CN115407306A - Data processing method for improving effective detection distance of wind-measuring laser radar - Google Patents

Data processing method for improving effective detection distance of wind-measuring laser radar Download PDF

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CN115407306A
CN115407306A CN202211361887.8A CN202211361887A CN115407306A CN 115407306 A CN115407306 A CN 115407306A CN 202211361887 A CN202211361887 A CN 202211361887A CN 115407306 A CN115407306 A CN 115407306A
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data processing
power spectrum
processing method
wind
effective detection
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CN115407306B (en
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袁金龙
夏海云
舒志峰
董晶晶
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Nanjing University of Information Science and Technology
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    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • 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
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/95—Lidar systems specially adapted for specific applications for meteorological use
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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  • Optical Radar Systems And Details Thereof (AREA)

Abstract

The invention discloses a data processing method for improving the effective detection distance of a wind lidar, which belongs to the field of data processing, and aims at improving the accuracy and the extraction probability of extracting wind speed by using a power spectrum signal of a coherent Doppler wind lidar, a method for reducing resolution ratio is adopted to construct a power spectrum, so that a background wind field covered by noise can be effectively extracted, an index interval of the wind speed can be locked and reduced according to the background wind field, and the inversion probability of the wind speed is enhanced; the method for fitting and denoising the range gates one by one is simple and effective, low in time complexity and good in real-time performance, and the Gaussian fitting area is used as the signal-to-noise ratio, so that the jitter caused by background noise of the range gates at different distances can be effectively reduced, and the effective detection distance of the laser radar is effectively increased.

Description

Data processing method for improving effective detection distance of wind-measuring laser radar
Technical Field
The invention relates to the field of data processing, in particular to a data processing method for improving the effective detection distance of a wind lidar.
Background
The wind measurement laser radar is an active laser remote sensing device, has the characteristics of small volume, long dynamic detection distance, high space-time resolution, high precision and the like, and is widely applied to the field of atmospheric wind field remote sensing. The coherent Doppler wind lidar has been demonstrated in foundation, ship-borne and airborne platforms after decades of development, has mature technology, can realize the detection of complex wind fields, atmospheric turbulence, gravity waves, wind shear, wake flow and tornado, and is widely applied to the fields of weather, wind energy, military and civil airports, short-term weather forecast and the like.
However, according to the lidar equation, the intensity of the lidar return signal is rapidly attenuated as the detection distance is increased, and factors such as interference of background light and random noise also have influence during the detection process. Echo signals at far distances are often swamped by noise. Therefore, a proper denoising algorithm is researched, signals are extracted from noise, and the method has an important effect on improving the effective detection distance of the wind lidar. With the development of continuous laser radar signal processing technology, wavelet Transform (WT), empirical Mode Decomposition (EMD), other denoising methods, and the like are widely applied to laser radar signal processing. However, wavelet transforms cannot adaptively find the best combination of different problems. In contrast, EMD techniques compensate for the WT's drawbacks. Based on the conventional EMD, su et al propose a new frequency conversion resolution decomposition method (VFEMD), which extends the original EMD method to a high resolution scale, overcoming the limitation that the resolution depends only on the length of the decomposed signal. Nevertheless, EMD and its variants have some drawbacks, such as mode aliasing, over-decomposition, and end-of-line effects. The existing denoising algorithm is generally high in computation complexity and time complexity, complex and various in noise types and sources, limited in applicability and difficult to extract weak signals from noise. Therefore, how to improve the accuracy and extraction probability of extracting wind speed by using the power spectrum signal of the coherent doppler wind lidar is an urgent problem to be solved.
Disclosure of Invention
1. Technical problem to be solved
Aiming at the problems in the prior art, the invention aims to provide a data processing method for improving the effective detection distance of a wind lidar, which can independently de-noise each range gate by a fitting method, reduce a wind speed inversion interval by a resolution reduction method and effectively improve the effective detection distance of the lidar.
2. Technical scheme
In order to solve the above problems, the present invention adopts the following technical solutions.
A data processing method for improving the effective detection distance of a wind lidar comprises the following steps:
s1, reading original laser radar signal power spectrum
Figure 943148DEST_PATH_IMAGE001
In which represents
Figure 441257DEST_PATH_IMAGE002
Frequency, representative of
Figure 917238DEST_PATH_IMAGE003
A distance gate;
s2, according to the original laser radar signal power spectrum
Figure 362999DEST_PATH_IMAGE004
Performing resolution reduction processing to construct a power spectrum
Figure 508809DEST_PATH_IMAGE005
；
S3, denoising through distance gate fitting one by one, and obtaining a power spectrum
Figure 274640DEST_PATH_IMAGE005
Extracting a center frequency point for each range gate
Figure 39465DEST_PATH_IMAGE006
；
S4, repeating S3, and aiming at the original power spectrum
Figure 574351DEST_PATH_IMAGE007
Denoising the image in the interval
Figure 891063DEST_PATH_IMAGE008
Extracting the power spectrum
Figure 894922DEST_PATH_IMAGE007
Center frequency point of
Figure 712706DEST_PATH_IMAGE009
And calculating the corresponding signal-to-noise ratio
Figure 243044DEST_PATH_IMAGE010
，
Figure 340444DEST_PATH_IMAGE011
Is a third index frequency bandwidth;
s5, using a Doppler frequency shift formula to point the central frequency
Figure 80867DEST_PATH_IMAGE009
Converted into wind speed
Figure 918986DEST_PATH_IMAGE012
；
And S6, performing quality control according to the signal-to-noise ratio and the wind speed variance, and removing abnormal values.
Further, in S2, power spectrum
Figure 428464DEST_PATH_IMAGE013
The calculation method is as follows:
Figure 352558DEST_PATH_IMAGE014
；
wherein
Figure 65430DEST_PATH_IMAGE015
To gate the first range to bandwidth.
Further, in S3, the denoising algorithm process is as follows:
in the interval
Figure 693858DEST_PATH_IMAGE016
Lifting devicePower spectrum of measurement
Figure 464368DEST_PATH_IMAGE017
Peak position of
Figure 169150DEST_PATH_IMAGE018
Wherein
Figure 353006DEST_PATH_IMAGE019
For the first index frequency bandwidth,
Figure 67015DEST_PATH_IMAGE020
doppler shift location.
Further, deducting the interval
Figure 285507DEST_PATH_IMAGE021
Corresponding power spectrum
Figure 551403DEST_PATH_IMAGE022
Obtaining a power spectrum
Figure 241798DEST_PATH_IMAGE023
Residual power spectrum
Figure 212028DEST_PATH_IMAGE023
Is mainly composed of noise, and the noise is generated,
Figure 301337DEST_PATH_IMAGE024
the frequency bandwidth is indexed by a second index.
Further, for the remaining power spectrum
Figure 472556DEST_PATH_IMAGE024
Carrying out noise fitting modeling, wherein the noise fitting modeling prefers a polynomial fitting mode:
Figure 896584DEST_PATH_IMAGE025
；
wherein
Figure 686816DEST_PATH_IMAGE026
Is as follows
Figure 879900DEST_PATH_IMAGE027
Of a distance gate, the first
Figure 222020DEST_PATH_IMAGE028
An order coefficient;
wherein
Figure 884077DEST_PATH_IMAGE029
Figure 992847DEST_PATH_IMAGE030
；
And obtaining a noise curve according to a polynomial fitting result:
Figure 522661DEST_PATH_IMAGE031
；
wherein
Figure 35682DEST_PATH_IMAGE032
。
In a further aspect of the present invention,
Figure 699881DEST_PATH_IMAGE033
denoising power spectrum:
Figure 831917DEST_PATH_IMAGE034
；
extracting the center frequency point of each range gate by Gaussian fitting
Figure 874959DEST_PATH_IMAGE035
The Gaussian fitting model is:
Figure 683515DEST_PATH_IMAGE036
；
Figure 320164DEST_PATH_IMAGE037
in order to be the strength of the signal,
Figure 746914DEST_PATH_IMAGE039
the area calculation of the Gaussian fitting curve is the aerosol spectral width and the signal-to-noise ratio, and the expression is
Figure 867317DEST_PATH_IMAGE040
。
Further, in S4, the first step,
Figure 974950DEST_PATH_IMAGE041
the denoised power spectrum is
Figure 439999DEST_PATH_IMAGE042
。
Further, in S5, wind speed
Figure 582267DEST_PATH_IMAGE043
The expression of (c) is:
Figure 607992DEST_PATH_IMAGE044
；
wherein is
Figure 953654DEST_PATH_IMAGE045
A laser wavelength.
Further, when the signal to noise ratio is small
Figure 480450DEST_PATH_IMAGE046
,
Figure 227957DEST_PATH_IMAGE047
The value is assigned to be NaN,
Figure 690163DEST_PATH_IMAGE048
is a first signal-to-noise ratio threshold.
Further, wind speed is calculated
Figure 772388DEST_PATH_IMAGE049
Variance of (2)
Figure 322449DEST_PATH_IMAGE050
，Variance is measured
Figure 314676DEST_PATH_IMAGE050
Wind speed greater than a specified threshold from a door
Figure 72417DEST_PATH_IMAGE049
By replacement with
Figure 389741DEST_PATH_IMAGE051
。
3. Advantageous effects
Compared with the prior art, the invention has the advantages that:
(1) The invention adopts a method for reducing resolution ratio to construct a power spectrum
Figure 992761DEST_PATH_IMAGE052
The background wind field covered by noise can be effectively extracted, the index interval of the wind speed can be locked and reduced according to the background wind field, and the inversion probability of the wind speed is enhanced;
(2) The method adopts a fitting denoising method of distance gates one by one, is simple and effective, has low time complexity and good real-time performance, and can effectively reduce the jitter caused by background noise of different distance gates by using the Gaussian fitting area as the signal-to-noise ratio.
Drawings
Fig. 1 is a flowchart of a data processing method for increasing an effective detection distance of a wind lidar according to an embodiment of the present invention;
FIG. 2 is an example diagram of a power spectrum provided by an embodiment of the present invention;
fig. 3 is a comparison graph of results of a conventional data processing method provided in the embodiment of the present invention and a data processing method provided in the present invention.
Detailed Description
The drawings in the embodiments of the invention will be combined; the technical scheme in the embodiment of the invention is clearly and completely described; obviously; the described embodiments are only some of the embodiments of the invention; but not all embodiments, are based on the embodiments of the invention; all other embodiments obtained by a person skilled in the art without making any inventive step; all fall within the scope of protection of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "top/bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted", "provided", "fitted/connected", "connected", and the like, are to be interpreted broadly, such as "connected", which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1:
referring to fig. 1, a data processing method for increasing an effective detection distance of a wind lidar includes the following steps:
s1, reading original laser radar signal power spectrum
Figure 839494DEST_PATH_IMAGE053
In which represents
Figure 518868DEST_PATH_IMAGE054
Frequency, representative of
Figure 310107DEST_PATH_IMAGE055
A distance gate;
in this embodiment, the power spectra corresponding to the range gates 288, 289, 290, 291, 292
Figure 857763DEST_PATH_IMAGE056
、
Figure 434369DEST_PATH_IMAGE057
、
Figure 268332DEST_PATH_IMAGE058
As shown in fig. 2 (1), 2 (2), 3 (3) and 4 (4) of fig. 2 and 5 (2), respectively, it can be seen that the power spectrum signals corresponding to the range gates 288-292 are all buried by noise, and no signal peak is seen.
S2, according to the power spectrum of the original laser radar signal
Figure 32020DEST_PATH_IMAGE059
Performing resolution reduction processing to construct a power spectrum
Figure 242422DEST_PATH_IMAGE060
；
Power spectrum of
Figure 676464DEST_PATH_IMAGE060
The calculation method is as follows:
Figure 822274DEST_PATH_IMAGE061
；
wherein
Figure 588105DEST_PATH_IMAGE062
To gate the first range to bandwidth.
In this embodiment, the structural power spectrum corresponding to the range gate 290
Figure 87351DEST_PATH_IMAGE063
As shown in (3) of FIG. 2, the power spectrum is shown
Figure 887816DEST_PATH_IMAGE064
With distinct signal peaks.
S3, denoising through fitting of one-by-one range gate, and obtaining a power spectrum
Figure 470107DEST_PATH_IMAGE065
Extracting a center frequency point for each range gate
Figure 473967DEST_PATH_IMAGE066
；
The denoising algorithm process is as follows:
in the interval
Figure 26171DEST_PATH_IMAGE067
Extracting the power spectrum
Figure 290930DEST_PATH_IMAGE068
Peak position of
Figure 653909DEST_PATH_IMAGE069
Wherein
Figure 394332DEST_PATH_IMAGE070
For the first index frequency bandwidth,
Figure 498030DEST_PATH_IMAGE071
doppler shift location.
Wherein the deduction interval
Figure 882875DEST_PATH_IMAGE072
Corresponding power spectrum
Figure 400444DEST_PATH_IMAGE073
That is, the signal region of the power spectrum is deducted to obtain the power spectrum
Figure 378895DEST_PATH_IMAGE074
Residual power spectrum
Figure 272902DEST_PATH_IMAGE074
Mainly consisting of noise.
Figure 777833DEST_PATH_IMAGE075
The frequency bandwidth is indexed by a second index.
Wherein for the remaining power spectrum
Figure 217035DEST_PATH_IMAGE074
The noise fitting modeling is carried out and,
noise fitting modeling prefers the way of polynomial fitting:
Figure 197630DEST_PATH_IMAGE076
；
wherein
Figure 770694DEST_PATH_IMAGE077
Is as follows
Figure 739918DEST_PATH_IMAGE078
Of a distance gate
Figure 864869DEST_PATH_IMAGE079
Order coefficient of which
Figure 379481DEST_PATH_IMAGE080
Figure 756236DEST_PATH_IMAGE030
。
Obtaining a noise curve according to a polynomial fitting result
Figure 94814DEST_PATH_IMAGE081
；
Wherein
Figure 141398DEST_PATH_IMAGE082
。
Wherein the content of the first and second substances,
Figure 565426DEST_PATH_IMAGE083
denoised power spectrum
Figure 480293DEST_PATH_IMAGE084
。
Extracting the center frequency point of each range gate by Gaussian fitting
Figure 689688DEST_PATH_IMAGE085
The Gaussian fitting model is:
Figure 156442DEST_PATH_IMAGE086
；
Figure 943132DEST_PATH_IMAGE087
in order to be the strength of the signal,
Figure 271476DEST_PATH_IMAGE088
the area calculation of the Gaussian fitting curve is the aerosol spectral width and the signal-to-noise ratio, and the expression is
Figure 584646DEST_PATH_IMAGE089
。
In this embodiment, the structural power spectrum corresponding to the range gate 290
Figure 970103DEST_PATH_IMAGE090
As shown in (3) in FIG. 2, a power spectrum
Figure 244090DEST_PATH_IMAGE090
Corresponding center frequency point
Figure 890972DEST_PATH_IMAGE091
Is 86MHz.
S4, repeating S3, and aiming at the original power spectrum
Figure 809380DEST_PATH_IMAGE092
Denoising the image in the interval
Figure 493303DEST_PATH_IMAGE093
Extracting the power spectrum
Figure 113640DEST_PATH_IMAGE094
Center frequency point of
Figure 49366DEST_PATH_IMAGE095
And calculating the corresponding signal-to-noise ratio
Figure 71549DEST_PATH_IMAGE096
。
Figure 191951DEST_PATH_IMAGE097
Is a third indexed frequency bandwidth.
Figure 315896DEST_PATH_IMAGE094
The denoised power spectrum is
Figure 39002DEST_PATH_IMAGE098
。
S5, using a Doppler frequency shift formula to point the central frequency
Figure 791057DEST_PATH_IMAGE095
Converted into wind speed
Figure 960657DEST_PATH_IMAGE099
Wind speed
Figure 555586DEST_PATH_IMAGE099
The expression of (a) is:
Figure 833115DEST_PATH_IMAGE100
；
wherein is
Figure 439677DEST_PATH_IMAGE101
A laser wavelength.
S6, performing quality control according to the signal-to-noise ratio and the wind speed variance, and eliminating abnormal values:
when signal to noise ratio
Figure 26516DEST_PATH_IMAGE102
,
Figure 859474DEST_PATH_IMAGE103
The value is assigned to be NaN,
Figure 924382DEST_PATH_IMAGE104
is a first signal-to-noise ratio threshold.
Wherein the wind speed is calculated
Figure 651030DEST_PATH_IMAGE103
Variance of (2)
Figure 159502DEST_PATH_IMAGE105
，Variance is measured
Figure 463445DEST_PATH_IMAGE105
Wind speed greater than a specified threshold from door
Figure 79846DEST_PATH_IMAGE103
By replacement with
Figure 192159DEST_PATH_IMAGE106
，
As shown in FIG. 3, the effective detection of the data processing algorithm result of the invention is obviously more than that of the traditional processing algorithm, the effective detection range gates are more than 70, and the effectiveness of the invention is verified.
As described above; are merely preferred embodiments of the invention; the scope of the invention is not limited thereto; any person skilled in the art is within the technical scope of the present disclosure; the technical scheme and the improved concept of the invention are equally replaced or changed; are intended to be covered by the scope of the present invention.

Claims (10)

1. A data processing method for improving effective detection distance of a wind lidar is characterized by comprising the following steps: the method comprises the following steps:
s1, reading the power spectrum of the original laser radar signal
Figure 794332DEST_PATH_IMAGE001
In which represents
Figure 713878DEST_PATH_IMAGE002
Frequency, representative of
Figure 846919DEST_PATH_IMAGE003
A distance gate;
s2, according to the original laser radar signal power spectrum
Figure 444866DEST_PATH_IMAGE004
Performing resolution reduction processing to construct a power spectrum
Figure 19067DEST_PATH_IMAGE005
；
S3, denoising through fitting of one-by-one range gate, and obtaining a power spectrum
Figure 93202DEST_PATH_IMAGE005
Extracting the center frequency point of each range gate
Figure 933113DEST_PATH_IMAGE006
；
S4, repeating S3, and aiming at the original power spectrum
Figure 524632DEST_PATH_IMAGE004
Denoising the image in the interval
Figure 15656DEST_PATH_IMAGE007
Extracting the power spectrum
Figure 277004DEST_PATH_IMAGE004
Center frequency point of
Figure 119058DEST_PATH_IMAGE008
And calculating the corresponding signal-to-noise ratio
Figure 248688DEST_PATH_IMAGE009
Said
Figure 344951DEST_PATH_IMAGE010
A third indexed frequency bandwidth;
s5, using a Doppler frequency shift formula to point the central frequency
Figure 26468DEST_PATH_IMAGE011
Converted into wind speed
Figure 27922DEST_PATH_IMAGE012
；
And S6, performing quality control according to the signal-to-noise ratio and the wind speed variance, and removing abnormal values.
2. The data processing method for improving the effective detection distance of the wind lidar according to claim 1, wherein the data processing method comprises the following steps: in S2, the power spectrum
Figure 765503DEST_PATH_IMAGE013
The calculation method is as follows:
Figure 27857DEST_PATH_IMAGE014
；
wherein
Figure 834271DEST_PATH_IMAGE015
To gate the first range to bandwidth.
3. The data processing method for improving the effective detection distance of the wind lidar according to claim 2, wherein the data processing method comprises the following steps: in S3, the denoising algorithm process is as follows:
in the interval
Figure 57442DEST_PATH_IMAGE016
Extracting the power spectrum
Figure 653508DEST_PATH_IMAGE017
Peak position of
Figure 724363DEST_PATH_IMAGE018
In which
Figure 888628DEST_PATH_IMAGE019
For the first index frequency bandwidth,
Figure 661412DEST_PATH_IMAGE020
doppler shift location.
4. The data processing method for improving the effective detection distance of the wind lidar according to claim 3, wherein: deduction interval
Figure 811902DEST_PATH_IMAGE021
Corresponding power spectrum
Figure 252111DEST_PATH_IMAGE022
Obtaining a power spectrum
Figure 56119DEST_PATH_IMAGE023
Residual power spectrum
Figure 391897DEST_PATH_IMAGE023
Is mainly composed of noise, the
Figure 267450DEST_PATH_IMAGE024
The frequency bandwidth is indexed by a second index.
5. The laser mine for improving wind measurement according to claim 4The data processing method for achieving the effective detection distance is characterized by comprising the following steps: for the remaining power spectrum
Figure 499848DEST_PATH_IMAGE023
Carrying out noise fitting modeling, wherein the noise fitting modeling prefers a polynomial fitting mode:
Figure 553386DEST_PATH_IMAGE025
；
wherein
Figure 628658DEST_PATH_IMAGE026
Is as follows
Figure 980005DEST_PATH_IMAGE027
Of a distance gate, the first
Figure 879959DEST_PATH_IMAGE028
An order coefficient;
wherein
Figure 681562DEST_PATH_IMAGE029
Figure 666966DEST_PATH_IMAGE030
；
And obtaining a noise curve according to a polynomial fitting result:
Figure 822004DEST_PATH_IMAGE031
；
wherein
Figure 91311DEST_PATH_IMAGE032
。
6. The data processing method for improving the effective detection distance of the wind lidar according to claim 5, wherein: the described
Figure 551898DEST_PATH_IMAGE022
Denoising power spectrum:
Figure 945971DEST_PATH_IMAGE033
；
extracting center frequency points of each range gate by Gaussian fitting
Figure 967016DEST_PATH_IMAGE034
The Gaussian fitting model is as follows:
Figure 903879DEST_PATH_IMAGE035
；
Figure 250547DEST_PATH_IMAGE036
in order to be the strength of the signal,
Figure 131915DEST_PATH_IMAGE037
the area calculation of the Gaussian fitting curve is the aerosol spectral width and the signal-to-noise ratio, and the expression is
Figure 441805DEST_PATH_IMAGE038
。
7. The data processing method for improving the effective detection distance of the wind lidar according to claim 1, wherein the data processing method comprises the following steps: in S4, the
Figure 482442DEST_PATH_IMAGE039
The denoised power spectrum is
Figure 485165DEST_PATH_IMAGE040
。
8. Root of herbaceous plantThe data processing method for improving the effective detection distance of the wind lidar according to claim 1, wherein the data processing method comprises the following steps: in S5, the wind speed
Figure 119408DEST_PATH_IMAGE041
The expression of (a) is:
Figure 482256DEST_PATH_IMAGE042
；
wherein is
Figure 125203DEST_PATH_IMAGE043
A laser wavelength.
9. The data processing method for improving the effective detection distance of the wind lidar according to claim 1, wherein the data processing method comprises the following steps: when signal to noise ratio
Figure 548094DEST_PATH_IMAGE044
Assigned a value of NaN, said
Figure 669634DEST_PATH_IMAGE045
Is a first signal-to-noise ratio threshold.
10. The data processing method for improving the effective detection distance of the wind lidar according to claim 9, wherein the data processing method comprises: calculating wind speed
Figure 321326DEST_PATH_IMAGE046
Variance of (2)
Figure 336555DEST_PATH_IMAGE047
，Variance is measured
Figure 681080DEST_PATH_IMAGE047
Wind speed greater than a specified threshold from door
Figure 24337DEST_PATH_IMAGE048
By substitution into
Figure 994567DEST_PATH_IMAGE049
。
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