Unmanned aerial vehicle flight altitude performance evaluation method, device, equipment and storage medium

Abstract

The application discloses a kind of unmanned aerial vehicle flight height performance evaluation method, device, equipment and storage medium, wherein the method includes steps: obtaining the flight data of unmanned aerial vehicle at different heights under different wind speeds;Based on the flight data, the deviation rate and fluctuation value of unmanned aerial vehicle flight at each height under different wind speeds are calculated;Through the deviation rate and fluctuation value, the stability index of unmanned aerial vehicle flight at each height under different wind speeds is calculated, and the stability of the flight height maintaining performance of unmanned aerial vehicle under different wind speeds is evaluated based on the stability index.The application can quantitatively evaluate the height maintaining performance of unmanned aerial vehicle at different heights, and more comprehensively and carefully understand the stability of unmanned aerial vehicle height control.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) performance testing technology, and in particular to a method, apparatus, equipment, and storage medium for evaluating the flight altitude performance of UAVs. Background Technology

[0002] With the increasingly widespread application of drones, they play a vital role in numerous fields such as agricultural plant protection, logistics delivery, aerial photography, and geographic surveying. In these applications, the altitude-keeping performance of drones is a key indicator, affecting mission execution quality and safety. Actual drone flight is affected by various factors, with wind speed being a significant external factor. Altitude fluctuations under different wind speeds impact altitude-keeping performance. Therefore, accurately assessing the altitude-keeping performance of drones under different wind speeds is crucial for design optimization and flight control strategy development. While some current drone flight performance evaluation methods exist, they often rely on single indicators and lack a systematic consideration of the impact of wind speed, making it difficult to comprehensively reflect the actual performance of drones in complex environments.

[0003] Therefore, accurately assessing the altitude-keeping performance of drones in complex environments is a pressing technical problem that needs to be solved. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, device, and storage medium for evaluating the flight altitude performance of unmanned aerial vehicles (UAVs), which can quantitatively evaluate the altitude-keeping performance of UAVs at different altitudes and provide a more comprehensive and detailed understanding of the stability of UAV altitude control.

[0005] In a first aspect, this application provides a method for evaluating the flight altitude performance of an unmanned aerial vehicle (UAV), wherein the method includes the following steps: Acquire flight data of the drone at different altitudes under different wind speeds; Based on the flight data, the deviation rate and fluctuation value of the UAV at different altitudes under different wind speeds are calculated; Using the deviation rate and fluctuation value, the stability index of the UAV at different altitudes under different wind speeds is calculated, and the stability index is used to evaluate the stability of the UAV's altitude maintenance performance under different wind speeds.

[0006] In conjunction with the first aspect mentioned above, as an optional implementation method, based on the stability index of the UAV at different altitudes obtained under different wind speeds, the relationship between wind speed and stability index is fitted as a function. The function is used to predict the stability index of the UAV under different wind speeds.

[0007] In conjunction with the first aspect mentioned above, as an optional implementation method, the relationship between wind speed and stability index is fitted as a linear function, the expression of which is: = ×(1- * ),in, The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

[0008] In conjunction with the first aspect mentioned above, as an optional implementation method, the relationship between wind speed and stability index is fitted to an exponential function, the expression of which is: = × ,in The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

[0009] In conjunction with the first aspect mentioned above, as an optional implementation method, the drone is controlled to fly at multiple set target altitudes under different wind speed conditions, and the actual flight data is recorded, including: flight altitude, flight speed, flight time and wind speed. The acquired flight data is processed to obtain different flight altitude data. This processing includes: after reaching each target altitude, horizontal flight is maintained for a set time; and after the set time has elapsed, flight altitude data within a set range is extracted. .

[0010] In conjunction with the first aspect mentioned above, as an optional implementation method, according to the formula: *100%, calculate the deviation rate of UAV flight at different altitudes under different wind speeds, where For the first The first target height intercepted One flight altitude data, The target flight altitude is set; According to the formula: The fluctuation values ​​of the UAV flight at different altitudes under different wind speeds were calculated.

[0011] In conjunction with the first aspect mentioned above, as an optional implementation method, according to the formula: To determine the stability index of UAVs flying at different altitudes under different wind speeds; According to the formula: To determine the stability index of drone flight under different wind speeds.

[0012] Secondly, this application provides a device for evaluating the flight altitude performance of a drone, the device comprising: The acquisition module is used to acquire flight data of the drone at different altitudes under different wind speeds; The calculation module is used to calculate the deviation rate and fluctuation value of the UAV at different altitudes under different wind speeds based on the flight data. The evaluation module is used to determine the stability index of the UAV flight at different altitudes under different wind speeds by using the deviation rate and fluctuation value, and to evaluate the stability of the UAV's flight altitude maintenance performance under different wind speeds based on the stability index.

[0013] Thirdly, this application also provides an electronic device, the electronic device comprising: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the method described in any one of the first aspects.

[0014] Fourthly, this application also provides a computer-readable storage medium storing computer program instructions that, when executed by a computer, cause the computer to perform the method described in any of the first aspects.

[0015] This application provides a method, apparatus, device, and storage medium for evaluating the flight altitude performance of a drone. The method includes the following steps: acquiring flight data of the drone at different altitudes under different wind speeds; calculating the deviation rate and fluctuation value of the drone's flight at each altitude under different wind speeds based on the flight data; calculating the stability index of the drone's flight at each altitude under different wind speeds using the deviation rate and fluctuation value; and evaluating the stability of the drone's altitude-keeping performance under different wind speeds based on the stability index. This application can quantitatively evaluate the altitude-keeping performance of a drone at different altitudes, providing a more comprehensive and detailed understanding of the stability of drone altitude control.

[0016] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit the invention. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] Figure 1 This is a flowchart of the UAV flight altitude performance evaluation method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the UAV flight altitude performance evaluation method provided in the embodiments of this application; Figure 3This is a schematic diagram of flight data acquisition provided in the embodiments of this application; Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of this application; Figure 5 This is a schematic diagram of a computer-readable program medium provided in an embodiment of this application. Detailed Implementation

[0019] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0020] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the drawings represent functional entities and do not necessarily correspond to physically or logically independent entities.

[0021] The embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0022] Reference Figure 1 , Figure 1 The diagram shown is a flowchart of a method for evaluating the flight altitude performance of a UAV provided by the present invention. Figure 1 As shown, the method includes the following steps: Step S101: Obtain flight data of the drone at different altitudes under different wind speeds.

[0023] Specifically, under different wind speed conditions, the drone is controlled to fly at multiple set target altitudes and the actual flight data is recorded, including: flight altitude, flight speed, flight time and wind speed. The acquired flight data is processed to obtain different flight altitude data. This processing includes: after reaching each target altitude, horizontal flight is maintained for a set time; and after the set time has elapsed, flight altitude data within a set range is extracted. (See details) Figure 3 illustrate) Step S102: Based on the flight data, calculate the deviation rate and fluctuation value of the UAV flight at different altitudes under different wind speeds.

[0024] Specifically, according to the formula: *100%, calculate the deviation rate of UAV flight at different altitudes under different wind speeds, where For the first The first target height intercepted One flight altitude data, The target flight altitude is set; According to the formula: The fluctuation values ​​of the UAV flight at different altitudes under different wind speeds were calculated.

[0025] For ease of understanding, here's an example illustrating the deviation rate at a single elevation point: *100%, calculates the relative deviation between the actual height and the target height.

[0026] Fluctuations at a single height point: Record the maximum deviation range of the actual height within ±5% of the target height (e.g., 50 meters corresponds to 47.5 meters to 52.5 meters).

[0027] It's important to explain that multiple altitude points are collected at different wind speeds. The calculation here focuses on the deviation rate and fluctuation value of a single altitude point under different wind speeds. Based on these deviation rates and fluctuation values, the stability index for that single altitude point is calculated. Summing these multiple stability indices yields the flight altitude maintenance stability index for different wind speeds. For example, if the wind speed is 0 m / s, multiple altitude points are collected, and the deviation rate and fluctuation value for each point are calculated to obtain the stability index for a wind speed of 0 m / s.

[0028] Step S103: Calculate the stability index of the UAV at different altitudes under different wind speeds using the deviation rate and fluctuation value, and evaluate the stability of the UAV's altitude maintenance performance under different wind speeds based on the stability index.

[0029] Specifically, according to the formula: To determine the stability index of UAVs flying at different altitudes under different wind speeds; According to the formula: To determine the stability index of drone flight under different wind speeds.

[0030] For ease of understanding, here's an example illustrating the stability index at a single elevation point: By combining the deviation rate and the fluctuation range, the stability index at that altitude point is calculated.

[0031] Stability index at a certain wind speed: Based on the stability index at different altitudes, calculate the average value.

[0032] In one embodiment, based on the stability index of the UAV at different altitudes under different wind speeds, the relationship between wind speed and stability index is fitted into a function; the stability index of the UAV under different wind speeds is then predicted using the function (it can be understood that the fitting objective 1 is to cover the stability index under the influence of wind speed. 2 is to achieve rapid prediction. In addition, the higher the calculated stability index, the more stable the flight performance).

[0033] Specifically, the relationship between wind speed and stability index is fitted as a linear function, and its expression is: = ×(1- * ),in, The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

[0034] Optionally, the relationship between wind speed and stability index can be fitted as an exponential function, the expression of which is: = × ,in The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

[0035] For ease of understanding, examples are given to test the drone's altitude-keeping performance under different wind speeds (e.g., 0 m / s, 2 m / s, 5 m / s, 10 m / s). Wind speed ( )and The relationship is fitted to a function, and the following two methods are available for selection.

[0036] Method 1: Linear Model = ×(1- * ),in, The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient. For example, through fitting, the model is: =1.00×(1-0.08 ).

[0037] Method 2: Exponential Model: The relationship between wind speed and stability index is fitted to an exponential function, the expression of which is: = × ,in The stability index is given by the wind speed. Wind speed The stability index at 0 m / s Let be the wind speed influence coefficient. For example, through fitting, the model is: where =1.00× , It should be explained that the wind speed influence coefficient is determined based on the fitted relationship between wind speed and stability index. Taking Method 1 as an example: using the data in Table 1 as an example.

[0038] Table 1

[0039] Will and Substituting into method 1, we can calculate ,in For a fixed value, the calculated Rounding to the nearest whole number, we get 0.08 (when...). =2, Stability index = 0.85, 0.85 = 1.00 × (1 - ×2), solving for , we get =0.075≈0.08).

[0040] The above model can be used to quickly predict the stability index of a drone at any wind speed, thereby further understanding the drone's altitude-keeping performance.

[0041] For example, if you want to obtain the stability index of a drone at a wind speed of 7 m / s, you would use a linear model. =1.00×(1-0.08 = 1.00 × (1 - 0.08 × 7) = 0.44 In summary, the beneficial effects of this application include: 1) By calculating indicators such as deviation rate, fluctuation range and stability index, the altitude holding performance of UAV at different altitudes can be quantitatively evaluated, which can provide a comprehensive and detailed understanding of the stability of UAV altitude control.

[0042] 2) The stability index under different wind speeds was considered. Based on the test data under different wind speed conditions, the altitude holding performance of the UAV under any wind speed was comprehensively evaluated, making the evaluation results more valuable for practical applications.

[0043] 3) The relationship between wind speed and stability index is fitted using both linear and exponential models, providing a scientific and reasonable method for predicting the stability index of UAVs under different wind speeds (the established model is used to predict the stability index of UAVs under any wind speed, providing an important reference for adjusting UAV control strategies and optimizing performance, and helping users better understand the performance of UAVs under different environmental conditions).

[0044] 4) Determine the wind speed influence coefficient through experimental data fitting, so that the fitted function can accurately reflect the influence of wind speed on the drone's altitude-keeping performance. Reference Figure 2 , Figure 2 The diagram shown is a schematic of a drone flight altitude performance evaluation device provided by the present invention. Figure 2 As shown, the device includes: Acquisition module 201: It is used to acquire flight data of the UAV at different altitudes under different wind speeds.

[0045] Calculation module 202: It is used to calculate the deviation rate and fluctuation value of the UAV flight at different altitudes under different wind speeds based on the flight data.

[0046] Evaluation module 203: It is used to determine the stability index of the UAV flight at different altitudes under different wind speeds by using the deviation rate and fluctuation value, and to evaluate the stability of the UAV's flight altitude maintenance performance under different wind speeds based on the stability index.

[0047] Furthermore, in one possible implementation, the evaluation module is also used to fit the relationship between wind speed and stability index as a function based on the stability index of the UAV at different altitudes obtained under different wind speeds. The function is used to predict the stability index of the UAV under different wind speeds.

[0048] Furthermore, in one possible implementation, the evaluation module is also used to fit a linear function based on the relationship between wind speed and the stability index, the expression of which is: = ×(1- * ),in, The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

[0049] Furthermore, in one possible implementation, the evaluation module is also used to fit an exponential function based on the relationship between wind speed and the stability index, the expression of which is: = × ,in The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

[0050] Furthermore, in one possible implementation, the acquisition module is also used to control the drone to fly at multiple set target altitudes under different wind speed conditions, and record actual flight data, including: flight altitude, flight speed, flight time and wind speed; The acquired flight data is processed to obtain different flight altitude data. This processing includes: after reaching each target altitude, horizontal flight is maintained for a set time; and after the set time has elapsed, flight altitude data within a set range is extracted. .

[0051] Furthermore, in one possible implementation, the calculation module is also used to calculate according to the formula: *100%, calculate the deviation rate of UAV flight at different altitudes under different wind speeds, where For the first The first target height intercepted One flight altitude data, The target flight altitude is set; According to the formula: The fluctuation values ​​of the UAV flight at different altitudes under different wind speeds were calculated.

[0052] Furthermore, in one possible implementation, the evaluation module is also used to evaluate according to the formula: To determine the stability index of UAVs flying at different altitudes under different wind speeds; According to the formula: To determine the stability index of drone flight under different wind speeds.

[0053] Reference Figure 3 , Figure 3 The diagram shown is a schematic representation of flight data acquisition provided by the present invention. Figure 3 As shown: At a specific wind speed (e.g., 0 m / s, 2 m / s, 5 m / s, 10 m / s), a flight path is set containing i altitude points Hi (e.g., selecting H1 (50 meters), H2 (100 meters), H3 (150 meters)). After reaching each altitude point, the aircraft flies horizontally for 30 seconds (selecting altitude points within a specified speed range). Data Hij is collected within each altitude point, where the altitude falls within the range of (0.95Hi, 1.05Hi) (e.g., obtaining 300 altitude data points). The altitude data from 0.95Hi to 1.05Hi represents 95% to 105% of the target altitude. See the diagram where H1, H2, and H3 represent the set target altitudes, and V1 represents 30 seconds of horizontal flight. Altitude data within V1 is captured during this time, i.e., multiple altitude points are captured within V1. Upon reaching H2, the aircraft flies horizontally for 30 seconds and then captures data from V2. Upon reaching H3, the aircraft flies horizontally for 30 seconds and then captures data from V3. The flight from H1 to H3 constitutes a complete flight process. Multiple altitude data points are obtained from V1, V2, and V3, representing multiple altitude points.

[0054] Flight data is acquired at different wind speeds, specifically at speeds of 0 m / s, 2 m / s, 5 m / s, and 10 m / s, where the height data from H1 to H3 is obtained respectively.

[0055] For example, in a wind speed scenario of 0 m / s, the deviation rate and fluctuation value at a single altitude point are calculated. Then, using the deviation rate and fluctuation value, the stability index at that single altitude point is calculated. The sum of the stability indices calculated for multiple single altitude points yields the drone's flight altitude maintenance stability index in a wind speed scenario of 0 m / s. This index is used to evaluate stability performance. The same principle applies to wind speeds of 2 m / s, 5 m / s, 10 m / s, etc.

[0056] This application can effectively quantify the relative impact of altitude deviation (such as the difference between a 3-meter altitude deviation at 50 meters and a 5-meter altitude deviation at 150 meters), and can provide a comprehensive and detailed understanding of the stability of UAV altitude control.

[0057] The following reference Figure 4 To describe an electronic device 400 according to this embodiment of the present invention. Figure 4 The electronic device 400 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0058] like Figure 4 As shown, the electronic device 400 is manifested in the form of a general-purpose computing device. The components of the electronic device 400 may include, but are not limited to: at least one processing unit 410, at least one storage unit 420, and a bus 430 connecting different system components (including storage unit 420 and processing unit 410).

[0059] The storage unit stores program code that can be executed by the processing unit 410, causing the processing unit 410 to perform the steps described in the "Embodiment Methods" section of this specification according to various exemplary embodiments of the present invention.

[0060] Storage unit 420 may include readable media in the form of volatile storage units, such as random access memory (RAM) 421 and / or cache memory 422, and may further include read-only memory (ROM) 423.

[0061] Storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0062] Bus 430 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0063] Electronic device 400 can also communicate with one or more external devices (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 400, and / or any device that enables electronic device 400 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 450. Furthermore, electronic device 400 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 460. As shown, network adapter 460 communicates with other modules of electronic device 400 via bus 430. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0064] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0065] According to the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0066] refer to Figure 5 As shown, a program product 500 for implementing the above-described method according to an embodiment of the present invention is described. It may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0067] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0068] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0069] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0070] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0071] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0072] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

[0073] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

Claims

1. A method for evaluating the flight altitude performance of an unmanned aerial vehicle (UAV), characterized in that, include: Acquire flight data of the drone at different altitudes under different wind speeds. Specifically, under different wind speed conditions, control the drone to fly at multiple set target altitudes and record the actual flight data, including: flight altitude, flight speed, flight time and wind speed. The acquired flight data is processed to obtain different flight altitude data. This processing includes: after reaching each target altitude, horizontal flight is maintained for a set time; and after the set time has elapsed, flight altitude data within a set range is extracted. ; Based on the flight data, the deviation rate and fluctuation value of the UAV at different altitudes under different wind speeds are calculated; Using the deviation rate and fluctuation value, the stability index of the UAV flight at different altitudes under different wind speeds is calculated, and the stability of the UAV's flight altitude maintenance performance under different wind speeds is evaluated based on the stability index. Among them, based on the stability index of the drone at different altitudes under different wind speeds, the relationship between wind speed and stability index is fitted as a function; The function is used to predict the stability index of the UAV under different wind speeds.

2. The method according to claim 1, characterized in that, The process of fitting the relationship between wind speed and stability index into a function includes: Based on the relationship between wind speed and stability index, a linear function is fitted, and its expression is: = ×(1 * ),in, The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

3. The method according to claim 1, characterized in that, Also includes: The relationship between wind speed and stability index is fitted to an exponential function, the expression of which is: = × ,in The stability index is given by the wind speed. Wind speed The stability index at 0 m / s This represents the wind speed influence coefficient.

4. The method according to claim 1, characterized in that, The calculation of the deviation rate and fluctuation value of the UAV flight at different altitudes under different wind speeds based on the flight data includes: According to the formula: *100%, calculate the deviation rate of UAV flight at different altitudes under different wind speeds, where For the first The first target height intercepted One flight altitude data, The target flight altitude is set; According to the formula: The fluctuation values ​​of the UAV flight at different altitudes under different wind speeds were calculated.

5. The method according to claim 1, characterized in that, The calculation of the stability index of the UAV at different altitudes under different wind speeds, using the deviation rate and fluctuation value, includes: According to the formula: To determine the stability index of UAVs flying at different altitudes under different wind speeds; According to the formula: To determine the stability index of drone flight under different wind speeds.

6. A UAV flight altitude performance evaluation device for implementing the UAV flight altitude performance evaluation method as described in any one of claims 1-5, characterized in that, include: The acquisition module is used to acquire flight data of the drone at different altitudes under different wind speeds. Under different wind speed conditions, the drone is controlled to fly at multiple set target altitudes and the actual flight data is recorded, including: flight altitude, flight speed, flight time and wind speed. The acquired flight data is processed to obtain different flight altitude data. This processing includes: after reaching each target altitude, horizontal flight is maintained for a set time; and after the set time has elapsed, flight altitude data within a set range is extracted. ; The calculation module is used to calculate the deviation rate and fluctuation value of the UAV at different altitudes under different wind speeds based on the flight data. The evaluation module is used to determine the stability index of the UAV flight at different altitudes under different wind speeds by using the deviation rate and fluctuation value, and to evaluate the stability of the UAV's flight altitude maintenance performance under different wind speeds based on the stability index. The evaluation module is also used to fit the relationship between wind speed and stability index as a function based on the stability index of the drone at different altitudes obtained from testing under different wind speeds. The function is used to predict the stability index of the UAV under different wind speeds.

7. An electronic device, characterized in that, The electronic device includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, It stores computer program instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 5.

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