CN104698462B - Synthetic aperture radar Ocean Wind-field fusion method based on variation - Google Patents

Abstract

The invention discloses a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation.First, choose the obvious region of SAR image apoplexy streak feature, high-precision wind direction of ocean surface is obtained using small wave converting method analysis, and then obtains ocean surface wind speed using physical geography module function inverting；Secondly, by the use of WRF pattern wind direction as the Ocean Wind-field of initial wind direction inverting SAR observation area；Last with the Ocean Wind-field based on wind striped inverting as observation field, the Ocean Wind-field based on WRF pattern wind direction inverting is ambient field, by observation field, ambient field is optimized with adjustment, the Ocean Wind-field after acquisition fusion using variational method.The invention provides a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation, solve the problems, such as that wind direction of ocean surface inverting relies on wind striped, and using variational method, the Ocean Wind-field after inverting is optimized with adjustment, improve the overall precision of regional ocean surface wind retrieving.

Description

Synthetic aperture radar Ocean Wind-field fusion method based on variation

Technical field

The invention belongs to remote sensing technology field, particularly a kind of synthetic aperture radar Ocean Wind-field fusion side based on variation Method.

Background technology

SAR (synthetic aperture radar, synthetic aperture radar, SAR) has round-the-clock, round-the-clock and high-altitude Between resolution feature, the Ocean Wind-field of high-spatial and temporal resolution can be obtained.But the single angle of incidence mechanism of SAR makes it anti- Drill and first will obtain wind direction during wind field, then calculation of wind speed.The obtaining means of wind direction have two classes, and a class is based on SAR image wind striped Inverting wind direction, the wind direction high precision that the method obtains, but count in the image showing nearly 60% and do not have obvious wind striped to be available for Inverting uses, so being difficult by the Wind-field Retrieval that wind striped carries out large area region；Another kind of is using scatterometer or numerical value Forecast Mode wind direction is as outside wind direction, and realizes Wind-field Retrieval with reference to SAR image information Wind Speed Inversion, and the method stably may be used By it is easy to carry out regional SAR ocean surface wind retrieving work, but its wind direction data spatial resolution of being provided and precision are all relatively Low it is impossible to obtain little yardstick on sea surface wind vector changing condition, also have impact on the precision of wind speed retrieval.

In air and Marine Sciences, fusion method is a lot, and being applied to wind field fusion method mainly has：Objective analyses method, progressively Correct method, B- spline method, the calculus of variations, variation with reference to regularization method, Loess low pass filtering method etc., wherein variational method Have become as the mainstream technology of current Data Assimilation, be the dominant direction of Meteorological Data Assimilation.Because wind field merges answering of problem Polygamy, with regard to Ocean Wind-field, the theoretical research merged and operational use are relatively fewer, and SAR is subject in terms of ocean surface wind retrieving To the restriction of wind striped, using the detection datas such as microwave altimeter, scatterometer and radiometer, the height of SAR data more than fusion data Resolution feature is not fully utilized.SAR image and numerical model data are worked in coordination with inverting Ocean Wind-field and are solved wind bar The problem of stricture of vagina disappearance, is carried out as the WIND FIELDS of initial wind direction by the use of high-resolution wind striped WIND FIELDS to pattern wind direction Optimize and revise, the operational use for realizing SAR high accuracy ocean surface wind retrieving provides important support.At present, for SAR sea The method that wind field merges have not been reported, it is, thus, sought for a kind of synthetic aperture radar Ocean Wind-field based on variation merges Method.

Content of the invention

It is an object of the invention to provide a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation, using change Point method is optimized adjustment to improve the overall precision of regional ocean surface wind retrieving to the Ocean Wind-field after SAR inverting.

The technical solution realizing the object of the invention is：A kind of synthetic aperture radar Ocean Wind-field based on variation merges Method, the method comprising the steps of：

A kind of synthetic aperture radar Ocean Wind-field fusion method based on variation, comprises the following steps：

Step 1, carries out experience differentiation to SAR image after calibration, SAR image is divided into the obvious region of feature and feature Fuzzy Region；(class is the obvious region of wind striped aspect ratio, and a class is free from wind striped feature or wind striped feature is fuzzyyer Region, above-mentioned classification foundation experience differentiates；)

Step 2, the obvious region of the feature described in selecting step 1, using two-dimentional Continuous Wavelet Transform inverting wind direction, and In conjunction with physical geography module function calculation of wind speed, obtain the obvious region of described feature based on wind striped inverting Ocean Wind-field；

Step 3, chooses NCEP (Environmental forecasting centre, the National matching with SAR observed image space-time Centers for Environmental Prediction) (weather is pre- to WRF pattern simulation calculating WRF for data input Report pattern, Weather Research and Forecasting Mode) wind direction, then by WRF wind direction and corresponding SAR number According to being jointly input to physical geography module function calculation of wind speed, obtain the sea based on WRF wind direction inverting for whole SAR observation areas Wind field；

Step 4, with step 2 obtain based on wind striped inverting Ocean Wind-field as observation field, with step 3 obtain base In WRF wind direction inverting Ocean Wind-field be ambient field, using variational method pass through observation field ambient field is carried out merge adjust, obtain Take the Ocean Wind-field after fusion.

Feature of present invention fuzzy region does not need to process, because the inventive method is exactly with the obvious area of feature in SAR image The domain wind field that to be the wind field that is finally inversed by of wind striped region overall to adjust the SAR image going out using WRF pattern simulation.

More preferably, step 2 specifically includes following steps,

201, two-dimentional continuous wavelet transform is carried out to the SAR image in the obvious region of wind striped feature, obtains under different scale Wavelet Energy Spectrum image,

Described two dimension Continuous Wavelet Transform is two-dimentional Mexican-hat wavelet transformation,

Described two dimension Mexican-hat wavelet transformation formula is formula (1)：

In formula：A represents the variable of two dimensional spatial frequency domain；Represent inner product of vectors, Ψ_HA () represents wavelet transformation letter Number；

202, Wavelet Energy Spectrum image is carried out with two-dimentional fast Fourier (FFT) conversion, calculates wind striped in SAR image Wave-number spectrum：

Two-dimensional fast fourier transform formula is formula (2)：

Wherein, Y is the wave-number spectrum of wind striped in SAR image, and X is image intensity value, and l, m represent that SAR image pixel is horizontal To, lengthwise position；L, m=1,2 ..., N, N are the item number after two-dimensional fast fourier transform；J, b represent SAR image pixel Location variable.

203, the line of two-dimentional wave number spectrum peak is done vertical line, described vertical line is carried out after wind direction deblurring, obtain sea surface wind To.

More preferably, geophysical model is C-band geophysical model CMOD (C-band models), described C-band ground Ball physical model function is：

σ_C(θ, φ, u)=10^A(u,θ)(1+B(u,θ)cos(φ)+C(u,θ)cos2φ) (3)

In formula, σ_CRepresent VV polarimetric radar backscattering coefficient, φ represents the relative wind direction that wind direction is with respect to radar look-directions, θ represents radar antenna angle of incidence, and u represents ocean surface wind speed；A (u, θ), B (u, θ) and C (u, θ) represent by ten meters of sea height wind Speed, the coefficient that wind direction, polarization mode, radar frequency and angle of incidence determine relatively.

More preferably, ambient field is carried out merge adjustment by observation field using variational method in step 4, obtain after merging Ocean Wind-field, specifically includes following steps：

401, the method using two-dimentional variation (2D-Var) carries out fusion calculation, the object function being defined by formula (4) Minimum enters row constraint：

J=J_q+J_m(4)

The object function J of wherein wind striped wind field_qObject function J with WRF pattern_mIt is defined as formula (5) and formula (6)：

Wherein, U and V is to merge the zonal wind obtaining and meridional wind (on region mode mesh point) respectively, q and m represents Wind striped wind field and region WRF pattern, i.e. U_q、V_qRepresent zonal wind and the meridional wind of wind striped wind field, U respectively_m、V_mTable respectively Show the zonal wind under the WRF pattern of region and meridional wind, described Q_u、Q_vRepresent the zonal wind error covariance of wind striped wind field respectively Matrix and meridional wind error co-variance matrix, M_u、M_vRepresent zonal wind error co-variance matrix and the meridional wind of WRF pattern respectively Error co-variance matrix, q and m represents wind striped wind field and region WRF pattern, H_qFor space interpolation operator, field projection will be analyzed To observation space, ()^TRepresent matrix transpose, ()^-1Represent inverse of a matrix；

402, construct space interpolation operator H using Kriging interpolation method_qIt is assumed that V_iFor i-th point in outside wind field Wind speed and direction value, i=1,2, n (n is the sum of observation station in outside wind field),It is interpolated into wind bar for outside wind field The wind speed and direction value of k-th point (observation station) on stricture of vagina wind field region, k be wind striped wind field region on k-th point (k=1, 2, K, K are observation station sum on wind striped wind field region),For i-th data, the contribution of k-th impact point is weighed Weight, order

X=(V₁,V₂,…V_n)^T,

Then：

Space interpolation operator H_qIt is expressed as formula (7),

Contribution weightObtained by Kriging equation group：

Wherein, Lagrange multiplier when μ is processed for minimization, c (x_i,x_j) it is mesh point x in outside wind field_iWith x_jIt Between covariance function, x^kFor the interpolation point on wind striped wind field region；

403 using observation more than difference method tectonic setting error co-variance matrix, background error covariance matrix be formula (9) and (10)：

＜ U_m-U_q＞²=dQ_u+dM_u(9)

＜ V_m-V_q＞²=dQ_v+dM_v(10)

Wherein ＜ ＞ represents time average, dQ_u、dM_uRepresent zonal wind error variance and the WRF mould of wind striped wind field respectively The zonal wind error variance of formula, dQ_v、dM_vRepresent the meridional wind error variance of wind striped wind field and the meridional wind of WRF pattern respectively Error variance, dQ_u、dQ_v、dM_u、dM_vRespectively with Q_u、Q_v、M_u、M_vDiagonal element consistent；

404, minimum based on object function, using variation analysis method, wind striped wind field and WRF pattern wind field are melted Close the zonal wind u and meridional wind v obtaining optimized analysis wind field.

More preferably, step 404 specifically includes following steps：

The zonal wind u of optimized analysis wind field and meridional wind v is to meet object function least commitment condition (formula after fusion (4) value is minimum) the zonal wind U that obtains of fusion and meridional wind V, that is, meet formula (11)：

Based on the calculus of variations, can obtain：

δ J, δ U, δ V are respectively the variation of J, U, V；

Using the arbitrariness of δ U, δ V, U, V meet following condition：

Thus showing that the zonal wind u and meridional wind v of optimized analysis wind field are：

Compared with prior art, the present invention includes following beneficial effect：

The invention provides a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation, for SAR data The feature of high-spatial and temporal resolution, works in coordination with inverting Ocean Wind-field using SAR image with numerical model data, solves wind striped disappearance Problem, and using variational method the Ocean Wind-field after inverting is optimized with adjustment, improves regional ocean surface wind retrieving Overall precision, the operational use for realizing SAR high accuracy ocean surface wind retrieving provides important support.

Brief description

Fig. 1 is the synthetic aperture radar Ocean Wind-field fusion method flow chart based on variation of the present invention；

Fig. 2 is data used by embodiments of the invention；

Fig. 3 (a), 3 (b) are SAR data Wind-field Retrieval images, and wherein 4 (a) is based on wind striped WIND FIELDS image 4 B () is based on WRF pattern wind direction WIND FIELDS image.

Specific embodiment

Below in conjunction with the accompanying drawings the present invention is further described.

Below with reference to the accompanying drawing of the present invention, clear, complete description is carried out to the technical scheme in the embodiment of the present invention With discussion it is clear that a part of example of the only present invention as described herein, it is not whole examples, based on the present invention In embodiment, the every other enforcement that those of ordinary skill in the art are obtained on the premise of not making creative work Example, broadly falls into protection scope of the present invention.

For the ease of the understanding to the embodiment of the present invention, make further below in conjunction with accompanying drawing taking specific embodiment as a example Illustrate, and each embodiment does not constitute the restriction to the embodiment of the present invention.

A kind of SAR Ocean Wind-field fusion method based on variation of the present invention.In conjunction with Fig. 1, comprise the following steps：

1st, Feature Selection：Experience differentiation is carried out to SAR image after calibration, SAR image is divided into the obvious region of feature and spy Levy fuzzy region；(class is the obvious region of wind striped aspect ratio, and a class is free from wind striped feature or wind striped aspect ratio Relatively fuzzy region；)

The obvious region of wind striped aspect ratio is chosen in SAR image after calibration.

2nd, the ocean surface wind retrieving based on SAR image wind striped：The obvious region of feature described in selecting step 1, utilizes two Dimension Continuous Wavelet Transform inverting wind direction, and combine physical geography module function calculation of wind speed, obtain the obvious area of described feature Domain based on wind striped inverting Ocean Wind-field；

Step 2 specifically includes following steps,

201, two-dimentional continuous wavelet transform is carried out to the SAR image in the obvious region of wind striped feature, obtains under different scale Wavelet Energy Spectrum image,

Described two dimension Continuous Wavelet Transform is two-dimentional Mexican-hat wavelet transformation,

Described two dimension Mexican-hat wavelet transformation formula is formula (1)：

In formula：A represents the variable of two dimensional spatial frequency domain；Represent inner product of vectors, Ψ_HA () represents wavelet transformation letter Number；

202, Wavelet Energy Spectrum image is carried out with two-dimentional fast Fourier (FFT) conversion, calculates wind striped in SAR image Wave-number spectrum：

Two-dimensional fast fourier transform formula is formula (2)：

Wherein, Y:For the wave-number spectrum of wind striped in SAR image, X is image intensity value, and l, m represent that SAR image pixel is horizontal To, lengthwise position；J, b represent SAR image pixel location variable.

203, the line of two-dimentional wave number spectrum peak is done vertical line, described vertical line is carried out after wind direction deblurring, obtain sea surface wind To.

More preferably, geophysical model is C-band geophysical model CMOD (C-band models), described C-band ground Ball physical model function is：

σ_C(θ, φ, u)=10^A(u,θ)(1+B(u,θ)cos(φ)+C(u,θ)cos2φ) (3)

In formula, σ_CRepresent VV polarimetric radar backscattering coefficient, φ represents the relative wind direction that wind direction is with respect to radar look-directions, θ represents radar antenna angle of incidence, and u represents ocean surface wind speed；A (u, θ), B (u, θ) and C (u, θ) represent by ten meters of sea height wind Speed, the coefficient that wind direction, polarization mode, radar frequency and angle of incidence determine relatively.

3, the ocean surface wind retrieving based on WRF wind direction：

Choose the NCEP data input matching with SAR observed image space-time to be simulated calculating WRF wind to WRF pattern To then WRF wind direction and corresponding SAR data being input to physical geography module function calculation of wind speed jointly, obtain whole SAR The Ocean Wind-field based on WRF wind direction inverting for the observation area.

4, optimize and revise Ocean Wind-field using variation fusion method：To obtain in step 2 based on wind striped inverting sea Wind field is observation field, and the Ocean Wind-field based on WRF wind direction inverting being obtained with step 3, as ambient field, is led to using variational method Cross observation field ambient field to be carried out merge adjustment, obtain the Ocean Wind-field after merging.

Ambient field is carried out merge adjustment by observation field using variational method in step 4, obtain the sea surface wind after merging , specifically include following steps：

4.1 carry out fusion calculation using the method for two-dimentional variation (2D-Var), and the object function being defined by formula (4) is Little enter row constraint：

J=J_q+J_m(4)

The object function J of wherein wind striped wind field_qObject function J with WRF pattern_mIt is defined as formula (5) and formula (6)：

Wherein, U and V is to merge the zonal wind obtaining and meridional wind (on region mode mesh point) respectively, q and m represents Wind striped wind field and region WRF pattern, i.e. U_q、V_qRepresent zonal wind and the meridional wind of wind striped wind field, U respectively_m、V_mTable respectively Show the zonal wind under the WRF pattern of region and meridional wind, described Q_u、Q_vRepresent the zonal wind error covariance of wind striped wind field respectively Matrix and meridional wind error co-variance matrix, M_u、M_vRepresent zonal wind error co-variance matrix and the meridional wind of WRF pattern respectively Error co-variance matrix, q and m represents wind striped wind field and region WRF pattern, H_qFor space interpolation operator, field projection will be analyzed To observation space, ()^TRepresent matrix transpose, ()^-1Represent inverse of a matrix；

4.2 utilize Kriging interpolation method to construct space interpolation operator H_qIt is assumed that V_iFor i-th point in outside wind field of wind Fast wind direction value, i=1,2, n,It is interpolated into (observation station) on wind striped wind field region for outside wind field at k-th point Wind speed and direction value, k be wind striped wind field region on k-th point (k=1,2, K, K represent institute on wind striped wind field region Some observation station numbers),For i-th data contribution weight to k-th impact point, order：

X=(V₁,V₂,…V_n)^T,

Then

Space interpolation operator H_qIt is expressed as formula (7),

Contribution weightObtained by Kriging equation group：

Wherein, Lagrange multiplier when μ is processed for minimization, c (x_i,x_j) it is mesh point x in outside wind field_iWith x_jIt Between covariance function, x^kFor the interpolation point on wind striped wind field region；

4.3 are taken using difference method tectonic setting error co-variance matrix more than observation, the error of the present embodiment observational data Statistical value is 1.7m/s, and background error covariance matrix is formula (9) and (10)：

＜ U_m-U_q＞²=dQ_u+dM_u(9)

＜ V_m-V_q＞²=dQ_v+dM_v(10)

Wherein ＜ ＞ represents time average, dQ_u、dM_uRepresent zonal wind error variance and the WRF mould of wind striped wind field respectively The zonal wind error variance of formula, dQ_v、dM_vRepresent the meridional wind error variance of wind striped wind field and the meridional wind of WRF pattern respectively Error variance, dQ_u、dQ_v、dM_u、dM_vRespectively with Q_u、Q_v、M_u、M_vDiagonal element consistent；

4.4 are based on object function minimum, using variation analysis method, wind striped wind field and WRF pattern wind field are merged Obtain the zonal wind u and meridional wind v of optimized analysis wind field.

The zonal wind u of optimized analysis wind field and meridional wind v is to meet object function least commitment condition (formula after fusion (4) value is minimum) the zonal wind U that obtains of fusion and meridional wind V, that is, meet formula (11)：

Based on variational method, can obtain：

Using the arbitrariness of δ U, δ V, U, V meet following condition：

Thus showing that the zonal wind u and meridional wind v of optimized analysis wind field are：

With reference to embodiment, the present invention is done into one Walk detailed description：

The flow process of the present embodiment number as shown in figure 1, the WSM imaging pattern VV of SAR data ENVISAT/ASAR used polarizes According to when detection time is 24 days 8 May in 2011, spatial resolution is 75m, and image size is 3 ° × 3 °, and image center is geographical to be sat It is designated as 56.5N, 152.5W, as shown in Figure 2；The buoy data comparing analysis use adopts the buoy observational data of NDBC offer, Float and be numbered 40678, position is 56.07N, 152.57W, the time is 7:50AM, is differed with SAR image detection time 10min.Concretely comprise the following steps：

The first step, carries out experience to SAR image after calibration and differentiates the selection obvious region of wind striped aspect ratio.As Fig. 2 Shown, white edge region is the obvious region of wind striped feature, and white point is buoy position.

Second step, using two-dimension continuous wavelet transform, to wind striped, obvious region carries out ocean surface wind retrieving, first to SAR Image carries out two-dimentional continuous N exican-hat wavelet transformation, obtains the Wavelet Energy Spectrum image under different scale, extracts wind striped Information；Then energy spectrum image is carried out with Two-dimensional FFT conversion, calculates the wave-number spectrum of wind striped in SAR image；Finally by two-dimentional ripple The line of number spectrum peak does vertical line, it is carried out obtain wind direction of ocean surface after wind direction deblurring, and combines physical geography module function Calculation of wind speed.Fig. 3 (a) is the Wind-field Retrieval result being obtained using Mexican-hat wavelet method inverting.

3rd step, outside wind direction selects the 20Km resolution WRF wind field data of 8h, identical with SAR data detection time, when Between mate the most.Carry out the segmentation of extra large land to SAR image first, and carry out gridding by 20Km resolution to image dividing, finally will WRF wind direction matches each wind field unit as initial wind direction, and calculates corresponding ocean surface wind speed using physical geography module function. Fig. 3 (b) is for SAR image by the use of WRF wind direction as the Wind-field Retrieval result of initial wind direction.

4th step, the method using two-dimentional variation (2D-Var) carries out Ocean Wind-field fusion：

(1) Kriging interpolation method is adopted to construct space interpolation operator H_q；

(2) error of this example observational data takes [Choisnard J, Laroche S.Properties of variational data assimilation for synthetic aperture radar wind retrieval[J] .Journal of Geophysical Research:Oceans (1,978 2012), 2008,113 (C5) .] statistical value 1.7m/s, then utilizes difference method tectonic setting error co-variance matrix more than observation；

(3) finally fusion is carried out to wind striped wind field and pattern wind field using variation analysis method and obtain optimized analysis wind ?.

5th step, observation field, ambient field and analysis field and buoy measured data is compared, verifies the present invention's Effectiveness, the result is as shown in table 1.

The root-mean-square error statistical nature of table 1 observation field, ambient field and analysis field

As known from Table 1, ambient field (is based on by observation field (Ocean Wind-field based on wind striped inverting) through the present invention The Ocean Wind-field of WRF pattern wind direction inverting) be optimized adjustment obtain analyze wind field, analysis wind field root-mean-square error substantially little In the root-mean-square error of Background Winds, inversion accuracy is effectively improved it was demonstrated that effectiveness of the invention.

The above is only the preferred embodiment of the present invention it should be pointed out that：Those skilled in the art are come Say, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should be regarded as Protection scope of the present invention.

Claims (5)

1. a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation is it is characterised in that comprise the following steps：

Step 1, carries out experience differentiation to SAR image after calibration, SAR image is divided into the obvious region of feature and feature Fuzzy area Domain；

Step 2, the obvious region of the feature described in selecting step 1, using two-dimentional Continuous Wavelet Transform inverting wind direction, and combine Physical geography module function calculation of wind speed, obtain the obvious region of described feature based on wind striped inverting Ocean Wind-field；

Step 3, is chosen the NCEP data input being matched with SAR observed image space-time and is simulated calculating WRF wind to WRF pattern To then WRF wind direction and corresponding SAR data being input to physical geography module function calculation of wind speed jointly, obtain whole SAR The Ocean Wind-field based on WRF wind direction inverting for the observation area；

Step 4, with step 2 obtain high-precision based on wind striped inverting Ocean Wind-field as observation field, with step 3 obtain The Ocean Wind-field based on WRF wind direction inverting be ambient field, using variational method pass through observation field ambient field is carried out merge tune Whole, obtain the Ocean Wind-field after merging.

2. a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation according to claim 1, its feature exists In, step 2 specifically includes following steps,

201, two-dimentional continuous wavelet transform is carried out to the SAR image in the obvious region of wind striped feature, obtains little under different scale Wave energy spectrogram picture,

Described two dimension Continuous Wavelet Transform is two-dimentional Mexican-hat wavelet transformation,

Described two dimension Mexican-hat wavelet transformation formula is formula (1)：

${\mathrm{\Ψ}}_H\left(a\right)=(a\·a)e^{\left(\frac{1}{2(a\·a)}\right)}---\left(1\right)$

In formula：A represents the variable of two dimensional spatial frequency domain；Represent inner product of vectors, Ψ_HA () represents wavelet transform function；

202, Wavelet Energy Spectrum image is carried out with two-dimensional fast fourier transform, calculates the wave-number spectrum of wind striped in SAR image：

Two-dimensional fast fourier transform formula is formula (2)：

$Y_{l,m}=\underset{j=1}{\overset{N}{\Σ}}\underset{b=1}{\overset{N}{\Σ}}{X}_{j,b}{e}^{-2\mathrm{\π}i(jl+bm)/N}---\left(2\right)$

Wherein, Y is the wave-number spectrum of wind striped in SAR image, and X is image intensity value, l, m=1,2 ..., N；N is quick Fu of two dimension In item number after leaf transformation；L, m represent SAR image pixel laterally, lengthwise position；J, b represent SAR image pixel laterally, Lengthwise position variable；

203, the line of two-dimentional wave number spectrum peak is done vertical line, described vertical line is carried out after wind direction deblurring, obtain wind direction of ocean surface.

3. a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation according to claim 1, its feature exists In,

Described geophysical model is C-band geophysical model CMOD5, and described C-band physical geography module function is：

σ_C(θ, φ, u)=10^A(u,θ)(1+B(u,θ)cos(φ)+C(u,θ)cos2φ) (3)

In formula, σ_CRepresent VV polarimetric radar backscattering coefficient, φ represents the relative wind direction that wind direction is with respect to radar look-directions, and θ represents Radar antenna angle of incidence, u represents ocean surface wind speed；A (u, θ), B (u, θ) and C (u, θ) represent by ten meters of sea height wind speed, phase The coefficient that wind direction, polarization mode, radar frequency and angle of incidence are determined.

4. a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation according to claim 1, its feature exists In, using variational method, fusion is carried out by observation field to ambient field in step 4 and adjust, the Ocean Wind-field after acquisition fusion, tool Body comprises the following steps：

401, fusion calculation is carried out using two-dimentional variational approach, row constraint is entered by the object function minimum that formula (4) defines：

J=J_q+J_m(4)

The object function J of wherein wind striped wind field_qObject function J with WRF pattern_mIt is defined as formula (5) and formula (6)：

$J_q=\frac{1}{2}{(H_{q}U-U_q)}^T{Q_u}^{-1}(H_{q}U-U_q)+\frac{1}{2}{(H_{q}V-V_q)}^T{Q_v}^{-1}(H_{q}V-V_q)---\left(5\right)$

$J_m=\frac{1}{2}{(U-U_m)}^T{M_u}^{-1}(U-U_m)+\frac{1}{2}{(V-V_m)}^T{M_v}^{-1}(V-V_m)---\left(6\right)$

Wherein, U and V is to merge the zonal wind obtaining and meridional wind respectively, q and m represents wind striped wind field and region WRF mould respectively Formula, i.e. U_q、V_qRepresent zonal wind and the meridional wind of wind striped wind field, U respectively_m、V_mRepresent the broadwise under the WRF pattern of region respectively Wind and meridional wind, described Q_u、Q_vRepresent zonal wind error co-variance matrix and the meridional wind error covariance of wind striped wind field respectively Matrix, M_u、M_vRepresent zonal wind error co-variance matrix and the meridional wind error co-variance matrix of WRF pattern, H respectively_qFor space Interpolation operator, analysis field is projected to observation space；

402, construct space interpolation operator H using Kriging interpolation method_qIt is assumed that V_iFor i-th point in outside wind field of wind speed Wind direction value, i=1,2, n,It is interpolated into the wind speed and wind of k-th observation station on wind striped wind field region for outside wind field To value, k is k=1 k-th point on wind striped wind field region, 2, K, K represent all of sight on wind striped wind field region Measuring point number；For i-th data contribution weight to k-th impact point, order：

$\stackrel{\‾}{Y}={({\stackrel{\‾}{V}}_1,{\stackrel{\‾}{V}}_2,...,{\stackrel{\‾}{V}}_k)}^T,$

X=(V₁,V₂,…V_n)^T,

Then：

$\stackrel{\‾}{Y}=H_{q}X$

Space interpolation operator H_qIt is expressed as formula (7),

$H_q={\left(h_i^k\right)}_{K\×N}---\left(7\right)$

Contribution weightObtained by Kriging equation group：

Wherein, Lagrange multiplier when μ is processed for minimization, c (x_i,x_j) it is mesh point x in outside wind field_iWith x_jBetween association Variance function, x^kFor the interpolation point on wind striped wind field region；

403, using observation more than difference method tectonic setting error co-variance matrix, background error covariance matrix be formula (9) and (10)：

＜ U_m-U_q＞²=dQ_u+dM_u(9)

＜ V_m-V_q＞²=dQ_v+dM_v(10)

Wherein ＜ ＞ represents time average, dQ_u、dM_uRepresent the zonal wind error variance of wind striped wind field and WRF pattern respectively Zonal wind error variance, dQ_v、dM_vRepresent the meridional wind error variance of wind striped wind field and the warp-wise wind error of WRF pattern respectively Variance, dQ_u、dQ_v、dM_u、dM_vRespectively with Q_u、Q_v、M_u、M_vDiagonal element consistent；

404, minimum based on object function, using variation analysis method, wind striped wind field and WRF pattern wind field are carried out merging Zonal wind u and meridional wind v to optimized analysis wind field.

5. a kind of synthetic aperture radar Ocean Wind-field fusion method based on variation according to claim 4, its feature exists In step 404 specifically includes following steps：

The zonal wind u of optimized analysis wind field and meridional wind v is that the fusion of object function least commitment condition after satisfaction merges obtains Zonal wind U and meridional wind V, meet formula (11)：

$\begin{array}{c}J=\frac{1}{2}{(H_{q}U-U_q)}^T{Q_u}^{-1}(H_{q}U-U_q)+\frac{1}{2}{(H_{q}V-V_q)}^T{Q_v}^{-1}(H_{q}V-V_q)+\\ \frac{1}{2}{(U-U_m)}^T{M_u}^{-1}(U-U_m)+\frac{1}{2}{(V-V_m)}^T{M_v}^{-1}(V-V_m)=\min !\end{array}---\left(11\right)$

Based on variational method, can obtain：

$\begin{array}{c}\mathrm{\δ}J=H_q^T{Q}_u^{-1}(H_{q}U-U_q)\mathrm{\δ}U+H_q^T{Q_v}^{-1}(H_{q}V-V_q)\mathrm{\δ}V+\\ {M_u}^{-1}(U-U_m)\mathrm{\δ}U+{M_v}^{-1}(V-V_m)\mathrm{\δ}V=0!\end{array}---\left(12\right)$

δ J, δ U, δ V are respectively the variation of J, U, V；

Using the arbitrariness of δ U, δ V, U, V meet following condition：

$H_q^T{Q}_u^{-1}(U_q-H_{q}U)+{M_u}^{-1}(U-U_m)=0$

$H_q^T{Q_v}^{-1}(V_q-H_{q}V)+{M_v}^{-1}(V_m-V)=0---\left(13\right)$

Thus showing that the zonal wind u and meridional wind v of optimized analysis wind field are：

$u=U={\[H_q^T{Q}_u^{-1}{H}_q+{M_u}^{-1}\]}^{-1}\[H_q^T{Q}_u^{-1}{U}_q+{M_u}^{-1}{U}_m\]$

$v=V={\[H_q^T{Q_v}^{-1}{H}_q+{M_v}^{-1}\]}^{-1}\[H_q^T{Q_v}^{-1}{V}_q+{M_v}^{-1}{V}_m\].$