Shore-based ultra-high frequency radar wind speed inversion method and system

Abstract

The application discloses a kind of shore-based ultra-high frequency radar wind speed inversion method and system, first obtain the wind speed measurement time series value of wind speed measuring instrument actual measurement, find the radar echo doppler spectrum corresponding to wind speed actual measurement value Calculation Bragg spectrum peak width, then obtain the wind direction corresponding to wind speed actual measurement value, according to the wind speed, Bragg spectrum peak width and wind direction time series obtained, utilize least square method to solve the parameter of wind speed inversion model, finally according to the radar echo doppler spectrum used for wind speed inversion Bragg spectrum peak width and wind direction, substitute into above-mentioned wind speed inversion model and obtain wind speed.The application proposes the relationship model of Bragg spectrum peak width and wind speed, wind direction, and with the aid of a small amount of standard wind speed, Bragg spectrum peak width and wind direction data, model parameters are solved, and then fast, real-time wind speed inversion is realized, the application range of shore-based ultra-high frequency radar ocean remote sensing is expanded, and it is helpful to improve the wind speed monitoring capability of nearshore sea area.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of marine environment radar monitoring, and particularly relates to a shore-based ultra-high frequency radar wind speed inversion method and system. BACKGROUND

[0002] Nearshore wind speed measurement is crucial for various applications such as weather forecasting, marine navigation, offshore energy production, and coastal engineering. Wind is a key factor in determining weather and sea conditions in coastal areas, and to ensure the safety of marine activities and infrastructure, it is necessary to accurately measure wind speed and direction. In addition, wind energy production, as a renewable energy source, is increasingly valued by people, and understanding the dynamics of nearshore wind patterns is beneficial for optimizing the performance of wind turbines and reducing the cost of energy production. Therefore, nearshore wind speed measurement is essential for selecting and designing offshore wind farms.

[0003] Existing instruments for measuring nearshore wind speed include anemometers, lidar, space-borne synthetic aperture radar, space-borne scatterometer, X-band radar, and high-frequency ground wave radar. Anemometers are usually installed on buoys or ships, and they can only provide measurements at a fixed location or a single track, and cannot obtain the spatial variation of wind speed in a larger area. In addition, anemometers need to be regularly calibrated and maintained to ensure accurate measurements, but in the nearshore environment, this is a significant challenge because the instruments are often exposed to harsh conditions such as saltwater spray, strong winds, and large waves. Lidar can provide high-resolution, real-time wind speed measurements, but the measurement range is limited to a few hundred meters, and the measurement accuracy is easily affected by atmospheric conditions such as fog, rain, and haze. Space-borne instruments have a large spatial coverage, but they cannot stay in a particular area for a long time, so the time continuity of wind speed measurement in a specific area is poor. X-band radar can measure wind speed in a large area with high resolution and in real time, but it is easily disturbed by weather factors. High-frequency ground wave radar has the advantages of large range, all-weather, real-time, continuous measurement, and less required maintenance, but the spatial resolution is limited, and there is often a near-range blind zone of several kilometers in the nearshore sea area, and it is easily disturbed by other radio waves.

[0004] Compared with high-frequency ground wave radar, shore-based ultra-high frequency radar also has the advantages of all-weather, real-time, continuous measurement, and less required maintenance. Moreover, ultra-high frequency radar has a higher operating frequency, so it has a higher spatial resolution, and the detection range is more concentrated in the nearshore sea area, and there is less radio wave interference in the operating frequency band. In addition, ultra-high frequency radar is more sensitive to small changes in sea waves, so it is beneficial to obtain higher measurement accuracy.

[0005] Currently, the shore-based ultra-high frequency radar is mainly applied to river flow velocity detection, and is mainly applied to sea clutter observation in the field of ocean perception. The existing shore-based ultra-high frequency radar wind direction measurement methods include a method of inverting the wind direction according to the power ratio (Bragg Peak Power Ratio, BPPR for short) of the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak on the echo Doppler spectrum, and a method of inverting the wind direction according to the modified echo Doppler spectrum centroid (MDSC for short). However, there is no public document about the shore-based ultra-high frequency radar wind speed measurement method at present. SUMMARY

[0006] In view of the deficiencies in the prior art, the present application provides a shore-based ultra-high frequency radar wind speed inversion method and system, so as to apply the shore-based ultra-high frequency radar to the near-shore sea area wind speed measurement and exert its potential advantages in the near-shore ocean environment monitoring.

[0007] In order to achieve the above-mentioned purpose, the technical scheme provided by the present application is a shore-based ultra-high frequency radar wind speed inversion method, comprising the following steps:

[0008] Step 1: selecting a wind speed measurement time sequence measured by a wind speed measurement instrument in a radar coverage area to construct a standard wind speed time sequence;

[0009] Step 2: calculating a Bragg spectrum peak width time sequence according to the radar echo Doppler spectrum of the place corresponding to the standard wind speed time sequence in step 1;

[0010] Step 2.1: finding the range and azimuth element corresponding to the standard wind speed U0(t) at time t in step 1, searching for the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak near the positive and negative standard Bragg frequencies for the echo Doppler spectrum of the element, and the positive and negative frequency first-order Bragg peaks are the sharpest peaks with the maximum power on the positive and negative frequency half-axes of the Doppler spectrum; if both Bragg peaks can be found, comparing the powers of the two Bragg peaks, and recording the frequency of the Bragg peak with higher power as ω BH0 (t); if only the positive frequency first-order Bragg peak or only the negative frequency first-order Bragg peak can be found, recording the frequency of the Bragg peak as ω BH0 (t);

[0011] Step 2.2: finding the spectrum peak with power exceeding a set threshold on the left side of ω BH0 (t) and taking the frequency corresponding to the spectrum peak as the left boundary ω BHL0 (t) of the Bragg peak; finding the spectrum peak with power exceeding the set threshold on the right side of ω BH0 (t) and taking the frequency corresponding to the spectrum peak as the right boundary ω BHR0 (t) of the Bragg peak;

[0012] Step 2.3, fitting the Doppler spectrum between the left boundary ω BHL0 (t) and the right boundary ω BHR0 (t) using a Gaussian function, i.e.,

[0013]

[0014] where G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, a0, b0, c0, d0 are constants to be determined by fitting;

[0015] Step 2.4, taking the value of the constant c0 obtained in Step 2.3 as the Bragg spectral peak width W0(t) at time t;

[0016] Step 3, obtaining a time series of wind direction corresponding to the time series of standard wind speed;

[0017] Step 4, inputting the values of the time series of standard wind speed, the time series of Bragg spectral peak width and the time series of wind direction obtained in Steps 1-3 into a wind speed inversion model, and solving the parameters of the wind speed inversion model using the least square method;

[0018] Step 5, calculating the Bragg spectral peak width according to the radar echo Doppler spectrum used for wind speed inversion;

[0019] Step 5.1, searching for the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak near the positive and negative standard Bragg frequencies of the radar echo Doppler spectrum used for wind speed inversion; if both Bragg peaks can be found, comparing the powers of the two Bragg peaks, and taking the frequency of the Bragg peak with higher power as ω BH ; if only the positive frequency first-order Bragg peak or only the negative frequency first-order Bragg peak can be found, taking the frequency of this Bragg peak as ω BH ;

[0020] Step 5.2, finding the spectral peak with power exceeding a preset threshold closest to the left of ω BH , taking the frequency of the spectral peak as the left boundary ω BHL of the Bragg peak, and finding the spectral peak with power exceeding the preset threshold closest to the right of ω BH , taking the frequency of the spectral peak as the right boundary ω BHR of the Bragg peak;

[0021] Step 5.3, fitting the Doppler spectrum between the left boundary ω BHL and the right boundary ω BHR using a Gaussian function, i.e.,

[0022]

[0023] In the formula, G(·) represents the echo Doppler spectrum, ω represents the angular frequency, a, b, c, d are constants to be determined by fitting;

[0024] Step 5.4, taking the value of the constant C obtained in step 5.3 as the Bragg spectrum peak width W;

[0025] Step 6, calculating the wind direction according to the radar echo Doppler spectrum for wind speed inversion;

[0026] Step 7, substituting the Bragg spectrum peak width obtained in step 5 and the wind direction obtained in step 6 into the wind speed inversion model to calculate the wind speed.

[0027] Moreover, the specific method for searching for the positive frequency and negative frequency first-order Bragg peaks in step 2.1 is:

[0028] ①According to the maximum flow velocity value of the detected sea area, the frequency range of the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak is respectively determined near the positive and negative standard Bragg frequencies;

[0029] ②Search for spectrum peaks with power and prominence exceeding the set threshold in the frequency range of the positive frequency first-order Bragg peak, and record the frequency values as ω P1 , ω P2 , ω P3 , ……; Take the same approach to obtain the spectrum peak frequency values ω N1 , ω N2 , ω N3 , …… in the frequency range of the negative frequency first-order Bragg peak;

[0030] ③Select one spectrum peak from each frequency range to form a spectrum peak pair, calculate the frequency difference, and record it as ω P1 -ω N1 , ω P1 -ω N2 , ω P2 -ω N1 , ω P2 -ω N2If the frequency difference exceeds a set threshold, the spectrum peak pair is discarded; if the number of the final spectrum peak pairs is not zero, the spectrum peak pair with the largest average power is selected from them, and the corresponding spectrum peak is taken as the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak; if the number of the final spectrum peak pairs is zero, it is considered that the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak of the Doppler spectrum cannot be found; if the number of the spectrum peaks searched in the positive frequency first-order Bragg peak distribution range is not zero, the spectrum peak with the largest power is taken as the positive frequency first-order Bragg peak, and it is considered that the negative frequency first-order Bragg peak of the Doppler spectrum cannot be found; if the number of the spectrum peaks searched in the negative frequency first-order Bragg peak distribution range is not zero, the spectrum peak with the largest power is taken as the negative frequency first-order Bragg peak, and it is considered that the positive frequency first-order Bragg peak of the Doppler spectrum cannot be found.

[0031] Moreover, the wind direction measurement value measured by the wind direction finder at the same time and at the same place in the radar coverage area in step 3 is used to construct the wind direction time sequence Φ0(t), or the Φ0(t) is obtained by inverting the Doppler spectrum BPPR value of the radar echo at the place corresponding to the standard wind speed time sequence, or the Φ0(t) is obtained by inverting the Doppler spectrum centroid MDSC value of the echo at the place corresponding to the modified standard wind speed time sequence.

[0032] The specific calculation process of the wind speed value obtained by inverting the Doppler spectrum centroid MDSC value of the echo at the place corresponding to the modified standard wind speed time sequence is as follows:

[0033] If two first-order Bragg peaks are found, the MDSC is calculated according to the following formula, that is:

[0034]

[0035] In the formula, M represents the MDSC value, G(·) represents the echo Doppler spectrum, ω represents the angular frequency, ω P represents the angular frequency of the positive frequency first-order Bragg peak, and ω N represents the angular frequency of the negative frequency first-order Bragg peak, and ω B represents the echo angular frequency of the Bragg resonant sea wave.

[0036] If only the positive frequency first-order Bragg peak is found, the MDSC is calculated according to the following formula, that is:

[0037]

[0038] In the formula, M represents the MDSC, G(·) represents the echo Doppler spectrum, ω represents the angular frequency, ω P represents the angular frequency of the positive frequency first-order Bragg peak, and ω B represents the echo angular frequency of the Bragg resonant sea wave.

[0039] If only the negative frequency first order Bragg peak is found, MDSC is calculated according to the following formula, i.e.

[0040]

[0041] In the formula, M represents MDSC, G(·) represents echo Doppler spectrum, ω represents angular frequency, ω N represents angular frequency of the negative frequency first order Bragg peak, and ω B represents echo angular frequency of the Bragg resonant sea wave.

[0042] When the cosine form of the wave direction spreading function is selected, the obtained M value is substituted into formula (5) to obtain θ w , and the value of θ w is taken as the wind direction value Φ0(t) at time t, i.e.

[0043]

[0044] In the formula, S is a parameter of the direction spreading function, θ r represents the direction of the radar beam.

[0045] Moreover, the wind speed inversion model in step 4 has two forms, and the values of the standard wind speed time series U0(t), the Bragg spectrum peak width time series W0(t) and the wind direction time series Φ0(t) obtained in steps 1-3 are substituted into the following two model formulas, and the parameters of the two models are solved using the least square algorithm.

[0046] Model 1:

[0047]

[0048] Model 2:

[0049]

[0050] In the formula, W0(t) is the Bragg spectrum peak width at time t, U0(t) is the standard wind speed at time t, Φ0(t) is the wind direction at time t, θ r is the direction of the radar beam, and (e1, g1, h1) and (e2, f2, g2, h2) are model parameters to be solved.

[0051] Moreover, in step 6, the wind direction Φ is obtained according to the radar echo Doppler spectrum BPPR value used for wind speed inversion, or Φ is obtained according to the radar echo Doppler spectrum MDSC value used for wind speed inversion.

[0052] Moreover, in step 7, the Bragg spectrum peak width W obtained in step 5 and the wind direction Φ obtained in step 6 are substituted into any one of the following two models, so that the wind speed U can be obtained.

[0053] Model 1:

[0054]

[0055] Model 2:

[0056]

[0057] wherein W is the Bragg spectral peak width, U is the wind speed, is the wind direction, is the direction of the radar beam, and (e1, g1, h1) and (e2, f2, g2, h2) are model parameters. r

[0058] The application further provides a shore-based ultra-high frequency radar wind speed inversion system for implementing the shore-based ultra-high frequency radar wind speed inversion method.

[0059] Moreover, the shore-based ultra-high frequency radar wind speed inversion system comprises a processor and a memory, the memory is used for storing program instructions, and the processor is used for calling the program instructions in the memory to execute the shore-based ultra-high frequency radar wind speed inversion method.

[0060] Alternatively, the shore-based ultra-high frequency radar wind speed inversion system comprises a readable storage medium, and the readable storage medium stores a computer program, the computer program is executed to implement the shore-based ultra-high frequency radar wind speed inversion method.

[0061] Compared with the prior art, the application has the following advantages:

[0062] 1) The application proposes a relationship model of the Bragg spectral peak width and the wind speed and the wind direction, and model parameters are obtained by means of a small amount of standard wind speed, Bragg spectral peak width and wind direction data, so that the wind speed is quickly and real-timely inverted.

[0063] 2) The application solves the problem of lacking a method suitable for shore-based ultra-high frequency radar wind speed inversion, expands the application range of shore-based ultra-high frequency radar ocean remote sensing, and helps to improve the wind speed monitoring capability of the near-shore sea area. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 is a flowchart of the method of the embodiment of the application.

[0065] ​Figure 2 is a comparison of the results of wind speed inversion using the method proposed in this invention and wind speed measurement using an anemometer mounted on a buoy. Figures (a) and (c) show the changes in wind speed values ​​measured by the shore-based UHF radar and the anemometer mounted on the buoy at the same location over time, respectively. The horizontal axis represents the date, and the vertical axis represents the wind speed. The solid curve represents the radar measurement result, and the dashed curve represents the buoy measurement result. Figures (b) and (d) are scatter plots of wind speed values ​​measured by the radar and the buoy. The horizontal axis represents the wind speed measured by the buoy, and the vertical axis represents the wind speed measured by the radar. The color intensity represents the angle between the wind direction and the radial direction of the radar. Figures (a) and (b) are the results obtained using the formula of Model 1, and Figures (c) and (d) are the results obtained using the formula of Model 2. Detailed Implementation

[0066] This invention provides a method and system for wind speed inversion using shore-based ultra-high frequency radar. The technical solution of this invention will be further described below with reference to the accompanying drawings and embodiments.

[0067] Example 1

[0068] like Figure 1 As shown, this invention provides a method for wind speed inversion using shore-based ultra-high frequency radar, comprising the following steps:

[0069] Step 1: Select the wind speed measurement time series measured by the wind speed measuring instrument within the radar coverage area to construct the standard wind speed time series.

[0070] In this embodiment, wind speed measurements from anemometers within the radar coverage area at multiple time points are used to construct a standard wind speed time series. When selecting data, it is necessary to consider that the wind speed at the corresponding time point can cover the required wind speed measurement range, such as 0–20 m / s, and that the wind direction at the corresponding time point can cover a wide wind direction measurement range, such as 0–360 degrees.

[0071] Step 2: Calculate the time series of Bragg peak width based on the radar echo Doppler spectrum of the location corresponding to the standard wind speed time series in Step 1.

[0072] Step 2.1: Locate the range azimuth element corresponding to the standard wind speed U0(t) at time t in Step 1. For this element's radar echo Doppler spectrum, search for positive and negative first-order Bragg peaks near the positive and negative standard Bragg frequencies. These positive and negative first-order Bragg peaks are the highest power spikes on the positive and negative frequency half-axis of the Doppler spectrum, respectively. If both Bragg peaks can be found, compare their powers and denote the frequency of the Bragg peak with higher power as ω. BH0 (t); If only a positive frequency first-order Bragg peak or only a negative frequency first-order Bragg peak can be found, then the frequency of this Bragg peak is denoted as ω. BH0 (t).

[0073] The specific method for searching for first-order Bragg peaks at positive and negative frequencies is as follows:

[0074] ①Based on the maximum current velocity value of the detected sea area, the frequency ranges of the positive and negative standard Bragg peaks are defined near the positive and negative standard Bragg frequencies, respectively.

[0075] ② Search for spectral peaks whose power and salience both exceed a set threshold within the positive frequency range of the first-order Bragg peak, and record their frequency values ​​as ω. P1 ω P2 ω P3 Using the same approach, the spectral peak frequency values ​​ω within the negative frequency first-order Bragg peak frequency range were obtained. N1 ω N2 ω N3 , ……

[0076] ③ Select one spectral peak from each of the two frequency ranges to form a spectral peak pair, calculate their frequency difference, and denot it as ω. P1 -ω N1 ω P1 -ω N2 ω P2 -ω N1 ω P2 -ω N2 If the frequency difference exceeds a set threshold, the spectral peak pair is discarded. In this embodiment, the frequency difference threshold is set to 2.5ω. B ω B This represents the echo angular frequency of the Bragg resonant ocean wave. If the number of peak pairs obtained is not zero, the peak pair with the highest average power is selected, and its corresponding peaks are considered the positive and negative first-order Bragg peaks. If the number of peak pairs obtained is zero, it is considered that the positive and negative first-order Bragg peaks of this Doppler spectrum cannot be found. If the number of peaks searched only within the distribution range of the positive first-order Bragg peak is not zero, the peak with the highest power is considered the positive first-order Bragg peak, and it is considered that the negative first-order Bragg peak of this Doppler spectrum cannot be found. If the number of peaks searched only within the distribution range of the negative first-order Bragg peak is not zero, the peak with the highest power is considered the negative first-order Bragg peak, and it is considered that the positive first-order Bragg peak of this Doppler spectrum cannot be found.

[0077] Step 2.2, at ω BH0 Find the nearest spectral peak whose power exceeds a set threshold to the left of (t), and take its corresponding frequency as the left boundary ω of the Bragg peak. BHL0 (t); at ω BH0 Find the nearest spectral peak whose power exceeds a set threshold to the right of (t), and take its corresponding frequency as the right boundary ω of the Bragg peak.BHR0 (t).

[0078] Step 2.3. Fit the Doppler spectrum between the left boundary ω BHL0 (t) and the right boundary ω BHR0 (t) obtained in Step 2.2 using a Gaussian function, i.e.

[0079]

[0080] where G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, a0, b0, c0, d0 are constants to be determined by fitting.

[0081] Step 2.4. Take the value of the constant c0 obtained in Step 2.3 as the Bragg spectral peak width W0(t) at time t.

[0082] Step 3. Obtain the time series of wind direction corresponding to the time series of standard wind speed.

[0083] Construct the time series of wind direction Φ0(t) using the wind direction measurement values measured by the anemometer at the same time and at the same place within the radar coverage, or obtain Φ0(t) by inversion according to the BPPR values of the echo Doppler spectrum at the place corresponding to the time series of standard wind speed, or obtain Φ0(t) by inversion according to the MDSC values of the echo Doppler spectrum at the place corresponding to the time series of modified standard wind speed.

[0084] This embodiment uses the MDSC values of the echo Doppler spectrum at the place corresponding to the time series of modified standard wind speed to obtain the wind speed values, and the specific calculation process is as follows:

[0085] If two first-order Bragg peaks are found, MDSC is calculated according to the following formula:

[0086]

[0087] where M denotes MDSC, G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, ω P denotes the angular frequency of the positive frequency first-order Bragg peak, and ω N denotes the angular frequency of the negative frequency first-order Bragg peak, and ω B denotes the echo angular frequency of the Bragg resonant sea wave.

[0088] If only the positive frequency first-order Bragg peak is found, MDSC is calculated according to the following formula:

[0089]

[0090] where M denotes MDSC, G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, ω P denotes the angular frequency of the positive frequency first-order Bragg peak, and ωB This represents the echo angular frequency of the Bragg resonant ocean waves.

[0091] If only a first-order Bragg peak at a negative frequency is found, the MDSC is calculated according to the following formula:

[0092]

[0093] In the formula, M represents MDSC, G(·) represents the echo Doppler spectrum, ω represents the angular frequency, and ω N ω represents the angular frequency of the first-order Bragg peak, which is a negative frequency. B This represents the echo angular frequency of the Bragg resonant ocean waves.

[0094] If a cosine-form wave direction expansion function is chosen, then the value of M is substituted into the following formula to obtain θ. w and θ w The value of Φ0(t) is taken as the wind direction value at time t, that is:

[0095]

[0096] In the formula, S is the parameter of the directional spread function, and θ r Indicates the direction of the radar beam.

[0097] In practice, other forms of wave direction spread functions can be selected to solve for θ as needed. w Examples include the hyperbolic secant form of the spread function proposed by Donelan, the Gaussian function form of the directional spread function proposed by Apel, and the unified propagation model proposed by Elfouhaily.

[0098] Step 4: Input the values ​​of the standard wind speed time series, Bragg peak width time series, and wind direction time series obtained in Steps 1 to 3 into the wind speed inversion model, and use the least squares method to solve for the parameters of the wind speed inversion model.

[0099] Considering that the wavelength of the electromagnetic waves emitted by UHF radar is much smaller than the main wavelength of ocean waves, a two-scale model is used to describe sea surface roughness. Based on the two-scale model, the echo Doppler spectrum function of the shore-based UHF radar can be calculated, and then the relationship between the echo Doppler spectrum and the wave spectrum can be established. The wave spectrum can be expressed as the product of the undirected wave height spectrum and the wave direction function. In order to obtain an analytical expression, the undirected wave height spectrum is approximated as the PM saturated wave spectrum, and it is assumed that the main wave direction is consistent with the wind direction, so that the wave spectrum can be expressed as a function of wind speed and wind direction. Then, based on the echo Doppler spectrum function, the relationship model between the Doppler spectrum width and wind speed and wind direction is established as follows:

[0100] Model 1:

[0101]

[0102] where W0(t) is the Bragg spectral peak width at time t, U0(t) is the standard wind speed at time t, Φ0(t) is the wind direction at time t, θ is the direction of the radar beam, and (e1, g1, h1) are the model parameters to be solved. r

[0103] Based on the measured data, the model 1 is optimized as follows:

[0104] Model 2:

[0105]

[0106] where W0(t) is the Bragg spectral peak width at time t, U0(t) is the standard wind speed at time t, Φ0(t) is the wind direction at time t, θ is the direction of the radar beam, and (e2, f2, g2, h2) are the model parameters to be solved. r

[0107] The values of the standard wind speed time series, the Bragg spectral peak width time series, and the wind direction time series obtained in steps 1-3 are substituted into the wind speed inversion model in formula (6) or formula (7), and the parameters of the two models are solved using the least squares algorithm.

[0108] Step 5, the Bragg spectral peak width is calculated based on the radar echo Doppler spectrum used for wind speed inversion.

[0109] Step 5.1, search for the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak near the positive and negative standard Bragg frequencies of the echo Doppler spectrum. If both Bragg peaks can be found, compare their powers, and record the frequency of the Bragg peak with higher power as ω BH ; if only the positive frequency first-order Bragg peak or only the negative frequency first-order Bragg peak can be found, record the frequency of this Bragg peak as ω BH .

[0110] Step 5.2, find the nearest spectral peak with power exceeding the preset threshold on the left side of ω BH , and take its corresponding frequency as the left boundary ω BHL of the Bragg peak; find the nearest spectral peak with power exceeding the preset threshold on the right side of ω BH , and take its corresponding frequency as the right boundary ω BHR of the Bragg peak.

[0111] Step 5.3, fit the Doppler spectrum between the left boundary ω BHL and the right boundary ω BHR using a Gaussian function, that is:

[0112] ​​

[0113] where G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, and a, b, c, d are constants to be determined by fitting.

[0114] Step 5.4, take the value of constant C obtained in step 5.3 as the Bragg spectral peak width W.

[0115] Step 6, calculate the wind direction from the radar echo Doppler spectrum for wind speed inversion.

[0116] Invert the wind direction Φ from the radar echo Doppler spectrum BPPR value for wind speed inversion, or invert Φ from the radar echo Doppler spectrum MDSC value for wind speed inversion.

[0117] Step 7, substitute the Bragg spectral peak width obtained in step 5 and the wind direction obtained in step 6 into the wind speed inversion model to calculate the wind speed.

[0118] Substitute the Bragg spectral peak width W obtained in step 5 and the wind direction Φ obtained in step 6 into any one of the following two models to obtain the wind speed U.

[0119] Model 1:

[0120]

[0121] Model 2:

[0122]

[0123] where W is the Bragg spectral peak width, U is the standard wind speed, θ r is the direction of the radar beam, Φ is the wind direction, and (e1, g1, h1) and (e2, f2, g2, h2) are model parameters.

[0124] Comparative experiment

[0125] Fig. 2 shows a comparison experiment conducted in October 2015 at Huangqi Peninsula, Fujian. Fig. (a) and Fig. (c) are the measured values of the shore-based UHF radar and the anemometer installed on the buoy at the same location over time, respectively, with the horizontal axis representing the date and the vertical axis representing the wind speed, and the solid line curve representing the radar measurement result and the dotted line curve representing the buoy measurement result. Fig. (b) and Fig. (d) are scatter plots, with the horizontal axis representing the wind speed measured by the buoy and the vertical axis representing the wind speed measured by the radar, and the color depth representing the angle between the wind direction and the radial direction of the radar. Fig. (a) and Fig. (b) are the results obtained using the formula of Model 1, and Fig. (c) and Fig. (d) are the results obtained using the formula of Model 2. As can be seen from Fig. (a) and Fig. (b), Model 1 is closer to the wind speed measurement value of the buoy when the wind speed is less than 7.5 m / s. As can be seen from Fig. (c) and Fig. (d), Model 2 has good consistency with the wind speed measurement value of the buoy during the entire experiment period. The calculation results show that the mean square error of the wind speed measurement of Model 1 during the experiment is 3 m / s, and the mean square error of the wind speed measurement of Model 2 is 1 m / s. The experimental results show that the wind speed inversion method proposed by the present application is suitable for shore-based UHF radar, effectively expands the application range of shore-based UHF radar ocean remote sensing, and helps to improve the wind speed monitoring capability of the nearshore sea area.

[0126] Embodiment Two

[0127] Based on the same inventive concept, the present application also provides a shore-based UHF radar wind speed inversion system, comprising a processor and a memory, the memory being used to store program instructions, and the processor being used to call the program instructions in the memory to execute a shore-based UHF radar wind speed inversion method as described above.

[0128] Embodiment Three

[0129] Based on the same inventive concept, the present application also provides a shore-based UHF radar wind speed inversion system, comprising a readable storage medium, and a computer program stored on the readable storage medium, the computer program being executed to implement a shore-based UHF radar wind speed inversion system method as described above.

[0130] The specific embodiments described herein merely exemplify the spirit of the present application. Those skilled in the art of the present application can make various modifications or supplements to the described specific embodiments or use similar ways to replace them, without deviating from the spirit of the present application or exceeding the scope defined by the appended claims.

Claims

1. A shore-based ultra-high frequency radar wind speed retrieval method, characterized in that, The method comprises the following steps: Step 1, selecting a time series of standard wind speed measured by a wind speed measuring instrument in a radar coverage area to construct a time series of standard wind speed; Step 2, calculating a time series of Bragg spectrum peak width according to radar echo Doppler spectrum of a place corresponding to the time series of standard wind speed in step 1; Step 3, obtaining a time series of wind direction corresponding to the time series of standard wind speed; Step 4, inputting values of the time series of standard wind speed, the time series of Bragg spectrum peak width and the time series of wind direction obtained in steps 1-3 into a wind speed inversion model, and solving parameters of the wind speed inversion model by using a least square method; Step 5, calculating Bragg spectrum peak width according to radar echo Doppler spectrum used for wind speed inversion; Step 6, calculating wind direction according to radar echo Doppler spectrum used for wind speed inversion; Step 7, substituting the Bragg spectrum peak width obtained in step 5 and the wind direction obtained in step 6 into the wind speed inversion model to calculate wind speed.

2. The shore-based ultra-high frequency radar wind speed retrieval method of claim 1, wherein: Step 2 comprises the following steps: Step 2.1, find the range bin corresponding to the standard wind speed U0(t) at time t in step 1, search the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak near the positive and negative Bragg frequency of the echo Doppler spectrum of the bin, the positive and negative frequency first-order Bragg peaks are the sharpest peaks with the maximum power on the positive and negative frequency half-axes of the Doppler spectrum respectively; if both the Bragg peaks can be found, compare the powers of the two, and record the frequency of the Bragg peak with the higher power as ω BH0 (t); if only the positive frequency first-order Bragg peak or only the negative frequency first-order Bragg peak can be found, record the frequency of the Bragg peak as ω BH0 (t). Step 2.2, at the left of ω BH0 (t) find the nearest spectral peak whose power exceeds a set threshold, take its corresponding frequency as the left boundary of the Bragg peak ω BHL0 (t); at the right of ω BH0 (t) find the nearest spectral peak whose power exceeds a set threshold, take its corresponding frequency as the right boundary of the Bragg peak ω BHR0 (t). Step 2.

3. Doppler spectrum fitting between left boundary ω BHL0 (t) and right boundary ω BHR0 (t) obtained from step 2.2 using a Gaussian function, i.e.: In the formula, G(·) represents echo Doppler spectrum, ω represents angular frequency, a0, b0, c0 and d0 are constants that need to be determined by fitting; Step 2.4, taking the value of the constant c0 obtained in step 2.3 as Bragg spectrum peak width W0(t) at time t.

3. A shore-based ultra-high frequency radar wind speed retrieval method according to claim 2, characterized in that: The specific method for searching positive frequency and negative frequency first-order Bragg peaks in step 2.1 is as follows: According to the maximum flow value of a detected sea area, the frequency range of the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak is respectively determined near the positive and negative standard Bragg frequencies; ii. In the range of positive frequency first-order Bragg peak frequency, search the spectrum peak whose power and prominence exceed the set threshold, and record its frequency value as ω P1 , ω P2 , ω P3 , …; In the same way, the spectrum peak frequency value ω N1 , ω N2 , ω N3 , … in the range of negative frequency first-order Bragg peak frequency is obtained; ③Select one spectral peak from each of the two frequency ranges to form a spectral peak pair, calculate the frequency difference, denoted as ω P1 -ω N1 , ω P1 -ω N2 , ω P2 -ω N1 , ω P2 -ω N2 , …; if the frequency difference exceeds the set threshold, discard this spectral peak pair; if the number of the final spectral peak pairs is not zero, select the spectral peak pair with the maximum average power from them, and the corresponding spectral peak is the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak; if the number of the final spectral peak pairs is zero, it is considered that the positive frequency first-order Bragg peak and the negative frequency first-order Bragg peak of the Doppler spectrum cannot be found; if the number of the spectral peaks searched in the positive frequency first-order Bragg peak distribution range is not zero, the spectral peak with the maximum power is taken as the positive frequency first-order Bragg peak, and it is considered that the negative frequency first-order Bragg peak of the Doppler spectrum cannot be found; if the number of the spectral peaks searched in the negative frequency first-order Bragg peak distribution range is not zero, the spectral peak with the maximum power is taken as the negative frequency first-order Bragg peak, and it is considered that the positive frequency first-order Bragg peak of the Doppler spectrum cannot be found.

4. The shore-based ultra-high frequency radar wind speed retrieval method of claim 1, wherein: In step 3, a time series of wind direction Φ0(t) is constructed by using wind direction measurement values measured by a wind direction instrument at the same time and the same place in the radar coverage area, or Φ0(t) is obtained by inversion according to BPPR values of radar echo Doppler spectrum of the place corresponding to the time series of standard wind speed, or Φ0(t) is obtained by inversion according to MDSC values of echo Doppler spectrum of the place corresponding to the time series of standard wind speed after correction; The specific calculation process of obtaining wind speed values by using MDSC values of echo Doppler spectrum of the place corresponding to the time series of standard wind speed after correction is as follows: If two first-order Bragg peaks are found, MDSC is calculated according to the following formula: where M denotes the MDSC value, G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, ω P denotes the angular frequency of the positive frequency first order Bragg peak, ω N denotes the angular frequency of the negative frequency first order Bragg peak, ω B denotes the echo angular frequency of the Bragg resonant sea wave; If only the positive frequency first-order Bragg peak is found, MDSC is calculated according to the following formula: where M denotes MDSC, G(·) denotes the echo Doppler spectrum, ω denotes the angular frequency, ω P denotes the angular frequency of the positive frequency first order Bragg peak, ω B denotes the echo angular frequency of the Bragg resonant sea wave; If only the negative frequency first-order Bragg peak is found, MDSC is calculated according to the following formula: where M represents MDSC, G(·) represents the echo Doppler spectrum, ω represents the angular frequency, ω N represents the angular frequency of the negative frequency first order Bragg peak, ω B represents the echo angular frequency of the Bragg resonant sea wave; When the wave direction spreading function of the cosine form is selected, the value of M obtained is substituted into Equation (5) to obtain θ w , and the value of θ w is taken as the wind direction value Φ0(t) at time t, that is: where S is a parameter of the directional spreading function, θ r denotes the direction of the radar beam.

5. The shore-based ultra-high frequency radar wind speed retrieval method of claim 1, wherein: In step 4, the wind speed inversion model has two forms, and the values of the time series of standard wind speed U0(t), the time series of Bragg spectrum peak width W0(t) and the time series of wind direction Φ0(t) obtained in steps 1-3 are substituted into the following two model formulas, and the parameters of the two models are solved by using a least square algorithm; Model 1: Model 2: In the formula, W0(t) is the Bragg spectrum peak width at time t, U0(t) is the standard wind speed at time t, Φ0(t) is the wind direction at time t, θ r is the direction of the radar beam, and (e1, g1, h1) and (e2, f2, g2, h2) are model parameters to be solved.

6. The shore-based ultra-high frequency radar wind speed retrieval method of claim 1, wherein: Step 5 comprises the following steps: Step 5.1, search positive frequency first order Bragg peak and negative frequency first order Bragg peak around the positive and negative standard Bragg frequency of the Doppler spectrum of the radar echo of the wind speed inversion; if both Bragg peaks can be found, compare the power of the two, and record the frequency of the Bragg peak with higher power as ω BH ; if only positive frequency first order Bragg peak or only negative frequency first order Bragg peak can be found, record the frequency of this Bragg peak as ω BH ; Step 5.2, find the nearest spectral peak with power exceeding a preset threshold on the left side of ω BH , take its corresponding frequency as the left boundary of the Bragg peak ω BHL ; find the nearest spectral peak with power exceeding a preset threshold on the right side of ω BH , take its corresponding frequency as the right boundary of the Bragg peak ω BHR ; Step 5.

3. Fit the Doppler spectrum between the above left boundary ω BHL and right boundary ω BHR using a Gaussian function, i.e.: In the formula, G(·) represents echo Doppler spectrum, ω represents angular frequency, a, b, c and d are constants that need to be determined by fitting; Step 5.4, taking the value of the constant C obtained in step 5.3 as Bragg spectrum peak width W.

7. The shore-based ultra-high frequency radar wind speed retrieval method of claim 1, wherein: In step 6, the wind direction Φ is retrieved according to the BPPR value of the radar echo Doppler spectrum for wind speed retrieval, or according to the MDSC value of the radar echo Doppler spectrum for wind speed retrieval.

8. The shore-based ultra-high frequency radar wind speed retrieval method of claim 1, wherein: In step 7, the Bragg spectrum peak width W obtained in step 5 and the wind direction Φ obtained in step 6 are substituted into any one of the following two models, so as to obtain the wind speed U. Model 1: Model 2: where W is the Bragg peak width, U is the wind speed, Φ is the wind direction, θ r is the direction of the radar beam, and (e1, g1, h1) and (e2, f2, g2, h2) are model parameters.

9. A shore-based ultra-high frequency radar wind speed retrieval system, characterized in that, The device comprises a processor and a memory, the memory is used for storing program instructions, and the processor is used for calling the program instructions in the memory to execute the shore-based ultra-high frequency radar wind speed retrieval method according to any one of claims 1-8.

10. A shore-based ultra-high frequency radar wind speed retrieval system, characterized in that, The device comprises a readable storage medium, and the readable storage medium stores a computer program, and the computer program is executed to implement the shore-based ultra-high frequency radar wind speed retrieval method according to any one of claims 1-8.

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