CN115980788B - Wind field processing method of coherent wind lidar - Google Patents
Wind field processing method of coherent wind lidar Download PDFInfo
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Abstract
The invention discloses a wind field processing method of a coherent wind-measuring laser radar, which relates to the technical field of wind field detection, wherein before the radar performs navigation detection, radar parameters and frequency intervals are acquired, and frequency calibration correction is performed for eliminating errors; when the radar is in navigation detection, laser is respectively emitted to three different directions at the current time and the current position, the radial wind speeds of the three different directions are obtained through calculation according to the power spectrums of the three different directions, and meanwhile, the attitude angles of the radar at the current time and the current position are monitored in real time by utilizing the sensor and used for compensating and correcting the three-dimensional wind field to obtain the high-precision three-dimensional wind field. In addition, when the wind speed is calculated, the method and the device also carry out signal abnormality judgment and abnormality rejection through the carrier-to-noise ratio, so that the influence of weak signals on wind speed calculation can be eliminated to a certain extent, and the three-dimensional wind field can be inverted more accurately.
Description
Technical Field
The invention relates to the technical field of wind field detection, in particular to a wind field processing method of a coherent wind-finding laser radar.
Background
The atmospheric wind field is an important atmospheric physical parameter, and the accurate observation of the atmospheric wind field has great significance for preventing and controlling atmospheric pollution, improving aerospace safety, forecasting military environment, improving climate research model, improving accuracy of long-term weather forecast and the like. The wind-measuring laser radar is used as an active atmosphere remote sensing instrument, has the advantages of high wind field measurement precision, high time and space resolution, no influence of ground clutter and the like, and is very suitable for rapid and accurate wind field measurement.
The navigation detection mode has the characteristics of flexibility and convenience, and the wind field information based on the geographic position can be obtained by continuous automatic monitoring in the travelling process. At present, wind field measurement of the traditional laser radar mainly adopts conical scanning formed by combining single wave beam with motor azimuth transformation, and larger calculation errors can be generated along with space position and time during navigation detection. The inversion wind field is known to at least need three groups of radial wind speed synthesis, such as acquisition card signal acquisition, operation such as rotation of a motor to a target azimuth angle can consume time, and the radial wind speed group obtained under the condition is under different working conditions, so that larger errors are inevitably generated. In addition, in the travelling process, the attitude of the radar is also changed in real time, and the three-dimensional wind field inversion is also affected to a certain extent.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a wind field processing method of a coherent wind-measuring laser radar, when in navigation detection, the radar emits laser in three different directions simultaneously, radial wind speeds in three different directions are obtained through calculation according to power spectrums in three different directions, and simultaneously, the attitude angle of the radar is monitored in real time by utilizing a sensor and used for compensating and correcting a three-dimensional wind field to obtain the high-precision three-dimensional wind field.
In order to achieve the above purpose, the present invention adopts the following technical scheme, including:
a wind field processing method of a coherent wind lidar comprises the following steps:
when the coherent wind lidar is used for navigation detection, laser is respectively emitted to three different directions at the current time and the current position to obtain power spectrums in the three different directions; radial wind speeds in all directions are calculated according to the power spectrums in all directions respectively to obtain three radial wind speeds in different directions, namely Los1, los2 and Los3;
when the coherent wind lidar is in navigation detection, a sensor is also utilized to acquire the attitude angle of the coherent wind lidar at the current time and the current position; the attitude angle includes: yaw angle v, pitch angle delta, roll angle ρ;
combining the attitude angles of the coherent wind lidar to obtain a compensated and corrected three-dimensional wind field; the three directions of the three-dimensional wind field are respectively as follows: a horizontal east direction, a horizontal north direction and a vertical direction;
in the three-dimensional wind field after compensation correction, a wind speed component k1 along the horizontal forward direction, a wind speed component k2 along the horizontal forward north direction and a wind speed component k3 along the vertical direction are respectively:
k1=(Los1-Los3×sinθ×sinρ×sinδ)/(sinθ×cosρ×cosδ)；
k2=(Los2-Los3×sinθ×sinρ×sinδ)/(sinθ×cosρ×cosδ)；
k3=Los3×sinθ×sinρ×sinδ；
wherein θ is the zenith angle of the radar relative to the vehicle; the yaw angle v is the included angle between the radar and the horizontal northbound direction, the pitch angle delta is the included angle between the radar and the horizontal northbound direction, and the roll angle rho is the included angle between the radar and the vertical direction.
Preferably, before the navigation detection, the coherent wind lidar acquires radar parameters and frequency intervals, and the method is specifically as follows:
s11, reading the center wavelength lambda of the local oscillation light of the laser;
s12, calculating the frequency fi= (i multiplied by F)/N of each point in the distance gate according to the sampling frequency F and the total point number N in the distance gate; wherein i represents the i-th point, i=1, 2, 3..n; fi represents the frequency of the ith point within the range gate.
S13, searching a position where the central frequency of the pulse light of the laser is located, namely a hump position Mid of the pulse light under a windless scene;
s14, determining a frequency interval (Left, right) according to the hump position Mid;
s15, determining the central frequency shift AOM of laser pulse light;
s16, determining an actual frequency spectrum Freq according to the corresponding relation between the central frequency shift AOM of the pulse light and the hump position Mid of the pulse light;
when the coherent wind-measuring laser radar is used for navigation detection, the radial wind speed Los along the laser emission direction is calculated, and the specific mode is as follows:
s21, acquiring a laser echo signal of the coherent wind lidar in the laser transmitting direction to obtain an original power spectrum;
s22, aiming at an original power spectrum, calculating a background noise array corresponding to the original power spectrum;
s23, filtering background noise from the original power spectrum according to the background noise array of the original power spectrum to obtain a filtered background noise power spectrum;
s24, extracting data of a background noise filtering power spectrum in a frequency interval (Left, right) to obtain power spectrum interval data;
s25, calculating signal power values Pc of all distance gates in the power spectrum interval data according to the power spectrum interval data;
s26, calculating radial wind speed los=λ× (pc×freq-AOM)/2 along the laser emission direction; wherein the radial wind speed comprises the wind speed of each range gate.
Preferably, in step S22, the background noise array is calculated in the following manner:
and extracting data of the last n distance gates in the original power spectrum, performing counterpoint, namely point-to-point averaging on the extracted data, wherein the average value of each point obtained after the counterpoint averaging is the background noise of each point, and the background noise of each point forms a background noise array.
Preferably, in step S23, background noise is filtered out from the original power spectrum in the following specific manner:
and respectively subtracting the background noise of the corresponding point from the value of each point in each distance gate of the original power spectrum to obtain a power spectrum after filtering the background noise, namely a filtered background noise power spectrum.
Preferably, in step S25, the signal power value Pc of each range gate is calculated by:
searching the intra-gate peak positions of all distance gates in the power spectrum interval data, determining a search interval of the signal data according to the intra-gate peak positions, wherein the data in the search interval is the signal data, smoothing and eliminating abnormality of the signal data, and calculating to obtain a signal power value Pc of each distance gate by adopting an area method, namely an integration method;
the search interval determination mode of the signal data is as follows: after the position of the peak in the door is obtained, searching is respectively carried out on the left side and the right side, the point with different first change trends found to the left is a left boundary point, and the frequency corresponding to the left boundary point is the lower limit of the search interval; the first point with different change trends found to the right is the right boundary point, and the frequency corresponding to the right boundary point is the upper limit of the search interval.
Preferably, in step S25, the carrier-to-noise ratio CNR of each distance gate in the power spectrum interval data is calculated according to the power spectrum interval data, and if the carrier-to-noise ratio CNR of a certain distance gate does not meet the set threshold requirement, the laser echo signal in the distance gate is not credible and is not used for performing the radial wind speed calculation in step S26; if the carrier-to-noise ratio CNR of a certain range gate meets the set threshold requirement, the laser echo signal in the range gate is reliable and is used for carrying out radial wind speed calculation in the step S26;
carrier-to-noise ratio cnr=10×lg (Pc/Pn) for each range gate in the power spectrum interval data; where Pn is the noise power value Pn for each range gate in the power spectral interval data.
Preferably, in step S14, the frequency range (Left, right) is determined in the following manner: after obtaining the hump position Mid, searching Left and right sides respectively, wherein points with different first change trends found Left are Left boundary points, and frequencies corresponding to the Left boundary points are the lower limit Left of a frequency interval; the first point with different change trends found to the Right is the Right boundary point, and the frequency corresponding to the Right boundary point is the upper limit Right of the search interval.
Preferably, in the three-dimensional wind field after compensation correction, the calculation process of the wind speed component k1 along the horizontal positive east direction, the wind speed component k2 along the horizontal positive north direction and the wind speed component k3 along the vertical direction is as follows:
assume that: three different directions are Y1, Y2, Y3 respectively:
Y1=[sinθ×cosρ×cosδ×sin(φ1+υ)，sinθ×cosρ×cosδ×cos(φ1+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 1+ v) is the angle between the direction Y1 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 1+ v) is the angle between the direction Y1 and the horizontal forward direction, and sin theta x sin rho x sin delta is the angle between the direction Y1 and the vertical direction. θ is the zenith angle of the radar relative to the vehicle; phi 1 is the azimuth of the direction Y1 relative to the plane of the vehicle;
Y2=[sinθ×cosρ×cosδ×sin(φ2+υ)，sinθ×cosρ×cosδ×cos(φ2+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 2+ v) is the angle between the direction Y2 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 2+ v) is the angle between the direction Y2 and the horizontal forward direction, and sin theta x sin rho x sin delta is the angle between the direction Y2 and the vertical direction. Phi 2 is the azimuth of the direction Y2 relative to the plane of the vehicle;
Y3=[sinθ×cosρ×cosδ×sin(φ3+υ)，sinθ×cosρ×cosδ×cos(φ3+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 3+ v) is the angle between the direction Y3 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 3+ v) is the angle between the direction Y3 and the horizontal forward direction, and sin theta x sin rho x sin delta is the angle between the direction Y3 and the vertical direction. Phi 3 is the azimuth of direction Y3 relative to the plane of the vehicle;
then, the radial wind speed expressions in three different directions are respectively:
V1=k1×sinθ×cosρ×cosδ×sin(φ1+υ)+k2×sinθ×cosρ×cosδ×cos(φ1+υ)+k3×sinθ×sinρ×sinδ；
V2=k1×sinθ×cosρ×cosδ×sin(φ2+υ)+k2×sinθ×cosρ×cosδ×cos(φ2+υ)+k3×sinθ×sinρ×sinδ；
V3=k1×sinθ×cosρ×cosδ×sin(φ3+υ)+k2×sinθ×cosρ×cosδ×cos(φ3+υ)+k3×sinθ×sinρ×sinδ；
simultaneous v1=los1, v2=los2, v3=los3;
the wind speed component k1 along the horizontal positive east direction, the wind speed component k2 along the horizontal positive north direction and the wind speed component k3 along the vertical direction are obtained through solving.
Preferably, Φ1=0, Φ2=120°, Φ3=240°.
Preferably, the coherent wind lidar is fixedly arranged on a vehicle, navigation detection is carried out through movement of the vehicle, the attitude angles of the vehicle and the coherent wind lidar are kept consistent, and an attitude sensor is arranged on the vehicle or the coherent wind lidar to collect the attitude angle of the coherent wind lidar.
The invention has the advantages that:
(1) According to the invention, during navigation detection, the radar emits laser in three different directions at the current time and the current position, the radial wind speeds in three different directions are obtained through calculation according to the power spectrums in the three different directions, and meanwhile, the attitude angles of the radar at the current time and the current position are monitored in real time by using the sensor and used for compensating and correcting the three-dimensional wind field to obtain the high-precision three-dimensional wind field.
(2) The invention is different from the traditional navigation mode, and because the three laser beams of the radar are transmitted and received simultaneously, the operation compensation such as the vehicle running speed, the acquisition of the acquisition card signal, the rotation of the motor to the target azimuth angle and the like is not needed to be considered, and the algorithm complexity is reduced.
(3) Before the navigation detection, the method acquires radar parameters and frequency intervals for frequency calibration correction, and eliminates errors.
(4) When the wind speed is calculated, the method and the device perform signal abnormality judgment and abnormality rejection through the carrier-to-noise ratio, can eliminate the influence of weak signals on wind speed calculation to a certain extent, and can more accurately invert the three-dimensional wind field.
(5) On the basis of high-precision wind field inversion, the method is networked with other monitoring radars (such as monitoring particulate matters, ozone, carbon dioxide and the like), and pollutant flux and transmission direction can be calculated by combining pollutant data, so that pollutant causes in a navigation area can be analyzed macroscopically.
Drawings
FIG. 1 is a flow chart of a method for processing a wind field of a coherent wind lidar according to the present invention.
Fig. 2 is a schematic view of the attitude angle of the radar.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In this embodiment, the coherent wind lidar is fixedly installed on a vehicle, the navigation detection is performed by the movement of the vehicle, the attitude angles of the vehicle and the coherent wind lidar are kept consistent, and an attitude sensor can be arranged on the vehicle or on the coherent wind lidar to collect the attitude angle of the coherent wind lidar.
As shown in fig. 1, a wind field processing method of a coherent wind lidar includes the following steps:
s1, acquiring radar parameters and frequency intervals before navigation detection by the coherent wind lidar.
The specific procedure of step S1 is as follows:
s11, reading the center wavelength lambda of the local oscillation light of the laser.
S12, calculating the frequency fi= (i multiplied by F)/N of each point in the distance gate according to the sampling frequency F and the total point number N in the distance gate; wherein i represents the i-th point, i=1, 2, 3..n; fi represents the frequency of the ith point within the range gate.
In this embodiment, the sampling frequency F of the sampling card is 1GSa/s, and the total number of points N in the range gate is 1024 points, i.e., the frequency fi= (i×1000)/1024 of the i-th point in the range gate.
And S13, searching the position of the central frequency of the pulsed light of the laser in the windless scene, namely the hump position Mid of the pulsed light.
S14, acquiring a frequency interval (Left, right) according to the hump position Mid. The specific method is as follows: after the hump position Mid is obtained, searching is respectively carried out on the Left side and the right side, the point with different first change trends, namely, the Left boundary point, is found to the Left, and the frequency corresponding to the Left boundary point is the lower limit Left of the frequency interval; finding out the point with different first change trend Right, namely the Right boundary point, and the frequency corresponding to the Right boundary point is the upper limit Right of the frequency interval.
S15, determining the central frequency shift AOM of the laser pulse light by using a frequency meter. In this embodiment, the AOM is 80MHz.
S16, according to the corresponding relation between the central frequency shift AOM of the pulse light and the hump position Mid of the pulse light, the actual frequency spectrum Freq is finally determined.
S2, when the coherent wind-finding laser radar is used for navigation detection, laser is respectively emitted to three different directions at the current time and the current position, so that power spectrums in the three different directions are obtained; and respectively calculating radial wind speeds in all directions according to the power spectrums in all directions to obtain three radial wind speeds in all directions, namely Los1, los2 and Los3.
The specific procedure of step S2 is as follows:
s21, acquiring laser echo signals of the coherent wind lidar in three different directions at the current time and the current position, and obtaining three original power spectrums in different directions. Wherein the direction refers to the laser emission direction.
S22, for the original power spectrums in all directions, respectively calculating background noise arrays corresponding to the original power spectrums in all directions, wherein the calculation mode is as follows:
and extracting data of the last n distance gates in the original power spectrum, and performing para-position, namely point-to-point average on the extracted data to obtain a background noise array corresponding to the original power spectrum. The average value of each point obtained by averaging the positions is the background noise of each point, and the background noise of each point forms a background noise array.
S23, according to the background noise arrays of the original power spectrums in all directions, background noise is filtered from the original power spectrums in all directions, and three filtered background noise power spectrums in different directions are obtained, wherein the specific modes are as follows:
and utilizing the background noise array of the original power spectrum to perform counterpoint filtering on the original power spectrum to remove background noise, namely respectively subtracting the background noise of the corresponding point from the value of each point in each distance gate of the original power spectrum to obtain a power spectrum after removing the background noise, namely a background noise filtering power spectrum.
S24, respectively extracting data of the background noise filtering power spectrums in three different directions in a frequency interval (Left, right) to obtain power spectrum interval data in three different directions.
S25, for the power spectrum interval data in each direction extracted in the step S24, respectively calculating the signal power value Pc of each distance gate in the power spectrum interval data in each direction, wherein the specific mode is as follows:
searching the intra-gate peak positions of all the distance gates in the power spectrum interval data, determining the search interval of the signal data according to the intra-gate peak positions, wherein the data in the search interval is the signal data, smoothing and eliminating the abnormality of the signal data, and calculating the signal power value Pc of each distance gate by adopting an area method, namely an integration method.
The search interval determination mode of the signal data is as follows: after the position of the peak in the door is obtained, searching is respectively carried out on the left side and the right side, the point with different first change trends found in the left searching is the left boundary point, and the frequency corresponding to the left boundary point is the lower limit of the searching interval; the first point with different change trends found to the right is the right boundary point, and the frequency corresponding to the right boundary point is the upper limit of the search interval.
In step S25, for the power spectrum interval data in each direction extracted in step S24, the noise power value Pn of each distance gate in the power spectrum interval data in each direction is also calculated, where the calculation mode is as follows: and calculating the intra-door noise data of each distance door in the power spectrum interval data, smoothing and removing abnormality from the intra-door noise data of each distance door, and calculating the noise power value Pn of each distance door by adopting an area method, namely an integration method.
The carrier-to-noise ratio cnr=10×lg (Pc/Pn) of each range gate is then calculated using the signal power value Pc and the noise power value Pn of each range gate. If the carrier-to-noise ratio CNR of a certain range gate does not meet the set threshold requirement, the laser echo signal in the range gate is not reliable, and is not used for performing the radial wind speed calculation in step S26, and the radial wind speed of the range gate can be obtained directly by an interpolation method. If the carrier-to-noise ratio CNR of a certain range gate meets the set threshold requirement, the laser echo signal in the range gate is reliable, and the laser echo signal is used for performing radial wind speed calculation in step S26.
S26, calculating radial wind speed Los along the laser emission direction under the current working condition:
Los=λ×(Pc×Freq-AOM)/2；
wherein the radial wind speed comprises the wind speed of each range gate.
And S3, when the coherent wind lidar performs navigation detection, acquiring the attitude angle of the coherent wind lidar at the current time and the current position by using a sensor. The attitude angle includes: yaw angle v, pitch angle delta, roll angle ρ; as shown in fig. 2, the yaw angle v is an angle between the radar and the horizontal northbound direction, the pitch angle δ is an angle between the radar and the horizontal northbound direction, and the roll angle ρ is an angle between the radar and the vertical direction.
And S4, compensating and correcting the three-dimensional wind field according to the attitude angle of the coherent wind lidar to obtain a compensated and corrected three-dimensional wind field. The three directions of the three-dimensional wind field are respectively as follows: horizontal east direction, horizontal north direction, vertical direction.
The specific procedure of step S4 is as follows:
assume that: the three different laser emission directions are Y1, Y2 and Y3 respectively:
Y1=[sinθ×cosρ×cosδ×sin(φ1+υ)，sinθ×cosρ×cosδ×cos(φ1+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 1+ v) is the included angle between the laser emitting direction Y1 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 1+ v) is the included angle between the laser emitting direction Y1 and the horizontal forward direction, and sin theta x sin rho x sin delta is the included angle between the laser emitting direction Y1 and the vertical direction; θ is the zenith angle of the radar relative to the vehicle; phi 1 is the azimuth angle of the laser emission direction Y1 relative to the plane of the vehicle;
Y2=[sinθ×cosρ×cosδ×sin(φ2+υ)，sinθ×cosρ×cosδ×cos(φ2+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 2+ v) is the included angle between the laser emitting direction Y2 and the horizontal direction, sin theta x cos rho x cos delta x cos (phi 2+ v) is the included angle between the laser emitting direction Y2 and the horizontal direction, and sin theta x sin rho x sin delta is the included angle between the laser emitting direction Y2 and the vertical direction; phi 2 is the azimuth angle of the laser emission direction Y2 relative to the plane of the vehicle;
Y3=[sinθ×cosρ×cosδ×sin(φ3+υ)，sinθ×cosρ×cosδ×cos(φ3+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 3+ v) is the included angle between the laser emitting direction Y3 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 3+ v) is the included angle between the laser emitting direction Y3 and the horizontal forward direction, and sin theta x sin rho x sin delta is the included angle between the laser emitting direction Y3 and the vertical direction; phi 3 is the azimuth angle of the laser emission direction Y3 relative to the plane of the vehicle;
in the embodiment, θ is fixed to 17.8 degrees; phi 1, phi 2 and phi 3 are respectively 0 degree, 120 degrees and 240 degrees.
Then, the radial wind speed expressions in three different directions are respectively:
V1=k1×sinθ×cosρ×cosδ×sin(φ1+υ)+k2×sinθ×cosρ×cosδ×cos(φ1+υ)+k3×sinθ×sinρ×sinδ；
V2=k1×sinθ×cosρ×cosδ×sin(φ2+υ)+k2×sinθ×cosρ×cosδ×cos(φ2+υ)+k3×sinθ×sinρ×sinδ；
V3=k1×sinθ×cosρ×cosδ×sin(φ3+υ)+k2×sinθ×cosρ×cosδ×cos(φ3+υ)+k3×sinθ×sinρ×sinδ；
simultaneous v1=los1, v2=los2, v3=los3;
solving to obtain a wind speed component k1 along the horizontal positive east direction, a wind speed component k2 along the horizontal positive north direction and a wind speed component k3 along the vertical direction, wherein the wind speed components are respectively as follows:
k1=(Los1-Los3×sinθ×sinρ×sinδ)/(sinθ×cosρ×cosδ)；
k2=(Los2-Los3×sinθ×sinρ×sinδ)/(sinθ×cosρ×cosδ)；
k3=Los3×sinθ×sinρ×sinδ。
then, the wind speed component k1 along the horizontal positive east direction and the wind speed component k2 along the horizontal positive north direction are subjected to inverse tangent, and the angle wd=arctan (k 2/k 1) +180 degrees of the horizontal wind direction can be obtained.
The wind speed WS=of the horizontal wind can be obtained by modulo the wind speed component k1 along the horizontal forward direction and the wind speed component k2 along the horizontal forward north direction
。
k3 is positive and k3 is negative, respectively, indicating that the wind velocity component in the vertical direction is vertically upwind and the wind velocity component in the vertical direction is vertically downwind.
In the embodiment, for a coherent wind-finding laser radar system with the laser wavelength of 1.55um, a frequency shift deviation of 1MHz can bring about a wind speed error of 0.775m/s, and the radar system performs frequency calibration correction before monitoring to eliminate the error. The radar system monitors the attitude angle of the radar in real time during monitoring and is used for compensating and correcting the three-position wind field, meanwhile, the integral influence of weak signals on the radar system can be eliminated to a certain extent through the judgment of the carrier-to-noise ratio, and the change condition of the wind field can be measured more accurately. The radar structure adopts three-channel lasers to transmit and receive simultaneously, eliminates the influence caused by the movement of vehicles along with time and space, forms a specific wind field model in a mode of changing and measuring simultaneously, and can calculate the flux and the transmission direction of pollutants by combining pollutant data, so as to macroscopically analyze and judge the cause of the pollutants.
The method is applied to acquisition software of a coherent wind lidar system, and the acquisition software performs frequency calibration correction when initialized after started; after the monitoring is started, the attitude angle of the attitude sensor is obtained in real time to compensate and correct the current three-dimensional wind field, and the carrier-to-noise ratio is adopted to judge and reject the abnormal value, so that the influence of the weak signal on wind field inversion is eliminated, and the system precision is improved.
The above embodiments are merely preferred embodiments of the present invention and are not intended to limit the present invention, and any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (9)
1. A wind field processing method of a coherent wind lidar is characterized in that the process is as follows:
when the coherent wind lidar is used for navigation detection, laser is respectively emitted to three different directions at the current time and the current position to obtain power spectrums in the three different directions; radial wind speeds in all directions are calculated according to the power spectrums in all directions respectively to obtain three radial wind speeds in different directions, namely Los1, los2 and Los3;
when the coherent wind lidar is in navigation detection, a sensor is also utilized to acquire the attitude angle of the coherent wind lidar at the current time and the current position; the attitude angle includes: yaw angle v, pitch angle delta, roll angle ρ;
combining the attitude angles of the coherent wind lidar to obtain a compensated and corrected three-dimensional wind field; the three directions of the three-dimensional wind field are respectively as follows: a horizontal east direction, a horizontal north direction and a vertical direction;
in the three-dimensional wind field after compensation correction, a wind speed component k1 along the horizontal forward direction, a wind speed component k2 along the horizontal forward north direction and a wind speed component k3 along the vertical direction are respectively:
k1=(Los1-Los3×sinθ×sinρ×sinδ)/(sinθ×cosρ×cosδ)；
k2=(Los2-Los3×sinθ×sinρ×sinδ)/(sinθ×cosρ×cosδ)；
k3=Los3×sinθ×sinρ×sinδ；
wherein θ is the zenith angle of the radar relative to the vehicle; the yaw angle v is the included angle between the radar and the horizontal northbound direction, the pitch angle delta is the included angle between the radar and the horizontal northbound direction, and the roll angle rho is the included angle between the radar and the vertical direction.
2. The wind field processing method of a coherent wind lidar according to claim 1, wherein the coherent wind lidar acquires radar parameters and frequency intervals before the navigation detection, specifically as follows:
s11, reading the center wavelength lambda of the local oscillation light of the laser;
s12, calculating the frequency fi= (i multiplied by F)/N of each point in the distance gate according to the sampling frequency F and the total point number N in the distance gate; wherein i represents the i-th point, i=1, 2, 3..n; fi represents the frequency of the ith point within the range gate;
s13, searching a position where the central frequency of the pulse light of the laser is located, namely a hump position Mid of the pulse light under a windless scene;
s14, determining a frequency interval (Left, right) according to the hump position Mid;
s15, determining the central frequency shift AOM of laser pulse light;
s16, determining an actual frequency spectrum Freq according to the corresponding relation between the central frequency shift AOM of the pulse light and the hump position Mid of the pulse light;
when the coherent wind-measuring laser radar is used for navigation detection, the radial wind speed Los along the laser emission direction is calculated, and the specific mode is as follows:
s21, acquiring a laser echo signal of the coherent wind lidar in the laser transmitting direction to obtain an original power spectrum;
s22, aiming at an original power spectrum, calculating a background noise array corresponding to the original power spectrum;
s23, filtering background noise from the original power spectrum according to the background noise array of the original power spectrum to obtain a filtered background noise power spectrum;
s24, extracting data of a background noise filtering power spectrum in a frequency interval (Left, right) to obtain power spectrum interval data;
s25, calculating signal power values Pc of all distance gates in the power spectrum interval data according to the power spectrum interval data;
s26, calculating radial wind speed los=λ× (pc×freq-AOM)/2 along the laser emission direction; wherein the radial wind speed comprises the wind speed of each range gate.
3. The wind field processing method of a coherent wind lidar according to claim 2, wherein in step S22, the background noise array is calculated by:
and extracting data of the last n distance gates in the original power spectrum, performing counterpoint, namely point-to-point averaging on the extracted data, wherein the average value of each point obtained after the counterpoint averaging is the background noise of each point, and the background noise of each point forms a background noise array.
4. A method for processing a wind field of a coherent wind lidar according to claim 3, wherein in step S23, background noise is filtered out from an original power spectrum by:
and respectively subtracting the background noise of the corresponding point from the value of each point in each distance gate of the original power spectrum to obtain a power spectrum after filtering the background noise, namely a filtered background noise power spectrum.
5. The wind field processing method of coherent wind lidar according to claim 2, wherein in step S25, the signal power value Pc of each range gate is calculated by:
searching the intra-gate peak positions of all distance gates in the power spectrum interval data, determining a search interval of the signal data according to the intra-gate peak positions, wherein the data in the search interval is the signal data, smoothing and eliminating abnormality of the signal data, and calculating to obtain a signal power value Pc of each distance gate by adopting an area method, namely an integration method;
the search interval determination mode of the signal data is as follows: after the position of the peak in the door is obtained, searching is respectively carried out on the left side and the right side, the point with different first change trends found to the left is a left boundary point, and the frequency corresponding to the left boundary point is the lower limit of the search interval; the first point with different change trends found to the right is the right boundary point, and the frequency corresponding to the right boundary point is the upper limit of the search interval.
6. The wind field processing method of a coherent wind lidar according to claim 2 or 5, wherein in step S25, a carrier-to-noise ratio CNR of each range gate in the power spectrum interval data is calculated according to the power spectrum interval data, and if the carrier-to-noise ratio CNR of a certain range gate does not meet a set threshold requirement, it indicates that the laser echo signal in the range gate is not reliable and is not used for performing the radial wind speed calculation in step S26; if the carrier-to-noise ratio CNR of a certain range gate meets the set threshold requirement, the laser echo signal in the range gate is reliable and is used for carrying out radial wind speed calculation in the step S26;
carrier-to-noise ratio cnr=10×lg (Pc/Pn) for each range gate in the power spectrum interval data; where Pn is the noise power value Pn for each range gate in the power spectral interval data.
7. The wind field processing method of a coherent wind lidar according to claim 2, wherein in step S14, the frequency range (Left, right) is determined by: after obtaining the hump position Mid, searching Left and right sides respectively, wherein points with different first change trends found Left are Left boundary points, and frequencies corresponding to the Left boundary points are the lower limit Left of a frequency interval; the first point with different change trends found to the Right is the Right boundary point, and the frequency corresponding to the Right boundary point is the upper limit Right of the search interval.
8. The wind field processing method of a coherent wind lidar according to claim 1, wherein the calculation process of the wind speed component k1 along the horizontal forward direction, the wind speed component k2 along the horizontal forward direction, and the wind speed component k3 along the vertical direction in the three-dimensional wind field after compensation correction is as follows:
assume that: three different directions are Y1, Y2, Y3 respectively:
Y1=[sinθ×cosρ×cosδ×sin(φ1+υ)，sinθ×cosρ×cosδ×cos(φ1+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 1+ v) is the angle between the direction Y1 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 1+ v) is the angle between the direction Y1 and the horizontal forward direction, and sin theta x sin rho x sin delta is the angle between the direction Y1 and the vertical direction. θ is the zenith angle of the radar relative to the vehicle; phi 1 is the azimuth of the direction Y1 relative to the plane of the vehicle;
Y2=[sinθ×cosρ×cosδ×sin(φ2+υ)，sinθ×cosρ×cosδ×cos(φ2+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 2+ v) is the angle between the direction Y2 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 2+ v) is the angle between the direction Y2 and the horizontal forward direction, and sin theta x sin rho x sin delta is the angle between the direction Y2 and the vertical direction. Phi 2 is the azimuth of the direction Y2 relative to the plane of the vehicle;
Y3=[sinθ×cosρ×cosδ×sin(φ3+υ)，sinθ×cosρ×cosδ×cos(φ3+υ)，sinθ×sinρ×sinδ]；
wherein sin theta x cos rho x cos delta x sin (phi 3+ v) is the angle between the direction Y3 and the horizontal forward direction, sin theta x cos rho x cos delta x cos (phi 3+ v) is the angle between the direction Y3 and the horizontal forward direction, and sin theta x sin rho x sin delta is the angle between the direction Y3 and the vertical direction. Phi 3 is the azimuth of direction Y3 relative to the plane of the vehicle;
then, the radial wind speed expressions in three different directions are respectively:
V1=k1×sinθ×cosρ×cosδ×sin(φ1+υ)+k2×sinθ×cosρ×cosδ×cos(φ1+υ)+k3×sinθ×sinρ×sinδ；
V2=k1×sinθ×cosρ×cosδ×sin(φ2+υ)+k2×sinθ×cosρ×cosδ×cos(φ2+υ)+k3×sinθ×sinρ×sinδ；
V3=k1×sinθ×cosρ×cosδ×sin(φ3+υ)+k2×sinθ×cosρ×cosδ×cos(φ3+υ)+k3×sinθ×sinρ×sinδ；
simultaneous v1=los1, v2=los2, v3=los3;
solving to obtain a wind speed component k1 along the horizontal positive east direction, a wind speed component k2 along the horizontal positive north direction and a wind speed component k3 along the vertical direction;
wherein, phi 1=0, phi 2=120°, phi 3=240°.
9. The wind field processing method of a coherent wind lidar according to claim 1, wherein the coherent wind lidar is fixedly installed on a vehicle, navigation detection is performed by movement of the vehicle, attitude angles of the vehicle and the coherent wind lidar are kept consistent, and an attitude sensor is provided on the vehicle or on the coherent wind lidar to collect the attitude angle of the coherent wind lidar.
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