UAV Flight Control Data Acquisition and Control System and Method Based on Intelligent Sensors

Abstract

This application discloses a UAV flight control data acquisition and control system and method based on intelligent sensors, relating to the field of UAV flight control technology. This application imports the operational environment data of UAV airspace operations into the UAV operational environment state analysis strategy, calculates and obtains the UAV real-time environmental adaptation index, establishes the UAV kinematic model in airspace operations, inputs the flight behavior pattern data of UAV in airspace operations into the UAV kinematic model, outputs the UAV flight state response index, inputs the UAV real-time environmental adaptation index and flight state response index into the UAV maneuver strategy decision analysis model, evaluates the influence weight of the UAV airspace operational environment, and outputs the behavior control strategy of the UAV under the current airspace operation. By controlling the UAV in real time under airspace operations, the flight stability and safety of the UAV under airspace operations are significantly improved.

Description

Technical Field

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

[0002] With the rapid development of technology, drones are playing an increasingly important role. Due to their high degree of stealth and flexibility, they can perform missions without revealing their location and were first applied in the military field. The most traditional drone control method is manual remote control, where the operator uses a remote control to directly control the drone's flight direction, speed, and altitude via wireless signals. Currently, drones are usually equipped with automatic flight control systems that automatically control the flight path according to a pre-set flight plan to ensure that the drone flies along the predetermined route. However, current drones are affected by environmental factors, such as sudden changes in wind speed and air pressure. Due to insufficient response time, the control system lacks flexible response capabilities and cannot adjust the flight strategy in real time according to different drone flight environments, which reduces the stability and safety of drone flight. In order to solve the problems mentioned in the background technology, this application designs a drone flight control data acquisition and control system and method based on intelligent sensors. Summary of the Invention

[0003] To address the aforementioned technical shortcomings, this application proposes a UAV flight control data acquisition and control system and method based on intelligent sensors.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: This application provides a method for acquiring and controlling UAV flight control data based on intelligent sensors, which includes the following specific steps:

[0005] S1. Real-time recording of operational environment data and flight behavior pattern data during UAV airspace operations;

[0006] S2. Import the operational environment data of the UAV in the airspace into the UAV's operational environment status analysis strategy, and calculate and obtain the UAV's real-time environmental adaptation index.

[0007] S3. Establish a UAV kinematic model for UAV airspace operations, input flight behavior pattern data of UAV airspace operations into the UAV kinematic model, and output the UAV flight state response index.

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

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

[0010] S11. Acquire operational environment data for UAV airspace operations through sensors, including environmental wind data, pressure data, and altitude data.

[0011] S12. Obtain flight behavior pattern data of UAV airspace operations through gyroscope, including 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 a preferred technical solution for the UAV flight control data acquisition and control system and method based on intelligent sensors, step S2 includes the following specific steps:

[0014] S21. Obtain the environmental wind data of UAV airspace operation per unit time, and obtain the environmental interference assessment value of UAV airspace operation per unit time from the environmental wind data of UAV airspace operation per unit time.

[0015] 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 assessment 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.

[0016] S23. Based on the environmental wind interference assessment results and air pressure interference assessment results of UAV airspace operations per unit time, the real-time environmental adaptation index of UAV per unit time is obtained.

[0017] It should be noted that, as a preferred technical solution for the UAV flight control data acquisition and control system and method based on intelligent sensors, S21 includes the following specific steps: importing the environmental wind data per unit time into the environmental wind interference assessment value calculation formula to calculate the environmental wind interference assessment value for UAV airspace operations per unit time, wherein the environmental wind interference assessment value calculation formula is: Where i is the number corresponding to each data unit time, and i is any item from 1 to N, ρ i Let be the air density during the UAV's airspace operation in the i-th data unit time. Let C be the velocity vector of the UAV in the airspace during the i-th data unit time. w,i Let S be the lift coefficient of the UAV in the airspace during the i-th data unit time, and let S be the reference area of ​​the UAV wing, cos(θ) iF represents the angle between the wind and the drone's flight direction during drone airspace operations. wind The set wind speed influence reference value should be noted in this formula. ρ is the sum of the velocity vector and wind speed vector of the UAV relative to the ground during a unit of time in the airspace. i This is the ratio of air pressure to the product of gas constant and temperature during UAV airspace operations per unit time. By comprehensively evaluating the relationship between the actual wind speed and the reference wind speed during UAV airspace operations, based on air density, velocity vector, lift coefficient, wing reference area, and the angle between the wind and the UAV's flight direction, we can obtain the environmental wind interference assessment value for UAV airspace operations per unit time.

[0018] It should be noted that, as a preferred technical solution for the UAV flight control data acquisition and control system and method based on intelligent sensors, S22 includes the following specific steps: importing the pressure data and altitude data of the UAV airspace operation per unit time into the air pressure interference evaluation value calculation formula to calculate the air pressure interference evaluation value of the UAV airspace operation per unit time, wherein the air pressure interference evaluation value calculation formula is: Where P0 is the sea level pressure, L i h represents the temperature decay rate of UAV airspace operations per unit time. i T represents the flight altitude of the UAV in the airspace during a unit of data time. 0,i Let g be the sea level temperature during UAV airspace operations per unit time, g0 be the gravitational acceleration, M be the molar mass of air, R be the gas constant, and P be the mass of air. h Let be the reference pressure at an airspace operating altitude of h within a unit of time, and ΔP be the allowable pressure variation during drone airspace operation. It should be noted that in this formula... By comprehensively analyzing the temperature lapse rate per unit time and the ratio of flight altitude to sea level temperature, the impact of temperature and altitude on UAV airspace operations is analyzed. The exponent in this formula determines the degree to which air pressure decreases as the drone's flight altitude increases. A higher exponent value means that the air pressure decreases faster, while a lower exponent value means that the air pressure decreases slower. In other words, the larger the exponent value, the faster the air pressure decreases, and the smaller the exponent value, the slower the air pressure decreases.

[0019] It should be noted that, as a preferred technical solution for the UAV flight control data acquisition and control system and method based on intelligent sensors, S23 includes the following steps: weighting and summing the calculated environmental wind interference assessment value and air pressure interference assessment value of the UAV airspace operation per unit time to obtain the UAV real-time environmental adaptation index.

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

[0021] S31. Acquire roll angle data, pitch angle data and yaw angle data of UAV airspace operations per unit time;

[0022] S32. Import the roll angle data, pitch angle data, and yaw angle data of the UAV airspace operation per unit time into the UAV flight status response index calculation formula to calculate the UAV flight status response index per unit time. The flight status response index calculation formula is as follows: Where t is the data unit of time, α 1,i (t) represents the roll angle at time t, which is the time interval of the i-th data unit. 2,i (t) represents the pitch angle at time t, the i-th data unit time interval, α 3,i (t) represents the yaw angle at time t of the i-th data unit time interval, and dt represents the integral over the data unit time. It should be noted that the lower the flight state response index, that is, the lower the change in the UAV's flight attitude in the data unit time, the higher the flight stability. In this formula, the roll angle data, pitch angle data and yaw angle data are obtained from the UAV gyroscope.

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

[0024] S41. Import the UAV environmental real-time adaptation index and flight status response index per unit time into the airspace operation environment impact assessment value calculation formula to calculate the UAV airspace operation environment impact assessment value per unit time. The airspace operation environment impact assessment value calculation formula is as follows: Where, ε i Let ε be the real-time environmental adaptation index of the UAV during airspace operations in the i-th data unit time, Δε be the standard value of the real-time environmental adaptation index of the UAV during airspace operations, γ be the standard flight state response index of the UAV during airspace operations, and c be the weight of the UAV real-time environmental adaptation index. It should be noted that this formula combines the real-time environmental adaptation index and the flight state response index to analyze the influence weight of the UAV airspace operation environment, thereby improving the accuracy of flight control during UAV airspace operations.

[0025] S42. Based on the calculated environmental impact assessment value of UAV airspace operations per unit time, dynamically control the flight speed of UAVs during airspace operations.

[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. Specifically, it includes an airspace operation data acquisition module, an operation environment status analysis module, a flight status response output module, and a maneuver strategy decision output module. The airspace operation data acquisition module is used to record the operation environment data and flight behavior pattern data of the UAV in airspace operations in real time.

[0027] The operational environment status analysis module is used to import operational environment data from UAV airspace operations into the UAV operational environment status analysis strategy and calculate and obtain the UAV's real-time environmental adaptation index.

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

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

[0030] An electronic device includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0031] The processor executes the aforementioned 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 storing instructions that, when executed on a computer, cause the computer to perform the aforementioned intelligent sensor-based UAV flight control data acquisition and control method.

[0033] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention records the operational environment data and flight behavior pattern data of UAVs in airspace operations in real time, imports the operational environment data of UAVs in airspace operations into the UAV's operational environment state analysis strategy, calculates and obtains the UAV's real-time environmental adaptation index, establishes the UAV's kinematic model in airspace operations, inputs the UAV's flight behavior pattern data in airspace operations into the UAV's kinematic model, outputs the UAV's flight state response index, inputs the UAV's real-time environmental adaptation index and flight state response index into the UAV's maneuver strategy decision analysis model, evaluates the influence weight of the UAV's airspace operational environment, and outputs the behavior control strategy of the UAV under the current airspace operation. Through real-time control of the UAV under airspace operations, the flight stability and safety of the UAV under airspace operations are significantly improved. Attached Figure Description

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

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

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

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

[0038] Figure 4 This is a scenario diagram for the implementation of this application. Detailed Implementation

[0039] To better understand this application, various aspects of this application will be described in more detail with reference to the accompanying drawings. It should be understood that these detailed descriptions are merely illustrative of exemplary embodiments of this application and are not intended to limit the scope of this 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, the size, dimensions, and shapes of the elements have been slightly adjusted for ease of illustration. The drawings are for illustrative purposes only and are not strictly to scale. As used herein, the terms “approximately,” “about,” and similar terms are used to indicate approximation, not degree, and are intended to illustrate inherent deviations in measured or calculated values ​​that will be recognized by those skilled in the art. Furthermore, the order in which the steps are described in this application does not necessarily indicate the order in which these steps occur in actual operation, unless otherwise expressly defined or deduced from the context. It should also be understood that expressions such as “comprising,” “including,” “having,” “containing,” and / or “comprising” are open-ended rather than closed-ended expressions in this specification, indicating the presence of the stated features, elements, and / or components, but not excluding the presence of one or more other features, elements, components, and / or combinations thereof. Moreover, when expressions such as “at least one of…” appear after a list of listed features, they modify the entire list of features, not just individual elements in the list. Additionally, when describing embodiments of this application, the word “may” is used to mean “one or more embodiments of this application.” Furthermore, the term "exemplary" is intended to refer to an example or illustration. Unless otherwise specified, all terms used herein (including engineering and technical terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that, unless expressly stated herein, words defined in common dictionaries shall be interpreted as having meanings consistent with their meanings in the context of the relevant art, and not as idealized or overly formalized meanings.

[0041] To address the technical problems mentioned in the background section, this application provides a preferred embodiment: Please refer to... Figure 4 The following is a demonstration of the implementation scenario of this embodiment: data is collected from the data acquisition terminal, transmitted to the data processing terminal, and the data processing terminal analyzes and calculates to obtain the airspace operation environment impact assessment value.

[0042] The specific content of this embodiment is as follows:

[0043] like Figure 1 As shown, the UAV flight control data acquisition and control system and method based on intelligent sensors include the following specific steps:

[0044] S1. Real-time recording of operational environment data and flight behavior pattern data during UAV airspace operations;

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

[0046] S11. Acquire operational environment data for UAV airspace operations through sensors, including environmental wind data, pressure data, and altitude data.

[0047] S12. Obtain flight behavior pattern data of UAV airspace operations through gyroscope, including roll angle data, pitch angle data and yaw angle data;

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

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

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

[0051] S21. Obtain the environmental wind data of UAV airspace operation per unit time, and obtain the environmental interference assessment value of UAV airspace operation per unit time from the environmental wind data of UAV airspace operation per unit time.

[0052] 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 assessment 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.

[0053] S23. Based on the environmental wind interference assessment results and air pressure interference assessment results of UAV airspace operations per unit time, the real-time environmental adaptation index of UAV per unit time is obtained.

[0054] In this embodiment, S21 specifically includes the following steps: importing the environmental wind data in the data unit time into the environmental wind interference assessment value calculation formula to calculate the environmental wind interference assessment value of the UAV airspace operation in the data unit time, wherein the environmental wind interference assessment value calculation formula is: Where i is the number corresponding to each data unit time, and i is any item from 1 to N, ρ i Let be the air density during the UAV's airspace operation in the i-th data unit time. Let C be the velocity vector of the UAV in the airspace during the i-th data unit time. w,i Let S be the lift coefficient of the UAV in the airspace during the i-th data unit time, and let S be the reference area of ​​the UAV wing, cos(θ) i F represents the angle between the wind and the drone's flight direction during drone airspace operations. wind The set wind speed influence reference value should be noted in this formula. ρ is the sum of the velocity vector and wind speed vector of the UAV relative to the ground during a unit of time in the airspace. i This represents the ratio of air pressure to the product of the gas constant and temperature during UAV airspace operations per unit time. It comprehensively assesses the relationship between the actual and reference wind speed effects during UAV airspace operations by considering air density, velocity vector, lift coefficient, wing reference area, and the angle between the wind and the UAV's flight direction. This yields the environmental wind interference assessment value for UAV airspace operations per unit time. For example, cos(θ) is used to illustrate this. i The value of cos(θ) affects the drone's flight speed. If the wind direction is the same as the drone's flight direction, i.e., in the case of a tailwind, the value of cos(θ) is... i A positive value for cos(θ) indicates that the wind increases the flight speed; if the wind direction is opposite to the drone's flight direction, i.e., in a headwind situation, the value of cos(θ) is positive. i A negative value indicates that the wind reduces flight speed.

[0055] In this embodiment, S22 specifically includes the following steps: importing the pressure data and altitude data of the UAV airspace operation per unit time into the air pressure interference assessment value calculation formula to calculate the air pressure interference assessment value of the UAV airspace operation per unit time, wherein the air pressure interference assessment value calculation formula is: Where P0 is the sea level pressure, L i h represents the temperature decay rate of UAV airspace operations per unit time. i T represents the flight altitude of the UAV in the airspace during a unit of data time. 0,i Let g be the sea level temperature during UAV airspace operations per unit time, g0 be the gravitational acceleration, M be the molar mass of air, R be the gas constant, and P be the mass of air. h Let be the reference pressure at an airspace operating altitude of h within a unit of time, and ΔP be the allowable pressure variation during drone airspace operation. It should be noted that in this formula... By comprehensively analyzing the temperature lapse rate per unit time and the ratio of flight altitude to sea level temperature, the impact of temperature and altitude on UAV airspace operations is analyzed. The exponent in this formula determines the degree to which air pressure decreases as the drone's flight altitude increases. A higher exponent value means that the air pressure decreases faster, while a lower exponent value means that the air pressure decreases slower. In other words, the larger the exponent value, the faster the air pressure decreases, and the smaller the exponent value, the slower the air pressure decreases.

[0056] In this embodiment, S23 specifically includes the following steps: weighting and summing the calculated environmental wind interference assessment value and air pressure interference assessment value of the UAV airspace operation per unit time to obtain the UAV real-time environmental adaptation index.

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

[0058] In this embodiment, step S3 is as follows:

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

[0060] S32. Import the roll angle data, pitch angle data, and yaw angle data of the UAV airspace operation per unit time into the UAV flight status response index calculation formula to calculate the UAV flight status response index per unit time. The flight status response index calculation formula is as follows: Where t is the data unit of time, α 1,i (t) represents the roll angle at time t, which is the time interval of the i-th data unit. 2,i (t) represents the pitch angle at time t, the i-th data unit time interval, α 3,i (t) represents the yaw angle at time t of the i-th data unit time interval, and dt is the integral over the data unit time. It should be noted that the lower the flight state response index, i.e., the lower the change in UAV flight attitude per data unit time, the higher the flight stability. In this formula, the roll angle, pitch angle, and yaw angle data are obtained from the UAV gyroscope. For example, α... 1,i (t), α 2,i (t) and α 3,i The value of (t), α 1,i (t-1) represents the roll angle at time t-1, which is the time interval of the i-th data unit. This represents the angular velocity of the gyroscope around the X-axis during UAV airspace operations per unit time. α 2,i (t-1) is the pitch angle at time t-1 of the i-th data unit time interval. This represents the angular velocity of the gyroscope around the Y-axis during UAV airspace operations per unit time. α 3,i (t-1) represents the yaw angle at time t-1, which is the data unit time interval of the i-th time. Δt represents the angular velocity of the gyroscope around the Z-axis during UAV airspace operations per unit time, and Δt is the sampling time interval.

[0061] S4. Input the UAV's real-time environmental adaptation index and flight status response index into the UAV's maneuver strategy decision analysis model, evaluate the UAV's airspace operation environment impact weight, and output the behavior control 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 UAV environmental real-time adaptation index and flight status response index per unit time into the airspace operation environment impact assessment value calculation formula to calculate the UAV airspace operation environment impact assessment value per unit time. The airspace operation environment impact assessment value calculation formula is as follows: Where, ε i Let ε be the real-time environmental adaptation index of the UAV during airspace operations in the i-th data unit time, Δε be the standard value of the real-time environmental adaptation index of the UAV during airspace operations, γ be the standard flight state response index of the UAV during airspace operations, and c be the weight of the UAV real-time environmental adaptation index. It should be noted that this formula combines the real-time environmental adaptation index and the flight state response index to analyze the influence weight of the UAV airspace operation environment, thereby improving the accuracy of flight control during UAV airspace operations.

[0064] S42. Based on the calculated airspace operation environment impact assessment value of the UAV in a unit of time, dynamically control the flight speed of the UAV during airspace operation. For example, if the airspace operation environment impact assessment value in a certain data time unit is 0.7, and the UAV airspace operation speed is 15 meters per second at this time, then the speed should be reduced to 10.5 meters per second.

[0065] It should be noted that the parameters set in this embodiment (such as weights and thresholds) need to be set by those skilled in the art based on relevant experiments. The specific experimental method is as follows: obtain real-time recorded operational environment data and flight behavior pattern data of UAV airspace operations, and use them in the steps of this embodiment to calculate the UAV environment real-time adaptation index and flight status response index. Import the calculated UAV environment real-time adaptation index and flight status response index into fitting software for continuous fitting, and output the value of the set parameter (such as weights and thresholds) with the highest compliance with the UAV airspace operational environment influence value.

[0066] Based on the above implementation, this embodiment has the following advantages over the prior art: This embodiment records the operational environment data and flight behavior pattern data of UAVs in airspace operations in real time, imports the operational environment data of UAVs in airspace operations into the UAV's operational environment state analysis strategy, calculates and obtains the UAV's real-time environmental adaptation index, establishes the UAV's kinematic model in airspace operations, inputs the UAV's flight behavior pattern data in airspace operations into the UAV's kinematic model, outputs the UAV's flight state response index, inputs the UAV's real-time environmental adaptation index and flight state response index into the UAV's maneuver strategy decision analysis model, evaluates the UAV's airspace operational environment influence weight, and outputs a behavior control strategy for the UAV under the current airspace operation. By controlling the UAV in airspace operations in real time, the flight stability and safety of the UAV under airspace operations are significantly improved.

[0067] like Figure 3 As shown, this embodiment also provides a UAV flight control data acquisition and control system based on intelligent sensors. This system is implemented based on the aforementioned UAV flight control data acquisition and control method based on intelligent sensors. 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. The airspace operation data acquisition module records real-time operation environment data and flight behavior pattern data during UAV airspace operations. The operation environment state analysis module imports the operation environment data from UAV airspace operations into the UAV's operation environment state analysis strategy and calculates the UAV's real-time environmental adaptation index. The flight state response output module establishes a UAV kinematic model for airspace operations, inputs the flight behavior pattern data into the UAV kinematic model, and outputs the UAV's flight state response index. The maneuver strategy decision output module inputs the UAV's real-time environmental adaptation index and flight state response index into the UAV's maneuver strategy decision analysis model, evaluates the influence weight of the UAV's airspace operation environment, and outputs a behavior control strategy for the UAV under the current airspace operation.

[0068] The specific steps for each unit module in the UAV flight control data acquisition and control system based on intelligent sensors to implement the corresponding functions described above can be found in the steps of the embodiments of the UAV flight control data acquisition and control method based on intelligent sensors described above, and will not be repeated here.

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

[0070] The processor executes the aforementioned UAV flight control data acquisition and control method based on smart sensors by calling the computer program stored in the memory.

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

[0072] The processor may include one or more processing cores. The processor executes instructions, programs, code sets, or instruction sets stored in memory, and calls data stored in memory to perform various functions and process data as described in this application. The processor may 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 is understood that, for different devices, the electronic devices used to implement the above-described processor functions may also be other types, and the embodiments of this application do not specifically limit this.

[0073] It may also include a communication bus, which can include a pathway for transmitting information between the aforementioned 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 address bus, data bus, control bus, etc.

[0074] This embodiment also proposes a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the aforementioned UAV flight control data acquisition and control method based on intelligent sensors.

[0075] For example, computer-readable storage media can be read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, and optical data storage devices.

[0076] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A 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, all or part of the processes or functions according to the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, 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 and / or wireless network. A computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0077] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0078] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the foregoing application concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. A method for acquiring and controlling flight control data of unmanned aerial vehicles (UAVs) based on intelligent sensors, characterized in that, include: S1. Real-time recording of operational environment data and flight behavior pattern data during UAV airspace operations; S2. Import the operational environment data of the UAV in the airspace into the UAV's operational environment status analysis strategy, and calculate and obtain the UAV's real-time environmental adaptation index. S2 includes the following specific steps: S21. Obtain the environmental wind data of UAV airspace operation per unit time, and obtain the environmental interference assessment value of UAV airspace operation per unit time from the environmental wind data of UAV airspace operation per 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 assessment 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. Based on the environmental wind interference assessment value and air pressure interference assessment value of UAV airspace operation per unit time, the real-time environmental adaptation index of UAV per unit time is obtained. S3. Establish a UAV kinematic model for UAV airspace operations. Input the flight behavior pattern data of the UAV in airspace operations into the UAV kinematic model and output the UAV's flight state response index. S3 includes the following steps: S31. Acquire roll angle data, pitch angle data and yaw angle data of UAV airspace operations per unit time; S32. Import the roll angle data, pitch angle data, and yaw angle data of the UAV airspace operation per unit time into the UAV flight status response index calculation formula to calculate the UAV flight status response index per unit time. The flight status response index calculation formula is as follows: Where t is the data unit of time, Let be the roll angle at time t, which is the time interval of the i-th data unit. Let be the pitch angle at time t, which is the data unit time interval. Let yaw angle be the yaw angle at time t of the i-th data unit time interval, and dt be the integral over the data unit time. S4. Input the UAV's real-time environmental adaptation index and flight status response index into the UAV's maneuver strategy decision analysis model, evaluate the UAV's airspace operation environment influence weight, and output the behavior control strategy for the UAV under the current airspace operation.

2. The UAV flight control data acquisition and control method based on intelligent sensors as described in claim 1, characterized in that, S21 includes the following specific steps: importing the environmental wind data in the data unit time into the environmental wind interference assessment value calculation formula to calculate the environmental wind interference assessment value of the UAV airspace operation in the data unit time, wherein the environmental wind interference assessment value calculation formula is: Where i is the number corresponding to each data unit time, and i is any item from 1 to N. Let be the air density during the UAV's airspace operation in the i-th data unit time. Let be the velocity vector of the UAV in the airspace during the i-th data unit time. Let S be the lift coefficient during the UAV's airspace operation in the i-th data unit time, and S be the reference area of ​​the UAV wing. F is the angle between the wind and the flight direction of the drone during drone airspace operations. wind This is the set reference value for the wind speed's impact.

3. The UAV flight control data acquisition and control method based on intelligent sensors as described in claim 2, characterized in that, S22 includes the following specific steps: importing the pressure data and altitude data of the UAV airspace operation per unit time into the air pressure interference assessment value calculation formula to calculate the air pressure interference assessment value of the UAV airspace operation per unit time, wherein the air pressure interference assessment value calculation formula is: ,in, The air pressure at sea level, L i h represents the temperature decay rate of UAV airspace operations per unit time. i T represents the flight altitude of the UAV in the airspace during a unit of data time. 0,i Let g be the sea level temperature during UAV airspace operations per unit time, g0 be the gravitational acceleration, M be the molar mass of air, R be the gas constant, and P be the mass of air. h This represents the reference pressure at an airspace operating altitude of h for a given unit of time. This represents the permissible pressure variation value during drone airspace operations.

4. The UAV flight control data acquisition and control method based on intelligent sensors as described in claim 3, characterized in that, S23 includes the following steps: weighting the calculated environmental wind interference assessment value and air pressure interference assessment value of the UAV airspace operation per unit time and then summing them to obtain the UAV real-time environmental adaptation index.

5. The UAV flight control data acquisition and control method based on intelligent sensors as described in claim 4, characterized in that, The specific steps of S4 are as follows: S41. The impact assessment value of the UAV airspace operation environment per unit time is obtained from the UAV environmental real-time adaptation index and flight status response index per unit time. S42. Dynamically control the flight speed of UAVs during airspace operations based on the calculated environmental impact assessment value of UAV airspace operations per unit time.

6. A UAV flight control data acquisition and control system based on intelligent sensors, implemented based on the UAV flight control data acquisition and control method based on intelligent sensors according to any one of claims 1-5, characterized in that, Specifically, it includes an airspace operation data acquisition module, an operation environment status analysis module, a flight status response output module, and a maneuver strategy decision output module. The airspace operation data acquisition module is used to record the operation environment data and flight behavior pattern data of UAV airspace operations in real time. The operational environment status analysis module is used to import operational environment data from UAV airspace operations into the UAV operational environment status analysis strategy and calculate and obtain the UAV's real-time environmental adaptation index. The flight status response output module is used to establish a UAV kinematic model in UAV airspace operations, input flight behavior pattern data of UAV in airspace operations into the UAV kinematic model, and output the UAV flight status response index. The maneuver strategy decision output module is used to input the UAV's real-time environmental adaptation index and flight status response index into the UAV's maneuver strategy decision analysis model, evaluate the UAV's airspace operation environment influence weight, and output the behavior control strategy of the UAV under the current airspace operation.

7. An electronic device, comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor is characterized in that it executes the UAV flight control data acquisition and control method based on intelligent sensors as described in any one of claims 1-5 by calling a computer program stored in the memory.

8. A computer-readable storage medium, characterized in that, The system stores instructions that, when executed on a computer, cause the computer to perform the UAV flight control data acquisition and control method based on intelligent sensors as described in any one of claims 1-5.

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