CN113108767A - Real-time monitoring method for hydrological information of unmanned aerial vehicle-mounted radar - Google Patents
Real-time monitoring method for hydrological information of unmanned aerial vehicle-mounted radar Download PDFInfo
- Publication number
- CN113108767A CN113108767A CN202110370971.5A CN202110370971A CN113108767A CN 113108767 A CN113108767 A CN 113108767A CN 202110370971 A CN202110370971 A CN 202110370971A CN 113108767 A CN113108767 A CN 113108767A
- Authority
- CN
- China
- Prior art keywords
- radar
- aerial vehicle
- unmanned aerial
- frequency
- flow
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C13/00—Surveying specially adapted to open water, e.g. sea, lake, river or canal
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
Abstract
The invention discloses a hydrological information real-time monitoring method and device for an unmanned aerial vehicle radar, which relate to the technical field of hydrological monitoring, and the technical scheme key points are as follows: the method comprises the following steps: s1, calculating the water level flow rate by a radar; s2, eliminating 1/f noise; s3, Kalman filtering inclination angle estimation, and stability of the flow measurement is enhanced by introducing a stability augmentation platform; and S4, carrying out multipoint flow measurement. The invention also provides a real-time monitoring device for hydrological information of the unmanned aerial vehicle-mounted radar, which comprises a water level measuring radar, a flow velocity measuring radar, a stability-increasing cradle head, an unmanned aerial vehicle, a wireless data transmission device and a ground receiving device. The method can improve the flow measurement capability under the condition of weak signals and overcome the influence of 1/f noise on the flow measurement precision; by adopting a Kalman filtering inclination angle estimation technology, the stability of flow measurement is enhanced, and the influence of water surface floaters on the flow measurement precision is overcome; the multi-point flow measuring technology of space-time filtering is provided, the interference of floaters is reduced, and the problem that the radar flow measuring inclination angle is not fixed due to the shaking of an unmanned machine body and wind power is solved.
Description
Technical Field
The invention relates to the technical field of hydrological monitoring, in particular to a hydrological information real-time monitoring method for an unmanned aerial vehicle radar.
Background
The river basin is numerous in China, the rainfall is not uniformly distributed, and flood disasters occur frequently in certain areas. In order to reduce the loss of people's lives and properties caused by flood disasters, hydrological information such as river water level, flow velocity and the like needs to be monitored in real time. At present, common water level meters have differential pressure type, communication type and the like, and flow velocity meters comprise a rotary cup type, a rotary propeller type and the like, so that the flow velocity meter is suitable for river channels with less floating objects, less sediment and low flow velocity. The tool is soaked in water for a long time and is influenced by water flow corrosion and scouring, so that the scales are unclear, the position is inclined and deviated, and the reading is difficult; meanwhile, the tools need to be completed manually, and the problems of large workload, poor timeliness, serious waste of human resources and the like exist. Especially when flood disasters come, the personal safety of measuring personnel is difficult to guarantee.
With the development of electronic information technology, non-contact monitoring means are increasing. The ultrasonic measurement obtains distance information according to the time delay of transmitted and received waves, and has the advantages of high precision and quick response, but the propagation speed of the ultrasonic waves in a medium is easily influenced by temperature; the laser measurement principle is similar to that of ultrasonic waves, the directional measurement method has the advantage of strong directivity, the precision can reach millimeter level, and the method is easily influenced by dense fog, rain and the like; a Doppler flow profiler (ADCP) emits a pulse wave from an ultrasonic transducer, and calculates the magnitude of the flow velocity by Doppler shift. But as a result, the water quality of rivers, floating objects, and the like are easily affected. The radar flow measurement principle is similar to that of ADCP, the flow velocity is calculated by utilizing the water flow Doppler effect, but the electromagnetic wave can penetrate fog, smoke and dust and is not influenced by river water quality, floaters and the like, and the speed measurement range and precision are greatly improved. Therefore, it is becoming a mainstream flow measuring means at present and in the future. At present, the hydrology is measured by radar mainly in a fixed mode and is erected on the shore or under a bridge. However, in the case of flood caused by rainstorm or snow melting, the water flow does not necessarily travel along the river channel where the radar flow meter is installed, and temporary emergency measurement is required.
Therefore, the invention aims to design a method and a device for monitoring hydrological information of an unmanned aerial vehicle radar in real time so as to solve the problems.
Disclosure of Invention
The invention aims to provide a method and a device for monitoring hydrological information of an unmanned aerial vehicle radar in real time, wherein the method offsets intermediate frequency signals to 1/f noise, can improve flow measurement capability under the condition of weak signals and overcomes the influence of the 1/f noise on flow measurement precision; meanwhile, by adopting a Kalman filtering inclination angle estimation technology, the flow measurement stability can be enhanced, the influence of water surface floaters on the flow measurement precision is overcome, the interference of floaters is reduced through multi-point flow measurement of space-time filtering, and the problem that the radar flow measurement inclination angle is not fixed due to unmanned airframe shaking and wind power is solved. The device has the advantages of flexibility, convenience in deployment, quick response and the like of the unmanned aerial vehicle, has strong electromagnetic wave penetrability and is not influenced by river water quality and floaters, and can improve the flow measurement precision, the flow velocity range and the deployment flexibility; meanwhile, the device is small in weight and low in power consumption, is suitable for flexible deployment of the common unmanned aerial vehicle, and can be widely applied to occasions such as flood prevention emergency rescue.
The technical purpose of the invention is realized by the following technical scheme: a hydrological information real-time monitoring method for an unmanned aerial vehicle-mounted radar specifically comprises the following steps:
s1, calculating the water level flow rate by the radar, emitting the electromagnetic signal along the axial direction ahead by the radar, generating diffuse reflection after the emitted signal meets the front water surface, receiving the signal returned along the axial direction, and when the axis of the flow meter and the direction of the water flow are in a vertical plane, measuring the flow rate as follows: v ═ vdA/cos α, where v is the flow rate and v isdThe Doppler velocity measured by the radar is measured, and alpha is an included angle;
s2, 1/f noise elimination, namely offsetting an intermediate frequency beside a radar 24GHz local oscillation frequency, and reducing the influence of 1/f noise interference, wherein the intermediate frequency is required to be greater than a 1/f noise corner frequency;
s3, Kalman filtering inclination angle estimation, wherein the stability of flow measurement is enhanced by introducing a stability augmentation platform, a 9-axis attitude detection sensor is configured on the stability augmentation platform, then the inclination angle estimation is carried out by utilizing a Kalman filtering algorithm, the influence of accelerometer noise is inhibited, and the drift accumulated error of the gyroscope is corrected, wherein the angle measured by the gyroscope is as follows:
wherein, thetakIs the angle at the present moment, θk-1Is the angle of the last moment of time,
is the angular velocity at the present moment in time,
is the angular velocity offset at the current time;
s4, carrying out multi-point flow measurement, arranging N measuring points on the cross section of the river channel, measuring each point M times at a time interval delta t, and measuring the value
And 10% of the maximum and minimum values were removed from the data set, and then the arithmetic mean of the remaining data was calculated as the flow rate value.
Further, v described in step S1dThe measurement of (2) adopts a frequency modulation continuous wave radar.
Further, the kalman filtering in step S3 uses the observed quantity as the input quantity of the filter and uses the state quantity estimated value as the output quantity of the filter, and performs the data processing of optimal estimation by the statistical characteristics of the system noise and the observed noise, and the state equation of the system is:
wherein the content of the first and second substances,
for the actual value X of the current statekIs estimated by the estimation of (a) a,
k-1 pre-estimates for k times, and T is the sampling period.
Further, v is measured using frequency modulated continuous wave radardWhen a triangular wave frequency modulation signal is selected, the frequency f of the transmitted signal istComprises the following steps:
wherein B isModulation bandwidth, T modulation period, f0Is the center frequency; then, assuming that the distance radar of the moving target is R, the frequency f of the echo signalrComprises the following steps:
wherein f isdThe Doppler frequency of the moving target is C, the light speed is C, and +/-the positive and negative slope conditions of the front half period and the back half period of the modulation wave are obtained;
difference frequency between first half period echo signal and transmitted signal
Comprises the following steps:
difference frequency between echo signal and transmitted signal in second half period
Comprises the following steps:
f is thendThe relation with the difference frequency is as follows:
from the doppler formula, the velocity can be calculated:
wherein λ is a radar wavelength;
will be provided with
And
adding, the distance:
further, in step S2, a 32.768KHz crystal oscillator is used for generating the intermediate frequency.
The invention provides a real-time hydrological information monitoring device for an unmanned aerial vehicle-mounted radar, which comprises a water level measuring radar, a flow velocity measuring radar, a stability augmentation cloud platform, an unmanned aerial vehicle, a wireless data transmission device and a ground receiving device, wherein the water level measuring radar is installed on the unmanned aerial vehicle; the wireless data transmission device is installed on the unmanned aerial vehicle and is in communication connection with the ground receiving device.
Furthermore, the stability augmentation tripod head contains a gyroscope, an accelerometer and an electronic compass.
In conclusion, the invention has the following beneficial effects:
1. the method of the invention offsets the frequency of the intermediate frequency signal to the outside of the 1/f noise, can improve the flow measurement capability under the weak signal condition, and overcomes the influence of the 1/f noise on the flow measurement precision; meanwhile, by adopting a Kalman filtering inclination angle estimation technology, the flow measurement stability can be enhanced, the influence of water surface floaters on the flow measurement precision is overcome, the interference of floaters is reduced through multi-point flow measurement of time-space filtering, and the problem that the radar flow measurement inclination angle is not fixed due to unmanned airframe shaking and wind power is solved;
2. the device has the advantages of flexibility, convenience in deployment, quick response and the like of the unmanned aerial vehicle, has strong electromagnetic wave penetrability and is not influenced by river water quality and floaters, and can improve the flow measurement precision, the flow velocity range and the deployment flexibility;
3. the device is small in weight and low in power consumption, is suitable for flexible deployment of the common unmanned aerial vehicle, and can be widely applied to occasions such as flood prevention emergency rescue.
Drawings
FIG. 1 is a flowchart in example 1 of the present invention;
FIG. 2 is a schematic diagram of radar measurement in embodiment 1 of the present invention;
FIG. 3 is a diagram of the variation of frequency with time of an FMCW radar signal in embodiment 1 of the present invention;
FIG. 4 is a graph showing the amplitude-frequency characteristics of 1/f noise in embodiment 1 of the present invention;
FIG. 5 is a circuit diagram of 1/f noise canceling circuit in embodiment 1 of the present invention;
FIG. 6 is a schematic view of a multipoint flow measurement in example 1 of the present invention;
FIG. 7 is a block diagram of a system in embodiment 2 of the present invention;
fig. 8 is a system diagram in embodiment 1 of the present invention.
In the figure: 1. a water level measuring radar; 2. a flow velocity measurement radar; 3. a stability augmentation holder; 4. an unmanned aerial vehicle; 5. a wireless data transmission device; 6. and a ground receiving device.
Detailed Description
The present invention is described in further detail below with reference to figures 1-8.
Example 1: a real-time monitoring method for hydrological information of an unmanned airborne radar is shown in figure 1 and specifically comprises the following steps:
s1, calculating the water level flow rate by the radar, emitting the electromagnetic signal along the axial direction ahead by the radar, generating diffuse reflection after the emitted signal meets the front water surface, receiving the signal returned along the axial direction, and when the axis of the flow meter and the direction of the water flow are in a vertical plane, measuring the flow rate as follows: v ═ vdA/cos α, where v is the flow rate and v isdThe Doppler velocity measured by the radar is measured, and alpha is an included angle;
s2, 1/f noise elimination, namely offsetting an intermediate frequency beside a radar 24GHz local oscillation frequency, and reducing the influence of 1/f noise interference, wherein the intermediate frequency is required to be greater than a 1/f noise corner frequency;
s3, Kalman filtering inclination angle estimation, flow measurement stability is enhanced by introducing a stability augmentation platform, and 9-axis postures are configured on the stability augmentation platformDetecting a sensor, then estimating an inclination angle by using a Kalman filtering algorithm, inhibiting the noise influence of an accelerometer, and correcting the drift accumulated error of the gyroscope, wherein the angle measured by the gyroscope is as follows:
wherein, thetakIs the angle at the present moment, θk-1Is the angle of the last moment of time,
is the angular velocity at the present moment in time,
is the angular velocity offset at the current time;
s4, carrying out multi-point flow measurement, arranging N measuring points on the cross section of the river channel, measuring each point M times at a time interval delta t, and measuring the value
And 10% of the maximum and minimum values were removed from the data set, and then the arithmetic mean of the remaining data was calculated as the flow rate value.
Wherein v is the same as that in step S1dThe measurement of (2) adopts a frequency modulation continuous wave radar.
In the kalman filtering in step S3, the observed quantity is used as the input quantity of the filter, the state quantity estimation value is used as the output quantity of the filter, and the data processing of the optimal estimation is performed according to the statistical characteristics of the system noise and the observation noise, and the state equation of the system is:
wherein the content of the first and second substances,
for the actual value X of the current statekIs estimated by the estimation of (a) a,
k-1 pre-estimates for k times, and T is the sampling period.
Wherein, the v is measured by frequency modulation continuous wave radardWhen a triangular wave frequency modulation signal is selected, the frequency f of the transmitted signal istComprises the following steps:
where B is the modulation bandwidth, T is the modulation period, f0Is the center frequency; then, assuming that the distance radar of the moving target is R, the frequency f of the echo signalrComprises the following steps:
wherein f isdThe Doppler frequency of the moving target is C, the light speed is C, and +/-the positive and negative slope conditions of the front half period and the back half period of the modulation wave are obtained;
difference frequency between first half period echo signal and transmitted signal
Comprises the following steps:
difference frequency between echo signal and transmitted signal in second half period
Comprises the following steps:
f is thendThe relation with the difference frequency is as follows:
from the doppler formula, the velocity can be calculated:
wherein λ is a radar wavelength;
will be provided with
And
adding, the distance:
in step S2, a 32.768KHz crystal oscillator is used to generate the intermediate frequency.
In this embodiment, the radar sends out electromagnetic signal along axial place ahead, and the signal takes place the diffuse reflection after meetting the place ahead surface of water, and the signal of following the axial return is received. Due to the movement of the water flow, the frequency of the received echo signal generates Doppler frequency shift, and the frequency shift is in direct proportion to the flow velocity. When the axis of the current meter and the direction of the water flow are in a vertical plane (as shown in fig. 2), the measured flow rates are: v ═ vd/cosα。
In the present embodiment, v isdThe measurement is generally performed using Frequency Modulated Continuous Wave (FMCW) radar. As shown in fig. 3, the blue line is the transmission signal frequency, the green line is the static target echo frequency, and the red line is the moving target echo frequency.
1/f noise is a ubiquitous low frequency noise whose noise power is inversely proportional to frequency. The 1/f noise amplitude-frequency characteristic of the radar receiver is shown in fig. 3. The 1/f noise corner frequency is 10kHz, and the water flow Doppler frequency range is 30 Hz-2 kHz. At 30Hz, the 1/f noise voltage amplitude is 18 times that of the thermal noise. Therefore, the 1/f noise greatly affects the doppler measurement accuracy.
In step S2, the 1/f noise is a ubiquitous low-frequency noise whose noise power is inversely proportional to the frequency. The 1/f noise amplitude-frequency characteristic of the radar receiver is shown in fig. 4. The 1/f noise corner frequency is 10kHz, and the water flow Doppler frequency range is 30 Hz-2 kHz. At 30Hz, the 1/f noise voltage amplitude is 18 times that of the thermal noise. Therefore, the 1/f noise greatly affects the doppler measurement accuracy.
Example 2: as shown in fig. 7, the real-time monitoring device for hydrological information of the unmanned aerial vehicle-mounted radar provided by the invention comprises a water level measuring radar, a flow velocity measuring radar, a stability augmentation cloud platform, an unmanned aerial vehicle, a wireless data transmission device and a ground receiving device, wherein the water level measuring radar is mounted on the unmanned aerial vehicle, the stability augmentation cloud platform is mounted on the unmanned aerial vehicle, and the flow velocity measuring radar is mounted on the stability augmentation cloud platform and is used for forming a fixed inclination angle; the wireless data transmission device is installed on the unmanned aerial vehicle and is in communication connection with the ground receiving device.
The stability-increasing cradle head comprises a gyroscope, an accelerometer and an electronic compass.
In the embodiment, the flow velocity measurement radar adopts a 24G onboard radar to perform lateral flow velocity measurement. The water level measuring radar adopts a small radar on a 122G chip to measure the vertical distance. The wireless data transmission device adopts 3DR Radio telemetrology. Unmanned aerial vehicle adopts Da Jiang M600 Pro. The gyroscope, the accelerometer and the electronic compass are contained in the stability-increasing cradle head, so that the angular speed, the acceleration and the magnetic induction intensity of 3 axes can be measured, and the angle of the radar current meter can be controlled in real time.
The measurement accuracy range, stability and power consumption analysis of the real-time monitoring device for the hydrological information of the unmanned airborne radar are explained below.
1. Range of measurement accuracy
Due to the adoption of a 122GHz range radar, the precision can reach +/-1 mm and the range is 45 m. Compared with a 24GHz range radar (with the precision of +/-1 cm) which is generally adopted in the market, the precision is improved by nearly thousand times. Due to the adoption of the 32.768K frequency offset scheme, the influence of 1/f noise is greatly reduced, the speed measurement precision can reach +/-0.01 m/s, and the speed measurement precision is doubled compared with that of the traditional radar; the speed measuring range is 0.05-40 m/s, which is more than doubled compared with the traditional speed measuring range of 0.15-15 m/s.
2. Stability performance
Because the stability augmentation platform is introduced, the 9-axis attitude detection sensor is configured, and the Kalman filtering inclination angle estimation technology is adopted, the stability of the flow measurement direction angle of the unmanned aerial vehicle is enhanced, so that the unmanned aerial vehicle can normally work at the wind speed of 0-60 m/s. And other similar products do not have the function.
3. Power consumption analysis
The power consumption of the traditional 24G continuous wave radar ranging is about 1W; and the power consumption is about 400mW when the radar is used for distance measurement at 122 GHz. The power consumption is lower for unmanned aerial vehicle duration strengthens 1 time.
The method and the device for monitoring hydrological information of the unmanned aerial vehicle radar in real time in the embodiment of the invention have the beneficial effects that: the invention can improve the flow measurement capability under the weak signal condition by offsetting the intermediate frequency signal to the outside of the 1/f noise, and overcomes the influence of the 1/f noise on the flow measurement precision; by adopting a Kalman filtering inclination angle estimation technology, the stability of flow measurement can be enhanced, and the influence of water surface floaters on the flow measurement precision is overcome; by adopting a multi-point flow measuring technology of space-time filtering, the interference of floaters can be reduced, and the problem that the radar flow measuring inclination angle is not fixed due to the shaking of an unmanned machine body and wind power is solved; meanwhile, the unmanned aerial vehicle-mounted radar hydrological information real-time monitoring device has the advantages of flexibility, convenience in deployment, quick response and the like of the unmanned aerial vehicle and the advantages of strong electromagnetic wave penetrability and no influence of river water quality, floaters and the like, can improve the flow measurement precision, the flow velocity range and the deployment flexibility, has the advantages of small weight, low power consumption and the like, is suitable for flexible deployment of common unmanned aerial vehicles, and can be widely applied to occasions such as flood prevention emergency rescue.
The present embodiment is only for explaining the present invention, and it is not limited to the present invention, and those skilled in the art can make modifications of the present embodiment without inventive contribution as needed after reading the present specification, but all of them are protected by patent law within the scope of the claims of the present invention.
Claims (7)
1. A hydrological information real-time monitoring method for an unmanned aerial vehicle-mounted radar is characterized by comprising the following steps: the method specifically comprises the following steps:
s1, calculating the water level flow rate by the radar, emitting the electromagnetic signal along the axial direction ahead by the radar, generating diffuse reflection after the emitted signal meets the front water surface, receiving the signal returned along the axial direction, and when the axis of the flow meter and the direction of the water flow are in a vertical plane, measuring the flow rate as follows: v ═ vdA/cos α, where v is the flow rate and v isdThe Doppler velocity measured by the radar is measured, and alpha is an included angle;
s2, 1/f noise elimination, namely offsetting an intermediate frequency beside a radar 24GHz local oscillation frequency, and reducing the influence of 1/f noise interference, wherein the intermediate frequency is required to be greater than a 1/f noise corner frequency;
s3, Kalman filtering inclination angle estimation, wherein the stability of flow measurement is enhanced by introducing a stability augmentation platform, a 9-axis attitude detection sensor is configured on the stability augmentation platform, then the inclination angle estimation is carried out by utilizing a Kalman filtering algorithm, the influence of accelerometer noise is inhibited, and the drift accumulated error of the gyroscope is corrected, wherein the angle measured by the gyroscope is as follows:
wherein, thetakIs the angle at the present moment, θk-1Is the angle of the last moment of time,
is the angular velocity at the present moment in time,
is the angular velocity offset at the current time;
s4, carrying out multi-point flow measurement, arranging N measuring points on the cross section of the river channel, measuring each point M times at a time interval delta t, and measuring the value
And 10% of the maximum and minimum values were removed from the data set, and then the arithmetic mean of the remaining data was calculated as the flow rate value.
2. An unmanned airborne mine according to claim 1The method for monitoring the hydrological information in real time is characterized by comprising the following steps: v in step S1dThe measurement of (2) adopts a frequency modulation continuous wave radar.
3. The method for monitoring hydrological information of the unmanned aerial vehicle-mounted radar in real time as claimed in claim 1, wherein the method comprises the following steps: in the kalman filtering in step S3, the observed quantity is used as the input quantity of the filter, the state quantity estimation value is used as the output quantity of the filter, and the data processing of the optimal estimation is performed according to the statistical characteristics of the system noise and the observation noise, and the state equation of the system is:
wherein the content of the first and second substances,
for the actual value X of the current statekIs estimated by the estimation of (a) a,
k-1 pre-estimates for k times, and T is the sampling period.
4. The method for monitoring hydrological information of the unmanned aerial vehicle-mounted radar in real time as claimed in claim 2, wherein the method comprises the following steps: measurement of v by frequency modulated continuous wave radardWhen a triangular wave frequency modulation signal is selected, the frequency f of the transmitted signal istComprises the following steps:
where B is the modulation bandwidth, T is the modulation period, f0Is the center frequency; then, assuming that the distance radar of the moving target is R, the frequency f of the echo signalrComprises the following steps:
wherein f isdThe Doppler frequency of the moving target is C, the light speed is C, and +/-the positive and negative slope conditions of the front half period and the back half period of the modulation wave are obtained;
difference frequency between first half period echo signal and transmitted signal
Comprises the following steps:
difference frequency between echo signal and transmitted signal in second half period
Comprises the following steps:
f is thendThe relation with the difference frequency is as follows:
from the doppler formula, the velocity can be calculated:
wherein λ is a radar wavelength;
will be provided with
And
adding, the distance:
5. the method for monitoring hydrological information of the unmanned aerial vehicle-mounted radar in real time as claimed in claim 1, wherein the method comprises the following steps: in step S2, a 32.768KHz crystal oscillator is used for generating the intermediate frequency.
6. The utility model provides an unmanned aerial vehicle carries radar hydrology information real-time supervision device which characterized by: the system comprises a water level measuring radar, a flow velocity measuring radar, a stability augmentation cloud platform, an unmanned aerial vehicle, a wireless data transmission device and a ground receiving device, wherein the water level measuring radar is installed on the unmanned aerial vehicle, the stability augmentation cloud platform is installed on the unmanned aerial vehicle, and the flow velocity measuring radar is installed on the stability augmentation cloud platform and is used for forming a fixed inclination angle; the wireless data transmission device is installed on the unmanned aerial vehicle and is in communication connection with the ground receiving device.
7. The real-time monitoring device for hydrological information of the unmanned aerial vehicle-mounted radar as claimed in claim 6, wherein: the stability augmentation tripod head comprises a gyroscope, an accelerometer and an electronic compass.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110370971.5A CN113108767A (en) | 2021-04-07 | 2021-04-07 | Real-time monitoring method for hydrological information of unmanned aerial vehicle-mounted radar |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110370971.5A CN113108767A (en) | 2021-04-07 | 2021-04-07 | Real-time monitoring method for hydrological information of unmanned aerial vehicle-mounted radar |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113108767A true CN113108767A (en) | 2021-07-13 |
Family
ID=76715359
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110370971.5A Pending CN113108767A (en) | 2021-04-07 | 2021-04-07 | Real-time monitoring method for hydrological information of unmanned aerial vehicle-mounted radar |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113108767A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113884988A (en) * | 2021-12-07 | 2022-01-04 | 成都中星世通电子科技有限公司 | Radar communication integrated monitoring method, receiving front end and monitoring system |
| CN114001718A (en) * | 2021-10-12 | 2022-02-01 | 山东华特智慧科技有限公司 | Hydrological monitoring method and system based on intelligent flow measuring robot |
| CN114485578A (en) * | 2022-01-17 | 2022-05-13 | 青岛黄海学院 | Marine ecology monitoring device and working method thereof |
| CN114778885A (en) * | 2022-04-28 | 2022-07-22 | 珠海微度芯创科技有限责任公司 | Radar current meter and control method and device |
| CN115308435A (en) * | 2022-09-05 | 2022-11-08 | 智驰华芯(无锡)传感科技有限公司 | Two-way flow measurement side-scan Doppler radar current meter |
| CN117091515A (en) * | 2023-10-19 | 2023-11-21 | 阳泉市水文水资源勘测站 | Hydrology surface of water width caliber |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5181037A (en) * | 1991-02-15 | 1993-01-19 | Honda Giken Kogyo Kabushiki Kaisha | Fm radar system |
| JPH05346463A (en) * | 1992-04-15 | 1993-12-27 | Fujitsu Ltd | Doppler radar equipment |
| CN104482988A (en) * | 2014-12-31 | 2015-04-01 | 北京奥特美克科技股份有限公司 | Equipment and method for measuring water level and flow rate |
| CN206459711U (en) * | 2017-01-20 | 2017-09-01 | 秦福清 | A kind of unmanned plane radar flow measuring system |
| CN107202570A (en) * | 2017-07-14 | 2017-09-26 | 珠江水利委员会珠江水利科学研究院 | Water level flow rate monitoring integration device, monitoring system and monitoring method |
| CN107543546A (en) * | 2016-06-28 | 2018-01-05 | 沈阳新松机器人自动化股份有限公司 | A kind of attitude algorithm method and device of six axis movement sensors |
| CN207923129U (en) * | 2018-04-03 | 2018-09-28 | 无锡航征科技有限公司 | A kind of full-automatic flow measuring system of unmanned plane radar |
| CN108627152A (en) * | 2018-04-25 | 2018-10-09 | 珠海全志科技股份有限公司 | A kind of air navigation aid of the miniature drone based on Fusion |
| CN207965138U (en) * | 2018-01-26 | 2018-10-12 | 万胜磊 | A kind of unmanned plane radar measuring flow system |
| CN108827313A (en) * | 2018-08-10 | 2018-11-16 | 哈尔滨工业大学 | Multi-mode rotor craft Attitude estimation method based on extended Kalman filter |
| CN109061623A (en) * | 2018-06-25 | 2018-12-21 | 南京信息工程大学 | A kind of Planar integration type micro-wave height finding radar and measurement method applied to unmanned plane |
| CN109839513A (en) * | 2019-02-28 | 2019-06-04 | 北京瞭望者科技有限责任公司 | Current velocity flow-measuring method, apparatus and system |
| CN110018469A (en) * | 2019-04-12 | 2019-07-16 | 无锡智图汇联科技有限公司 | A kind of overlength distance intelligence unmanned plane flow measuring system applied to water conservancy |
| CN110186437A (en) * | 2019-06-06 | 2019-08-30 | 谭钧元 | One kind being based on unmanned plane carrier water surface flow measuring system |
| CN111649745A (en) * | 2020-05-18 | 2020-09-11 | 北京三快在线科技有限公司 | Attitude estimation method and apparatus for electronic device, and storage medium |
-
2021
- 2021-04-07 CN CN202110370971.5A patent/CN113108767A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5181037A (en) * | 1991-02-15 | 1993-01-19 | Honda Giken Kogyo Kabushiki Kaisha | Fm radar system |
| JPH05346463A (en) * | 1992-04-15 | 1993-12-27 | Fujitsu Ltd | Doppler radar equipment |
| CN104482988A (en) * | 2014-12-31 | 2015-04-01 | 北京奥特美克科技股份有限公司 | Equipment and method for measuring water level and flow rate |
| CN107543546A (en) * | 2016-06-28 | 2018-01-05 | 沈阳新松机器人自动化股份有限公司 | A kind of attitude algorithm method and device of six axis movement sensors |
| CN206459711U (en) * | 2017-01-20 | 2017-09-01 | 秦福清 | A kind of unmanned plane radar flow measuring system |
| CN107202570A (en) * | 2017-07-14 | 2017-09-26 | 珠江水利委员会珠江水利科学研究院 | Water level flow rate monitoring integration device, monitoring system and monitoring method |
| CN207965138U (en) * | 2018-01-26 | 2018-10-12 | 万胜磊 | A kind of unmanned plane radar measuring flow system |
| CN207923129U (en) * | 2018-04-03 | 2018-09-28 | 无锡航征科技有限公司 | A kind of full-automatic flow measuring system of unmanned plane radar |
| CN108627152A (en) * | 2018-04-25 | 2018-10-09 | 珠海全志科技股份有限公司 | A kind of air navigation aid of the miniature drone based on Fusion |
| CN109061623A (en) * | 2018-06-25 | 2018-12-21 | 南京信息工程大学 | A kind of Planar integration type micro-wave height finding radar and measurement method applied to unmanned plane |
| CN108827313A (en) * | 2018-08-10 | 2018-11-16 | 哈尔滨工业大学 | Multi-mode rotor craft Attitude estimation method based on extended Kalman filter |
| CN109839513A (en) * | 2019-02-28 | 2019-06-04 | 北京瞭望者科技有限责任公司 | Current velocity flow-measuring method, apparatus and system |
| CN110018469A (en) * | 2019-04-12 | 2019-07-16 | 无锡智图汇联科技有限公司 | A kind of overlength distance intelligence unmanned plane flow measuring system applied to water conservancy |
| CN110186437A (en) * | 2019-06-06 | 2019-08-30 | 谭钧元 | One kind being based on unmanned plane carrier water surface flow measuring system |
| CN111649745A (en) * | 2020-05-18 | 2020-09-11 | 北京三快在线科技有限公司 | Attitude estimation method and apparatus for electronic device, and storage medium |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114001718A (en) * | 2021-10-12 | 2022-02-01 | 山东华特智慧科技有限公司 | Hydrological monitoring method and system based on intelligent flow measuring robot |
| CN113884988A (en) * | 2021-12-07 | 2022-01-04 | 成都中星世通电子科技有限公司 | Radar communication integrated monitoring method, receiving front end and monitoring system |
| CN114485578A (en) * | 2022-01-17 | 2022-05-13 | 青岛黄海学院 | Marine ecology monitoring device and working method thereof |
| CN114778885A (en) * | 2022-04-28 | 2022-07-22 | 珠海微度芯创科技有限责任公司 | Radar current meter and control method and device |
| CN114778885B (en) * | 2022-04-28 | 2023-11-07 | 珠海微度芯创科技有限责任公司 | Radar flow velocity meter and control method and device |
| CN115308435A (en) * | 2022-09-05 | 2022-11-08 | 智驰华芯(无锡)传感科技有限公司 | Two-way flow measurement side-scan Doppler radar current meter |
| CN115308435B (en) * | 2022-09-05 | 2024-04-16 | 智驰华芯(无锡)传感科技有限公司 | Side-scanning Doppler radar flow velocity meter capable of measuring flow in two directions |
| CN117091515A (en) * | 2023-10-19 | 2023-11-21 | 阳泉市水文水资源勘测站 | Hydrology surface of water width caliber |
| CN117091515B (en) * | 2023-10-19 | 2023-12-15 | 阳泉市水文水资源勘测站 | Hydrology surface of water width caliber |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113108767A (en) | Real-time monitoring method for hydrological information of unmanned aerial vehicle-mounted radar | |
| CN107202570B (en) | Water level flow rate monitoring integration device, monitoring system and monitoring method | |
| EP2786175B1 (en) | Motion-stabilised lidar and method for wind speed measurement | |
| JP3658595B2 (en) | GPS wave height / flow direction flow velocity measuring device and GPS wave height / flow direction flow velocity measuring system | |
| CN109116360B (en) | A kind of deep-sea real-time high-precision locating method and system | |
| CN104007286A (en) | System for automatically monitoring surface velocity of riverway | |
| CN203385413U (en) | Altitude measurement system suitable for low-altitude unmanned aerial vehicle | |
| CN110988884B (en) | Medium latitude ionosphere detection method based on high-frequency ground wave radar | |
| CN103134472A (en) | Measuring device capable of monitoring wave height and frequency of river and sea waves in real time | |
| CN107179420A (en) | A kind of use directional ultrasonic measurement ship speed through water and the method in direction | |
| JP6567665B2 (en) | A method for estimating each drift (floating) vector at all points in a ship's route | |
| Cario et al. | Analysis of error sources in underwater localization systems | |
| CN105093220A (en) | Method for measuring ocean surface flow speed by use of real aperture radar | |
| Wang et al. | Water velocity and level monitoring based on UAV radar | |
| CN111638514A (en) | Unmanned aerial vehicle height measurement method and unmanned aerial vehicle navigation filter | |
| RU2664456C2 (en) | Ultrasonic method of measuring the velocity of flow and water expenditure in open water | |
| CN109959907B (en) | Method for processing height data | |
| Cui et al. | Retrieval of ocean wave characteristics from K-band radar | |
| CN109959928B (en) | Unmanned aerial vehicle radar altimeter system for petroleum pipeline inspection | |
| CN109959929B (en) | Signal processing method of unmanned aerial vehicle radar altimeter in oil pipeline inspection | |
| CN217484507U (en) | Underwater speed measuring device based on electronic gyroscope | |
| CN115656933A (en) | Water surface flow velocity measuring method and device under severe weather conditions | |
| RU2468387C1 (en) | Device for measuring vertical component of wind velocity for detecting wind shift | |
| Bandini et al. | Measuring River Surface Velocity with Doppler Radar and Particle Image Velocimetry (PIV) Using Unmanned Aerial Systems (UASs) | |
| SENSOR et al. | on the incident angle as shown in Figure 3. For example, a speed error of±135 to-i5'results from a trim or list of 18'for an inci-dent beam angle of 45 (the angle used by the Ryan model 547). |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210713 |