piece of program, a code set or an instruction set, the at least one instruction, the at least one A program, the code set or the instruction set is loaded and executed by the processor to implement the method for determining the attribute data of the drone according to any one of claims 1-4. 10. A computer-readable storage medium, wherein the storage medium stores at least one instruction, at least one piece of program, code set or instruction set, the at least one instruction, the at least one piece of program, the code The set or instruction set is loaded and executed by the processor to implement the method for determining the attribute data of the drone according to any one of claims 1-4.

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