CN114114273A - Wind profile radar signal processing method - Google Patents
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Abstract
The invention discloses a wind profile radar signal processing method, which comprises the following steps: s1: collecting original power spectrum data of the wind profile radar; s2: performing basic processing on the original power spectrum data acquired in the step S1; s3: respectively identifying the peak position and judging whether the power spectrum data subjected to basic processing in the step S2 has meteorological significance, and recording the peak position and the intensity of the signal spectrum with meteorological significance; s4: the turbulence signal is identified in the meteorological signal spectrum of step S3. The wind profile radar signal processing method not only solves the problem of data loss in the precipitation period in the existing algorithm, but also verifies the reliability of the inversion of the horizontal wind field by the method.
Description
Technical Field
The invention relates to the technical field of meteorological prediction, in particular to a wind profile radar signal processing method.
Background
The wind profile radar has the characteristic of high space-time resolution, so that the wind profile radar becomes an important reference tool for the current short-time nowcasting. The existing domestic wind profile radar adopts five-beam detection, wherein the five-beam detection comprises a vertical beam and inclined beams which are uniformly distributed in four directions and respectively point to the zenith, east, south, west and north directions, and the zenith angle of the inclined beams is about 15 degrees. The following formula (1) can be obtained according to the spatial geometrical relationship between the three-dimensional wind field and the radial velocity shown in fig. 1 a:
the above equation (1), i.e. the radial velocity
Expressions about three components of the wind field u, v and w; wherein
Is radial velocity, u, v and w are three components of a wind field in a rectangular coordinate system, theta is a zenith angle,
for azimuth, i is 0,1,2,3, indicating different azimuths.
The five beams adopt an alternate detection mode, the vertical velocity is obtained from the vertical beams, and the four inclined beams are combined to obtain a wind field. Based on the assumption that the wind field is locally uniform, the east-west (or north-south) beam radial velocity average value is obtained through the following formulas (2) and (3) to obtain the wind field u (V) component, and then the wind speed (V) is obtained through the formulas (4) and (5) according to the geometric relationship shown in fig. 1bh) And the wind direction (alpha)h)。
u＝[Vr(θ,π/2)-Vr(θ,3π/2)]/2sinθ (2)
v＝[Vr(θ,0)-Vr(θ,π)]/2sinθ (3)
However, the algorithm has certain errors, and the main reason is that the precipitation weather often brings errors to the wind field synthesis of the wind profile radar. The assumption that the source of error is that the wind field and vertical airflow are locally uniform is not true. In precipitation weather, because airflow activity has the characteristics of small spatial scale and strong local property, horizontal and vertical airflows hardly meet the assumption of local uniformity at the same time, and thus errors are brought to wind field synthesis. For example, the wind speed at the height H is 6 m.s-1The wind direction is west wind, the east wave beam (zenith angle theta is 15 degrees) is not influenced by vertical airflow, and the west wave beam (zenith angle theta is 15 degrees) is influenced by downward dragging airflow formed by falling raindrops. The return signal of the east beam is the projection of the wind in the oblique direction, and the detected radial velocity is 1.5 m.s-1(ii) a The return signal of the West beam is the sum of the projections of the wind and the vertical airflow in the inclined direction, and the detected radial speed is-3 m.s-1According to the formula (2), the resultant wind speed is 9 m.s-1Thereby causing 3 m.s to be generated with the actual wind speed-1The error of (2).
The second error source is turbulence information identification interference caused by precipitation particle scattering. Under the clear sky condition, wind profile radar echo signals are caused by atmospheric turbulence scattering, and all wave beams are in a distribution form of a single-peak spectrum; in precipitation weather, the wind profile radar echo signal comprises a turbulence echo and an echo caused by precipitation particle scattering such as raindrops and ice crystals, the turbulence echo and the echo have echo speed and intensity with equivalent magnitude, and a power spectrum is in a 'bimodal spectrum' form. The "trimodal spectrum" condition also occurs when the vertical gas flow is strong.
For the vertical beam, since the actual falling speed of the raindrop is the vector sum of the falling end speed of the raindrop (the falling speed of the raindrop when the vertical airflow speed is 0) and the vertical airflow speed, the precipitation spectrum always accompanies the turbulence spectrum. If the vertical velocity is defined as positive downwards, the precipitation spectrum peak is always located to the right of the turbulence spectrum peak. For the oblique beam, the echo signal in the precipitation weather comprises the projection of the wind speed, the vertical airflow speed and the raindrop falling end speed in the oblique beam direction. Because the meteorological information represented by each wave crest can not be determined according to the relative position, inaccurate identification of turbulence information can cause a certain deviation of a radial velocity value, and the radial velocity determines the size and the direction of wind, the inversion of a wind field is often seriously influenced in precipitation weather. Fig. 2(a), (b), and (c) are power spectral density actual maps of "single peak spectrum", "double peak spectrum", and "triple peak spectrum", respectively, where the abscissa is velocity, the ordinate is relative value of power spectral density, and the number of fft sequences corresponds to velocity value one to one.
At present, the power spectrum of the wind profile radar is less researched and has certain limitation in the aspect of being interfered by precipitation water at home and abroad, and some technicians judge whether the data is polluted by the precipitation water or not through radial speed, spectral width and the like by utilizing different spectral moment characteristics of precipitation water and clear-space wind profile radar, but do not carry out effective quality control on the data polluted by the precipitation water; some technicians fill and reprocess data in precipitation weather according to a wind profile radar power spectrum re-analysis method and a detection principle, but cannot meet the requirement on wind profile radar data in a forecast early warning service; technicians divide the precipitation spectrum and the turbulence spectrum by using the lowest point of the connection of the two peaks in the return signal power spectrum, but the error of the separation method is often larger; according to the statistical principle that turbulence spectrums and precipitation spectrums in original power spectrums tend to be Gaussian when the average times of spectrums are sufficient, some technicians identify and separate turbulence spectrums from mixed and superposed power spectrums and use the turbulence spectrums for wind field inversion, so that the inversion quality of a wind field is improved, but the method omits the condition of 'multi-peak spectrums' (a plurality of spectrum peaks appear in the power spectrums). Therefore, research on a wind profile radar signal processing method is urgently needed.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defects existing in the prior art when the wind profile radar signal is used for forecasting precipitation, and further provide a wind profile radar signal processing method.
In order to achieve the purpose, the invention adopts the following technical scheme:
a wind profile radar signal processing method comprises the following steps:
s1: collecting original power spectrum data of the wind profile radar;
s2: performing basic processing on the original power spectrum data acquired in the step S1;
s3: respectively identifying the peak position and judging whether the power spectrum data subjected to basic processing in the step S2 has meteorological significance, and recording the peak position and the intensity of the signal spectrum with meteorological significance;
s4: the turbulence signal is identified in the meteorological signal spectrum of step S3.
Preferably, the basic processing in step S2 includes denoising and spectral data smoothing processing.
Preferably, the denoising processing method is as follows: taking the first 50 × power spectrum data (fft number/512) from the power spectrum fft data, and finding the maximum value as a noise value; denoising by subtracting a noise value from the power spectrum data, and setting a negative value as 0; after denoising, a non-zero signal interval and the initial position and the end position of the research area are found and used as signal intervals.
Preferably, the spectral data smoothing process is performed in the following manner: and performing 3-point sliding average on the power spectrum curve after the noise is removed for 20 times, so that the curve is smooth and the extreme point is prominent.
Preferably, in the step S3, the number of the peaks searched is at least three, and the searching method is as follows: for the smoothed power spectrum sequence, firstly finding a maximum value point of the sequence as a first maximum value point, respectively searching two first minimum value points from two sides, and temporarily setting the power spectrum between the two first minimum value points as a 0 value; then finding out the maximum point of the new sequence as a second extreme point, and respectively searching two second extreme points from two sides of the second extreme point; then temporarily setting the power spectrum between the two second minimum value points to be zero, and searching a third maximum value point in a new sequence; and identifying the meteorological significance wave crest for the found plurality of maximum value points.
Preferably, the method for identifying the meteorological significance peaks for the plurality of maximum points meets the following conditions: a. the spectral width of a signal spectrum is more than or equal to 3 m/s; b. 1/3 that the signal intensity at the corresponding maximum extremum point is greater than or equal to the difference in intensity from the maximum extremum point to the adjacent minimum extremum point; c. the signal spectrums are independent from each other, and the distance between the adjacent maximum value points is greater than 1/4 of the total length of the signal interval; and recording the number, the position and the intensity of the maximum value points meeting the common conditions of the three signals.
Preferably, the identification of the turbulence signal in the signal spectrum of meteorological significance comprises the identification of the turbulence signal in the vertical beam and the identification of the turbulence signal in the oblique beam.
Preferably, the turbulent signal in the vertical beam is identified by the following method: the wave crest having meteorological significance to the vertical wave beam is a single peak or double peaks; if the signal spectrum is double peaks, the signal spectrum on the left side is a turbulence spectrum; if the height is double peak and the adjacent height is single peak, determining the peak representing the turbulence spectrum on the height from the peak position of the single peak spectrum of the adjacent height.
Preferably, in the identification of the turbulence signal in the oblique beam, the east-west beam is performed according to the number of peaks and the beam direction, which have meteorological significance, as follows:
A. if the beams in the east-west direction are all 'single-peak spectrums', the east-west beams are not influenced by precipitation and pass through a formula
The radial velocities of the beams in the east and west directions are calculated respectively,
wherein M is0As the 0-order moment of the signal, M1Is the first moment of the signal, siIs the power density value of the ith point, viIs the speed value of the ith point, k is the number of FFT points of the power spectrum, and then passes through the formula
The horizontal wind u component is calculated,
wherein, Vre、VrwThe radial velocities are in the east-west direction respectively, theta is an included angle between the inclined wave beam and the vertical direction, and u is the east-west direction component of the horizontal wind;
B. if one side of the beam in the east-west direction is a 'unimodal spectrum' and the other side of the beam in the east-west direction is a 'bimodal spectrum' or a 'trimodal spectrum', one side of the 'unimodal spectrum' is combined with the vertical beam to calculate a u component;
when east beam is "unimodal spectrum
Calculating radial velocity of east beam by formula
Calculating a horizontal wind u component;
formula is adopted when west wave beam is' unimodal spectrum
Calculating the radial velocity of west beam by formula
Calculating a horizontal wind u component;
wherein, ω iszThe vertical radial velocity after quality control;
C. if the east-west wave beams are all 'three-peak spectrums', the wave beams are processed by a formula
Respectively calculating the radial velocity of the wave beams in the east and west directions, and then passing through a formula
Calculating a horizontal wind u component;
D. if the east and west beams are both "bimodal," the following two cases are distinguished:
a. if the wave spectrum of one side of the wave beams in the east-west direction is a negative value, the wave spectrum of the negative value is considered to be a turbulence spectrum, turbulence information of the horizontal wave beams can be represented, and the turbulence spectrum of the vertical wave beams is combined with the inclined wave beams with the negative value wave spectrum, so that the horizontal wind u component is obtained by calculation according to the mode B;
b. if the 'double peak spectrums' of the wave beams in the east and west directions are positive values, the two sides are considered to have strong sinking speeds, the magnitude of the horizontal wind is relatively small, the situation is similar to that of the vertical wave beams, the left sides of the two wave peaks are considered to be 'turbulence spectrums', the right sides of the two wave peaks are considered to be 'precipitation spectrums', and the mode A is used for calculating to obtain the u component of the horizontal wind;
E. if one side of the east-west beam is a bimodal spectrum and the other side is a trimodal spectrum, the following two situations are distinguished:
a. if the vertical velocity is a positive value, the abscissa of the leftmost spectrum in the trimodal spectrum is a negative value, the positive and negative of the vertical velocity are judged according to the turbulence spectrum of the vertical wave beam, if the vertical velocity is a positive value, the wave peak of which the abscissa is a negative value in the trimodal spectrum represents the inclined component of the horizontal wind field, the abscissa of the wave peak is taken as the radial velocity of the inclined wave beam, and the horizontal wind u component is calculated according to the mode B.
b. And under the condition that the a is not satisfied, considering that a pair of wave crests with the minimum absolute value difference of the abscissas and opposite numerical values are wave crests representing the horizontal wind speed, considering the horizontal wind speed radial component of the wave beam in the east-west direction as the abscissa corresponding to the wave crests, and calculating according to the mode A to obtain the horizontal wind u component.
Preferably, the calculation method of the v component of the horizontal wind of the wave beams in the north-south direction is the same as the calculation method of the u component of the horizontal wind; wind speed VhAnd wind direction alphahThe calculation is respectively carried out by the following two formulas:
the invention has the beneficial effects that:
the wind profile radar signal processing method not only solves the problem of data loss in the precipitation period in the existing algorithm, but also verifies the reliability of the WPR-HW algorithm for inverting the horizontal wind field through mode inspection and case inspection.
Drawings
In order that the present invention may be more readily and clearly understood, reference is now made to the following detailed description taken in conjunction with the accompanying drawings, in which:
FIG. 1a is a schematic diagram of a spatial geometry of a three-dimensional wind field with radial velocity;
FIG. 1b shows the wind speed VhAnd wind direction alphahA schematic diagram of the coordinate relationship with the components u and v;
FIG. 2a is a schematic diagram showing the measured power spectral density of a single peak of a wind profile radar echo signal in the prior art;
FIG. 2b is a schematic diagram showing measured dual peak power spectral density of a prior art wind profile radar echo signal;
FIG. 2c is a schematic representation of a prior art measured trimodal power spectral density of a wind profile radar echo signal;
FIG. 3 is a schematic diagram of a wind profile radar signal processing method of the present invention;
FIG. 4 is a schematic diagram of a further refinement of the wind profile radar signal processing method of the present invention;
fig. 5a, 5b, 5c, and 5dw are schematic diagrams illustrating steps of a power spectrum maximum point identification method.
The reference numbers in the figures denote:
Detailed Description
Referring to fig. 3-4, the wind profile radar signal processing method of the present invention uses wind profile radar original power spectrum data as a processing object, and first performs basic processing on the original power spectrum data, including denoising and spectrum data smoothing; and then respectively identifying the position of the wave peak of the smoothed data and judging whether the smoothed data has meteorological significance, recording the position and the intensity of the wave peak of the signal spectrum with meteorological significance, and then identifying the turbulent flow signal in the signal spectrum with meteorological significance. For vertical beams, the identification method is simple, for oblique beams, a WPR-HW algorithm is used, for example, east and west beams are used, the horizontal component u of the wind field is calculated by different methods according to different distribution of the number of peaks of east and west beam signal spectrum, the vertical component v of the horizontal wind field is calculated by north and south beams in the same way, and finally the horizontal velocity is calculated by using the values of u and v. The following is a detailed description in accordance with the sequence of reference numerals (r) - (c) in fig. 4.
Removing noise: in the power spectrum fft data, the first 50 × power spectrum data (fft number/512) are taken, and the maximum value is found as a noise value. Denoising by subtracting a noise value from the power spectrum data, and setting a negative value as 0. After denoising, a non-zero signal interval and the initial position and the end position of the research area are found and used as signal intervals.
Smoothing: and performing 3-point sliding average on the power spectrum curve after the noise is removed for 20 times, so that the curve is smooth and the extreme point is prominent.
Thirdly, identifying the position of a signal spectrum peak: and searching the number and the position of the wave crests. For the smoothed power spectrum sequence, taking a "trimodal spectrum" as an example, as shown in fig. 5a, first maximum point a1 of the sequence is found as a maximum point, and then first minimum points B1 and B2 are respectively found from two sides of a 1; as shown in fig. 5B, the power spectrums from B1 to B2 are temporarily set to be 0 values, which is beneficial to searching the next maximum value point; as shown in fig. 5C, find the second maximum point a2 of the new sequence as the second maximum point, and then respectively find the second minimum points C1 and C2 from the two sides of a 2; as shown in fig. 5d, the same method is used to find the third maximum point A3, so far, the three maximum points a1, a2, and A3 are found.
Judging whether the signal is normal or not with meteorological significance: the power spectrum sequence is a discrete sequence, the maximum value point judged from the waveform of the power spectrum is not necessarily a wave crest with meteorological significance, the maximum value point needs to be further judged, and the judgment conditions need to meet the following three conditions:
A. the signal spectrum is required to have a certain width, and the spectrum width is considered to be not less than 3m/s to reach the signal spectrum condition;
B. the signal spectrum is required to have certain intensity, and 1/3 that the intensity of the extreme point is not less than the intensity difference from the maximum point to the adjacent minimum point is considered to reach the signal spectrum condition;
C. the signal spectra are required to be independent of each other, and it is considered that 1/4 with a peak spacing greater than the total length of the signal interval achieves the signal spectrum condition.
Through discrimination, the number, position and strength of maximum points (wave crests) meeting the signal spectrum condition are recorded, and further inversion of the wind profile radar product under the precipitation condition is facilitated.
Vertical beam: the vertical wave beam has 1 or 2 wave peaks in meteorological significance generally, namely a single peak or a double peak, and the signal spectrum on the left side is a turbulent flow spectrum in the case of the double peak, but certain quality control is also carried out: for accurate judgment, if the height is a double peak and the adjacent height is a single peak, the peak representing the turbulence spectrum at the height is determined by the peak position of the single peak spectrum of the adjacent height.
Sixth, beam tilt: the WPR-HW signal algorithm is adopted for the inclined wave beams, the number of wave crests of the inclined wave beams with meteorological significance is generally 1-3, namely, the inclined wave beams can be a single peak, a double peak or a triple peak, the WPR-HW calculates the u component of the horizontal wind of the east-west wave beams (and the v component of the horizontal wind of the north-south wave beams) to invert the horizontal wind field in different modes by combining different combination methods that the east-west wave beams (or the north-south wave beams) meet the maximum value points of the meteorological signal characteristics and combining turbulence spectrums separated from the vertical wave beams. Here, the inversion method of the u component of the horizontal wind is described by taking an east-west beam as an example (the inversion method of the v component of the horizontal wind of the north-south beam is the same as the calculation method of the u component):
A. if the east and west beams are both "unimodal spectra". The east-west wave beams are not influenced by precipitation, and the radial velocities of the east-west wave beams are respectively calculated by the following formula (6), wherein M0As the 0-order moment of the signal, M1Is the first moment of the signal, siIs the power density value of the ith point, viIs the speed value of the ith point, k is the fft point number, and then the horizontal wind u component is calculated by the formula (2), wherein Vre、VrwRadial velocity in east-west directions, theta being the oblique beamAnd the included angle between the wind power generator and the vertical direction is U, which is the east-west component of horizontal wind.
B. If the east-west beam has a "single peak spectrum" on one side and a "bimodal spectrum" or "trimodal spectrum" on the other side. Since the tilted beam has some difficulty in determining the physical meaning of the peak, whereas the "unimodal spectrum" has a high probability of being a turbulent signal spectrum, the u-component is calculated using one side of the "unimodal spectrum" in combination with the vertical beam. When the east beam is a 'unimodal spectrum', the calculation is performed using the formula (6) and the formula (7), and when the west beam is a 'unimodal spectrum', the calculation is performed using the formula (6) and the formula (8), wherein ω iszThe vertical radial velocity after quality control.
C. If the east and west beams are all "trimodal spectra". Among the three peaks of the inclined beam, the peak position representing the vertical velocity component is determined according to the locally rising or sinking air current, the peak position representing the precipitation particle component is determined according to the locally falling end velocity of the raindrop, and the peak position representing the horizontal wind component is substantially symmetrical with respect to the east-west beam, and has stronger certainty than that. In the WPR-HW algorithm, in the three respective wave crests of east and west wave beams, a pair of wave crests with the smallest absolute value difference of abscissas and opposite numerical values are wave crests representing horizontal wind speed, the abscissas corresponding to the wave crests consider the radial component of the horizontal wind speed of the east and west wave beams, and u is obtained through the formula (6) and the formula (2).
D. If the east and west beams are "bimodal". The calculation is performed here in two cases:
a. if the spectrum on one side of the east-west wave beam is negative, the negative wave spectrum is considered as a turbulence spectrum, turbulence information of the horizontal wave beam can be represented, and the u component is obtained by the above formula (6) and formula (7) or the formula (6) and formula (8) by using the inclined wave beam with the negative wave spectrum and the 'turbulence spectrum' of the vertical wave beam.
b. If the 'double peak spectrum' of the east-west wave beam is positive, the appearance of the condition shows that both sides have stronger sinking speed and the horizontal wind magnitude is relatively small, the condition is similar to a vertical wave beam, the left side of the two wave peaks is considered to be a 'turbulence spectrum', the right side of the two wave peaks is considered to be a 'precipitation spectrum', and the u component is obtained through a formula (6) and a formula (2).
In practice, in the case where the east-west beams are "bimodal spectra", the spectrum of the east-west beams with the same existence side is almost not negative, and can be disregarded.
E. If one side of the east-west wave beam is a 'bimodal spectrum', the other side is a 'trimodal spectrum'. In this case, because of the difficulty in determining the wave crest meteorological significance, an assumption is made that the wind field in the vertical direction is uniform within the detection range, and the wind field is considered in two cases:
a. the vertical velocity is positive and the abscissa of the leftmost spectrum in the "trimodal spectrum" is negative. Judging whether the vertical velocity is positive or negative according to the 'turbulence spectrum' of the vertical wave beam, if the vertical velocity is positive, representing the inclined component of the horizontal wind field by the wave peak of which the abscissa is negative in the 'three-peak spectrum', taking the abscissa of the wave peak as the radial velocity of the inclined wave beam, and obtaining the u component through the formula (6) and the formula (7) or the formula (6) and the formula (8).
b. Under the condition that the a is not met, the WPR-HW algorithm is based on the principle that the component weight of a horizontal wind field in an inclined wave beam has symmetry, a pair of wave peaks with the minimum absolute value difference of the abscissa and opposite numerical values are wave peaks representing horizontal wind speed, the abscissa corresponding to the wave peaks is regarded as the radial component of the horizontal wind speed of the east-west wave beam, and the u component is obtained through the formula (6) and the formula (2).
And (c) calculating a horizontal wind field: according to the above-mentioned east-west waveThe calculation method of the beam u component obtains the value of the south-north beam V component by the same principle and calculation, and the wind speed V of the horizontal wind field can be obtained by calculating by using the following formula (4) and formula (5)hAnd wind direction alphah。
The horizontal wind field calculated by the WPR-HW algorithm solves the problem of data loss in the precipitation period in the existing algorithm, and simultaneously verifies the reliability of the WPR-HW algorithm for inverting the horizontal wind field through mode verification and case verification.
The invention provides a WPR-HW method for inverting a wind field based on a wind profile radar detection principle, the reason of wind field inversion errors in precipitation and WPR power spectrum characteristics. The WPR-HW method is used for processing power spectrum data, the number and the position of peak signals in each beam power spectrum are automatically identified, automatic identification and extraction of the turbulence spectrum are achieved in the signal spectrum of the symmetrical beams according to the characteristic that the turbulence spectrum is symmetrical about east-west (south-north) beams, interference of precipitation particle scattering is effectively inhibited, finally, the extracted turbulence spectrum is used for synthesizing a wind field according to the wind synthesis principle, and the influence of local unevenness of raindrop falling end speed on vertical airflow can be avoided. The quality control of the WPR-HW method is explained in detail by taking the example that east and west beams are trimodal spectrums. In the wave spectrum of the inclined wave beam, the vertical velocity component is determined by the vertical motion state of the local air flow, the precipitation particle component is determined by the falling end velocity of the local raindrop, the uncertainty is strong, and the wind field is basically symmetrical about the east-west wave beam under the assumption of local uniformity. Finding out the symmetrical wave spectrum of east and west wave beams to determine the radial component of the wind of the inclined wave beams, further obtaining the u component, combining the V component, and obtaining the wind speed V by the formula (4) and the formula (5)hAnd wind direction alphah. The WPR-HW method is advantageous in that it is superior to the conventional WIND method in thatBased on the wind profile radar power spectrum data, the data flow is from the power spectrum to the radial velocity data, and the radial velocity data is then to the product data, so that the regeneration error in the processing process is avoided. The WPR-HW method is based on comprehensive analysis of power spectrum data of each wave beam of the wind profile radar, makes full use of the physical process of multiple wave peaks generated during precipitation and the distribution rule of the wave peaks, can effectively identify turbulence spectrum data, and further reduces the error rate of single wave beam analysis.
The above embodiments are merely to explain the technical solutions of the present invention in detail, and the present invention is not limited to the above embodiments, and it should be understood by those skilled in the art that all modifications and substitutions based on the above principles and spirit of the present invention should be within the protection scope of the present invention.
Claims (10)
1. A wind profile radar signal processing method is characterized by comprising the following steps:
s1: collecting original power spectrum data of the wind profile radar;
s2: performing basic processing on the original power spectrum data acquired in the step S1;
s3: respectively identifying the peak position and judging whether the power spectrum data subjected to basic processing in the step S2 has meteorological significance, and recording the peak position and the intensity of the signal spectrum with meteorological significance;
s4: the turbulence signal is identified in the meteorological signal spectrum of step S3.
2. The wind profile radar signal processing method according to claim 1, characterized by: the basic processing in step S2 includes denoising and spectral data smoothing processing.
3. The wind profile radar signal processing method according to claim 2, characterized by:
the denoising processing mode is as follows: taking the first 50 × power spectrum data (fft number/512) from the power spectrum fft data, and finding the maximum value as a noise value; denoising by subtracting a noise value from the power spectrum data, and setting a negative value as 0; after denoising, a non-zero signal interval and the initial position and the end position of the research area are found and used as signal intervals.
4. The wind profile radar signal processing method according to claim 2, characterized by:
the spectral data smoothing method comprises the following steps: and performing 3-point sliding average on the power spectrum curve after the noise is removed for 20 times, so that the curve is smooth and the extreme point is prominent.
5. The wind profile radar signal processing method according to claim 1, characterized by: in step S3, the number of peaks to be searched is at least three, and the searching method is: for the smoothed power spectrum sequence, firstly finding a maximum value point of the sequence as a first maximum value point, respectively searching two first minimum value points from two sides, and temporarily setting the power spectrum between the two first minimum value points as a 0 value; then finding out the maximum point of the new sequence as a second extreme point, and respectively searching two second extreme points from two sides of the second extreme point; then temporarily setting the power spectrum between the two second minimum value points to be zero, and searching a third maximum value point in a new sequence; and identifying the meteorological significance wave crest for the found plurality of maximum value points.
6. The wind profile radar signal processing method according to claim 5, characterized by: the identification method for the meteorological significance peaks of the plurality of maximum value points meets the following conditions:
a. the spectral width of a signal spectrum is more than or equal to 3 m/s;
b. 1/3 that the signal intensity at the corresponding maximum extremum point is greater than or equal to the difference in intensity from the maximum extremum point to the adjacent minimum extremum point;
c. the signal spectrums are independent from each other, and the distance between the adjacent maximum value points is greater than 1/4 of the total length of the signal interval;
and recording the number, the position and the intensity of the maximum value points meeting the common conditions of the three signals.
7. The wind profile radar signal processing method according to claim 6, characterized by: the identification of turbulence signals in the signal spectrum of meteorological significance includes the identification of turbulence signals in vertical beams and the identification of turbulence signals in oblique beams.
8. The wind profile radar signal processing method according to claim 7, characterized by: the identification method of the turbulence signals in the vertical beams is as follows: the wave crest having meteorological significance to the vertical wave beam is a single peak or double peaks; if the signal spectrum is double peaks, the signal spectrum on the left side is a turbulence spectrum; if the height is double peak and the adjacent height is single peak, determining the peak representing the turbulence spectrum on the height from the peak position of the single peak spectrum of the adjacent height.
9. The wind profile radar signal processing method according to claim 7, characterized by: the identification of the turbulence signal in the oblique beam, based on its meteorologic number of peaks and beam direction, the east-west beam proceeds as follows:
A. if the beams in the east-west direction are all 'single-peak spectrums', the east-west beams are not influenced by precipitation and pass through a formula
The radial velocities of the beams in the east and west directions are calculated respectively,
wherein M is0As the 0-order moment of the signal, M1Is the first moment of the signal, siIs the power density value of the ith point, viIs the speed value of the ith point, k is the number of FFT points of the power spectrum, and then passes through the formula
The horizontal wind u component is calculated,
wherein, Vre、VrwRespectively, the radial velocity in the east-west direction, theta is the included angle between the inclined beam and the vertical direction, and u isThe east-west component of horizontal wind;
B. if one side of the beam in the east-west direction is a 'unimodal spectrum' and the other side of the beam in the east-west direction is a 'bimodal spectrum' or a 'trimodal spectrum', one side of the 'unimodal spectrum' is combined with the vertical beam to calculate a u component;
when east beam is "unimodal spectrum
Calculating radial velocity of east beam by formula
Calculating a horizontal wind u component;
formula is adopted when west wave beam is' unimodal spectrum
Calculating the radial velocity of west beam by formula
Calculating a horizontal wind u component;
wherein, ω iszThe vertical radial velocity after quality control;
C. if the wave beams in the east and west directions are all 'three-peak spectrums', the wave beams pass through a formula
Respectively calculating the radial velocity of the wave beams in the east and west directions, and then passing through a formula
Calculating a horizontal wind u component;
D. if the east and west beams are both "bimodal," the following two cases are distinguished:
a. if the wave spectrum of one side of the wave beams in the east-west direction is a negative value, the wave spectrum of the negative value is considered to be a turbulence spectrum, turbulence information of the horizontal wave beams can be represented, and the turbulence spectrum of the vertical wave beams is combined with the inclined wave beams with the negative value wave spectrum, so that the horizontal wind u component is obtained by calculation according to the mode B;
b. if the 'double peak spectrums' of the wave beams in the east and west directions are positive values, the two sides are considered to have strong sinking speeds, the magnitude of the horizontal wind is relatively small, the situation is similar to that of the vertical wave beams, the left sides of the two wave peaks are considered to be 'turbulence spectrums', the right sides of the two wave peaks are considered to be 'precipitation spectrums', and the mode A is used for calculating to obtain the u component of the horizontal wind;
E. if one side of the east-west beam is a bimodal spectrum and the other side is a trimodal spectrum, the following two situations are distinguished:
a. if the vertical velocity is a positive value, the abscissa of the leftmost spectrum in the trimodal spectrum is a negative value, the positive and negative of the vertical velocity are judged according to the turbulence spectrum of the vertical wave beam, if the vertical velocity is a positive value, the wave peak of which the abscissa is a negative value in the trimodal spectrum represents the inclined component of the horizontal wind field, the abscissa of the wave peak is taken as the radial velocity of the inclined wave beam, and the horizontal wind u component is calculated according to the mode B.
b. And under the condition that the a is not satisfied, considering that a pair of wave crests with the minimum absolute value difference of the abscissas and opposite numerical values are wave crests representing the horizontal wind speed, considering the horizontal wind speed radial component of the wave beam in the east-west direction as the abscissa corresponding to the wave crests, and calculating according to the mode A to obtain the horizontal wind u component.
10. The wind profile radar signal processing method according to claim 9, characterized by: method for calculating v component of horizontal wind of wave beams in north and south directions and method for calculating u component of horizontal wind of wave beams in east and west directionsThe same; wind speed VhAnd wind direction alphahThe calculation is respectively carried out by the following two formulas:
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