阅读说明：本技术 一种以无人机为载体的雷达流速测量系统及方法 (Radar flow velocity measurement system and method with unmanned aerial vehicle as carrier ) 是由 陶震宇 陈一如 张在琛 于 2020-11-30 设计创作，主要内容包括：本发明公开了一种以无人机为载体的雷达流速测量系统及方法,包括测量端以及数据接收端,所述测量端安装在无人机上,测量端包括雷达、陀螺仪、GPS模块、无线通信模块一、处理器以及电源模块,所述雷达、陀螺仪、GPS模块、无线通信模块一分别与处理器相连,电源模块分别为雷达、陀螺仪、GPS模块、无线通信模块、处理器供电；所述数据接收端包括无线通信模块二、数据接收平台,所述无线通信模块二与数据接收平台连接,且所述无线通信模块二与无线通信模块一无线连接,本发明能够提高流速测量的便携性,省去重复架设固定设备的成本,并使测量更加全面。(The invention discloses a radar flow velocity measuring system and method taking an unmanned aerial vehicle as a carrier, and the system comprises a measuring end and a data receiving end, wherein the measuring end is installed on the unmanned aerial vehicle and comprises a radar, a gyroscope, a GPS module, a first wireless communication module, a processor and a power supply module; the data receiving end comprises a second wireless communication module and a data receiving platform, the second wireless communication module is connected with the data receiving platform, and the second wireless communication module is wirelessly connected with the wireless communication module.)

1. The utility model provides an use radar velocity of flow measurement system of unmanned aerial vehicle as carrier which characterized in that: the unmanned aerial vehicle measurement system comprises a measurement end and a data receiving end, wherein the measurement end is installed on an unmanned aerial vehicle and comprises a radar, a gyroscope, a GPS module, a first wireless communication module, a processor and a power supply module, the radar, the gyroscope, the GPS module and the first wireless communication module are respectively connected with the processor, and the power supply module respectively supplies power for the radar, the gyroscope, the GPS module, the wireless communication module and the processor; the data receiving end comprises a second wireless communication module and a data receiving platform, the second wireless communication module is connected with the data receiving platform, and the second wireless communication module is wirelessly connected with the wireless communication module, wherein:

the data receiving platform sends a speed measurement control signal to the first wireless communication module through the second wireless communication module, the first wireless communication module sends the received speed measurement control signal to the processor, and the processor respectively controls the radar, the gyroscope and the GPS module to carry out measurement according to the speed measurement control signal to respectively obtain a radar signal, a gyroscope signal and a GPS signal; the processor obtains the flow velocity according to the radar signal, the gyroscope signal and the GPS signal, simultaneously sends the GPS signal and the flow velocity to the second wireless communication module through the second wireless communication module, the second wireless communication module receives the GPS signal and the flow velocity and pushes the GPS signal and the flow velocity to the data receiving platform, and the data receiving platform receives and stores the GPS signal and the flow velocity.

2. The radar flow velocity measurement system using unmanned aerial vehicle as carrier of claim 1, wherein: the processor adopts an Arduino nano processor, a VIN pin of the Arduino nano processor, a VCC pin of a gyroscope, a VCC pin of a GPS module and a VCC pin of a first wireless communication module are respectively connected with a 5v power connector of a power module, a GND pin and a RESET pin of the Arduino nano processor are grounded, a D1/TX pin of the Arduino nano processor is connected with an RX pin of the gyroscope, a D0/RX pin of the Arduino nano processor is connected with a TX pin of the gyroscope, a D2 pin of the Arduino nano processor is connected with a D pin of the first wireless communication module, a GND pin of the first wireless communication module is grounded, a D3 pin of the Arduino nano processor is connected with a TXD pin of the first wireless communication module, a D5 pin of the Arduino nano processor is connected with a TXD pin of the GPS module, a GND pin of the GPS module is grounded, and a GND pin of the Arduino nano processor is connected with a 7 level converter, the RXD pin of the level shifter is connected with the TXD pin of the radar, the VIN pin of the radar is connected with the 12v power connector of the power module, and the VIN pin of the level shifter is connected with the 3.3v power connector of the power module.

3. The radar flow velocity measurement system using unmanned aerial vehicle as carrier of claim 1, wherein: the data receiving platform is a computer or an industrial personal computer.

4. A measurement method of a radar flow velocity measurement system using an unmanned aerial vehicle as a carrier according to claim 1, characterized by comprising the following steps:

step 1, flow direction correctionQuasi-stage: placing the unmanned aerial vehicle on the shore to enable the unmanned aerial vehicle to face the same direction as the river flow direction; setting the Z-axis direction of the gyroscope as 1 and the XY direction as 0, measuring the three-axis Euler angle read by the gyroscope, and converting (0,0,1) in the gyroscope coordinate system into (X) in the northeast three-axis coordinate system by using a rotation matrix₁，Y₁，Z₁) The specific calculation is as follows:

X₁＝1×(sinθ_x×sinθ_z+cosθ_x×cosθ_z×sinθ_y)

Y₁＝1×(sinθ_z×sinθ_y×cosθ_x-cosθ_z×sinθ_x)

Z₁＝1×cosθ_x×cosθ_y

wherein, theta_xθ_yθ_zThe three-axis Euler angles measured by the gyroscope;

to X₁Y₁Using arctan function to obtain an included angle theta between the projection of the radar flow measurement direction on the horizontal plane and the east-righting direction₁；

Step 2, a measurement preparation stage: judging whether the measuring end is in a measuring state or not by using the GPS module, and when the speed of the unmanned aerial vehicle is higher than a threshold value, continuously integrating the speed measured by the GPS module to obtain the advancing distance of the unmanned aerial vehicle; when the speed of the unmanned aerial vehicle is lower than a threshold value, entering a measuring stage, and sending the measured and corrected data and the advancing distance of the unmanned aerial vehicle to a computer end;

step 3, an actual measurement stage: when the unmanned aerial vehicle hovers in the air for measurement, the three-axis Euler angle theta read by the gyroscope is measured_xθ_yθ_zThe rotation matrix is used to transform (0,0,1) in the gyroscope coordinate system into (X) in the northeast triaxial coordinate system₂，Y₂，Z₂) The conversion formula is the same as that in the flow direction calibration stage in the step 1; to X₂Y₂Using arctan function to obtain the included angle theta between the projection of the radar flow measurement direction on the horizontal plane and the east-ward direction₂(ii) a To 1 ÷ Z₂Using arcsin function to obtain included angle theta between flow measurement direction and horizontal plane₃(ii) a The measuring direction is on the horizontal planeThe included angle between the projection of the calibration stage and the flow direction of the river is theta₂-θ₁Determining the velocity v of the water flow in the direction of the radar beam₀The ratio beta to the actual flow velocity v,

β＝cosθ₃×cos(θ₂-θ₁)

v＝v₀÷β

step 4, considering the translation of the system, and respectively measuring the three-axis speeds v of the northeast sky measured by the GPS module_x1、v_y1、v_z1The velocity v in the radar beam direction, i.e. in the direction of the gyroscope Z axis, is derived using the rotation matrix_zSince the coordinate system is transformed from the northeast coordinate system to the gyroscope coordinate system, the euler angle during calculation is opposite to the data measured by the gyroscope, and the expression is as follows:

v_z＝-v_x1×sin(-θ_y)+v_y1×cos(-θ_y)×sin(-θ_x)+v_z1×cos(-θ_x)×cos(-θ_y)

＝v_x1×sin(θ_y)-v_y1×cos(θ_y)×sin(θ_x)+v_z1×cos(θ_x)×cos(θ_y)

v is to be_zAnd radar measured values v_MeasuringAdding to obtain the velocity v of the water flow in the radar beam direction₀Calculating the actual flow velocity v

v＝v₀÷β＝(v_z+v_Measuring)÷β

Step 5, smoothing the actual flow velocity v obtained by multiple measurements by using a Kalman filtering method to obtain an actual flow velocity correction value v';

step 6, when the speed measured by the GPS module is higher than a threshold value, averaging the latest obtained actual flow speed correction value v' to obtain the final flow speed, sending the final flow speed and the current moving distance to a data receiving end through the first wireless communication module, and returning to the measurement preparation stage;

step 7, measurement ending stage: the measurement preparation stage and the actual measurement stage are circulated for multiple times until the measurement is finished; and when the measurement is finished, the measuring end reads the longitude and latitude information measured by the GPS module, transmits the longitude and latitude information to the data receiving end, and finishes the measurement.

5. The radar flow velocity measurement system using unmanned aerial vehicle as carrier of claim 4, wherein: and 6, averaging the actual flow rate correction values v' obtained in the last twenty times to obtain the final flow rate.

Technical Field

The invention relates to a radar speed measurement system, in particular to a radar flow velocity measurement system and method with an unmanned aerial vehicle as a carrier.

Background

In current hydrological measurement, the radar velocimeter is mostly a fixed device erected on the bank in advance, the portability is poor, and the velocity of flow in a certain area can only be measured, which is not accurate enough. Therefore, it is desirable to design a radar flow rate measurement system that is more portable and measures the full range.

Disclosure of Invention

The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention provides a radar flow velocity measurement system and method using an unmanned aerial vehicle as a carrier, which can improve the portability of flow velocity measurement, save the cost of repeatedly erecting fixed equipment and enable the measurement to be more comprehensive.

The technical scheme is as follows: in order to achieve the purpose, the invention adopts the technical scheme that:

the utility model provides an use radar velocity of flow measurement system of unmanned aerial vehicle as carrier, includes measuring terminal and data receiving terminal, the measuring terminal is installed on unmanned aerial vehicle, and the measuring terminal includes radar, gyroscope, GPS (global positioning system) module, wireless communication module one, treater and power module, radar, gyroscope, GPS module, wireless communication module one link to each other with the treater respectively, and power module is radar, gyroscope, GPS module, wireless communication module, treater power supply respectively. The data receiving end comprises a second wireless communication module and a data receiving platform, the second wireless communication module is connected with the data receiving platform, and the second wireless communication module is wirelessly connected with the wireless communication module, wherein:

the data receiving platform sends a speed measurement control signal to the first wireless communication module through the second wireless communication module, the first wireless communication module sends the received speed measurement control signal to the processor, and the processor respectively controls the radar, the gyroscope and the GPS module to measure according to the speed measurement control signal to respectively obtain a radar signal, a gyroscope signal and a GPS signal. The processor obtains the flow velocity according to the radar signal, the gyroscope signal and the GPS signal, simultaneously sends the GPS signal and the flow velocity to the second wireless communication module through the second wireless communication module, the second wireless communication module receives the GPS signal and the flow velocity and pushes the GPS signal and the flow velocity to the data receiving platform, and the data receiving platform receives and stores the GPS signal and the flow velocity.

Preferably: the processor adopts an Arduino nano processor, a VIN pin of the Arduino nano processor, a VCC pin of a gyroscope, a VCC pin of a GPS module and a VCC pin of a first wireless communication module are respectively connected with a 5v power connector of a power module, a GND pin and a RESET pin of the Arduino nano processor are grounded, a D1/TX pin of the Arduino nano processor is connected with an RX pin of the gyroscope, a D0/RX pin of the Arduino nano processor is connected with a TX pin of the gyroscope, a D2 pin of the Arduino nano processor is connected with a D pin of the first wireless communication module, a GND pin of the first wireless communication module is grounded, a D3 pin of the Arduino nano processor is connected with a TXD pin of the first wireless communication module, a D5 pin of the Arduino nano processor is connected with a TXD pin of the GPS module, a GND pin of the GPS module is grounded, and a GND pin of the Arduino nano processor is connected with a 7 level converter, the RXD pin of the level shifter is connected with the TXD pin of the radar, the VIN pin of the radar is connected with the 12v power connector of the power module, and the VIN pin of the level shifter is connected with the 3.3v power connector of the power module.

Preferably: the data receiving platform is a computer or an industrial personal computer.

A radar flow velocity measuring method using an unmanned aerial vehicle as a carrier comprises the following steps:

step 1, flow direction calibration stage: the unmanned aerial vehicle is arranged on the shore, so that the orientation of the unmanned aerial vehicle is the same as the flow direction of the river. Setting the Z-axis direction of the gyroscope as 1 and the XY direction as 0, measuring the three-axis Euler angle read by the gyroscope, and converting (0,0,1) in the gyroscope coordinate system into (X) in the northeast three-axis coordinate system by using a rotation matrix₁,Y₁,Z₁) The specific calculation is as follows:

X₁＝1×(sinθ_x×sinθ_z+cosθ_x×cosθ_z×sinθ_y)

Y₁＝1×(sinθ_z×sinθ_y×cosθ_x-cosθ_z×sinθ_x)

Z₁＝1×cosθ_x×cosθ_y

wherein, theta_xθ_yθ_zThe three-axis euler angles measured by the gyroscope.

To X₁Y₁Using arctan functionsObtaining the included angle theta between the projection of the radar flow measurement direction on the horizontal plane and the east-righting direction₁。

Step 2, a measurement preparation stage: whether the measuring end is in a measuring state or not is judged by using the GPS module, and when the speed of the unmanned aerial vehicle is higher than a threshold value, the speed measured by the GPS module is continuously integrated to obtain the advancing distance of the unmanned aerial vehicle. And when the speed of the unmanned aerial vehicle is lower than the threshold value, entering a measuring stage, and sending the measured and corrected data and the advancing distance of the unmanned aerial vehicle to a computer terminal.

Step 3, an actual measurement stage: when the unmanned aerial vehicle hovers in the air for measurement, the three-axis Euler angle theta read by the gyroscope is measured_xθ_yθ_zThe rotation matrix is used to transform (0,0,1) in the gyroscope coordinate system into (X) in the northeast triaxial coordinate system₂,Y₂,Z₂) The transformation formula is the same as in the flow to calibration phase in step 1. To X₂Y₂Using arctan function to obtain the included angle theta between the projection of the radar flow measurement direction on the horizontal plane and the east-ward direction₂. To 1 ÷ Z₂Using arcsin function to obtain included angle theta between flow measurement direction and horizontal plane₃.. At the moment, the projection of the measuring direction on the horizontal plane and the river flow direction included angle obtained in the calibration stage are theta₂-θ₁Determining the velocity v of the water flow in the direction of the radar beam₀The ratio beta to the actual flow velocity v,

β＝cosθ₃×cos(θ₂-θ₁)

v＝v₀÷β

step 4, considering the translation of the system, and respectively measuring the three-axis speeds v of the northeast sky measured by the GPS module_x1、v_y1、v_z1The velocity v in the radar beam direction, i.e. in the direction of the gyroscope Z axis, is derived using the rotation matrix_zSince the coordinate system is transformed from the northeast coordinate system to the gyroscope coordinate system, the euler angle during calculation is opposite to the data measured by the gyroscope, and the expression is as follows:

v_z＝-v_x1×sin(-θ_y)+v_y1×cos(-θ_y)×sin(-θ_x)+v_z1×cos(-θ_x)×cos(-θ_y)

＝v_x1×sin(θ_y)-v_y1×cos(θ_y)×sin(θ_x)+v_z1×cos(θ_x)×cos(θ_y)

v is to be_zAnd radar measured values v_MeasuringAdding to obtain the velocity v of the water flow in the radar beam direction₀Calculating the actual flow velocity v

v＝v₀÷β＝(v_z+v_Measuring)÷β

And 5, smoothing the actual flow velocity v obtained by multiple measurements by using a Kalman filtering method to obtain an actual flow velocity correction value v'.

And 6, when the speed measured by the GPS module is higher than the threshold value, averaging the latest obtained actual flow speed correction value v' to obtain the final flow speed, sending the final flow speed and the current moving distance to a data receiving end through the first wireless communication module, and returning to the measurement preparation stage.

Step 7, measurement ending stage: the measurement preparation phase and the actual measurement phase are cycled for a plurality of times until the measurement is finished. And when the measurement is finished, the measuring end reads the longitude and latitude information measured by the GPS module, transmits the longitude and latitude information to the data receiving end, and finishes the measurement.

Preferably: and 6, averaging the actual flow rate correction values v' obtained in the last twenty times to obtain the final flow rate.

Compared with the prior art, the invention has the following beneficial effects:

1) under the condition that the water speed needs to be measured temporarily, the water speed can be measured quickly, and flow measuring equipment does not need to be erected in advance.

2) The river water flow measuring device can measure on the whole river, measuring positions are various, and data are comprehensive.

3) The system has simple structure and low cost except the radar required by the flow measurement.

Drawings

FIG. 1 is a schematic diagram of the structure of a system measurement module according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of a connection mode of a system measurement module according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a gyroscope coordinate system in accordance with an embodiment of the present invention;

FIG. 4 is a schematic diagram of a flow calibration phase in accordance with an embodiment of the present invention;

FIG. 5 is a schematic diagram of an actual measurement phase in an embodiment of the present invention;

fig. 6 is a schematic diagram of a system measurement end in an embodiment of the invention.

A represents a speed measuring radar, B represents a gyroscope, C represents a GPS module and an antenna, D represents a power module, E represents a processor, F represents the direction of millimeter waves transmitted and received by the radar, and G represents a first wireless communication module.

Detailed Description

The present invention is further illustrated by the following description in conjunction with the accompanying drawings and the specific embodiments, it is to be understood that these examples are given solely for the purpose of illustration and are not intended as a definition of the limits of the invention, since various equivalent modifications will occur to those skilled in the art upon reading the present invention and fall within the limits of the appended claims.

The utility model provides an use radar velocity of flow measurement system of unmanned aerial vehicle as carrier, as shown in fig. 1, 2, including measuring end and data receiving terminal, the measuring end is installed on unmanned aerial vehicle, and specific measuring end carries in the unmanned aerial vehicle below, and the measuring end includes radar, gyroscope, GPS (global positioning system) module, wireless communication module one, treater and power module, radar, gyroscope, GPS module, wireless communication module one link to each other with the treater respectively, and power module is radar, gyroscope, GPS module, wireless communication module, treater power supply respectively. The data receiving end comprises a second wireless communication module and a data receiving platform, the data receiving platform is a computer or an industrial personal computer, the second wireless communication module is connected with the data receiving platform, and the second wireless communication module is wirelessly connected with the wireless communication module, wherein:

the data receiving platform sends a speed measurement control signal to the first wireless communication module through the second wireless communication module, the first wireless communication module sends the received speed measurement control signal to the processor, and the processor respectively controls the radar, the gyroscope and the GPS module to measure according to the speed measurement control signal to respectively obtain a radar signal, a gyroscope signal and a GPS signal. The processor obtains the flow velocity according to the radar signal, the gyroscope signal and the GPS signal, simultaneously sends the GPS signal and the flow velocity to the second wireless communication module through the second wireless communication module, the second wireless communication module receives the GPS signal and the flow velocity and pushes the GPS signal and the flow velocity to the data receiving platform, and the data receiving platform receives and stores the GPS signal and the flow velocity.

As shown in fig. 6, the processor employs an Arduino nano processor, data is comprehensively processed on the Arduino, a VIN pin of the Arduino nano processor, a VCC pin of the gyroscope, a VCC pin of the GPS module, and a VCC pin of the first wireless communication module are respectively connected to a 5v power connector of the power module, a GND pin and a RESET pin of the Arduino nano processor are grounded, a D1/TX pin of the Arduino nano processor is connected to a TX pin of the gyroscope, a D0/RX pin of the Arduino nano processor is connected to a TX pin of the gyroscope, a D2 pin of the Arduino nano processor is connected to an RXD pin of the first wireless communication module, a pin of the first wireless communication module is grounded, a D3 pin of the Arduino processor is connected to a TXD pin of the first wireless communication module, a D5 pin of the Arduino processor is connected to a TXD pin of the GPS module, and a GND pin of the GPS module is connected to a GND, the D7 pin of the Arduino nano processor is connected with the TXD pin of the level shifter, the RXD pin of the level shifter is connected with the TXD pin of the radar, the VIN pin of the radar is connected with the 12v power connector of the power module, and the VIN pin of the level shifter is connected with the 3.3v power connector of the power module.

Preferably: the method is as follows.

A radar flow velocity measurement method using an unmanned aerial vehicle as a carrier, as shown in fig. 3, includes the following steps:

and (3) flow direction calibration: the system is placed on the shore, and the system is oriented to the same direction as the river. Setting the Z-axis direction (namely the speed measuring direction of the radar) of the gyroscope as 1 and setting the XY direction as 0. As shown in fig. 4, the three-axis euler angles read by the gyroscope are measured, and (0,0,1) in the gyroscope coordinate system is converted into three-axis coordinates of the northeast sky using the rotation matrixIs under (X)₁,Y₁,Z₁). The specific calculation is as follows:

X₁＝1×(sinθ_x×sinθ_z+cosθ_x×cosθ_z×sinθ_y)

Y₁＝1×(sinθ_z×sinθ_y×cosθ_x-cosθ_z×sinθ_x)

Z₁＝1×cosθ_x×cosθ_y

wherein, theta_xθ_yθ_zThe three-axis euler angles measured by the gyroscope.

To X₁Y₁Using arctan function to obtain an included angle theta between the projection of the radar flow measurement direction on the horizontal plane (same as the river flow direction) and the east-right direction₁。

A measurement preparation stage: because the measurement condition is that the unmanned aerial vehicle hovers, the measurement can not be kept all the time in the flight process. The system judges whether the unmanned aerial vehicle is in a measurement state by using the GPS module, and when the speed is higher than a threshold value, the speed measured by the GPS module is continuously integrated to obtain the advancing distance of the unmanned aerial vehicle; and when the speed is lower than the threshold value, entering a measuring stage, and sending the measured and corrected data and the advancing distance of the unmanned aerial vehicle to a computer terminal.

And (3) actual measurement stage: in the air hovering measurement, as shown in fig. 5, the three-axis euler angle θ read by the gyroscope is measured_xθ_yθ_zThe rotation matrix is used to transform (0,0,1) in the gyroscope coordinate system into (X) in the northeast triaxial coordinate system₂,Y₂,Z₂) The transformation formula is the same as in the flow direction calibration phase. To X₂Y₂Using arctan function to obtain the included angle theta between the projection of the radar flow measurement direction on the horizontal plane and the east-ward direction₂. To 1 ÷ Z₂Using arcsin function to obtain included angle theta between flow measurement direction and horizontal plane₃.. At the moment, the projection of the measuring direction on the horizontal plane and the river flow direction included angle obtained in the calibration stage are theta₂-θ₁. The velocity v of the water flow in the direction of the radar beam can be determined₀The ratio beta to the actual flow velocity v,

β＝cosθ₃×cos(θ₂-θ₁)

v＝v₀÷β

radar measured value v due to system jitter during measurement_MeasuringAnd v₀And do not remain equal. The dithering of the system can be divided into two aspects of translation and rotation. Firstly, considering the rotation of the system, the three-axis angular velocity measured by the gyroscope is omega_x、ω_y、ω_zAnd the distance from the radar to the water surface is S. The radar beam coincides with the Z-axis direction, so the relative velocity caused by rotation at the water surface is omega_x× S、ω_yXs, the velocity direction is perpendicular to the radar beam direction. And because the Doppler effect is only related to the speed of the measured object in the radial direction of the radar beam, the rotation does not cause the error of system measurement. The experiment is carried out, the radar is fixed, only the rotation in the three-axis direction is carried out, the speed measurement result is always zero, the experiment result accords with the expectation, and therefore the influence caused by the rotation of the system can be ignored. Secondly, considering the translation of the system, the three-axis speeds of the northeast measured by the GPS are respectively v_x1、v_y1、v_z1I.e. the speed of the system in the three-axis direction in the coordinate system of fig. 5. The velocity v in the direction of the radar beam, i.e. the direction of the gyroscope Z axis, is obtained by using the rotation matrix_zSince the coordinate system is transformed from the northeast coordinate system to the gyroscope coordinate system, the euler angle during calculation is opposite to the data measured by the gyroscope, and the expression is as follows:

v_z＝-v_x1×sin(-θ_y)+v_y1×cos(-θ_y)×sin(-θ_x)+v_z1×cos(-θ_x)×cos(-θ_y)

＝v_x1×sin(θ_y)-v_y1×cos(θ_y)×sin(θ_x)+v_z1×cos(θ_x)×cos(θ_y)

v is to be_zAnd radar measured values v_MeasuringAdding to obtain the velocity v of the water flow in the radar beam direction₀And calculating to obtain the actual flow velocity v,

v＝v₀÷β＝(v_z+v_measuring)÷β

Because the river flow velocity changes and other problems, the flow velocity measured every time is different, so the Kalman filtering algorithm is utilized to carry out smoothing treatment on the actual flow velocity v obtained by multiple measurements, and the obtained corrected value v' is stored locally. And when the speed measured by the GPS module is higher than a threshold value, averaging the v' corrected for the last twenty times to obtain final flow speed data, sending the flow speed and the current moving distance to a data receiving end through the wireless communication module, and returning to the measurement preparation stage.

And (3) a measurement ending stage: the measurement preparation phase and the actual measurement phase are cycled for a plurality of times until the measurement is finished. And when the measurement is finished, the measuring end reads the longitude and latitude information measured by the GPS, and transmits the longitude and latitude information to the data receiving end, and the measurement is finished.

The above description is only of the preferred embodiments of the present invention, and it should be noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the invention and these are intended to be within the scope of the invention.