Unmanned aerial vehicle flight control data acquisition control system and method based on intelligent sensor

Abstract

The invention discloses an unmanned aerial vehicle flight control data acquisition control system and method based on an intelligent sensor, and relates to the technical field of unmanned aerial vehicle flight control. Operation environment data in airspace operation of an unmanned aerial vehicle is imported into an operation environment state analysis strategy of the unmanned aerial vehicle, and an unmanned aerial vehicle environment real-time adaptation index is calculated and obtained; establishing an unmanned aerial vehicle kinematic model in the airspace operation of the unmanned aerial vehicle, inputting the flight behavior mode data in the airspace operation of the unmanned aerial vehicle into the unmanned aerial vehicle kinematic model, and outputting a flight state response index of the unmanned aerial vehicle, and inputting the unmanned aerial vehicle environment real-time adaptation index and the flight state response index into a maneuvering strategy decision analysis model of the unmanned aerial vehicle, evaluating the airspace operation environment influence weight of the unmanned aerial vehicle, and outputting a behavior regulation and control strategy for the unmanned aerial vehicle under the current airspace operation. And the flight stability and safety of the unmanned aerial vehicle under airspace operation are obviously improved.

Description

Technical Field

[0001] This application belongs to the field of UAV flight control, specifically a UAV flight control data acquisition control system and method based on intelligent sensors. Background Art

[0002] With the rapid development of technology, UAVs play an increasingly important role. Due to their high concealment and flexibility, they can perform tasks without revealing their positions and were first applied in the military field. The most traditional UAV control method is manual remote control, where the operator uses the remote control to directly control the flight direction, speed, altitude, etc. of the UAV through wireless signals. Currently, UAVs are usually equipped with an automatic flight control system that automatically controls the flight path according to a pre-set flight plan to ensure that the UAV flies along a predetermined route. However, when current UAVs are flying, they are affected by environmental factors such as sudden changes in wind speed and air pressure. Due to insufficient response time of the control system, they do not have a flexible response ability and cannot adjust the flight strategy in real time according to different UAV flight environments, reducing the flight stability and safety of the UAV. To solve the problems raised in this background art, this application designs a UAV flight control data acquisition control system and method based on intelligent sensors. Summary of the Invention

[0003] In view of the above technical deficiencies, this application proposes a UAV flight control data acquisition control system and method based on intelligent sensors.

[0004] To solve the above technical problems, the present invention adopts the following technical solutions: This application provides a UAV flight control data acquisition control method based on intelligent sensors, which includes the following specific steps:

[0005] S1. Record the operation environment data and flight behavior pattern data during the UAV's airspace operation in real time;

[0006] S2. Import the operation environment data during the UAV's airspace operation into the operation environment state analysis strategy of the UAV, and calculate and obtain the real-time UAV environment adaptation index;

[0007] S3. Establish a UAV kinematic model during the UAV's airspace operation, input the flight behavior pattern data during the UAV's airspace operation into the UAV kinematic model, and output the UAV's flight state response index;

[0008] S4. Input the real-time UAV environment adaptation index and the flight state response index into the UAV's maneuver strategy decision analysis model, evaluate the weight of the impact of the UAV's airspace operation environment, and output the behavior regulation strategy for the UAV under the current airspace operation.

[0009] It should be noted that as an optimal technical solution of the UAV flight control data acquisition control system and method based on intelligent sensors, the specific steps of S1 are as follows:

[0010] S11. Obtain the operation environment data during the UAV's airspace operation through sensors, where the operation environment data includes environmental wind data, pressure data, and altitude data;

[0011] S12. Obtain the flight behavior pattern data during the UAV's airspace operation through a gyroscope, where the flight behavior pattern data includes roll angle data, pitch angle data, and yaw angle data;

[0012] S13. Store the collected data in the storage component for use in the analysis process.

[0013] It should be noted that as an optimal technical solution of the UAV flight control data acquisition control system and method based on intelligent sensors, S2 includes the following specific steps:

[0014] S21. Obtain the environmental wind data of the UAV's airspace operation in the data unit time, and obtain the environmental interference evaluation value of the UAV's airspace operation in the data unit time from the environmental wind data of the UAV's airspace operation in the data unit time;

[0015] S22. Obtain the flight pressure data and flight altitude data of the UAV's airspace operation in the data unit time, and obtain the air pressure interference evaluation value of the UAV's airspace operation in the data unit time from the flight pressure data and flight altitude data of the UAV's airspace operation in the data unit time;

[0016] S23. Analyze based on the results of the environmental wind interference evaluation value and the air pressure interference evaluation value of the UAV's airspace operation in the data unit time to obtain the real-time environmental adaptation index of the UAV in the data unit time.

[0017] It should be noted that as an optimal technical solution of the UAV flight control data acquisition control system and method based on intelligent sensors, the specific steps of S21 are as follows: Import the environmental wind data in the data unit time into the environmental wind interference evaluation value calculation formula to calculate the environmental wind interference evaluation value of the UAV's airspace operation in the data unit time. Among them, the environmental wind interference evaluation value calculation formula is: Among them, i is the number corresponding to each data unit time, and i is any one of 1 to N, ρ i is the air density in the UAV's airspace operation in the i-th data unit time, is the velocity vector in the UAV's airspace operation in the i-th data unit time, C w,i is the lift coefficient in the UAV's airspace operation in the i-th data unit time, S is the reference area of the UAV wing, cos(θ i) is the angle between the wind and the flight direction of the drone during airspace operations, F wind is the reference value of the set wind speed influence. It should be noted that in this formula is the sum of the velocity vector of the drone's airspace operation relative to the ground and the wind speed vector in the data unit time, ρ i is the ratio of the air pressure to the product of the gas constant and temperature during the drone's airspace operation in the data unit time. By comprehensively evaluating the relationship between air density, velocity vector, lift coefficient, wing reference area, and the angle between the wind and the drone's flight direction, the relationship between the actual wind speed influence and the reference wind speed influence during the drone's airspace operation is obtained, and then the environmental wind interference evaluation value during the drone's airspace operation in the data unit time is obtained.

[0018] It should be noted that as an optimal technical solution of the drone flight control data acquisition control system and method based on intelligent sensors, the S22 includes the following specific steps: Import the pressure data and altitude data of the drone's airspace operation in the data unit time into the air pressure interference evaluation value calculation formula to calculate the air pressure interference evaluation value during the drone's airspace operation in the data unit time. Among them, the air pressure interference evaluation value calculation formula is: Among them, P0 is the sea-level air pressure, L i is the temperature lapse rate during the drone's airspace operation in the data unit time, h i is the flight altitude during the drone's airspace operation in the data unit time, T 0,i is the sea-level temperature during the drone's airspace operation in the data unit time, g0 is the acceleration due to gravity, M is the molar mass of air, R is the gas constant, P h is the reference pressure at the altitude h during the drone's airspace operation in the data unit time, ΔP is the allowable pressure change value during the drone's airspace operation. It should be noted that in this formula By comprehensively analyzing the influence of temperature and altitude on the drone's airspace operation through the temperature lapse rate and the ratio of flight altitude to sea-level temperature in the data unit time, As the exponential part in this formula, it determines the degree of air pressure drop as the drone's flight altitude increases. A higher exponential value means a faster air pressure drop, while a lower exponential value indicates a slower air pressure drop. That is, the larger the exponential value, the faster the air pressure drops, and the smaller the exponential value, the slower the air pressure drops.

[0019] It should be noted that as an optimal technical solution of the drone flight control data acquisition control system and method based on intelligent sensors, the S23 includes the following steps: Add the weighted environmental wind interference evaluation value and air pressure interference evaluation value of the drone's airspace operation in the calculated data unit time to obtain the real-time adaptation index of the drone environment.

[0020] It should be noted that, as an optimal technical solution of the UAV flight control data acquisition control system and method based on intelligent sensors, S3 includes the following steps:

[0021] S31. Obtain the roll angle data, pitch angle data, and yaw angle data of the UAV's airspace operation per unit time of data;

[0022] S32. Import the roll angle data, pitch angle data, and yaw angle data of the UAV's airspace operation per unit time of data into the UAV flight state response index calculation formula to calculate the UAV flight state response index per unit time of data. Among them, the flight state response index calculation formula is: where t is the per unit time of data, α 1,i (t) is the roll angle at the t-th moment of the i-th per unit time interval t of data, α 2,i (t) is the pitch angle at the t-th moment of the i-th per unit time interval t of data, α 3,i (t) is the yaw angle at the t-th moment of the i-th per unit time interval t of data, dt is the integration over the per unit time of data. It should be noted that the lower the flight state response index, that is, the lower the change amount of the UAV flight attitude per unit time of data, the higher the flight stability. In this formula, the acquisition methods of the roll angle data, pitch angle data, and yaw angle data are: obtaining the roll angle data, pitch angle data, and yaw angle data from the UAV gyroscope.

[0023] It should be noted that, as an optimal technical solution of the UAV flight control data acquisition control system and method based on intelligent sensors, the specific steps of S4 are:

[0024] S41. Import the UAV environmental real-time adaptation index and flight state response index per unit time of data into the airspace operation environment impact assessment value calculation formula to calculate the airspace operation environment impact assessment value of the UAV per unit time of data. Among them, the airspace operation environment impact assessment value calculation formula is: where ε i is the environmental real-time adaptation index of the UAV during airspace operation in the i-th per unit time of data, ε is the standard value of the environmental real-time adaptation index of the UAV during airspace operation, Δε is the allowable fluctuation value of the environmental real-time adaptation index of the UAV during airspace operation, γ is the standard flight state response index of the UAV during airspace operation, c is the proportion weight corresponding to the UAV environmental real-time adaptation index. It should be noted that this formula comprehensively analyzes the airspace operation environment impact weight of the UAV by combining the UAV environmental real-time adaptation index and flight state response index, improving the accuracy of flight control during the UAV's airspace operation;

[0025] S42. Dynamically control the flight speed of the UAV during airspace operation according to the calculated airspace operation environment impact assessment value of the UAV per unit time of data.

[0026] The UAV flight control data acquisition and control system based on intelligent sensors is implemented based on the above-mentioned UAV flight control data acquisition and control method based on intelligent sensors, and specifically includes an airspace operation data acquisition module, an operation environment state analysis module, a flight state response output module, and a maneuver strategy decision output module. Among them, the airspace operation data acquisition module is used to record the operation environment data and flight behavior pattern data in the UAV airspace operation in real time;

[0027] The operation environment state analysis module is used to import the operation environment data in the UAV airspace operation into the operation environment state analysis strategy of the UAV, and calculate and obtain the real-time environmental adaptation index of the UAV;

[0028] The flight state response output module is used to establish a kinematic model of the UAV in the UAV airspace operation, input the flight behavior pattern data in the UAV airspace operation into the kinematic model of the UAV, and output the flight state response index of the UAV;

[0029] The maneuver strategy decision output module is used to input the real-time environmental adaptation index and flight state response index of the UAV into the maneuver strategy decision analysis model of the UAV, evaluate the influence weight of the UAV airspace operation environment, and output the behavior regulation strategy for the UAV under the current airspace operation.

[0030] An electronic device includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory;

[0031] The processor executes the above-mentioned UAV flight control data acquisition and control method based on intelligent sensors by calling the computer program stored in the memory.

[0032] A computer-readable storage medium stores instructions. When the instructions run on a computer, the computer executes the above-mentioned UAV flight control data acquisition and control method based on intelligent sensors.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention records in real time the operation environment data and flight behavior pattern data in the unmanned aerial vehicle (UAV) airspace operation, imports the operation environment data in the UAV airspace operation into the operation environment state analysis strategy of the UAV, calculates and obtains the real-time UAV environment adaptation index, establishes the kinematic model of the UAV in the UAV airspace operation, inputs the flight behavior pattern data in the UAV airspace operation into the kinematic model of the UAV, outputs the flight state response index of the UAV, inputs the real-time UAV environment adaptation index and the flight state response index into the maneuver strategy decision analysis model of the UAV, evaluates the influence weight of the UAV airspace operation environment, and outputs the behavior regulation strategy for the UAV under the current airspace operation. By real-time regulating the UAV under the airspace operation, the flight stability and safety of the UAV under the airspace operation are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Other features, objects, and advantages of the present application will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings;

[0035] Figure 1 It is a schematic diagram of the overall process of the UAV flight control data acquisition and control method based on intelligent sensors of the present application.

[0036] Figure 2 It is a schematic diagram of the process of step S2 of the UAV flight control data acquisition and control method based on intelligent sensors of the present application.

[0037] Figure 3 It is a schematic diagram of the overall framework of the UAV flight control data acquisition and control system based on intelligent sensors of the present application.

[0038] Figure 4 It is a diagram of the implementation scenario of the present application DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] To better understand the present application, more detailed descriptions of various aspects of the present application will be made with reference to the accompanying drawings. It should be understood that these detailed descriptions are only descriptions of the exemplary embodiments of the present application and do not limit the scope of the present application in any way. Throughout the specification, the same reference numerals refer to the same elements. The expression "and / or" includes any and all combinations of one or more of the associated listed items.

[0040] In the accompanying drawings, for the sake of convenience in illustration, the sizes, dimensions and shapes of the elements have been slightly adjusted. The accompanying drawings are only examples and are not drawn to an exact scale. As used herein, terms such as "substantially", "about" and similar terms are used as terms indicating approximation, rather than terms indicating degree, and are intended to illustrate the inherent deviations in measured or calculated values that would be recognized by those of ordinary skill in the art. Additionally, in this application, the order of description of the various step processes does not necessarily represent the order in which these processes occur in actual operation, unless there are clear other limitations or can be deduced from the context. It should also be understood that expressions such as "including", "comprising", "having", "containing" and / or "comprising of" are open-ended rather than closed-ended expressions in this specification, which means that there are the stated features, elements and / or components, but do not exclude the existence of one or more other features, elements, components and / or combinations thereof. Furthermore, when an expression such as "at least one of..." appears after a list of listed features, it modifies the entire list of features, rather than just individual elements in the list. In addition, when describing the embodiments of this application, the use of "may" means "one or more embodiments of this application". And the term "exemplary" is intended to refer to an example or illustration. Unless otherwise defined, all terms used herein (including engineering terms and scientific and technical terms) have the same meaning as the ordinary understanding of those of ordinary skill in the art to which this application pertains. It should also be understood that unless there is a clear statement in this application, words defined in common dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense.

[0041] To solve the technical problems proposed in the background art, this application provides a preferred embodiment: Please refer to Figure 4 As shown, it demonstrates the implementation scenario of this embodiment. The implementation scenario is: collecting data from a data acquisition terminal, transmitting the data to a data processing terminal, and the data processing terminal performs analysis and calculation to obtain an assessment value of the impact on the airspace operation environment.

[0042] The specific content of this embodiment is:

[0043] As Figure 1 shown, the unmanned aerial vehicle flight control data acquisition control system and method based on intelligent sensors includes the following specific steps:

[0044] S1. Record the operation environment data and flight behavior pattern data during the unmanned aerial vehicle's airspace operation in real time;

[0045] In this embodiment, the specific steps of S1 are:

[0046] S11. Obtain the operation environment data during the UAV's airspace operation through sensors, where the operation environment data includes environmental wind data, pressure data, and altitude data;

[0047] S12. Obtain the flight behavior pattern data during the UAV's airspace operation through a gyroscope, where the flight behavior pattern data includes roll angle data, pitch angle data, and yaw angle data;

[0048] S13. Store the collected data in a storage component for use in the analysis process.

[0049] S2. Import the operation environment data during the UAV's airspace operation into the operation environment status analysis strategy of the UAV, and calculate to obtain the UAV's real-time environmental adaptation index;

[0050] As Figure 2 shown, in this embodiment, S2 includes the following specific steps:

[0051] S21. Obtain the environmental wind data of the UAV's airspace operation in the data unit time, and obtain the environmental interference evaluation value of the UAV's airspace operation in the data unit time from the environmental wind data of the UAV's airspace operation in the data unit time;

[0052] S22. Obtain the flight pressure data and flight altitude data of the UAV's airspace operation in the data unit time, and obtain the air pressure interference evaluation value of the UAV's airspace operation in the data unit time from the flight pressure data and flight altitude data of the UAV's airspace operation in the data unit time;

[0053] S23. Analyze based on the results of the environmental wind interference evaluation value and the air pressure interference evaluation value of the UAV's airspace operation in the data unit time to obtain the UAV's real-time environmental adaptation index in the data unit time.

[0054] In this embodiment, S21 specifically includes the following steps: Import the environmental wind data in the data unit time into the environmental wind interference evaluation value calculation formula to calculate the environmental wind interference evaluation value of the UAV's airspace operation in the data unit time. Among them, the environmental wind interference evaluation value calculation formula is: Among them, i is the number corresponding to each data unit time, i is any one of 1 to N, ρ i is the air density in the UAV's airspace operation at the i-th data unit time, is the velocity vector in the UAV's airspace operation at the i-th data unit time, C w,i is the lift coefficient in the UAV's airspace operation at the i-th data unit time, S is the reference area of the UAV's wing, cos(θ i ) is the included angle between the wind and the UAV's flight direction in the UAV's airspace operation, F wind is the set reference value of the wind speed influence, it should be noted that in this formula is the sum of the velocity vector of the UAV's airspace operation relative to the ground and the wind speed vector in the data unit time, ρ i is the ratio of the air pressure to the product of the gas constant and the temperature during the UAV's airspace operation in the data unit time. By comprehensively evaluating the relationship between the air density, velocity vector, lift coefficient, wing reference area, and the angle between the wind and the UAV's flight direction, the relationship between the actual wind speed influence and the reference wind speed influence during the UAV's airspace operation is obtained, and then the environmental wind interference evaluation value during the UAV's airspace operation in the data unit time is obtained. Exemplarily, an example is given to illustrate the influence of the value of cos(θ i ) on the UAV's flight speed. If the direction of the wind is the same as the UAV's flight direction, that is, in the case of a tailwind, cos(θ i ) is positive, indicating that the influence of the wind increases the flight speed; if the direction of the wind is opposite to the UAV's flight direction, that is, in the case of a headwind, cos(θ i ) is negative, indicating that the influence of the wind reduces the flight speed.

[0055] In this embodiment, S22 specifically includes the following steps: Import the pressure data and altitude data of the UAV's airspace operation in the data unit time into the air pressure interference evaluation value calculation formula to calculate the air pressure interference evaluation value of the UAV's airspace operation in the data unit time. Among them, the air pressure interference evaluation value calculation formula is: where P0 is the sea-level air pressure, L i is the temperature lapse rate of the UAV's airspace operation in the data unit time, h i is the flight altitude of the UAV's airspace operation in the data unit time, T 0,i is the sea-level temperature of the UAV's airspace operation in the data unit time, g0 is the acceleration due to gravity, M is the molar mass of air, R is the gas constant, P h is the reference pressure at the altitude h of the UAV's airspace operation in the data unit time, and ΔP is the allowable pressure change value during the UAV's airspace operation. It should be noted that in this formula By comprehensively analyzing the temperature lapse rate and the ratio of the flight altitude to the sea-level temperature in the data unit time, the influence of temperature and altitude on the UAV's airspace operation is analyzed, As the exponential part in this formula, it determines the degree of pressure drop as the UAV's flight altitude increases. A higher exponential value means a faster pressure drop, while a lower exponential value indicates a slower pressure drop. That is, the larger the exponential value, the faster the pressure drops, and the smaller the exponential value, the slower the pressure drops.

[0056] In this embodiment, S23 specifically includes the following steps: Add the calculated environmental wind interference evaluation value and air pressure interference evaluation value of the UAV's airspace operation in the data unit time after weighting to obtain the UAV's environmental real-time adaptation index.

[0057] S3. Establish a kinematic model of the UAV in airspace operations, input the flight behavior pattern data in the UAV airspace operations into the kinematic model of the UAV, and output the flight state response index of the UAV;

[0058] In this embodiment, the specific steps of S3 are as follows:

[0059] S31. Obtain the roll angle data, pitch angle data, and yaw angle data of the UAV in airspace operations per unit time of data;

[0060] S32. Import the roll angle data, pitch angle data, and yaw angle data of the UAV in airspace operations per unit time of data into the calculation formula of the UAV flight state response index to calculate the UAV flight state response index per unit time of data. Among them, the calculation formula of the flight state response index is: Among them, t is the unit time of data, α 1,i (t) is the roll angle at the t-th moment of the i-th data unit time interval t, α 2,i (t) is the pitch angle at the t-th moment of the i-th data unit time interval t, α 3,i (t) is the yaw angle at the t-th moment of the i-th data unit time interval t, dt is the integral over the unit time of data. It should be noted that the lower the flight state response index, that is, the lower the change amount of the UAV flight attitude per unit time of data, the higher the flight stability. In this formula, the acquisition methods of the roll angle data, pitch angle data, and yaw angle data are: obtain the roll angle data, pitch angle data, and yaw angle data from the UAV gyroscope. Exemplarily, illustrate the values of α 1,i (t), α 2,i (t) and α 3,i (t), α 1,i (t - 1) is the roll angle at the (t - 1)-th moment of the i-th data unit time interval, is the angular velocity of the gyroscope of the UAV around the X-axis during airspace operations per unit time of data, α 2,i (t - 1) is the pitch angle at the (t - 1)-th moment of the i-th data unit time interval, is the angular velocity of the gyroscope of the UAV around the Y-axis during airspace operations per unit time of data, α 3,i (t - 1) is the yaw angle at the (t - 1)-th moment of the i-th data unit time interval, is the angular velocity of the gyroscope of the UAV around the Z-axis during airspace operations per unit time of data, and Δt is the sampling time interval.

[0061] S4. Input the real-time environmental adaptation index and flight state response index of the UAV into the maneuver strategy decision analysis model of the UAV, evaluate the influence weight of the airspace operation environment of the UAV, and output the behavior regulation strategy for the UAV under the current airspace operation;

[0062] In this embodiment, the specific steps in S4 are as follows:

[0063] S41. Import the real-time environmental adaptation index and flight state response index of the UAV in the data unit time into the calculation formula of the airspace operation environment influence evaluation value to calculate the airspace operation environment influence evaluation value of the UAV in the data unit time. The calculation formula of the airspace operation environment influence evaluation value is: where ε i is the real-time environmental adaptation index of the UAV during airspace operation in the i-th data unit time, ε is the standard value of the real-time environmental adaptation index of the UAV during airspace operation, Δε is the allowable fluctuation value of the real-time environmental adaptation index of the UAV during airspace operation, γ is the standard flight state response index of the UAV during airspace operation, c is the proportion weight corresponding to the real-time environmental adaptation index of the UAV. It should be noted that this formula comprehensively analyzes the influence weight of the airspace operation environment of the UAV based on the real-time environmental adaptation index and flight state response index of the UAV, improving the accuracy of flight control during the airspace operation of the UAV;

[0064] S42. Dynamically control the flight speed of the UAV during airspace operation according to the calculated airspace operation environment influence evaluation value of the UAV in the data unit time. Exemplarily, an example is given to illustrate the dynamic control method of the flight speed of the UAV during airspace operation. If the result of the airspace operation environment influence evaluation value in a certain data time unit is 0.7, and if the airspace operation speed of the UAV at this time is 15 meters per second, the speed should be reduced to 10.5 meters per second.

[0065] Here, it should be noted that the set parameters (such as weights and thresholds, etc.) in this embodiment need to be set by those skilled in the art according to relevant experiments. The specific experimental method is: obtain the operation environment data and flight behavior pattern data in the real-time record of the UAV airspace operation, bring them into each step in this embodiment to calculate the real-time environmental adaptation index and flight state response index of the UAV, and import the calculated real-time environmental adaptation index and flight state response index of the UAV into the fitting software for continuous fitting, and output the values of the set parameters (such as weights and thresholds, etc.) with the highest compliance of the airspace operation environment influence value of the UAV.

[0066] According to the above embodiments, this embodiment has the following advantages over the prior art: This embodiment records in real time the operation environment data and flight behavior pattern data in the UAV airspace operation, imports the operation environment data in the UAV airspace operation into the operation environment state analysis strategy of the UAV, calculates and obtains the real-time UAV environment adaptation index, establishes the kinematic model of the UAV in the UAV airspace operation, inputs the flight behavior pattern data in the UAV airspace operation into the kinematic model of the UAV, outputs the flight state response index of the UAV, inputs the real-time UAV environment adaptation index and the flight state response index into the maneuver strategy decision analysis model of the UAV, evaluates the weight of the influence of the UAV airspace operation environment, and outputs the behavior regulation strategy for the UAV under the current airspace operation. By real-time regulating the UAV under the airspace operation, the flight stability and safety of the UAV under the airspace operation are significantly improved.

[0067] As Figure 3 shown, this embodiment also provides a UAV flight control data acquisition and control system based on intelligent sensors, which is implemented based on the above-mentioned UAV flight control data acquisition and control method based on intelligent sensors. It specifically includes an airspace operation data acquisition module, an operation environment state analysis module, a flight state response output module, and a maneuver strategy decision output module. Among them, the airspace operation data acquisition module is used to record in real time the operation environment data and flight behavior pattern data in the UAV airspace operation; the operation environment state analysis module is used to import the operation environment data in the UAV airspace operation into the operation environment state analysis strategy of the UAV, and calculate and obtain the real-time UAV environment adaptation index; the flight state response output module is used to establish the kinematic model of the UAV in the UAV airspace operation, input the flight behavior pattern data in the UAV airspace operation into the kinematic model of the UAV, and output the flight state response index of the UAV; the maneuver strategy decision output module is used to input the real-time UAV environment adaptation index and the flight state response index into the maneuver strategy decision analysis model of the UAV, evaluate the weight of the influence of the UAV airspace operation environment, and output the behavior regulation strategy for the UAV under the current airspace operation.

[0068] For the specific steps of each unit module in the above-mentioned UAV flight control data acquisition and control system based on intelligent sensors of the present application to implement the corresponding functions, reference can be made to the steps in the embodiments of the UAV flight control data acquisition and control method based on intelligent sensors in the above text, and details will not be described here.

[0069] This embodiment also provides an electronic device, including: a processor and a memory. Among them, the memory stores a computer program that can be called by the processor;

[0070] The processor executes the above-mentioned UAV flight control data acquisition and control method by calling the computer program stored in the memory.

[0071] The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory 310 may include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing the operating system, instructions for at least one function, and instructions for implementing the intelligent sensor-based UAV flight control data acquisition and control method provided in the above embodiments, etc.; the data storage area can store data involved in the intelligent sensor-based UAV flight control data acquisition and control method provided in the above embodiments, etc.

[0072] The processor may include one or more processing cores. By running or executing the instructions, programs, code sets or instruction sets stored in the memory, the processor calls the data stored in the memory and executes various functions of this application and processes data. The processor can be at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller and a microprocessor. It can be understood that for different devices, the electronic devices for implementing the above processor functions can also be others, and the embodiments of this application do not make specific limitations.

[0073] It may also include a communication bus, and the communication bus may include a path for transmitting information between the above components. The communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0074] This embodiment also proposes a computer-readable storage medium storing instructions, which when run on a computer, cause the computer to execute the above intelligent sensor-based UAV flight control data acquisition and control method.

[0075] For example, the computer-readable storage medium can be a read-only memory, a random access memory, a read-only optical disc, magnetic tape, a floppy disk and an optical data storage device, etc.

[0076] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that contains a collection of one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0077] The term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0078] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principle. Those skilled in the art should understand that the scope of the application involved in the present application is not limited to the technical solution formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned application concept. For example, the technical solutions formed by mutually replacing the above features with (but not limited to) technical features having similar functions in the present application.

Claims

1. A method for collecting and controlling flight control data of an unmanned aerial vehicle based on an intelligent sensor, characterized in that, Including: S1. Record the operation environment data and flight behavior pattern data during the UAV airspace operation in real time; S2. Import the operation environment data during the UAV airspace operation into the operation environment state analysis strategy of the UAV, and calculate and obtain the real-time UAV environment adaptation index; S3. Establish a kinematic model of the UAV during the UAV airspace operation, input the flight behavior pattern data during the UAV airspace operation into the kinematic model of the UAV, and output the flight state response index of the UAV; S4. Input the real-time UAV environment adaptation index and the flight state response index into the maneuver strategy decision analysis model of the UAV, evaluate the influence weight of the UAV airspace operation environment, and output the behavior regulation strategy for the UAV under the current airspace operation.

2. The method for collecting and controlling UAV flight control data based on intelligent sensors according to claim 1, characterized in that, The S2 includes the following specific steps: S21. Obtain the environmental wind data of the UAV airspace operation in the data unit time, and obtain the environmental interference evaluation value of the UAV airspace operation in the data unit time from the environmental wind data of the UAV airspace operation in the data unit time; S22. Obtain the flight pressure data and flight altitude data of the UAV airspace operation in the data unit time, and obtain the air pressure interference evaluation value of the UAV airspace operation in the data unit time from the flight pressure data and flight altitude data of the UAV airspace operation in the data unit time; S23. Analyze based on the results of the environmental wind interference evaluation value and the air pressure interference evaluation value of the UAV airspace operation in the data unit time to obtain the real-time UAV environment adaptation index in the data unit time.

3. The method for collecting and controlling UAV flight control data based on intelligent sensors according to claim 2, characterized in that, The S21 includes the following specific steps: Import the environmental wind data in the data unit time into the calculation formula of the environmental wind interference evaluation value to calculate the environmental wind interference evaluation value of the UAV airspace operation in the data unit time. The calculation formula of the environmental wind interference evaluation value is: where i is the number corresponding to each data unit time, and i is any one of 1 to N, ρ i is the air density in the UAV airspace operation in the i-th data unit time, is the velocity vector in the UAV airspace operation in the i-th data unit time, C w,i is the lift coefficient in the UAV airspace operation in the i-th data unit time, S is the reference area of the UAV wing, cos(θ i ) is the included angle between the wind and the UAV flight direction in the UAV airspace operation, F wind is the set reference value of the wind speed influence.

4. The method for collecting and controlling UAV flight control data based on intelligent sensors according to claim 3, wherein, The S22 includes the following specific steps: Import the pressure data and altitude data of the UAV airspace operation in the data unit time into the air pressure interference evaluation value calculation formula to calculate the air pressure interference evaluation value of the UAV airspace operation in the data unit time. The air pressure interference evaluation value calculation formula is as follows: where P0 is the sea-level air pressure, L i is the temperature lapse rate of the UAV airspace operation in the data unit time, h i is the flight altitude of the UAV airspace operation in the data unit time, T 0,i is the sea-level temperature of the UAV airspace operation in the data unit time, g0 is the acceleration due to gravity, M is the molar mass of air, R is the gas constant, P h is the reference pressure at the altitude h of the UAV airspace operation in the data unit time, and ΔP is the allowable pressure change value during the UAV airspace operation.

5. The method for collecting and controlling UAV flight control data based on intelligent sensors according to claim 4, characterized in that, The S23 includes the following steps: Add the calculated environmental wind interference evaluation value and air pressure interference evaluation value of the UAV airspace operation in the data unit time after weighting to obtain the real-time UAV environment adaptation index.

6. The method for collecting and controlling UAV flight control data based on an intelligent sensor according to claim 5, wherein The S3 includes the following steps: S31. Obtain the roll angle data, pitch angle data and yaw angle data of the UAV airspace operation in the data unit time; S32. Import the roll angle data, pitch angle data and yaw angle data of the UAV airspace operation in the data unit time into the calculation formula of the UAV flight state response index to calculate the UAV flight state response index in the data unit time, where the calculation formula of the flight state response index is: where t is the data unit time, and α 1,i (t) is the roll angle at the t-th moment of the i-th data unit time interval, and α 2,i (t) is the pitch angle at the t-th moment of the i-th data unit time interval, and α 3,i (t) is the yaw angle at the t-th moment of the i-th data unit time interval, and dt is integrated over the data unit time.

7. The method for collecting and controlling UAV flight control data based on intelligent sensors according to claim 6, characterized in that, The specific steps of S4 are: S41. Obtain the UAV airspace operation environment impact evaluation value in the data unit time from the real-time UAV environment adaptation index and the flight state response index in the data unit time; S42. Dynamically control the flight speed of the UAV during the UAV airspace operation according to the calculated UAV airspace operation environment impact evaluation value in the data unit time.

8. The UAV flight control data acquisition and control system based on intelligent sensors is implemented based on the UAV flight control data acquisition and control method based on intelligent sensors according to any one of claims 1-7, and is characterized in that, Specifically, it includes an airspace operation data acquisition module, an operation environment state analysis module, a flight state response output module and a maneuver strategy decision output module. Among them, the airspace operation data acquisition module is used to record the operation environment data and flight behavior pattern data during the UAV airspace operation in real time; The operation environment state analysis module is used to import the operation environment data during the UAV airspace operation into the operation environment state analysis strategy of the UAV, and calculate and obtain the real-time UAV environment adaptation index; The flight state response output module is used to establish a kinematic model of the UAV in airspace operations, input the flight behavior pattern data in the UAV airspace operations into the kinematic model of the UAV, and output the flight state response index of the UAV; The maneuver strategy decision output module is used to input the UAV environment real-time adaptation index and the flight state response index into the maneuver strategy decision analysis model of the UAV, evaluate the influence weight of the UAV airspace operation environment, and output the behavior regulation strategy for the UAV under the current airspace operation.

9. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the method for controlling UAV flight control data acquisition based on an intelligent sensor according to any one of claims 1-7 by calling the computer program stored in the memory.

10. A computer-readable storage medium, characterized in that, Stores instructions that, when run on a computer, cause the computer to execute the method for controlling UAV flight control data acquisition based on an intelligent sensor according to any one of claims 1-7.

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