CN114065500A - Offshore wind speed inversion method based on SAR image and Bragg scattering model - Google Patents

Offshore wind speed inversion method based on SAR image and Bragg scattering model Download PDF

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CN114065500A
CN114065500A CN202111331930.1A CN202111331930A CN114065500A CN 114065500 A CN114065500 A CN 114065500A CN 202111331930 A CN202111331930 A CN 202111331930A CN 114065500 A CN114065500 A CN 114065500A
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邵伟增
孙展凤
胡宇逸
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Abstract

The invention provides an offshore wind speed inversion method based on SAR images and Bragg scattering models, which comprises the following steps: acquiring a satellite-borne SAR image, and simulating Bragg resonance roughness through sea surface ocean current and discrete wind of HYCOM on the basis of a Bragg scattering theory to obtain Bragg resonance NRCS; non-Bragg roughness simulation is carried out by measuring SAR image NRCS under polarization to obtain non-Bragg NRCS, and simulated NRCS corresponding to each discrete wind speed is obtained by combining Bragg resonance NRCS and non-Bragg NRCS; taking the wind speed corresponding to the minimum difference between the simulated NRCS obtained by discrete wind simulation and the NRCS observed by the SAR as an inversion result to obtain an inversion wind field; and verifying the applicability of the wind speed inversion method. The method improves the reliability and accuracy of offshore SAR image wind field inversion.

Description

Offshore wind speed inversion method based on SAR image and Bragg scattering model
Technical Field
The invention relates to the technical field of ocean numerical simulation, in particular to an offshore wind speed inversion method based on SAR images and Bragg scattering models.
Background
Remote sensing technology has developed significantly over the past decades. The scatterometer is a non-imaging radar sensor, and typically, satellite scatterometers are for wind field observation, such as QuikSCA, advanced scatterometers, china ocean-2B, and medium ocean satellites. The radar incidence angle of the scatterometer is between 20 ° and 60 ° and bragg resonance is the dominant microwave scattering mechanism, so the wind vector including wind speed and wind direction is directly related to the normalized backscatter cross section NRCS and the radar incidence angle. Based on this principle, an empirical model of the geophysical model equation (GMF) was developed. Since it is difficult to obtain both wind speed and wind direction by solving a single equation, 2-3 radar beams are required to invert a sea surface wind field.
In the prior art, Synthetic Aperture Radars (SAR) are advanced sensors for marine dynamics monitoring, such as wind fields, sea waves, upwelling and internal waves. SAR has the advantage of allowing worldwide observations and achieving medium to fine spatial resolution, C-band wind field inversion polarising GMFs (known as CMOD series) from satellite scatterometry observations and other ancillary wind fields. With the proliferation of SAR sensors and the enrichment of data sets, different homopolarizing GMFs were developed, such as C-SARMOD, C-SARMOD2, csamod-GF, and QPWIND _ GF for fully polarized GF-3 SAR. Although the homopolarization GMF is suitable for inversion work of SAR wind, the error is 2m s-1However, due to the presence of other marine phenomena, such as ocean fronts and mesoscale vortices, the error in the inversion of wind speed increases.
Furthermore, the polarization ratio model is commonly used to apply VV-polarized GMF in horizontal (HH) polarized SAR wind speed inversion, but because of saturation problems in homopolarized SAR backscatter signals in strong winds, the saturation upper wind speed of cross-polarized SAR backscatter signals is as high as 50m s-1The SAR backscatter signals at the cross-polarized channels, such as VH and HV, are able to invert the wind speed of tropical cyclones. However, wind field inversion of cross-polarized SAR images relies on a fine noise signal, which is less at light to moderate wind speeds. Furthermore, since the cutoff of velocity in the high incidence angle direction is related to wind speed, some research has focused on developing wind field inversion GMFs using cutoff wavelengths. However, these GMFs are only suitable for use in stationary sea conditions, where the sea is unstable and complexUnder sea conditions, accuracy is low, particularly in coastal waters.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an offshore wind speed inversion method with small error based on an SAR image and a Bragg scattering model.
In order to solve the problems, the technical scheme of the invention is as follows:
an offshore wind speed inversion method based on SAR images and Bragg scattering models, the method comprising the steps of:
acquiring a satellite-borne SAR image, and simulating Bragg resonance roughness through sea surface ocean current and discrete wind of HYCOM on the basis of a Bragg scattering theory to obtain Bragg resonance NRCS;
non-Bragg roughness simulation is carried out by measuring SAR image NRCS under polarization to obtain non-Bragg NRCS, and simulated NRCS corresponding to each discrete wind speed is obtained by combining Bragg resonance NRCS and non-Bragg NRCS;
taking the wind speed corresponding to the minimum difference between the simulated NRCS obtained by discrete wind simulation and the NRCS observed by the SAR as an inversion result to obtain an inversion wind field; and
and verifying the applicability of the wind speed inversion method.
Optionally, the step of acquiring a satellite-borne SAR image, based on a bragg scattering theory, and simulating bragg resonance roughness through ocean currents on the sea surface and the discrete wind of HYCOM to obtain a bragg resonance NRCS specifically includes: on the basis of a Bragg scattering theory, a composite sea surface radar backscattering model is improved, and parameters such as a sea surface wind field, ocean current, an incident angle and a height angle are utilized to simulate Bragg resonance NRCS (non-resonant vibration) related to the sea surface roughness under a medium incident angle together with an Elfouhaily sea wave spectrum.
Optionally, the step of performing non-bragg roughness simulation by measuring the SAR image NRCS under polarization to obtain the non-bragg NRCS, and obtaining the simulated NRCS corresponding to each discrete wind speed by combining the bragg resonance NRCS and the non-bragg NRCS specifically includes: SAR backscattering Return NRCS σ 0 is Bragg resonance scattering of PP polarization (VV or HH)
Figure BDA0003349119460000021
And a non-Bragg component sigma caused by wave breakingwbThe formula is:
Figure BDA0003349119460000022
optionally, the Bragg scattering
Figure BDA0003349119460000023
The calculation formula of (2) is as follows:
Figure BDA0003349119460000024
wherein:
Figure BDA0003349119460000025
Figure BDA0003349119460000026
θi＝cos-1(cos(θ-Tp)×cosTt)
wherein PP and QQ denote HH and VV polarization, respectively,. epsilonrRepresents the dielectric constant of seawater, bHHAnd bVVIs the approximate complex scattering coefficient of HH polarization and VV polarization, θiIs the effective local angle of incidence from the sea surface slope T and the radar angle of incidence.
Optionally, the σwbThe calculation formula of (2) is as follows:
Figure BDA0003349119460000031
wherein:
Figure BDA0003349119460000032
Figure BDA0003349119460000033
wherein:
Figure BDA0003349119460000034
wherein G isHHAnd GVVIs the polarization factor, siThe mean square slope represents the isotropic slope of the oblique wave.
Optionally, said siIs obtained empirically:
Figure BDA0003349119460000035
wherein U is10Wind speed 10 m above sea surface, g is gravity acceleration, kbr2krsin θ, is related to radar wave number krThe calculation formula of the relevant Bragg wave number and the age beta is as follows:
Figure BDA0003349119460000036
peak wave number k of spectrumpThe calculation formula of (2) is as follows:
Figure BDA0003349119460000037
optionally, the U10At 0 to 20m s-1In the range of 0.2m s-1By combining Bragg resonance NRCS and non-Bragg NRCS to simulate each U10The simulated NRCS of (1).
Compared with the prior art, the wind speed inversion method is an analysis method based on the combination of a synthetic aperture radar empirical wind inversion algorithm, a Bragg resonance scattering model and a non-Bragg scattering model, SAR wind field inversion is carried out in coastal water areas based on a microwave radar backscattering model, SAR backscattering signal items caused by wave breaking in VV and HH polarization are also contained in the theoretical model, and therefore the problem that the SAR inversion wind field using empirical GMF may have larger errors due to distortion of sea surface roughness adjusted linearly and nonlinearly in the offshore area in other dynamic processes in the offshore area in the prior art is solved, and the reliability and accuracy of offshore SAR image wind field inversion are improved.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
fig. 1 is a flowchart of an offshore wind speed inversion method based on an SAR image and a bragg scattering model according to an embodiment of the present invention;
FIG. 2 is a graph comparing simulated NRCS provided by embodiments of the present invention with observed NRCS.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Specifically, as shown in fig. 1, fig. 1 is a flow chart of a wind speed inversion method based on an SAR image and a bragg scattering model according to an embodiment of the present invention, where the method includes the following steps:
s1: acquiring a satellite-borne SAR image, and simulating Bragg resonance roughness through sea surface ocean current and discrete wind of HYCOM on the basis of a Bragg scattering theory to obtain Bragg resonance NRCS;
specifically, an original spaceborne SAR image is obtained, a composite sea surface radar backscattering model is improved on the basis of a Bragg scattering theory, and the NRCS related to the sea surface under a medium incidence angle is predicted through sea surface ocean current and discrete wind simulation Bragg resonance roughness of HYCOM together with an Elfouhaily ocean spectrum.
Dispersing the wind speed within the range of 0.2-20m/s at intervals of 0.2m/s to obtain dispersed wind, and obtaining a sea surface flow field with the space interval of 1 degree/8 and the time interval of 1 hour from an open-release HYCOM data set, wherein the dispersed wind and the sea surface ocean current data are used for calculating the Bragg resonance NRCS.
According to the microwave radar imaging mechanism, NRCS σ 0 is obtained by integrating the radar backscatter cross section (RCS) in the azimuth x and range y directions:
Figure BDA0003349119460000041
wherein:
Figure BDA0003349119460000042
Figure BDA0003349119460000043
Figure BDA0003349119460000044
Figure BDA0003349119460000045
wherein the content of the first and second substances,
Figure BDA0003349119460000046
is the bragg resonance scattering in PP polarization (VV or HH), w is the weight coefficient, Sw is the spectrum generated by empirical functions, such as the Jonswap spectrum and elfouhal spectrum, k0 is the C-band radar beam wavenumber assumed to be 5.3cm, θ is the radar angle of incidence, Φ radar elevation, T is the sea surface slope dynamically adjusted by the environment, and is divided by the radar viewing direction into the parallel p and perpendicular T directions. The above equation must satisfy the condition: 4sin2 (theta-Tp)<d2 where d is the screening threshold with a value of 0.25.
The Bragg scattering
Figure BDA0003349119460000051
Calculated from the following equation:
Figure BDA0003349119460000052
wherein:
Figure BDA0003349119460000053
Figure BDA0003349119460000054
θi＝cos-1(cos(θ-Tp)×cosTt)
wherein PP and QQ denote HH and VV polarization, respectively,. epsilonrRepresents the dielectric constant of seawater, bHHAnd bVVIs the approximate complex scattering coefficient of HH polarization and VV polarization, θiIs the effective local angle of incidence from the sea surface slope T and the radar angle of incidence.
Specifically, the sea surface slope T is determined by the sea surface elevation ζ, which is determined by the sea surface waves and currents:
Figure BDA0003349119460000055
Figure BDA0003349119460000056
in particular, the wind field is used to calculate the spectrum Sw (k, φ), which is low BLAnd high BHElfouhaily spectrum consisting of wavenumber fraction: sw(k,φ)＝Ω-3(BL+BH)G(k,φ)，
Wherein:
Figure BDA0003349119460000057
Figure BDA0003349119460000058
Figure BDA0003349119460000059
αp＝0.006Ω0.5
Figure BDA00033491194600000510
Figure BDA00033491194600000511
where Ω represents a dimensionless wind zone related to sea surface wind speed U10, c is phase velocity, c ispIs the velocity of the primary wave, FpIs a function of the long-wave induction effect, FmIs a short-wave induction effect function, alphamDetermined by short-wave equilibrium interval parameters, cmIs the lowest wave velocity, cm＝0.23，a0＝0.1733，ap＝4，
Figure BDA00033491194600000512
Is coefficient of resistance to sea surface CdAnd sea surface wind speed U10The associated friction wind speed.
S2: non-Bragg roughness simulation is carried out by measuring SAR image NRCS under polarization to obtain non-Bragg NRCS, and simulated NRCS corresponding to each discrete wind speed is obtained by combining Bragg resonance NRCS and non-Bragg NRCS;
in particular, SAR backscattering returns to NRCS, σ 0 is Bragg resonance scattering retuning of PP polarization (VV or HH)
Figure BDA0003349119460000061
And a non-Bragg component sigma caused by wave breakingwbThe sum of (a) and (b) is as follows:
Figure BDA0003349119460000062
in principle, the wave breaking contribution σwbCan pass through the same polarization
Figure BDA0003349119460000063
The difference of (a) is directly removed. Thus, the wave breaking contribution σwbCan be expressed as:
Figure BDA0003349119460000064
wherein, the rootAccording to the conventional microwave backscattering theory, at a medium incidence angle theta>Polarization ratio p of dual-scale Bragg scattering component at 20 DEGBCalculated by the following equation:
Figure BDA0003349119460000065
wherein:
Figure BDA0003349119460000066
Figure BDA0003349119460000067
wherein G isHHAnd GVVIs the polarization factor, siThe mean square slope represents the isotropic slope of the oblique wave. siAre empirically available:
Figure BDA0003349119460000068
wherein U is10Wind speed 10 m above sea surface, g is gravity acceleration, kbr2krsin θ, is related to radar wave number krCorrelated Bragg wavenumber, age beta and spectral peak wavenumber kpCalculated by the following function:
Figure BDA0003349119460000069
Figure BDA00033491194600000610
in fact, U10At 0 to 20m s-1In the range of 0.2m s-1By combining Bragg resonance NRCS and non-Bragg NRCS to simulate each U10The simulated NRCS of (1).
S3: taking the wind speed corresponding to the minimum difference between the simulated NRCS obtained by discrete wind simulation and the NRCS observed by the SAR as an inversion result to obtain an inversion wind field;
s4: and verifying the applicability of the wind speed inversion method.
Specifically, during preprocessing, the NRCS is averaged over 1 square kilometer centered on the wind observation point, which is very close to the spatial resolution of the model simulation, e.g., 1/8 ° HYCOM and 0.1 ° WW3 model. The sub-scenes extracted from the collected images were matched to the ERA-5 wind field and the HYCOM flow field, for a total of over 10000 matched sub-scenes available to confirm the applicability of the analysis method. FIG. 2 is a graph comparing simulated NRCS to observed NRCS showing a root mean square error RMSE of 2.94dB versus a correlation coefficient COR of 0.80.
Compared with the prior art, the wind speed inversion method is an analysis method based on the combination of a synthetic aperture radar empirical wind inversion algorithm, a Bragg resonance scattering model and a non-Bragg scattering model, SAR wind field inversion is carried out in coastal water areas based on a microwave radar backscattering model, SAR backscattering signal items caused by wave breaking in VV and HH polarization are also contained in the theoretical model, and therefore the problem that the SAR inversion wind field using empirical GMF may have larger errors due to distortion of sea surface roughness adjusted linearly and nonlinearly in the offshore area in other dynamic processes in the offshore area in the prior art is solved, and the reliability and accuracy of offshore SAR image wind field inversion are improved.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.

Claims (7)

1. An offshore wind speed inversion method based on SAR images and Bragg scattering models is characterized by comprising the following steps:
acquiring a satellite-borne SAR image, and simulating Bragg resonance roughness through sea surface ocean current and discrete wind of HYCOM on the basis of a Bragg scattering theory to obtain Bragg resonance NRCS;
non-Bragg roughness simulation is carried out by measuring SAR image NRCS under polarization to obtain non-Bragg NRCS, and simulated NRCS corresponding to each discrete wind speed is obtained by combining Bragg resonance NRCS and non-Bragg NRCS;
taking the wind speed corresponding to the minimum difference between the simulated NRCS obtained by discrete wind simulation and the NRCS observed by the SAR as an inversion result to obtain an inversion wind field; and
and verifying the applicability of the wind speed inversion method.
2. The offshore wind speed inversion method based on the SAR image and the bragg scattering model according to claim 1, wherein the step of obtaining the onboard SAR image, based on the bragg scattering theory, by simulating bragg resonance roughness through ocean currents on the sea surface and the discrete wind of HYCOM, to obtain the bragg resonance NRCS specifically comprises: on the basis of a Bragg scattering theory, a composite sea surface radar backscattering model is improved, and parameters such as a sea surface wind field, ocean current, an incident angle and a height angle are utilized to simulate Bragg resonance NRCS (non-resonant vibration) related to the sea surface roughness under a medium incident angle together with an Elfouhaily sea wave spectrum.
3. The method for offshore wind speed inversion based on the SAR image and the bragg scattering model according to claim 1, wherein the step of obtaining the non-bragg NRCS by performing the non-bragg roughness simulation by measuring the SAR image NRCS under polarization, and the step of obtaining the simulated NRCS corresponding to each discrete wind speed by combining the bragg resonance NRCS and the non-bragg NRCS specifically comprises: SAR backscatter Return NRCS σ 0 is Bragg resonance Scattering of PP polarization
Figure FDA0003349119450000011
And a non-Bragg component sigma caused by wave breakingwbThe formula is:
Figure FDA0003349119450000012
4. the SAR image and Bragg scattering model based offshore wind speed inversion method of claim 3, wherein the Bragg scattering model is based on a model of the wind velocity distribution
Figure FDA0003349119450000013
The calculation formula of (2) is as follows:
Figure FDA0003349119450000014
wherein:
Figure FDA0003349119450000015
Figure FDA0003349119450000021
θi＝cos-1(cos(θ-Tp)×cosTt)
wherein PP and QQ denote HH and VV polarization, respectively,. epsilonrRepresents the dielectric constant of seawater, bHHAnd bVVIs the approximate complex scattering coefficient of HH polarization and VV polarization, θiIs the effective local angle of incidence from the sea surface slope T and the radar angle of incidence.
5. The SAR image and Bragg scattering model based offshore wind speed inversion method of claim 3, wherein σ iswbThe calculation formula of (2) is as follows:
Figure FDA0003349119450000022
wherein:
Figure FDA0003349119450000023
Figure FDA0003349119450000024
wherein:
Figure FDA0003349119450000025
wherein G isHHAnd GVVIs the polarization factor, siThe mean square slope represents the isotropic slope of the oblique wave.
6. The SAR image and Bragg scattering model based offshore wind speed inversion method of claim 5, wherein s isiIs obtained empirically:
Figure FDA0003349119450000026
wherein U is10Wind speed 10 m above sea surface, g is gravity acceleration, kbr2krsin θ, is related to radar wave number krThe calculation formula of the relevant Bragg wave number and the age beta is as follows:
Figure FDA0003349119450000027
peak wave number k of spectrumpThe calculation formula of (2) is as follows:
Figure FDA0003349119450000028
7. the SAR image and Bragg scattering model based offshore wind speed inversion method of claim 6, wherein the U is10At 0 to 20m s-1In the range of 0.2m s-1By combining Bragg resonance NRCS and non-Bragg NRCS to simulate each U10The simulated NRCS of (1).
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114818385A (en) * 2022-06-16 2022-07-29 自然资源部第一海洋研究所 SAR ocean image simulation method, device and medium
CN114910661A (en) * 2022-05-13 2022-08-16 北京大学 Sea surface wind speed inversion method, device, medium and computing equipment

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114910661A (en) * 2022-05-13 2022-08-16 北京大学 Sea surface wind speed inversion method, device, medium and computing equipment
CN114910661B (en) * 2022-05-13 2023-08-04 北京大学 Sea surface wind speed inversion method, device, medium and computing equipment
CN114818385A (en) * 2022-06-16 2022-07-29 自然资源部第一海洋研究所 SAR ocean image simulation method, device and medium
CN114818385B (en) * 2022-06-16 2023-11-21 自然资源部第一海洋研究所 SAR ocean image simulation method, device and medium

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