CN114237279B - Wind speed and direction detector based on multi-rotor unmanned aerial vehicle and detection method thereof - Google Patents
Wind speed and direction detector based on multi-rotor unmanned aerial vehicle and detection method thereof Download PDFInfo
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Abstract
The invention belongs to the field of meteorological detection and the field of aircrafts, and discloses a wind speed and direction detector based on a multi-rotor unmanned aerial vehicle and a detection method thereof. The data acquisition unit comprises a flight data acquisition module and a control signal acquisition module; the flight control unit comprises a flight attitude control module and a flight position control unit. The real-time wind speed and direction output unit inputs the control signal data of the onboard central processing unit and the wind traveling data of the unmanned aerial vehicle, which are acquired in real time by the data acquisition unit, into a trained model to obtain the real-time wind speed and direction. The wind speed and direction detector does not need an additional sensor, can reduce dead weight of the unmanned aerial vehicle during working, and can enhance endurance. The wind speed and wind direction detection method is based on the data of the unmanned aerial vehicle, and is not easy to be interfered by the environment.
Description
Technical Field
The invention relates to the field of meteorological detection and the field of aircrafts, in particular to a wind speed and direction detector based on a multi-rotor unmanned aerial vehicle and a detection method thereof.
Background
The multi-rotor unmanned aerial vehicle has the characteristics of low cost, easy deployment and high maneuvering, can make up the defects of the traditional weather detection method in the aspects of small time range and small space scale, provides a data source for detailed weather detection, and plays an important role in the weather detection field. However, in the traditional meteorological detection method based on the multi-rotor unmanned aerial vehicle, meteorological loads such as a wind speed sensor, a wind direction sensor and the like are carried on the multi-rotor unmanned aerial vehicle. Because the multi-rotor unmanned aerial vehicle has the problems of poor endurance, small load installation space and poor wind resistance and severe environment resistance. The traditional meteorological unmanned aerial vehicle needs to carry more sensors on the unmanned aerial vehicle, and has larger load on the unmanned aerial vehicle; moreover, wind measuring equipment on the platform of the multi-rotor unmanned aerial vehicle can be disturbed by rotor turbulence, and the meteorological detection precision is affected.
At present, the modification of a multi-rotor unmanned aerial vehicle aiming at meteorological detection is mostly stopped at wind resistance and load installation space increase, and the problem of how to avoid the interference of wind fields of the rotor unmanned aerial vehicle by meteorological loads is still studied freshly. The Shen Aotuan team of national defense science and technology provides a set of method for reducing the wind field interference of the unmanned aerial vehicle, but the method only has relatively obvious improvement on the detection precision of temperature and humidity. Has no obvious effect on improving the detection precision of wind speed and wind direction.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a wind speed and direction detector based on a multi-rotor unmanned aerial vehicle and a detection method thereof.
The scheme of the invention is as follows:
the wind speed and direction detector based on the multi-rotor unmanned aerial vehicle comprises a data acquisition unit, a functional relation fitting unit, a flight control unit and a real-time wind speed and direction output unit, wherein the data acquisition unit comprises a flight attitude acquisition module and a control signal acquisition module;
the flight attitude acquisition module is used for acquiring flight attitude data and flight position data of the unmanned aerial vehicle and transmitting the flight attitude data and the flight position data to the airborne central processing unit;
the control signal acquisition module records a control signal for controlling the hovering of the unmanned aerial vehicle through an onboard central processing unit;
the functional relation fitting unit establishes a mapping relation between the rotating speed of the rotor wing of the unmanned aerial vehicle and the lifting force F born by the unmanned aerial vehicle; based on the mapping relation between the rotation speed of the rotor wing of the unmanned aerial vehicle and the rotation speed of the motor, the mapping relation between the rotation speed of the motor and the control signal of the airborne central processing unit is obtained, the mapping relation between the lifting force F borne by the unmanned aerial vehicle and the control signal of the airborne central processing unit is obtained, and function fitting is carried out according to the fact that the lifting force of the unmanned aerial vehicle when hovering in an indoor windless environment is equal to the gravity of the unmanned aerial vehicle, so that the function relation between the lifting force F borne by the unmanned aerial vehicle and the control signal of the airborne central processing unit is obtained;
the flight control unit is used for controlling the flight of the aircraft, keeping the flight stability of the aircraft, processing the flight attitude data and the flight position data of the unmanned aerial vehicle through the central processing unit, sending a control instruction to the controller, and adjusting the flight attitude and the flight position of the aircraft through the controller; the controller is used for receiving a control signal of the onboard central processing unit and controlling the rotating speed of the motor so as to adjust the flight attitude and the flight position of the aircraft;
the real-time wind speed and direction output unit acquires control signal data of the airborne central processing unit in real time through the data acquisition unit, and obtains the lift force of the unmanned aerial vehicle when hovering in a windy environment according to the functional relation between the lift force F of the unmanned aerial vehicle and the control signal of the airborne central processing unit; the unmanned aerial vehicle flight attitude acquired in real time through the data acquisition unit obtains the wind direction born by the unmanned aerial vehicle.
Further, the data acquisition unit comprises a gyroscope, a barometer and a GPS module.
Further, the flight control unit comprises a flight attitude control module and a flight position control module, wherein the flight attitude control module is used for controlling the unmanned aerial vehicle to keep the yaw angle of the unmanned aerial vehicle stable within a specified error range in a windy environment within a specified time, and the flight position control module is used for controlling the unmanned aerial vehicle to keep the altitude and the GPS position of the unmanned aerial vehicle stable within the specified error range within the specified time in the windy environment.
The invention also discloses a wind speed and direction detection method based on the multi-rotor unmanned aerial vehicle, which calculates wind power according to a control signal for controlling the stability of the unmanned aerial vehicle.
Further, the method comprises a functional relation fitting algorithm, wherein the functional relation fitting algorithm specifically comprises the following steps:
performing unmanned aerial vehicle hover simulation in an indoor windless environment, measuring the rotating speed of a rotor required by unmanned aerial vehicle hover, changing the weight of an aircraft, measuring a plurality of groups of data, and fitting a curve to obtain the mathematical relationship between the rotating speed of the rotor and the lift force provided by the rotating speed of the rotor, wherein the rotating speed of the rotor and the rotating speed of a motor have a linear relationship, the rotating speed of the motor and a control signal of an onboard central processor have a one-to-one mapping relationship, and the actual obtained mathematical relationship is between the control signal of the onboard central processor and the lift force of the rotor.
Further, the method comprises the steps of flight attitude control, wherein the unmanned aerial vehicle hovers in a windy environment through a flight control unit; the data collected by the flight attitude collection module comprise the yaw angle, the GPS position and the height of the unmanned aerial vehicle, the unmanned aerial vehicle is controlled by a control algorithm to keep the flight attitude and the flight position unchanged under the condition of air interference, namely, the data of the yaw angle, the GPS position, the height and the like of the unmanned aerial vehicle are kept unchanged, and the unmanned aerial vehicle is in a pitching hovering state at the moment.
Further, the flight attitude control calculates a flight data difference between two moments of the unmanned aerial vehicle by using a least square method, and when the value is smaller than an allowable error delta and lasts for a specified time t, the flight attitude and the flight position of the unmanned aerial vehicle are considered to be stable, a yaw angle of the unmanned aerial vehicle is set as alpha, and when the following formula is satisfied, the advancing direction of the unmanned aerial vehicle is considered to be unchanged:
(α 1 -α 2 ) 2 <Δ
(α 1 -α 3 ) 2 <Δ
(α 1 -α n ) 2 <Δ
t 1 -t n >t
further, the method comprises a wind power magnitude detection algorithm, wherein the wind power magnitude detection algorithm is as follows: the unmanned aerial vehicle hovers in a windy environment through the flight control module; the control signals of the motors corresponding to each rotor wing during hovering are obtained through an onboard central processing unit; according to the mathematical relationship between the control signals and the lift force of the rotor wings, the lift force provided by each rotor wing is obtained, and according to the lift force and the weight of the unmanned aerial vehicle, the wind force F borne by the unmanned aerial vehicle can be obtained w The size, formula is as follows:
F·cosθ＝mg
F w ＝F·sinθ。
further, the wind direction detection method comprises the following steps: the flight control module obtains the information of the aircraft height and the aircraft deflection angle by reading the numerical values of the internal sensor elements, transmits the information to the airborne central processing unit, and obtains the advancing direction of the unmanned aerial vehicle in the windy environment when the unmanned aerial vehicle hovers, namely the opposite direction of the wind direction according to the deflection angle and the initial advancing direction of the aircraft.
The beneficial effects of the invention are as follows:
(1) The wind speed and direction detector does not need an additional sensor, directly obtains the wind speed and the wind direction from the rotating speed of the rotor wing, reduces the dead weight of the unmanned aerial vehicle during operation, enhances the endurance and improves the wind measuring precision.
(2) The wind speed and wind direction detection method is based on the data of the unmanned aerial vehicle, and is not easy to be interfered by the environment.
Drawings
FIG. 1 is a block diagram of the overall structure of the present invention;
FIG. 2 (a) is a three-dimensional spatial coordinate top view of the unmanned aerial vehicle of the present invention;
FIG. 2 (b) is a three-dimensional spatial coordinate elevation view of the unmanned aerial vehicle of the present invention;
FIG. 3 is a schematic diagram of wind power calculation according to the present invention;
FIG. 4 is a schematic view of wind direction calculation according to the present invention.
Detailed Description
In order to describe the wind speed and direction detector and the detection method based on the multi-rotor unmanned aerial vehicle in more detail, the present invention is described in detail below with reference to the accompanying drawings.
As shown in FIG. 1, the wind speed and direction detector based on the multi-rotor unmanned aerial vehicle comprises a data acquisition unit, a functional relation fitting unit, a flight control unit and a real-time wind speed and direction output unit. Wherein:
the data acquisition unit comprises a flight attitude acquisition module and a control signal acquisition module.
The flight attitude acquisition module is used for acquiring flight attitude data and flight position data of the unmanned aerial vehicle and transmitting the flight attitude data and the flight position data to the airborne central processing unit; the flight attitude acquisition module comprises a gyroscope, a barometer and a GPS module.
The control signal acquisition module records a control signal for controlling the unmanned aerial vehicle to hover through the onboard central processing unit.
The function relation fitting unit firstly establishes a mapping relation between the rotating speed of the rotor wing of the unmanned aerial vehicle and the lifting force F born by the unmanned aerial vehicle; based on the mapping relation between the rotation speed of the rotor wing of the unmanned aerial vehicle and the rotation speed of the motor, the mapping relation exists between the rotation speed of the motor and the control signal of the onboard central processing unit, and the mapping relation between the lifting force F borne by the unmanned aerial vehicle and the control signal of the onboard central processing unit can be obtained. And performing function fitting according to the fact that the lifting force of the unmanned aerial vehicle when hovering in an indoor windless environment is equal to the gravity of the unmanned aerial vehicle, and obtaining a functional relation between the lifting force F borne by the unmanned aerial vehicle and a control signal of an onboard central processing unit.
The flight control unit is used for controlling the flight of the aircraft and keeping the stability of the flight of the aircraft. The flight attitude data and the flight position data of the unmanned aerial vehicle are processed through the central processing unit, a control instruction is sent to the controller, and the flight attitude and the flight position of the aircraft are adjusted through the controller; the controller is used for receiving control signals of the onboard central processing unit and controlling the rotating speed of the motor so as to adjust the flight attitude and the flight position of the aircraft. The flight control unit comprises a flight attitude control module and a flight position control module.
The flight attitude control module is used for controlling the unmanned aerial vehicle to keep the yaw angle of the unmanned aerial vehicle stable within a specified error range in a windy environment.
The flying position control module is used for controlling the unmanned aerial vehicle to keep the altitude and the GPS position stable within a specified error range in a windy environment.
The real-time wind speed and direction output unit acquires control signal data of the airborne central processing unit in real time through the data acquisition unit, and obtains the lift force of the unmanned aerial vehicle when hovering in a windy environment according to the functional relation between the lift force F of the unmanned aerial vehicle and the control signal of the airborne central processing unit; and acquiring the flight attitude of the unmanned aerial vehicle in real time through a data acquisition unit to obtain the wind direction of the unmanned aerial vehicle.
Further, the flight control unit keeps the flight stability of the aircraft, and specifically, the unmanned aerial vehicle hovers in a windy environment through the flight control module; the flying attitude of the unmanned aerial vehicle can change in a windy environment, and the data acquired by the flying attitude acquisition module comprise the yaw angle, the GPS position, the height and the like of the unmanned aerial vehicle. The unmanned aerial vehicle is controlled by a control algorithm to keep the flight attitude and the flight position unchanged under the influence of air, namely, the data such as the yaw angle, the GPS position, the height and the like of the unmanned aerial vehicle are kept unchanged within a specified error range, and the unmanned aerial vehicle is in a pitching hovering state at the moment.
Further, the data such as the yaw angle, the GPS position and the altitude of the unmanned aerial vehicle are kept unchanged within a specified error range, specifically, a least square method is used for calculating the flight data difference between two moments of the unmanned aerial vehicle, and when the value is smaller than the allowable error delta and lasts for a specified time t, the flight attitude and the flight position of the unmanned aerial vehicle are considered to be stable.
Further, the wind power level detection algorithm is as follows: the unmanned aerial vehicle hovers in a windy environment through the flight control module; the control signals of the motors corresponding to each rotor wing during hovering are obtained through an onboard central processing unit; the lift provided by each rotor is derived from the mathematical relationship between the control signal and the rotor lift described above. According to the lifting force F and the weight mg of the unmanned aerial vehicle, the wind force F borne by the unmanned aerial vehicle can be obtained w Size of the product. The formula is as follows:
F·cosθ＝mg
F w ＝F·sinθ
further, the wind direction detection algorithm is as follows: the flight control module obtains information such as the aircraft altitude, the aircraft deflection angle and the like by reading the numerical values of the internal sensor elements, and transmits the information to the onboard central processing unit. And obtaining the advancing direction of the unmanned aerial vehicle in the windy environment when the unmanned aerial vehicle hovers, namely the opposite direction of the wind direction, according to the deflection angle and the initial advancing direction of the aircraft.
Specifically, the wind speed and direction detector based on the multi-rotor unmanned aerial vehicle can be just one multi-rotor unmanned aerial vehicle with a flight control function and a central processing unit. The sensor that many rotor unmanned aerial vehicle was used for flight control can regard as the flight gesture collection module of data acquisition unit, and central processing unit can regard as real-time wind speed wind direction output unit. The model training unit in the invention can be completed on other equipment, and the obtained model is directly input into the central processing unit.
Examples
The following takes a four-rotor unmanned aerial vehicle with a flight control module and a central processing unit as an example, and the specific working steps are as follows:
1) Fitting a functional relation: as shown in fig. 2 (a) and 2 (b), the three-dimensional space coordinate schematic diagram of the unmanned aerial vehicle is shown, unmanned aerial vehicle hovering simulation is carried out in an indoor windless environment, and the rotating speed of a rotor wing required by unmanned aerial vehicle hovering is measured. And changing the weight of the aircraft, measuring a plurality of groups of data, and fitting a curve to obtain the mathematical relationship between the rotating speed of the rotor wing and the lift force provided by the rotating speed of the rotor wing. The rotor rotation speed and the motor rotation speed have a linear relation, the motor rotation speed and the control signal of the airborne central processing unit have a one-to-one mapping relation, and the mathematical relation between the control signal of the airborne central processing unit and the rotor lift force is actually obtained.
2) Flight attitude control: the unmanned aerial vehicle hovers in a windy environment through the flight control unit; specifically, the flying attitude of the unmanned aerial vehicle can change in a windy environment, and the data collected by the flying attitude collecting module comprise the yaw angle, the GPS position, the height and the like of the unmanned aerial vehicle. The unmanned aerial vehicle is controlled by a control algorithm to keep the flight attitude and the flight position unchanged under the influence of air, namely, the data such as the yaw angle, the GPS position, the height and the like of the unmanned aerial vehicle are kept unchanged, and the unmanned aerial vehicle is in a pitching hovering state at the moment.
Further, the least square method is utilized to calculate the flight data difference between two moments of the unmanned aerial vehicle, and when the value is smaller than the allowable error delta and lasts for a specified time t, the flight attitude and the flight position of the unmanned aerial vehicle are considered to be stable. Taking the yaw angle α of the unmanned aerial vehicle as an example, the forward direction of the unmanned aerial vehicle is considered unchanged when the following equation is satisfied:
(α 1 -α 2 ) 2 <Δ
(α 1 -α 3 ) 2 <Δ
(α 1 -α n ) 2 <Δ
t 1 -t n >t
3) Wind power detection algorithm: as shown in FIG. 3, the flying control unit controls the unmanned aerial vehicle to maintain hovering of the flying attitude in the windy environment, and the flying attitude is obtained through the onboard central processing unitA control signal of a motor corresponding to each rotor wing during hovering; the lift provided by each rotor is derived from the mathematical relationship between the control signal and the rotor lift described above. According to the lifting force and the weight of the unmanned aerial vehicle, the wind power F borne by the unmanned aerial vehicle can be obtained w Size of the product. The formula is as follows:
F·cosθ＝mg
F w ＝F·sinθ
4) Wind direction detection algorithm: as shown in fig. 4, the flight control module obtains information such as aircraft altitude, aircraft yaw angle, etc. by reading the values of the internal sensor elements, and transmits the information to the onboard central processor. And obtaining the advancing direction of the unmanned aerial vehicle in the windy environment when the unmanned aerial vehicle hovers, namely the opposite direction of the wind direction, according to the deflection angle and the initial advancing direction of the aircraft.
The above-described embodiments are intended to illustrate the present invention, not to limit it, and any modifications and variations made thereto are within the spirit of the invention and the scope of the appended claims.
Claims (3)
1. The wind speed and direction detector comprises a data acquisition unit, a functional relation fitting unit, a flight control unit and a real-time wind speed and direction output unit, wherein the data acquisition unit comprises a flight attitude acquisition module and a control signal acquisition module;
the flight attitude acquisition module is used for acquiring flight attitude data and flight position data of the unmanned aerial vehicle and transmitting the flight attitude data and the flight position data to the airborne central processing unit;
the control signal acquisition module records a control signal for controlling the hovering of the unmanned aerial vehicle through an onboard central processing unit;
the functional relation fitting unit establishes a mapping relation between the rotating speed of the rotor wing of the unmanned aerial vehicle and the lifting force F born by the unmanned aerial vehicle; based on the mapping relation between the rotation speed of the rotor wing of the unmanned aerial vehicle and the rotation speed of the motor, the mapping relation between the rotation speed of the motor and the control signal of the airborne central processing unit is obtained, the mapping relation between the lifting force F borne by the unmanned aerial vehicle and the control signal of the airborne central processing unit is obtained, and function fitting is carried out according to the fact that the lifting force of the unmanned aerial vehicle when hovering in an indoor windless environment is equal to the gravity of the unmanned aerial vehicle, so that the function relation between the lifting force F borne by the unmanned aerial vehicle and the control signal of the airborne central processing unit is obtained;
the flight control unit is used for controlling the flight of the aircraft, keeping the flight stability of the aircraft, processing the flight attitude data and the flight position data of the unmanned aerial vehicle through the central processing unit, sending a control instruction to the controller, and adjusting the flight attitude and the flight position of the aircraft through the controller; the controller is used for receiving a control signal of the onboard central processing unit and controlling the rotating speed of the motor so as to adjust the flight attitude and the flight position of the aircraft;
the real-time wind speed and direction output unit acquires control signal data of the airborne central processing unit in real time through the data acquisition unit, and obtains the lift force of the unmanned aerial vehicle when hovering in a windy environment according to the functional relation between the lift force F of the unmanned aerial vehicle and the control signal of the airborne central processing unit; the unmanned aerial vehicle flight attitude acquired in real time through the data acquisition unit obtains the wind direction born by the unmanned aerial vehicle;
the method is characterized in that wind power is calculated according to a control signal for controlling the stability of the unmanned aerial vehicle;
the method comprises a functional relation fitting algorithm, wherein the functional relation fitting algorithm specifically comprises the following steps:
performing unmanned aerial vehicle hover simulation in an indoor windless environment, measuring the rotating speed of a rotor required by unmanned aerial vehicle hover, changing the weight of an aircraft, measuring a plurality of groups of data, and fitting a curve to obtain the mathematical relationship between the rotating speed of the rotor and the lift force provided by the rotating speed of the rotor, wherein the rotating speed of the rotor and the rotating speed of a motor have a linear relationship, and the rotating speed of the motor and a control signal of an onboard central processor have a one-to-one mapping relationship, so that the mathematical relationship between the control signal of the onboard central processor and the lift force of the rotor is actually obtained; the unmanned aerial vehicle hovers in a windy environment through a flight control unit; the data acquired by the flight attitude acquisition module comprise the yaw angle, the GPS position and the height of the unmanned aerial vehicle, the unmanned aerial vehicle is controlled by a control algorithm to keep the flight attitude and the flight position unchanged under the condition of air interference, namely, the data such as the yaw angle, the GPS position and the height of the unmanned aerial vehicle are kept unchanged, and the unmanned aerial vehicle is in a pitching hovering state at the moment;
the flight attitude control calculates the flight data difference between two moments of the unmanned aerial vehicle by using a least square method, and when the flight data difference is smaller than an allowable error delta and lasts for a specified time t, the flight attitude and the flight position of the unmanned aerial vehicle are considered to be stable, the yaw angle of the unmanned aerial vehicle is set as alpha, and when the following formula is satisfied, the advancing direction of the unmanned aerial vehicle is considered to be unchanged:
(α 1 -α 2 ) 2 <Δ
(α 1 -α 3 ) 2 <Δ
(α 1 -α n ) 2 <Δ
t 1 -t n >t；
the wind power generation method comprises a wind power magnitude detection algorithm, wherein the wind power magnitude detection algorithm is as follows: the unmanned aerial vehicle hovers in a windy environment through the flight control module; the control signals of the motors corresponding to each rotor wing during hovering are obtained through an onboard central processing unit; according to the mathematical relationship between the control signals and the lift force of the rotor wings, the lift force provided by each rotor wing is obtained, and according to the lift force and the weight of the unmanned aerial vehicle, the wind force F borne by the unmanned aerial vehicle can be obtained w The size, formula is as follows:
F·cosθ＝mg
F w ＝F·sinθ；
the wind power direction detection method comprises a wind power direction detection algorithm, wherein the wind power direction detection algorithm is as follows: the flight control module obtains the information of the aircraft height and the aircraft deflection angle by reading the numerical values of the internal sensor elements, transmits the information to the airborne central processing unit, and obtains the advancing direction of the unmanned aerial vehicle in the windy environment when the unmanned aerial vehicle hovers, namely the opposite direction of the wind direction according to the deflection angle and the initial advancing direction of the aircraft.
2. The method of claim 1, wherein the data acquisition unit comprises a gyroscope, a barometer, and a GPS module.
3. The method of claim 2, wherein the flight control unit comprises a flight attitude control module for controlling the drone to maintain its yaw angle stable within a specified error range for a specified time in a windy environment, and a flight position control module for controlling the drone to maintain its altitude and GPS position stable within a specified error range for a specified time in a windy environment.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20180031298A (en) * | 2016-09-19 | 2018-03-28 | 쓰리디토시스 주식회사 | The drone with the real time weather complex observation sensors such as self sensing of the direction and velocity of wind |
| CN111413997A (en) * | 2020-04-14 | 2020-07-14 | 中国人民解放军32180部队 | High-wind-resistance tilting rotor mooring unmanned aerial vehicle and flight control method thereof |
| JP6729884B1 (en) * | 2019-04-09 | 2020-07-29 | 国立大学法人秋田大学 | Wind direction wind speed measurement method and wind direction wind speed measurement system |
| CN112114383A (en) * | 2020-10-30 | 2020-12-22 | 南京多基观测技术研究院有限公司 | High-spatial-temporal-resolution wind measurement system and wind measurement method based on multi-rotor unmanned aerial vehicle |
| CN112986612A (en) * | 2021-03-24 | 2021-06-18 | 中国人民解放军63796部队 | Low-altitude moving type wind speed measuring method based on quad-rotor unmanned aerial vehicle |
-
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- 2021-11-24 CN CN202111402932.5A patent/CN114237279B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20180031298A (en) * | 2016-09-19 | 2018-03-28 | 쓰리디토시스 주식회사 | The drone with the real time weather complex observation sensors such as self sensing of the direction and velocity of wind |
| JP6729884B1 (en) * | 2019-04-09 | 2020-07-29 | 国立大学法人秋田大学 | Wind direction wind speed measurement method and wind direction wind speed measurement system |
| CN111413997A (en) * | 2020-04-14 | 2020-07-14 | 中国人民解放军32180部队 | High-wind-resistance tilting rotor mooring unmanned aerial vehicle and flight control method thereof |
| CN112114383A (en) * | 2020-10-30 | 2020-12-22 | 南京多基观测技术研究院有限公司 | High-spatial-temporal-resolution wind measurement system and wind measurement method based on multi-rotor unmanned aerial vehicle |
| CN112986612A (en) * | 2021-03-24 | 2021-06-18 | 中国人民解放军63796部队 | Low-altitude moving type wind speed measuring method based on quad-rotor unmanned aerial vehicle |
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