CN109541963B - Unmanned aerial vehicle wind measurement modeling method based on sideslip angle information - Google Patents

Unmanned aerial vehicle wind measurement modeling method based on sideslip angle information Download PDF

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CN109541963B
CN109541963B CN201811337127.7A CN201811337127A CN109541963B CN 109541963 B CN109541963 B CN 109541963B CN 201811337127 A CN201811337127 A CN 201811337127A CN 109541963 B CN109541963 B CN 109541963B
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aerial vehicle
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sideslip angle
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Beijing Institute Of Applied Meteorology
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Abstract

The invention is suitable for the field of atmospheric science, and provides an unmanned aerial vehicle wind measurement modeling method based on sideslip angle information, which comprises the following steps: establishing a horizontal side open-loop control model of the unmanned aerial vehicle; establishing a horizontal and lateral closed-loop navigation model of the unmanned aerial vehicle; establishing a relation model between actual measurement and sideslip angle; and establishing a wind field estimation model by utilizing the vector triangular relation of wind speed, ground speed and airspeed. According to the method provided by the invention, a sideslip angle sensor is not required to be installed, the wind field estimation model is perfected by establishing the unmanned aerial vehicle sideslip angle estimation model, the wind field estimation accuracy is improved, and the method is low in cost, simple and feasible. In addition, the method has the advantages of large wind measuring range and high frequency, can be used for measuring real-time continuous wind field information in larger areas including areas where people are not easy to reach and in severe weather, and has higher engineering application value.

Description

Unmanned aerial vehicle wind measurement modeling method based on sideslip angle information
Technical Field
The invention belongs to the field of atmospheric science, and relates to an unmanned aerial vehicle wind measurement modeling method based on sideslip angle information.
Background
The wind detection has important significance for knowing the atmospheric motion condition and improving the accuracy of weather forecast, and is an important means for researching global climate change. The current wind measuring and estimating methods include anemometry by an anemometer, anemometry by an balloon method, radar anemometry and unmanned aerial vehicle anemometry. The anemometry of the anemometer is usually used for measuring wind on the ground, so that only near-ground wind field information can be obtained; the balloon method is used for measuring wind energy to obtain wind field information of different height layers from the ground to the high altitude, the detection precision and the detection height are high, but the detection cost is high, the detection area is small, a large number of balloons are needed if large-range wind field information is obtained, and the economy is low; the radar wind measurement is suitable for researching wind field information of specific height of a specific area, has high detection precision, is easily influenced by weather and has high manufacturing cost. Along with the development of unmanned aerial vehicle technique, unmanned aerial vehicle has advantages such as the detection area is big, the time of endurance is long, the continuity is good, the cost is relatively lower, environmental suitability is high, the use is nimble convenient, unmanned aerial vehicle anemometry has obtained wide application increasingly.
The unmanned aerial vehicle wind measurement method can be divided into a horizontal airspeed return-to-zero method, an analytic wind measurement method, a dead reckoning method and a pitot-static pressure tube wind measurement method in terms of measurement principle. The documents of the invention, namely the research on unmanned aerial vehicle anemometry technology (sensor world, 2014) and the invention application (patent application No. 201711064897.4 and application date 2017.11.02) named as a method for calculating wind speed and wind direction based on flight parameters, analyze an airborne anemometry means and the prior related background technology for measuring wind speed and wind direction. Compared with the application and other related technologies, the unmanned aerial vehicle anemometry algorithm usually ignores the influence of the sideslip angle, but the sideslip angle always exists in the flight process of the airplane and is important information in airplane control and navigation, and the accuracy of control of each part is influenced by ignoring the sideslip angle information. At present, the measurement of the sideslip angle is mainly realized by a vane type sensor, a differential pressure tube type sensor and a zero differential pressure type sensor which are arranged on an airplane, and the sensors are influenced by local circulation related to icing and flight states and almost inevitably subjected to large zero point deviation. In addition, a sideslip angle sensor on the aircraft interferes with the airflow, so that the airflow field at different positions on the aircraft is different from an ideal flow field, and a local sideslip angle is generated. Therefore, even if a slip angle sensor is present, it is difficult to make an accurate measurement. In order to improve the wind measurement precision of the unmanned aerial vehicle, sideslip angle information is added into a wind measurement algorithm, and the establishment of a sideslip angle estimation model has very important practical significance in consideration of the characteristic that the sideslip angle is difficult to measure accurately. On the basis, a wind field estimation model based on sideslip angle information is established, and finally the purpose of improving a wind measurement algorithm is achieved.
Disclosure of Invention
In order to meet the urgent need of the unmanned aerial vehicle wind measurement on accurate sideslip angle information, the invention aims to provide an unmanned aerial vehicle wind measurement modeling method based on sideslip angle information, and aims to solve wind field information by establishing a sideslip angle estimation model and applying the sideslip angle estimation model to an unmanned aerial vehicle wind measurement estimation model and further adopting a vector triangle algorithm.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: an unmanned aerial vehicle anemometry modeling method based on sideslip angle information comprises the following steps:
step one, establishing a horizontal side open-loop control model of the unmanned aerial vehicle, specifically:
the state space equation for the transverse lateral open-loop control model can be expressed as the following form
Figure GSB0000193371730000011
In the formula (I), the compound is shown in the specification,
Figure GSB0000193371730000012
in order to be a state quantity,
Figure GSB0000193371730000013
in the form of a matrix of states,
Figure GSB0000193371730000014
in order to input the matrix, the input matrix is,
Figure GSB0000193371730000021
is an input quantity; beta is a sideslip angle, p is a roll angle rate, r is a yaw angle rate, and phi is a roll angle; y isb、Yp、Yr、Yph、Lb、Lp、Lx、Nb、Np、Nr、Yda、Ydr、Lda、Ldr、Nda、NdrThe parameters of the unmanned aerial vehicle in the transverse direction can be calculated according to the pneumatic parameters and the control parameters given by the unmanned aerial vehicle; deltaa、δrThe rudder deflection angle of the rudder and the ailerons;
the equation of the horizontal and lateral open-loop control model of the unmanned aerial vehicle is obtained by the formula (1)
Figure GSB0000193371730000022
Step two, establishing a horizontal and lateral closed-loop navigation model of the unmanned aerial vehicle, specifically:
given unmanned aerial vehicle heading psigThen, the flight control law can be given as
Figure GSB0000193371730000023
Where ψ is the heading angle, kp、kφ、kψ、kr、kφrCoefficients related to p, phi, psi, r, respectively;
substituting (3) into (2) to obtain
Figure GSB0000193371730000024
For the same reason have
Figure GSB0000193371730000025
Figure GSB0000193371730000026
Figure GSB0000193371730000027
Figure GSB0000193371730000028
The unmanned aerial vehicle transverse and lateral closed-loop navigation equation is obtained as
Figure GSB0000193371730000031
If the unmanned aerial vehicle is not provided with the sideslip angle sensor, the sideslip angle contained in the equation (9) can be indirectly obtained by measuring the roll angle information, and meanwhile, the measured sideslip angle information is filtered through a Kalman filter, so that the method can realize unbiased estimation of the sideslip angle and has higher theoretical precision;
step three, establishing a relation model between actual measurement and sideslip angle, specifically:
the airspeed component under the coordinate system of the body is
Figure GSB0000193371730000032
In the formula, VaIs airspeed, α is angle of attack, Vxb、Vyb、VzbIs airspeed component under the machine body system;
the airspeed component in the inertial frame is
Figure GSB0000193371730000033
In the formula, Vx、Vy、VzIs the airspeed component on the x, y and z axes under the inertial coordinate system,
Figure GSB0000193371730000034
converting coordinates from a body coordinate system to an inertial coordinate system;
Figure GSB0000193371730000035
wherein theta is a pitch angle,
Figure GSB0000193371730000036
is the track azimuth;
by expanding equation (12)
Figure GSB0000193371730000037
Step four, establishing a wind field estimation model by utilizing a vector triangle relation among wind speed, ground speed and airspeed, namely taking sideslip angle data as a variable in wind field estimation, and obtaining wind field information through a vector triangle together with the ground speed measured by a GPS, an attitude angle measured by a gyroscope and the airspeed measured by an airspeed tube;
the vector triangular relation between the wind speed and the airspeed and the ground speed of the aircraft obtains a wind speed expression as
Figure GSB0000193371730000038
In the formula (I), the compound is shown in the specification,
Figure GSB0000193371730000039
in order to obtain the ground speed,
Figure GSB00001933717300000310
in order to be the space velocity,
Figure GSB00001933717300000311
is the wind speed;
the formula (14) can be specifically expressed as
Figure GSB0000193371730000041
In the formula, VDx、VDy、VDzIs the component of the wind speed on the x, y and z axes under the inertial coordinate system,
Figure GSB0000193371730000042
calculated ground speed components for the GPS-based position measurements in the x, y, and z axes of the inertial frame.
The unmanned aerial vehicle anemometry modeling method based on sideslip angle information provided by the invention has the following beneficial effects:
(1) according to the method, a sideslip angle sensor is not required to be installed, the unmanned aerial vehicle sideslip angle estimation model is established, the wind field estimation model is perfected, the wind field estimation accuracy is improved, and the method is low in cost, simple and easy to implement;
(2) the method has the advantages of large wind measuring range and high frequency, can be used for measuring real-time continuous wind field information in larger areas including areas which are difficult to reach by human beings and severe weather, and has higher engineering application value.
Drawings
The invention is further described with reference to the following figures and detailed description.
FIG. 1 is a block diagram of a course-preserving model of an unmanned aerial vehicle;
FIG. 2 is a schematic diagram of a speed coordinate system and a body coordinate system;
FIG. 3 is a schematic diagram of an inertial coordinate system and a body coordinate system;
fig. 4 is a schematic view of a wind field vector triangle.
Detailed Description
In order to make the technical solution of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
Step one, establishing a horizontal side open-loop control model of the unmanned aerial vehicle. FIG. 1 is a block diagram of a fixed-wing drone heading maintenance model, in which the dotted line square frame ranges are a drone lateral open-loop control model. Can be expressed in the form of the following by the equation of state space
Figure GSB0000193371730000043
In the formula (I), the compound is shown in the specification,
Figure GSB0000193371730000044
in order to be a state quantity,
Figure GSB0000193371730000045
in the form of a matrix of states,
Figure GSB0000193371730000046
in order to input the matrix, the input matrix is,
Figure GSB0000193371730000047
is an input quantity; beta is a sideslip angle, p is a roll angle rate, r is a yaw angle rate, and phi is a roll angle; y isb、Yp、Yr、Yph、Lb、Lp、Lr、Nb、Np、Nr、Yda、Ydr、Lda、Ldr、Nda、NdrFor defining the lateral parameters of the unmanned planeThe number can be calculated according to the pneumatic parameters and the control parameters given by the unmanned aerial vehicle; deltaa、δrThe rudder deflection angle of the rudder and the ailerons;
the equation of the horizontal and lateral open-loop control model of the unmanned aerial vehicle is obtained by the formula (1)
Figure GSB0000193371730000051
Step two, establishing a horizontal and lateral closed-loop navigation model of the unmanned aerial vehicle, specifically:
given unmanned aerial vehicle heading angle psigThen, the flight control law can be given as
Figure GSB0000193371730000052
Where ψ is the heading angle, kp、kφ、kψ、kr、kφrCoefficients related to p, phi, psi, r, respectively;
substituting (3) into (2) to obtain
Figure GSB0000193371730000053
For the same reason have
Figure GSB0000193371730000054
Figure GSB0000193371730000055
Figure GSB0000193371730000056
Figure GSB0000193371730000057
The unmanned aerial vehicle transverse and lateral closed-loop navigation equation is obtained as
Figure GSB0000193371730000058
If the drone does not have a sideslip angle sensor, the sideslip angle contained in equation (9) can be indirectly obtained by measuring the roll angle information, while filtering the measured sideslip angle information through a Kalman filter. The method can realize unbiased estimation of the sideslip angle, and has higher theoretical precision;
and step three, establishing a relation model between actual measurement and sideslip angle. FIG. 2 is a schematic diagram of a speed coordinate system and a body coordinate system. According to FIG. 2, the airspeed component in the body coordinate system can be expressed as
Figure GSB0000193371730000061
In the formula, VaIs airspeed, α is angle of attack, Vxb、Vyb、VzbIs airspeed component under the machine body system;
FIG. 3 is a schematic diagram of an inertial coordinate system and a body coordinate system. According to FIG. 3, the airspeed component in the inertial frame may be expressed as
Figure GSB0000193371730000062
In the formula, Vx、Vy、VzIs the airspeed component on the x, y and z axes under the inertial coordinate system,
Figure GSB0000193371730000063
converting coordinates from a body coordinate system to an inertial coordinate system;
Figure GSB0000193371730000064
in the formula (I), the compound is shown in the specification,theta is a pitch angle and theta is a pitch angle,
Figure GSB0000193371730000065
is the track azimuth;
by expanding equation (12)
Figure GSB0000193371730000066
And step four, establishing a wind field estimation model by utilizing a vector triangle relation among wind speed, ground speed and airspeed, namely taking sideslip angle data as a variable in wind field estimation, and obtaining wind field information through a vector triangle together with the ground speed measured by a GPS, the attitude angle measured by a gyroscope and the airspeed measured by an airspeed head. FIG. 4 is a vector triangle diagram of wind speed, ground speed and airspeed. According to FIG. 4, the wind speed can be represented as
Figure GSB0000193371730000067
In the formula (I), the compound is shown in the specification,
Figure GSB0000193371730000068
in order to obtain the ground speed,
Figure GSB0000193371730000069
in order to be the space velocity,
Figure GSB00001933717300000610
is the wind speed;
equation (14) can be expressed specifically as:
Figure GSB00001933717300000611
in the formula, VDx、VDy、VDzIs the component of the wind speed on the x, y and z axes under the inertial coordinate system,
Figure GSB00001933717300000612
calculated ground speed components for the GPS-based position measurements in the x, y, and z axes of the inertial frame.

Claims (1)

1. An unmanned aerial vehicle anemometry modeling method based on sideslip angle information is characterized by comprising the following steps:
step one, establishing a horizontal side open-loop control model of the unmanned aerial vehicle, specifically:
the state space equation for the transverse lateral open-loop control model can be expressed as the following form
Figure FSB0000193371720000011
In the formula (I), the compound is shown in the specification,
Figure FSB0000193371720000012
in order to be a state quantity,
Figure FSB0000193371720000013
in the form of a matrix of states,
Figure FSB0000193371720000014
in order to input the matrix, the input matrix is,
Figure FSB0000193371720000015
is an input quantity; beta is a sideslip angle, p is a roll angle rate, r is a yaw angle rate, and phi is a roll angle; y isb、Yp、Yr、Yph、Lb、Lp、Lr、Nb、Np、Nr、Yda、Ydr、Lda、Ldr、Nda、NdrThe parameters of the unmanned aerial vehicle in the transverse direction can be calculated according to the pneumatic parameters and the control parameters given by the unmanned aerial vehicle; deltaa、δrThe rudder deflection angle of the rudder and the ailerons;
the equation of the horizontal and lateral open-loop control model of the unmanned aerial vehicle is obtained by the formula (1)
Figure FSB0000193371720000016
Step two, establishing a horizontal and lateral closed-loop navigation model of the unmanned aerial vehicle, specifically:
given unmanned aerial vehicle heading psigThen, the flight control law can be given as
Figure FSB0000193371720000017
Where ψ is the heading angle, kp、kφ、kψ、kr、kφrCoefficients related to p, phi, psi, r, respectively;
substituting (3) into (2) to obtain
Figure FSB0000193371720000018
For the same reason have
Figure FSB0000193371720000019
Figure FSB0000193371720000021
Figure FSB0000193371720000022
Figure FSB0000193371720000023
The unmanned aerial vehicle transverse and lateral closed-loop navigation equation is obtained as
Figure FSB0000193371720000024
If the unmanned aerial vehicle is not provided with the sideslip angle sensor, the sideslip angle contained in the equation (9) can be indirectly obtained by measuring the roll angle information, and meanwhile, the measured sideslip angle information is filtered through a Kalman filter, so that the method can realize unbiased estimation of the sideslip angle and has higher theoretical precision;
step three, establishing a relation model between actual measurement and sideslip angle, specifically:
the airspeed component under the coordinate system of the body is
Figure FSB0000193371720000025
In the formula, VaIs airspeed, α is angle of attack, Vxb、Vyb、VzbIs airspeed component under the coordinate system of the machine body;
the airspeed component in the inertial frame is
Figure FSB0000193371720000026
In the formula, Vx、Vy、VzIs the airspeed component on the x, y and z axes under the inertial coordinate system,
Figure FSB0000193371720000027
converting coordinates from a body coordinate system to an inertial coordinate system;
Figure FSB0000193371720000028
wherein theta is a pitch angle,
Figure FSB0000193371720000029
is the track azimuth;
by expanding equation (12)
Figure FSB00001933717200000210
Step four, establishing a wind field estimation model by utilizing a vector triangle relation among wind speed, ground speed and airspeed, namely taking sideslip angle data as a variable in wind field estimation, and obtaining wind field information through a vector triangle together with the ground speed measured by a GPS, an attitude angle measured by a gyroscope and the airspeed measured by an airspeed tube;
the vector triangular relation between the wind speed and the airspeed and the ground speed of the aircraft obtains a wind speed expression as
Figure FSB0000193371720000031
In the formula (I), the compound is shown in the specification,
Figure FSB0000193371720000032
in order to obtain the ground speed,
Figure FSB0000193371720000033
in order to be the space velocity,
Figure FSB0000193371720000034
is the wind speed;
the formula (14) can be specifically expressed as
Figure FSB0000193371720000035
In the formula, VDx、VDy、VDzIs the component of the wind speed on the x, y and z axes under the inertial coordinate system,
Figure FSB0000193371720000036
solving for GPS-based position measurements in the x, y, z axes of an inertial coordinate systemThe ground speed component of (a).
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CN111693999B (en) * 2020-05-27 2023-05-05 哈尔滨工程大学 Multi-sensor fusion wind speed and direction estimation method based on radar wind measurement combination strategy
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