CN105988114A - Doppler radar wind velocity data filling method - Google Patents
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Abstract
The invention discloses a Doppler radar wind velocity data filling method comprising the following steps: S1, a Doppler radar collects radar sample data of large-area precipitation process or clear-air echoes covering the detection range of a radar station through scanning at a low elevation angle Alpha, wherein the radar sample data is a radial velocity Vr0(Theta) in azimuth distribution on a range ring under polar coordinates, and the radial velocity Vr0(theta) is composed of the radial velocity V/r0 (Theta) of an echo area A and the radial velocity V//r0 (Theta) of a non-echo area B missing measurement; and S2, the Doppler velocity data of the non-echo area B missing measurement on the range ring is filled through an iteration method according to the radial velocity V/r0 (Theta) of the echo area A. A continuous accumulation Doppler velocity data measurement-missing area not greater than 90 degrees and a non-continuous accumulation measurement-missing area smaller than 120 degrees can be filled effectively, and the velocity diagram after filling can better reflect wide-range velocity field characteristics than that before filling.
Description
Technical field
The invention belongs to weather radar data data processing field, particularly relate to the complementing method of Doppler radar wind speed data under a kind of non-linear wind field.
Background technology
The wind field information that Doppler radar is detected lacks survey problem, always affects the application of Doppler Weather Radar Wind information analysis and a key of follow-up Velocity products exploitation, there is no effective technology at present and solve this problem.Wind field loss of learning is filled up, most common method is interpolation method at present, by the wind field data at the high elevation angle, the wind field data at the corresponding low elevation angle are filled up as in the Wang Jiahui " application single-Doppler radar observation carries out Typhoon Vortex initialization " that Taibei Taiwan Univ. 2002 publishes, but this is only applicable to the situation that high wind field in low layer is more consistent；Applicating atmosphere journal 2002,13 (5): 591-599 beam Haihe River published, in Zhang Peiyuan, Ge Runsheng " research of Data Processing of Wind Fields From Doppler Radar ", proposition K-neighborhood frequency method eliminates the noise in wind field and fills up scarce survey, only for scarce measuring point；The fertile big peak " design of Doppler Weather Radar second product development platform and realization " that Nanjing Institute of Meteorology 2003 publishes then carries out linear interpolation by the data adjacent with scarce survey region and fills up scarce survey, but is only applicable to the situation lacking interception angle continuously less than 8 °；Meteorological 2010,36 (5): 1-12 Deng Yong, the Yin Liyun published, permitted to meet outstanding person etc. and utilize VAD method and iteration to fill up technology to carry out lacking and survey region iteration and fill up test, these inversion methods are all built upon wind field in the hypothesis that certain space is linearly distributed, the method of Doppler anemometry data under non-linear wind field can be effectively filled up sum it up, there is presently no.
Summary of the invention
It is an object of the invention to provide a kind of method that can effectively fill up Doppler anemometry data in non-linear wind field.
For reaching above-mentioned purpose, the invention provides the complementing method of a kind of Doppler radar wind speed data, including step:
The first step: Doppler radar is collected with the scanning of low angle of elevation alpha and covered the large-area precipitation process of radar station investigative range or the radar sample data of clear air echo, described radar sample data is radial velocity V with azimuthal distribution on a certain range ring under polar coordinater0(θ), this radial velocity Vr0(θ) by radial velocity V of echo area A/ r0(θ) with radial velocity V lacking the echo free space B surveyed// r0(θ) formed；
Second step: utilize iterative method according to radial velocity V of described echo area A/ r0(θ) the doppler velocity data of the scarce survey echo free space B on described a certain range ring is filled up；It is characterized in that:
Use iterative method that the radial velocity of the scarce survey echo free space B on described a certain range ring is filled up to comprise the steps:
S1: go out the non-linear radial direction wind speed V calculating under polar coordinate system with fourier coefficient according to VAD theoretical derivationr(θ) formula (1)；
(1)
S2: formula (1) is carried out three rank Fourier coefficients and launches to obtain formula (2),
(2),
Wherein, apFor fourier coefficient, fp(θ) it is basic function, f0(θ)=1, f1(θ)=sin (θ), f2(θ)=cos (θ), f3(θ)=
Sin (2 θ), f4(θ)=cos (2 θ), f5(θ)=
Sin (3 θ), f6(θ)= cos(3θ)；
S3: by radial velocity V of echo area A/ r0(θ) substitute into formula (2) respectively and form one group of radial velocity V/ r0(θ) Fourier expansion equation group (3),
(3)
M represents echo area A radial velocity V/ r0(θ) total number of sample data；
S4: according to the character of method of least square, GPR Detection Data V former to echo area A/ r0(θ) error function with the radial velocity obtained through VAD inverting seeks extreme value, it is thus achieved that solve fourier coefficient P*=(a0, a1, a2, a3, a4, a5, a6) iterative formula (11) of optimal solution:
(11)
Wherein, μkFor damping factor, I is unit matrix, J(PK) it is fourier coefficient PK(a0, a1, a2, a3, a4, a5, a6) Jacobian matrix,JT(PK) it is J(PK) transposed matrix；
S5: solve according to iterative formula (11) progressive alternate and can draw fourier coefficient P*The optimal solution of (a0, a1, a2, a3, a4, a5, a6)；
S6: the fourier coefficient P that step S5 is tried to achieve*=(a0, a1, a2, a3, a4, a5, a6) optimal solution substitutes in formula (1), it is thus achieved that one group new is coated with echo area A and radial velocity V of echo free space Br1(θ), described Vr1(θ) corresponding to V inr0(θ) part having echo A in is V/ r1(θ), corresponding to Vr0(θ) in, the part without echo B is V// r1(θ), V is used// r1(θ) go to fill up the V in echo free space B// r0(θ), in having echo area A, original radar detection value V is still retained/ r0(θ) new radial velocity V of former echo free space B data vacancy, has the most been eliminatedrWith the distribution of azimuth angle theta, it is defined as Vr2(θ)；
S7: calculate and have echo area A Central Plains GPR Detection Data V/ r0(θ) with data V obtained through VAD inverting and iterative/ r1(θ) root-mean-square error RMS between；
S8: repeat step S1 to S7, when the value of described root-mean-square error RMS or the sliding average of continuous many group root-mean-square errors RMS is little terminates to iteration filling in process when meeting default constraints.
Described step S4 derivation iterative formula (11) comprises the steps:
S4-1: definition actual measurement echo and inverting echo values error, be designated as
(4)
Wherein, j=1,2 ..., M；
S4-2: assume error target function:
(5)
Wherein P represents fourier coefficient, P=(a0, a1, a2, a3, a4, a5, a6);
S4-3: for making error target function minimum, the fourier coefficient P of optimal solution to be obtained*Make Φ (P) minimum, according to multinomial extreme value essential condition:
(6)
I.e.
(7)
Wherein J (P*) it is following Jacobian matrix:
(8).
S4-4: according to Taylor's formula JTAnd dif (P) is at initial value P=P (P)*Place launches, and is translated into system of linear equations and with suitable step-length Sk(wherein iterations k=0,1 ...) progressive alternate solves, after normalization process, iterative equation and normal equation are as follows:
(9)
(10)
Wherein, μkFor damping factor, I is unit matrix, J(PK) it is fourier coefficient PK(a0, a1, a2, a3, a4, a5, a6) Jacobian matrix,JT(PK) it is J(PK) transposed matrix；
S4-5: formula (10) substitution (9) can be obtained the fourier coefficient P solving optimal solution*=(a0, a1, a2, a3, a4, a5, a6) iterative formula (11).
Step-length S of described step S4-4kIt is specially 1 degree.
In described step S7, the computing formula of root-mean-square error RMS is as follows:
The sliding average of the most described group root-mean-square errors RMS refers to the sliding average of root-mean-square error RMS of continuous three times or more than three times iteration.
The scanning of described Doppler radar low angle of elevation alpha refers to that radar angle of elevation alpha is less than 10 degree.
When the described first step collects radar sample data, if described radial velocity Vr0(θ) there is velocity ambiguity phenomenon, then need to carry out back speed degree Fuzzy Processing.
Compared with prior art, present invention have the advantage that the present invention can effectively fill up for the doppler velocity data Que Ce district of no more than 90 ° of continuous accumulations with less than 120 ° of discontinuous accumulation Que Ce districts, image produced by Doppler's radial velocity data after filling up can well combine together with measuring image, fills up excellent.
Accompanying drawing explanation
Referring to the drawings, the present invention will be better understood.Accompanying drawing is as follows:
Fig. 1 is Doppler radar wind speed data complementing method flow chart of the present invention；
Fig. 2 is the flow chart that Doppler radar wind speed data complementing method second step of the present invention uses that the radial velocity of scarce survey echo free space B is filled up by iterative method:
Fig. 3 is the flow chart of Doppler radar wind speed data complementing method of the present invention；
Fig. 4 is the effect schematic diagram after utilizing Doppler radar wind speed data complementing method of the present invention to fill up speed data；
Fig. 5 is that to utilize Doppler radar wind speed data complementing method of the present invention be that radar wind speed field data when 60 ° fills up before and after's Contrast on effect schematic diagram to discontinuous accumulation breach；
Fig. 6 is that to utilize Doppler radar wind speed data complementing method of the present invention be that radar wind speed field data when 120 ° fills up before and after's Contrast on effect schematic diagram to discontinuous accumulation breach；
Fig. 7 is that to utilize Doppler radar wind speed data complementing method of the present invention be that radar wind speed field data when 30 ° fills up before and after's Contrast on effect schematic diagram to continuous accumulation breach；
Fig. 8 is that to utilize Doppler radar wind speed data complementing method of the present invention be that radar wind speed field data when 60 ° fills up before and after's Contrast on effect schematic diagram to continuous accumulation breach；
Fig. 9 is that to utilize Doppler radar wind speed data complementing method of the present invention be that radar wind speed field data when 90 ° fills up before and after's Contrast on effect schematic diagram to discontinuous accumulation breach.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme, beneficial effect clearer, below in conjunction with drawings and Examples, the present invention is described in further details.Should be appreciated that specific embodiment described herein is used only for explaining the present invention, be not intended to limit the present invention.
Below in conjunction with specific embodiment, the realization of the present invention is described in detail:
As shown in Figure 1 to Figure 2, Doppler radar wind speed data complementing method of the present invention comprises the following steps:
The first step: Doppler radar is collected with the scanning of low angle of elevation alpha and covered the large-area precipitation process of radar station investigative range or the radar sample data of clear air echo, described radar sample data is radial velocity V with azimuthal distribution on a certain range ring under polar coordinater0(θ), this radial velocity Vr0(θ) by radial velocity V of echo area A/ r0(θ) with radial velocity V lacking the echo free space B surveyed// r0(θ) formed.
In this step, the scanning of Doppler radar low angle of elevation alpha refers to that radar angle of elevation alpha is less than 10 degree.
The embodiment of the present invention selects the radar sample data that Longyan radar station is collected.The detection range of Longyan radar station radar is 460 kilometers, and effective radius of investigation of wind field speed is 150 kilometers.The embodiment of the present invention selects on July 13rd, 2013, and during " Su Li " typhoon influence, the speed data of the Heavy Rainfall Weather that Longyan radar observes using 0.5 ° of elevation angle is as radar sample data.
When collecting radar sample data, if described radial velocity Vr0(θ) there is velocity ambiguity phenomenon, then could continue to use the complementing method of the present invention to carry out speed after needing to carry out back speed degree Fuzzy Processing and fill up.Back speed degree Fuzzy Processing has been a ripe prior art, sees plateau meteorology, 2012,31(4), 1119-1128, Xiao Yanjiao, Wan Yufa, Wang Yu, wait a kind of Doppler radar speed automatically to move back fuzzy algorithmic approach research [J], do not repeat at this.
Second step: utilize iterative method according to radial velocity V of described echo area A/ r0(θ) the doppler velocity data of the scarce survey echo free space B on described a certain range ring is filled up.Use iterative method that the radial velocity of the scarce survey echo free space B on described a certain range ring is filled up to comprise the steps:
S1: go out the non-linear radial direction wind speed V calculating under polar coordinate system with fourier coefficient according to VAD theoretical derivationr(θ) formula (1).
In non-linear wind field, radial velocity carries out Fourier exponent number expansion, it is assumed that wind field is second order distributed at horizontal space, then Fourier exponent number is not to just having truncated error when three, can obtain formula (1):
(1)
According to D Caya and I Zawadzki[6]Research understands, in non-linear wind field, except zeroth order harmonic wave a0Still representing average divergence, one order harmonics and the second harmonic can not be construed to AVG W/C and averaged deformation again.Therefore, in non-linear wind field, fourier coefficient is except a0, the physical interpretation of other coefficients is entirely different with linear wind field, does not have clear and definite physical significance.
S2: formula (1) is carried out three rank Fourier coefficients and launches to obtain formula (2),
(2),
Wherein, apFor fourier coefficient, fp(θ) it is basic function, f0(θ)=1, f1(θ)=sin (θ), f2(θ)=cos (θ), f3(θ)=
Sin (2 θ), f4(θ)=cos (2 θ), f5(θ)=
Sin (3 θ), f6(θ)= cos(3θ)。
S3: by radial velocity V of echo area A/ r0(θ) substitute into formula (2) respectively and form one group of radial velocity V/ r0(θ) Fourier expansion equation group (3),
(3)
M represents echo area A radial velocity V/ r0(θ) total number of sample data.
S4: according to the character of method of least square, GPR Detection Data V former to echo area A/ r0(θ) error function with the radial velocity obtained through VAD inverting seeks extreme value, it is thus achieved that solve fourier coefficient P*=(a0, a1, a2, a3, a4, a5, a6) iterative formula (11) of optimal solution:
(11)
Wherein, μkFor damping factor, I is unit matrix, J(PK) it is fourier coefficient PK (a0, a1, a2, a3, a4, a5, a6) Jacobian matrix,JT(PK) it is J(PK) transposed matrix.
Step S4 derivation iterative formula (11) comprises the steps:
S4-1: definition actual measurement echo and inverting echo values error, be designated as
(4)
Wherein, j=1,2 ..., M；
S4-2: assume error target function:
(5)
Wherein P represents fourier coefficient, P=(a0, a1, a2, a3, a4, a5, a6);
S4-3: for making error target function minimum, the fourier coefficient P of optimal solution to be obtained*Make Φ (P) minimum, according to multinomial extreme value essential condition:
(6)
I.e.
(7)
Wherein JT(P*) it is following Jacobian matrix:
(8).
S4-4: according to Taylor's formula JTAnd dif (P) is at initial value P=P (P)*Place launches, and is translated into system of linear equations and with suitable step-length Sk(wherein iterations k=0,1 ...) progressive alternate solves, after normalization process, iterative equation and normal equation are as follows:
(9)
(10)
Wherein, μkFor damping factor, I is unit matrix, J (PK) it is fourier coefficient PK (a0, a1, a2, a3, a4, a5, a6) Jacobian matrix,JT(PK) it is J (PK) transposed matrix.
Damping factor μkValue mode is: set iterations as k, constant C=10, damping factor μkTake initial value 0.08, in an iterative process, as error sum of squares Φ (Pk+1)> Φ(Pk) time, damping factor μk=μk×C；Otherwise as error sum of squares Φ (Pk+1)<= Φ(Pk) time, damping factor μk=μk/C。
Step-length SkIt is specially 1 degree.
S4-5: formula (10) substitution (9) can be obtained the fourier coefficient P solving optimal solution*=(a0, a1, a2, a3, a4, a5, a6) iterative formula (11).
S5: solve according to iterative formula (11) progressive alternate and can draw fourier coefficient P*The optimal solution of (a0, a1, a2, a3, a4, a5, a6).
S6: the fourier coefficient P that step S5 is tried to achieve*=(a0, a1, a2, a3, a4, a5, a6) optimal solution substitutes in formula (1), it is thus achieved that one group new is coated with echo area A and radial velocity V of echo free space Br1(θ), described Vr1(θ) corresponding to V inr0(θ) part having echo A in is V/ r1(θ), corresponding to Vr0(θ) in, the part without echo B is V// r1(θ), V is used// r1(θ) go to fill up the V in echo free space B// r0(θ), in having echo area A, original radar detection value V is still retained/ r0(θ) new radial velocity V of former echo free space B data vacancy, has the most been eliminatedrWith the distribution of azimuth angle theta, it is defined as Vr2(θ)。
Vr2(θ) for the complete radial velocity data obtained after once filling up, but it still suffers from deviation with actual radial velocity data, therefore definition echo area A Central Plains GPR Detection Data V/ r0(θ) with data V obtained through VAD inverting/ r1(θ) root-mean-square error RMS between is as the constraints of iteration.
S7: calculate and have echo area A Central Plains GPR Detection Data V/ r0(θ) with data V obtained through VAD inverting and iterative/ r1(θ) root-mean-square error RMS between.
The computing formula of root-mean-square error RMS is as follows:
RMS value is the least, shows that the radial velocity data calculating gained are the least relative to the error of former GPR Detection Data.In order to make RMS be reduced to minimum, utilize new radial velocity V that step S3 obtainsr2(θ) repeat step S2 to S4, be calculated a series of root-mean-square error RMS.
S8: repeat step S1 to S7, when the value of described root-mean-square error RMS or the sliding average of continuous many group root-mean-square errors RMS is little terminates to iteration filling in process when meeting default constraints.
The sliding average of the most described group root-mean-square errors RMS refers to the sliding average of root-mean-square error RMS of continuous three times or more than three times iteration.
RMS value is the least, shows that the data of gained are the least relative to the error of initial data after iteration.According to experiment statistics, when continuous accumulation breach is 30 degree, total iterations is 10758 times, iteration ends when root-mean-square error RMS is 2.50；When continuous accumulation breach reaches 60 degree, total iterations is 36501 times, iteration ends when root-mean-square error RMS is 2.80；When continuous accumulation breach reaches 90 degree, total iterations 150795 times, iteration ends when root-mean-square error RMS is 4.45.As can be seen here, along with the increase of scarce survey data breach, iterations increases, and root-mean-square error value also increases.
Utilize the inventive method carry out lack degree of testing the speed fill up effect as shown in Fig. 4 to Fig. 9.0.5 ° of elevation angle actual measurement doppler velocity field of 58 points of (universal time) Longyan radars when left figure in Fig. 4 is 13 days 16 July in 2013, the right figure in Fig. 4 is directly to carry out lacking the design sketch after degree of testing the speed is filled up；0.5 ° of elevation angle actual measurement doppler velocity field of 0 point of (universal time) Longyan radar when left figure in Fig. 5 to Fig. 6 is 13 days 10 July in 2013, middle figure is to the artificial scarce mapping done on the basis of left figure, and right figure is to utilize the method for the present invention to carry out the design sketch after doppler velocity is filled up；0.5 ° of elevation angle actual measurement doppler velocity field of 35 points of (universal time) Longyan radars when left figure in Fig. 7 to Fig. 9 is 13 days 13 July in 2013, middle figure is to the artificial scarce mapping done on the basis of left figure, and right figure is to utilize the method for the present invention to carry out the design sketch after doppler velocity is filled up.As shown in Figure 4, it is seen that, the right figure of Fig. 4 to fill up effectiveness comparison good.In order to enable preferably to verify the quality that the present invention fills up effect, actual measurement doppler velocity field artificially manufactures scarce survey region, has utilized Doppler radar wind speed data complementing method of the present invention to fill up, be then analyzed filling up effect.As shown in Figure 7 to 9, Zuo Zetu is as measured drawing, and middle graph is artificial manufacture and lacks mapping, and right part of flg is as filling up design sketch, the image that the doppler velocity data utilizing the inventive method to fill up produces well combines together with measuring image, fills up excellent.
Compared with prior art, present invention have the advantage that the present invention can effectively fill up for the doppler velocity data Que Ce district of no more than 90 ° of continuous accumulations with less than 120 ° of discontinuous accumulation Que Ce districts, the hodograph ratio after filling up more can reflect large-scale velocity field characteristics before filling up.
The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all any amendment, equivalent and improvement etc. made within the spirit and principles in the present invention, should be included within the scope of the present invention.
Claims (6)
1. a complementing method for Doppler radar wind speed data, including step:
The first step: Doppler radar is collected with the scanning of low angle of elevation alpha and covered the large-area precipitation process of radar station investigative range or the radar sample data of clear air echo, described radar sample data is radial velocity V with azimuthal distribution on a certain range ring under polar coordinater0(θ), this radial velocity Vr0(θ) by radial velocity V of echo area A/ r0(θ) with radial velocity V lacking the echo free space B surveyed// r0(θ) formed；
Second step: utilize iterative method according to radial velocity V of described echo area A/ r0(θ) the doppler velocity data of the scarce survey echo free space B on described a certain range ring is filled up；It is characterized in that:
Use iterative method that the radial velocity of the scarce survey echo free space B on described a certain range ring is filled up to comprise the steps:
S1: go out the non-linear radial direction wind speed V calculating under polar coordinate system with fourier coefficient according to VAD theoretical derivationr(θ) formula (1)；
(1)
S2: formula (1) is carried out three rank Fourier coefficients and launches to obtain formula (2),
(2),
Wherein, apFor fourier coefficient, fp(θ) it is basic function, f0(θ)=1, f1(θ)=sin (θ), f2(θ)=cos (θ), f3(θ)=sin (2 θ), f4(θ)=cos (2 θ), f5(θ)=sin (3 θ), f6(θ)= cos(3θ)；
S3: by radial velocity V of echo area A/ r0(θ) substitute into formula (2) respectively and form one group of radial velocity V/ r0(θ) Fourier expansion equation group (3),
(3)
M represents echo area A radial velocity V/ r0(θ) total number of sample data；
S4: according to the character of method of least square, GPR Detection Data V former to echo area A/ r0(θ) error function with the radial velocity obtained through VAD inverting seeks extreme value, it is thus achieved that solve fourier coefficient P*=(a0, a1, a2, a3, a4, a5, a6) iterative formula (11) of optimal solution:
(11)
Wherein, μkFor damping factor, I is unit matrix, J(PK) it is fourier coefficient PK(a0, a1, a2, a3, a4, a5, a6) Jacobian matrix,JT(PK) it is J(PK) transposed matrix；
S5: solve according to iterative formula (11) progressive alternate and can draw fourier coefficient P*The optimal solution of (a0, a1, a2, a3, a4, a5, a6)；
S6: the fourier coefficient P that step S5 is tried to achieve*=(a0, a1, a2, a3, a4, a5, a6) optimal solution substitutes in formula (1), it is thus achieved that one group new is coated with echo area A and radial velocity V of echo free space Br1(θ), described Vr1(θ) corresponding to V inr0(θ) part having echo A in is V/ r1(θ), corresponding to Vr0(θ) in, the part without echo B is V// r1(θ), V is used// r1(θ) go to fill up the V in echo free space B// r0(θ), in having echo area A, original radar detection value V is still retained/ r0(θ) new radial velocity V of former echo free space B data vacancy, has the most been eliminatedrWith the distribution of azimuth angle theta, it is defined as Vr2(θ)；
S7: calculate and have echo area A Central Plains GPR Detection Data V/ r0(θ) with data V obtained through VAD inverting and iterative/ r1(θ) root-mean-square error RMS between；
S8: repeat step S1 to S7, when the value of described root-mean-square error RMS or the sliding average of continuous many group root-mean-square errors RMS is little terminates to iteration filling in process when meeting default constraints.
2. the complementing method of Doppler radar wind speed data as claimed in claim 1, it is characterised in that: described step S4 derivation iterative formula (11) comprises the steps:
S4-1: definition actual measurement echo and inverting echo values error, be designated as
(4)
Wherein, j=1,2 ..., M；
S4-2: assume error target function:
(5)
Wherein P represents fourier coefficient, P=(a0, a1, a2, a3, a4, a5, a6);
S4-3: for making error target function minimum, the fourier coefficient P of optimal solution to be obtained*Make Φ (P) minimum, according to multinomial extreme value essential condition:
(6)
I.e.
(7)
Wherein J (P*) it is following Jacobian matrix:
(8)
S4-4: according to Taylor's formula JTAnd dif (P) is at initial value P=P (P)*Place launches, and is translated into system of linear equations and with suitable step-length Sk(wherein iterations k=0,1 ...) progressive alternate solves, after normalization process, iterative equation and normal equation are as follows:
(9)
(10)
Wherein, μkFor damping factor, I is unit matrix, J(PK) it is fourier coefficient PK(a0, a1, a2, a3, a4, a5, a6) Jacobian matrix,JT(PK) it is J(PK) transposed matrix；
S4-5: formula (10) substitution (9) can be obtained the fourier coefficient P solving optimal solution*=(a0, a1, a2, a3, a4, a5, a6) iterative formula (11).
3. the complementing method of Doppler radar wind speed data as claimed in claim 2, it is characterised in that: step-length S of described step S4-4kIt is specially 1 degree.
4. the complementing method of Doppler radar wind speed data as claimed in claim 1, it is characterised in that: in described step S7, the computing formula of root-mean-square error RMS is as follows:
The sliding average of the most described group root-mean-square errors RMS refers to the sliding average of root-mean-square error RMS of continuous three times or more than three times iteration.
5. the complementing method of the Doppler radar wind speed data as described in Claims 1-4 any one claim, it is characterised in that: the scanning of described Doppler radar low angle of elevation alpha refers to that radar angle of elevation alpha is less than 10 degree.
6. the complementing method of the Doppler radar wind speed data as described in Claims 1-4 any one claim, it is characterised in that: when the described first step collects radar sample data, if described radial velocity Vr0(θ) there is velocity ambiguity phenomenon, then need to carry out back speed degree Fuzzy Processing.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106842154A (en) * | 2017-01-06 | 2017-06-13 | 兰州大学 | Doppler Radar Radial Velocity based on image recognition moves back blur method |
| CN110780300A (en) * | 2019-10-31 | 2020-02-11 | 安徽四创电子股份有限公司 | Data processing method for wind profile radar |
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| CN110780300A (en) * | 2019-10-31 | 2020-02-11 | 安徽四创电子股份有限公司 | Data processing method for wind profile radar |
| CN111505596A (en) * | 2020-04-16 | 2020-08-07 | 北京理工大学重庆创新中心 | Three-dimensional wind field inversion method based on non-uniform sampling correction VAD technology |
| CN111505596B (en) * | 2020-04-16 | 2022-05-13 | 北京理工大学重庆创新中心 | Three-dimensional wind field inversion method based on non-uniform sampling correction VAD technology |
| CN115508865A (en) * | 2022-10-17 | 2022-12-23 | 上海能源科技发展有限公司 | Wind field inversion method and system based on coherent Doppler continuous wave laser radar |
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