CN107907864A - A kind of wind profile radar precipitation disturbance restraining method and system - Google Patents
A kind of wind profile radar precipitation disturbance restraining method and system Download PDFInfo
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- CN107907864A CN107907864A CN201711026531.8A CN201711026531A CN107907864A CN 107907864 A CN107907864 A CN 107907864A CN 201711026531 A CN201711026531 A CN 201711026531A CN 107907864 A CN107907864 A CN 107907864A
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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
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
Abstract
The present invention relates to a kind of wind profile radar precipitation disturbance restraining method and system.Method includes：Noise level is calculated according to wind profile radar modal data；Spectral peak identification is carried out to wind profile radar modal data；According to spectral peak recognition result and noise level, classified calculating spectrum parameter；Millimeter wave cloud radar data is introduced, bind profile parameter carries out precipitation AF panel, identifies wind number.System includes noise level computing module, spectral peak identification module, spectrum parameter calculating module and wind identification module.Processing stage is composed in wind profile radar, introduces the thought of multimodal processing, the information provided in combination with millimeter wave cloud radar, correctly identifies wind number, reasonable computation spectrum parameter, can effectively reduce influence of the precipitation to the wind profile radar quality of data.
Description
Technical field
The present invention relates to signal processing and data analysis field, more particularly to a kind of wind profile radar precipitation AF panel side
Method and system.
Background technology
Wind profile radar is a kind of clear sky detecting devices, can be with high time, high spatial resolution, real-time, continuous, fixed point
Detect the key element such as wind, uprush and Refractive-index-structure parameter above detecting devices.Wind profile radar is widely used in
Department or the fields such as meteorology, environmental protection, airport.Wind profile radar high sensitivity, it is thus possible to measure faint echo-signal, still
The interference of a variety of echo-signals is it is similarly subjected to, precipitation particles signal interference is exactly one kind therein, this just needs Wind outline thunder
Up to while being detected, the influence of noise signal can be reduced to the greatest extent.
The content of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the present invention proposes a kind of wind profile radar precipitation disturbance restraining method
And system, influence of the precipitation to the wind profile radar quality of data can be reduced.
The technical solution that the present invention solves above-mentioned technical problem is as follows：A kind of wind profile radar precipitation disturbance restraining method,
Specifically include step：
Noise level is calculated according to wind profile radar modal data；
Spectral peak identification is carried out to wind profile radar modal data；
According to spectral peak recognition result and noise level, classified calculating spectrum parameter；
Millimeter wave cloud radar data is introduced, bind profile parameter carries out precipitation AF panel, identifies wind number.
The beneficial effects of the present invention are：Processing stage is composed in wind profile radar, the thought of multimodal processing is introduced, ties at the same time
The information that millimeter wave cloud radar provides is closed, correctly identifies wind number, reasonable computation spectrum parameter, can effectively reduce precipitation to wind
The influence of the profile radar quality of data.
Further, before spectral peak identification is carried out, also wind profile radar modal data is pre-processed, the pretreatment bag
Include denoising bottom, go isolated value and sliding average.
By being pre-processed to wind profile radar modal data, it may be such that wind profile radar modal data is more smooth, be easy to
Follow-up identification.
Further, spectral peak identification is carried out to wind profile radar modal data includes continuum identification and local extremum judgement；
Continuum identification specifically includes：Wind profile radar modal data is analyzed, when wind profile radar modal data continues to exceed
Default threshold value and reach default data points, be then judged as continuum；
Local extremum judges to specifically include：The local maximum and local minimum in continuum are calculated, identification is each
Sub- peak and corresponding sub- peak number amount in continuum.
Identified by continuum, the initial position of doubtful wind number can be obtained, calculated and carry with parameter for follow-up identification
For basis；Local extremum judges that the differentiation to continuum concrete shape can be helped, is calculated easy to subsequently identify with parameter.
Further, include being known according to spectral peak recognition result according to spectral peak recognition result and noise level classified calculating spectrum parameter
The continuum not gone out and Zi Feng, spectrum parameter, the spectrum parameter are calculated by tradition spectrum parameter-calculation method or Gauss curve fitting method
Power, average speed and half spectrum width including Received Signal；
When group peak corresponding region is without in zero-frequency point and single continuum without more sub- peaks, joined by tradition spectrum
Number calculating method calculates spectrum parameter, specifically includes：
Power spectrum is S (f), then its k rank moment of the orign is：
mk=∫ fkS(f)df
Atmospheric echo power P is calculated according to frequency spectrumr, i.e.,：
Pr=∫ S (f) df=m0
Average Doppler frequencyFor：
The variance of Doppler frequencyFor：
Then atmospheric echo average speed is estimated as：
Speed spectrum width is estimated as：
Wherein, λ is radar operation wavelength；
When in group peak corresponding region point containing zero-frequency and single continuum containing more sub- peaks, pass through Gauss curve fitting method meter
Spectrum parameter is calculated, is specifically included：
Model, power spectral density function S are established to the power spectral density function of acquisitionm(v) it is：
Wherein, Noise is average noise level, Sa,σaRespectively the power of Received Signal, average speed and
Half spectrum width, Sm,σmPower, average speed and half spectrum width of respectively M noise jamming, observation are S (vi), observation
Deviation between model is：
So that deviation is minimum, you can to obtain the spectrum parameter of atmospheric echo.
Spectrum parameter is calculated different spectral peak classification of type, in the case where excessively increase spectrum does not calculate pressure, improves spectrum
The accuracy that parameter calculates.
Further, millimeter wave cloud radar data includes the falling speed of precipitation particles；
Millimeter wave cloud radar data is introduced, bind profile parameter carries out precipitation AF panel, and identification wind number includes：According to drop
The falling speed of water particle and spectrum parameter identification wind number.
In weak precipitation, millimeter wave cloud radar can detect the falling speed of precipitation particles, and wind profile radar is being visited
While measuring precipitation particles, wind information can be detected；The information of millimeter wave cloud radar is introduced, the knowledge of wind number can be helped
Indescribably take；Precipitation particles signal spectrum width is wider at the same time, contributes to the identification and extraction of wind number.
The technical solution that the present invention solves above-mentioned technical problem is as follows：A kind of wind profile radar precipitation Interference Suppression System,
Including：
Noise level computing module, for calculating noise level according to wind profile radar modal data；
Spectral peak identification module, for carrying out spectral peak identification to wind profile radar modal data；
Parameter calculating module is composed, for according to spectral peak recognition result and noise level, classified calculating spectrum parameter；
Wind identification module, for introducing millimeter wave cloud radar data, bind profile parameter carries out precipitation AF panel, knows
Other wind number.
Further, pretreatment module is further included, for being carried out before spectral peak identification is carried out to wind profile radar modal data
Pretreatment, the pretreatment include denoising bottom, go isolated value and sliding average.
Further, spectral peak identification module, which carries out wind profile radar modal data spectral peak identification, includes continuum identification drawn game
Portion's extreme value judges that spectral peak identification module includes：
Region identification block, for analyzing wind profile radar modal data, when wind profile radar modal data continue to exceed it is default
Threshold value and reach default data points, then be judged as continuum；
Extreme value judging unit, for calculating local maximum and local minimum in continuum, identification is each continuous
Sub- peak and corresponding sub- peak number amount in region.
Further, the continuum and Zi Feng that spectrum parameter calculating module is identified according to spectral peak recognition result, pass through tradition
Compose parameter-calculation method or Gauss curve fitting method calculates spectrum parameter, the spectrum parameter includes the power of Received Signal, average speed
Degree and half spectrum width；
When group peak corresponding region is without in zero-frequency point and single continuum without more sub- peaks, spectrum parameter calculates mould
Block calculates spectrum parameter by tradition spectrum parameter-calculation method, specifically includes：
Power spectrum is S (f), then its k rank moment of the orign is：
mk=∫ fkS(f)df
Atmospheric echo power P is calculated according to frequency spectrumr, i.e.,：
Pr=∫ S (f) df=m0
Average Doppler frequencyFor：
The variance of Doppler frequencyFor：
Then atmospheric echo average speed is estimated as：
Speed spectrum width is estimated as：
Wherein, λ is radar operation wavelength；
When in group peak corresponding region point containing zero-frequency and single continuum containing more sub- peaks, spectrum parameter calculating module is led to
Cross Gauss fitting process and calculate spectrum parameter, specifically include：
Model, power spectral density function S are established to the power spectral density function of acquisitionm(v) it is：
Wherein, Noise is average noise level, Sa,σaRespectively the power of Received Signal, average speed and
Half spectrum width, Sm,σmPower, average speed and half spectrum width of respectively M noise jamming, observation are S (vi), observation
Deviation between model is：
So that deviation is minimum, you can to obtain the spectrum parameter of atmospheric echo.
Further, millimeter wave cloud radar data includes the falling speed of precipitation particles；
Falling speed and spectrum parameter identification wind number of the wind identification module according to precipitation particles.
Brief description of the drawings
Fig. 1 is a kind of flow chart of wind profile radar precipitation disturbance restraining method of the present invention；
Fig. 2 is a kind of schematic diagram of wind profile radar precipitation Interference Suppression System of the present invention.
In attached drawing, parts list represented by the reference numerals is as follows：
1st, noise level computing module, 2, pretreatment module, 3, spectral peak identification module, 4, pass spectrum parameter calculating module, 5,
Wind identification module.
Embodiment
The principle and features of the present invention will be described below with reference to the accompanying drawings, and the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the present invention.
As shown in Figure 1, Fig. 1 is a kind of flow chart of wind profile radar precipitation disturbance restraining method of the present invention.A kind of wind is wide
Line radar precipitation disturbance restraining method, specifically includes step：
S1. noise level is calculated according to wind profile radar modal data；
S2. wind profile radar modal data is pre-processed；
S3. spectral peak identification is carried out to wind profile radar modal data；
S4. according to spectral peak recognition result and noise level, classified calculating spectrum parameter；
S5. millimeter wave cloud radar data is introduced, bind profile parameter carries out precipitation AF panel, identifies wind number.
Noise level, power spectral density S are calculated according to original wind profile radar modal datan=S (fn), with reference to default
Threshold value, the power spectrum below this threshold value is noise spot, and specific method is as follows：
Computational discrimination factor R1：Assuming that the frequency range of whole power spectrum is F, obtaining variance is：
Meanwhile the variance for calculating the sequence that the following noise spot of thresholding newly forms is：
If contain weather echo signal, R1More than 1.
Computational discrimination factor R2：
R2=P2/Qρ
Wherein, P is the average newly composed of point composition below thresholding, and N is the length newly composed, i.e.,：
Q is the variance newly composed, i.e.,：
ρ is the product of spectral average and the Sliding Mean Number for averaging spectrum.For white noise, R2Value should be consistent
, but if contain weather echo signal, R2Then it is less than 1.
Accordingly, noise level computing module 1 includes the first Assessing parameters computing unit and the second Assessing parameters calculate list
Member, the first Assessing parameters computing unit are used for computational discrimination factor R1；Second Assessing parameters computing unit be used for computational discrimination because
Sub- R2。
Calculate R1And R2, constantly adjust default threshold value, you can realize the noise electricity calculated in wind profile radar modal data
It is flat.In theory, no precipitation particles, when containing only white noise, R1=R2≈1.The R in actual mechanical process2Change it is more flat
It is slow so that R2=1 suitable decision condition that can be chosen as default threshold value.
Pretreatment is carried out to wind profile radar modal data to include denoising bottom, goes isolated value, sliding average etc. to operate, these operations
Be in order to enable spectrum it is more smooth, be easy to subsequently identify.Therefore, it is necessary to original spectrum be stored, after being used for before being pre-processed
Continuous parameter calculates.
Spectral peak identification is carried out to wind profile radar modal data includes continuum identification and local extremum judgement, is specially：
Continuum identification specifically includes：Wind profile radar modal data is analyzed, when wind profile radar modal data continues to exceed
Default threshold value and reach default data points, be then judged as continuum.Default threshold value, when there is certain data
Points modal data continues to exceed the threshold value, then it is assumed that the region is continuum；Meanwhile can be by adjusting thresholding so that
Continuum number is not more than certain numerical value, is set to 3 here, that is, thinks that the continuum number in each range gate is not more than 3
It is a, if more than 3, adjust threshold value so that continuum number is within 3.
Local extremum judges to specifically include：The local maximum and local minimum in continuum are calculated, identification is each
Sub- peak and corresponding sub- peak number amount in continuum.
Local extremum is calculated in each continuum identified, local extremum includes local maximum and identification is local
Minimum value.The sub- peak number in each continuum is identified by local maximum and identification local minimum.Equally to each company
Continuous region neutron peak number is configured, and is arranged to 3 herein, i.e., the sub- peak number in each continuum not over 3, if while
There are more sub- peaks, identify local minimum, stored.
Based on noise level, include being identified according to spectral peak according to spectral peak recognition result and noise level classified calculating spectrum parameter
As a result the continuum identified and Zi Feng, spectrum parameter is calculated by tradition spectrum parameter-calculation method or Gauss curve fitting method, described
Spectrum parameter includes power, average speed and half spectrum width of Received Signal.
When group peak corresponding region is without in zero-frequency point and single continuum without more sub- peaks, joined by tradition spectrum
Number calculating method calculates spectrum parameter, specifically includes：
Power spectrum is S (f), then its k rank moment of the orign is：
mk=∫ fkS(f)df
Atmospheric echo power P is calculated according to frequency spectrumr, i.e.,：
Pr=∫ S (f) df=m0
Average Doppler frequencyFor：
The variance of Doppler frequencyFor：
Then atmospheric echo average speed is estimated as：
Speed spectrum width is estimated as：
Wherein, λ is radar operation wavelength.
When in group peak corresponding region point containing zero-frequency and single continuum containing more sub- peaks, pass through Gauss curve fitting method meter
Calculate spectrum parameter.
Noise jamming in wind profile radar, including ground clutter interference and rain, snow echo interference, it is considered that interference work(
Gaussian is all presented in rate spectral density function, and Received Signal is also in Gaussian, then can be to the power spectral density letter of acquisition
Number establishes model, it is assumed that Gaussian is presented in the noise jamming in power spectrum, and noise is white noise, then can obtain power spectrum
Spend function Sm(v),
Wherein, Noise is average noise level, Sa,σaRespectively the power of Received Signal, average speed and
Half spectrum width, Sm,σmPower, average speed and half spectrum width of respectively M noise jamming, observation are S (vi), observation
Deviation between model is：
So that deviation is minimum, you can to obtain the spectrum parameter of atmospheric echo.
The data of millimeter wave cloud radar are introduced, bind profile parameter carries out precipitation AF panel identification wind number and is specially：
During weak precipitation, millimeter wave cloud radar can detect the falling speed of precipitation particles, and wind profile radar is detecting precipitation grain
While sub-, the information of wind can be detected, the information of millimeter wave cloud radar is introduced, the identification of wind number can be helped to extract；
Precipitation particles signal spectrum width is wider at the same time, which can be used for the identification and extraction of wind number.
As shown in Fig. 2, Fig. 2 is a kind of schematic diagram of wind profile radar precipitation Interference Suppression System of the present invention.
A kind of wind profile radar precipitation Interference Suppression System, it is characterised in that including：
Noise level computing module 1, for calculating noise level according to wind profile radar modal data；
Pretreatment module 2, it is described pre- for being pre-processed before spectral peak identification is carried out to wind profile radar modal data
Processing includes denoising bottom, goes isolated value and sliding average；
Spectral peak identification module 3, for carrying out spectral peak identification to wind profile radar modal data；
Parameter calculating module 4 is composed, for according to spectral peak recognition result and noise level, classified calculating spectrum parameter；
Wind identification module 5, for introducing millimeter wave cloud radar data, bind profile parameter carries out precipitation AF panel,
Identify wind number.
Spectral peak identification module 3, which carries out wind profile radar modal data spectral peak identification, includes continuum identification and local extremum
Judge, spectral peak identification module 3 includes：
Region identification block, for analyzing wind profile radar modal data, when wind profile radar modal data continue to exceed it is default
Threshold value and reach default data points, then be judged as continuum；
Extreme value judging unit, for calculating local maximum and local minimum in continuum, identification is each continuous
Sub- peak and corresponding sub- peak number amount in region.
The continuum and Zi Feng that spectrum parameter calculating module 4 is identified according to spectral peak recognition result, pass through tradition spectrum parameter
Calculating method or Gauss curve fitting method calculate spectrum parameter, the spectrum parameter include the power of Received Signal, average speed and
Half spectrum width.
When group peak corresponding region is without in zero-frequency point and single continuum without more sub- peaks, spectrum parameter calculates mould
Block 4 calculates spectrum parameter by tradition spectrum parameter-calculation method, specifically includes：
Power spectrum is S (f), then its k rank moment of the orign is：
mk=∫ fkS(f)df
Atmospheric echo power P is calculated according to frequency spectrumr, i.e.,：
Pr=∫ S (f) df=m0
Average Doppler frequencyFor：
The variance of Doppler frequencyFor：
Then atmospheric echo average speed is estimated as：
Speed spectrum width is estimated as：
Wherein, λ is radar operation wavelength.
When in group peak corresponding region point containing zero-frequency and single continuum containing more sub- peaks, parameter calculating module 4 is composed
Spectrum parameter is calculated by Gauss curve fitting method, is specifically included：
Model, power spectral density function S are established to the power spectral density function of acquisitionm(v) it is：
Wherein, Noise is average noise level, Sa,σaRespectively the power of Received Signal, average speed and
Half spectrum width, Sm,σmPower, average speed and half spectrum width of respectively M noise jamming, observation are S (vi), observation
Deviation between model is：
So that deviation is minimum, you can to obtain the spectrum parameter of atmospheric echo.
Millimeter wave cloud radar data includes the falling speed of precipitation particles；Wind identification module 5 is according to precipitation particles
Falling speed and spectrum parameter identification wind number.
The foregoing is merely presently preferred embodiments of the present invention, is not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent replacement, improvement and so on, should all be included in the protection scope of the present invention.
Claims (10)
1. a kind of wind profile radar precipitation disturbance restraining method, it is characterised in that specifically include step：
Noise level is calculated according to wind profile radar modal data；
Spectral peak identification is carried out to wind profile radar modal data；
According to spectral peak recognition result and noise level, classified calculating spectrum parameter；
Millimeter wave cloud radar data is introduced, bind profile parameter carries out precipitation AF panel, identifies wind number.
2. a kind of wind profile radar precipitation disturbance restraining method according to claim 1, it is characterised in that carrying out spectral peak
Before identification, further include：
Wind profile radar modal data is pre-processed, the pretreatment includes denoising bottom, goes isolated value and sliding average.
3. a kind of wind profile radar precipitation disturbance restraining method according to claim 1 or 2, it is characterised in that wide to wind
Line radar modal data, which carries out spectral peak identification, includes continuum identification and local extremum judgement；
Continuum identification specifically includes：Analyze wind profile radar modal data, when wind profile radar modal data continue to exceed it is default
Threshold value and reach default data points, then be judged as continuum；
Local extremum judges to specifically include：The local maximum and local minimum in continuum are calculated, identification is each continuous
Sub- peak and corresponding sub- peak number amount in region.
4. a kind of wind profile radar precipitation disturbance restraining method according to claim 3, it is characterised in that known according to spectral peak
Other result and noise level classified calculating spectrum parameter includes：The continuum identified according to spectral peak recognition result and Zi Feng, lead to
Cross tradition spectrum parameter-calculation method or Gauss curve fitting method calculates and composes parameter, the power of the spectrum parameter including Received Signal,
Average speed and half spectrum width；
When group peak corresponding region is without in zero-frequency point and single continuum without more sub- peaks, pass through tradition spectrum parameter meter
Algorithm calculates spectrum parameter, specifically includes：
Power spectrum is S (f), then its k rank moment of the orign is：
mk=∫ fkS(f)df
Atmospheric echo power P is calculated according to frequency spectrumr, i.e.,：
Pr=∫ S (f) df=m0
Average Doppler frequencyFor：
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Model, power spectral density function S are established to the power spectral density function of acquisitionm(v) it is：
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Wherein, Noise is average noise level, Sa,σaRespectively the power of Received Signal, average speed and half compose
Width, Sm,σmPower, average speed and half spectrum width of respectively M noise jamming, observation are S (vi), observation and mould
Deviation between type is：
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<mi>i</mi>
</msub>
<mo>)</mo>
<mo>-</mo>
<msub>
<mi>S</mi>
<mi>m</mi>
</msub>
<mo>(</mo>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
So that deviation is minimum, you can to obtain the spectrum parameter of atmospheric echo.
A kind of 5. wind profile radar precipitation disturbance restraining method according to claim 1 or 2, it is characterised in that millimeter wave
Cloud radar data includes the falling speed of precipitation particles；
Millimeter wave cloud radar data is introduced, bind profile parameter carries out precipitation AF panel, and identification wind number includes：According to precipitation grain
The falling speed of son and spectrum parameter identification wind number.
A kind of 6. wind profile radar precipitation Interference Suppression System, it is characterised in that including：
Noise level computing module (1), for calculating noise level according to wind profile radar modal data；
Spectral peak identification module (3), for carrying out spectral peak identification to wind profile radar modal data；
Parameter calculating module (4) is composed, for according to spectral peak recognition result and noise level, classified calculating spectrum parameter；
Wind identification module (5), for introducing millimeter wave cloud radar data, bind profile parameter carries out precipitation AF panel, knows
Other wind number.
7. a kind of wind profile radar precipitation Interference Suppression System according to claim 6, it is characterised in that further include pre- place
Module (2) is managed, for being pre-processed before spectral peak identification is carried out to wind profile radar modal data, the pretreatment includes going
Make an uproar bottom, go isolated value and sliding average.
8. a kind of wind profile radar precipitation Interference Suppression System according to claim 6 or 7, it is characterised in that spectral peak is known
Other module (3), which carries out wind profile radar modal data spectral peak identification, includes continuum identification and local extremum judgement, and spectral peak is known
Other module (3) includes：
Region identification block, for analyzing wind profile radar modal data, when wind profile radar modal data continues to exceed default door
Limit value and reach default data points, be then judged as continuum；
Extreme value judging unit, for calculating local maximum and local minimum in continuum, identifies each continuum
In sub- peak and corresponding sub- peak number amount.
9. a kind of wind profile radar precipitation Interference Suppression System according to claim 8, it is characterised in that spectrum parameter calculates
The continuum and Zi Feng that module (4) is identified according to spectral peak recognition result, are intended by tradition spectrum parameter-calculation method or Gauss
Legal to calculate spectrum parameter, the spectrum parameter includes power, average speed and half spectrum width of Received Signal；
When group peak corresponding region is without in zero-frequency point and single continuum without more sub- peaks, parameter calculating module is composed
(4) spectrum parameter is calculated by tradition spectrum parameter-calculation method, specifically included：
Power spectrum is S (f), then its k rank moment of the orign is：
mk=∫ fkS(f)df
Atmospheric echo power P is calculated according to frequency spectrumr, i.e.,：
Pr=∫ S (f) df=m0
Average Doppler frequencyFor：
<mrow>
<mover>
<mi>f</mi>
<mo>&OverBar;</mo>
</mover>
<mo>=</mo>
<mfrac>
<mrow>
<mo>&Integral;</mo>
<mi>f</mi>
<mi>S</mi>
<mrow>
<mo>(</mo>
<mi>f</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>f</mi>
</mrow>
<mrow>
<mo>&Integral;</mo>
<mi>S</mi>
<mrow>
<mo>(</mo>
<mi>f</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>f</mi>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<msub>
<mi>m</mi>
<mn>1</mn>
</msub>
<msub>
<mi>m</mi>
<mn>0</mn>
</msub>
</mfrac>
</mrow>
The variance of Doppler frequencyFor：
<mrow>
<msubsup>
<mi>&sigma;</mi>
<mi>f</mi>
<mn>2</mn>
</msubsup>
<mo>=</mo>
<mfrac>
<mrow>
<mo>&Integral;</mo>
<msup>
<mrow>
<mo>(</mo>
<mi>f</mi>
<mo>-</mo>
<mover>
<mi>f</mi>
<mo>&OverBar;</mo>
</mover>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mi>S</mi>
<mrow>
<mo>(</mo>
<mi>f</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>f</mi>
</mrow>
<mrow>
<mo>&Integral;</mo>
<mi>S</mi>
<mrow>
<mo>(</mo>
<mi>f</mi>
<mo>)</mo>
</mrow>
<mi>d</mi>
<mi>f</mi>
</mrow>
</mfrac>
<mo>=</mo>
<mfrac>
<mrow>
<msub>
<mi>m</mi>
<mn>2</mn>
</msub>
<mo>-</mo>
<msubsup>
<mi>m</mi>
<mn>1</mn>
<mn>2</mn>
</msubsup>
<mo>/</mo>
<msub>
<mi>m</mi>
<mn>0</mn>
</msub>
</mrow>
<msub>
<mi>m</mi>
<mn>0</mn>
</msub>
</mfrac>
</mrow>
Then atmospheric echo average speed is：
<mrow>
<mover>
<mi>v</mi>
<mo>&OverBar;</mo>
</mover>
<mo>=</mo>
<mo>-</mo>
<mfrac>
<mi>&lambda;</mi>
<mn>2</mn>
</mfrac>
<mover>
<mi>f</mi>
<mo>&OverBar;</mo>
</mover>
</mrow>
Speed spectrum width is：
<mrow>
<msub>
<mi>W</mi>
<mi>v</mi>
</msub>
<mo>=</mo>
<mn>2</mn>
<msub>
<mi>&sigma;</mi>
<mi>v</mi>
</msub>
<mo>=</mo>
<mn>2</mn>
<mfrac>
<mi>&lambda;</mi>
<mn>2</mn>
</mfrac>
<msub>
<mi>&sigma;</mi>
<mi>f</mi>
</msub>
</mrow>
Wherein, λ is radar operation wavelength；
When in group peak corresponding region point containing zero-frequency and single continuum containing more sub- peaks, spectrum parameter calculating module (4) is logical
Cross Gauss fitting process and calculate spectrum parameter, specifically include：
Model, power spectral density function S are established to the power spectral density function of acquisitionm(v) it is：
<mrow>
<msub>
<mi>S</mi>
<mi>m</mi>
</msub>
<mrow>
<mo>(</mo>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>N</mi>
<mi>o</mi>
<mi>i</mi>
<mi>s</mi>
<mi>e</mi>
<mo>+</mo>
<mfrac>
<msub>
<mi>S</mi>
<mi>a</mi>
</msub>
<mrow>
<msqrt>
<mrow>
<mn>2</mn>
<mi>&pi;</mi>
</mrow>
</msqrt>
<msub>
<mi>&sigma;</mi>
<mi>a</mi>
</msub>
</mrow>
</mfrac>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mrow>
<mo>-</mo>
<mfrac>
<msup>
<mrow>
<mo>(</mo>
<mrow>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mover>
<mi>v</mi>
<mo>&OverBar;</mo>
</mover>
<mi>a</mi>
</msub>
</mrow>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mrow>
<mn>2</mn>
<msubsup>
<mi>&sigma;</mi>
<mi>a</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
</mrow>
<mo>)</mo>
</mrow>
<mo>+</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>m</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>M</mi>
</munderover>
<mfrac>
<msub>
<mi>S</mi>
<mi>m</mi>
</msub>
<mrow>
<msqrt>
<mrow>
<mn>2</mn>
<mi>&pi;</mi>
</mrow>
</msqrt>
<msub>
<mi>&sigma;</mi>
<mi>m</mi>
</msub>
</mrow>
</mfrac>
<mi>exp</mi>
<mrow>
<mo>(</mo>
<mrow>
<mo>-</mo>
<mfrac>
<msup>
<mrow>
<mo>(</mo>
<mrow>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>-</mo>
<msub>
<mover>
<mi>v</mi>
<mo>&OverBar;</mo>
</mover>
<mi>m</mi>
</msub>
</mrow>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mrow>
<mn>2</mn>
<msubsup>
<mi>&sigma;</mi>
<mi>m</mi>
<mn>2</mn>
</msubsup>
</mrow>
</mfrac>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
Wherein, Noise is average noise level, Sa,σaRespectively the power of Received Signal, average speed and half compose
Width, Sm,σmPower, average speed and half spectrum width of respectively M noise jamming, observation are S (vi), observation and mould
Deviation between type is：
<mrow>
<msup>
<mi>&epsiv;</mi>
<mn>2</mn>
</msup>
<mo>=</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<mi>S</mi>
<mo>(</mo>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
<mo>-</mo>
<msub>
<mi>S</mi>
<mi>m</mi>
</msub>
<mo>(</mo>
<msub>
<mi>v</mi>
<mi>i</mi>
</msub>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
So that deviation is minimum, you can to obtain the spectrum parameter of atmospheric echo.
A kind of 10. wind profile radar precipitation Interference Suppression System according to claim 6 or 7, it is characterised in that millimeter wave
Cloud radar data includes the falling speed of precipitation particles；
Falling speed and spectrum parameter identification wind number of the wind identification module (5) according to precipitation particles.
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| CN110146855A (en) * | 2019-06-11 | 2019-08-20 | 北京无线电测量研究所 | Radar Intermittent AF panel thresholding calculation method and device |
| CN110333506A (en) * | 2019-06-12 | 2019-10-15 | 中铁大桥科学研究院有限公司 | A method of extracting the drag-line location parameter of cable force measurement radar |
| 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 |
| CN111239704A (en) * | 2020-02-12 | 2020-06-05 | 中国科学院大气物理研究所 | Atmospheric detection radar target echo identification processing method, device, equipment and medium |
| CN112526547A (en) * | 2020-11-18 | 2021-03-19 | 董晶晶 | Atmospheric boundary layer classification method and device based on wind lidar |
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| CN110146855A (en) * | 2019-06-11 | 2019-08-20 | 北京无线电测量研究所 | Radar Intermittent AF panel thresholding calculation method and device |
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| CN111239704A (en) * | 2020-02-12 | 2020-06-05 | 中国科学院大气物理研究所 | Atmospheric detection radar target echo identification processing method, device, equipment and medium |
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| CN114114273A (en) * | 2021-12-08 | 2022-03-01 | 天津市气象台 | Wind profile radar signal processing method |
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