Sea surface wind field inversion method and device based on small incidence angle synthetic aperture radar data

Abstract

The invention discloses a sea surface wind field inversion method and device based on small incidence angle synthetic aperture radar data, and relates to the field of ocean remote sensing and application. Calculating a C-band Bragg scattering backscattering coefficient based on a Bragg scattering geophysical model, and establishing a two-dimensional variational cost function; the two-dimensional variational cost function comprises a background item and an observation item; and carrying out iterative solution on the two-dimensional variational cost function to obtain an optimal sea surface wind field. The problems that the Bragg scattering factor is not fully considered and the existing small incident angle scattering model is not applicable in the interval of 11-20 degrees are solved.

Description

Technical Field

[0001] The present application relates to the field of marine remote sensing and applications, and particularly relates to a method and device for retrieving sea surface wind fields based on small incidence angle synthetic aperture radar data. Background Art

[0002] When the radar incidence angle is close to 0°, the sea surface scattering is mainly quasi-specular scattering. When the radar incidence angle is between 20° and 60°, the sea surface scattering is mainly Bragg scattering. After decades of iterative development, the relationship between the radar backscattering coefficient and the wind vector based on the principles of quasi-specular scattering and Bragg scattering has become mature. However, the sea surface scattering at small incidence angles (0 - 20°) is a mixture of specular scattering echoes and Bragg scattering echoes. For specular scattering, the rougher the sea surface, the weaker the radar echo; for Bragg scattering, the rougher the sea surface, the stronger the radar echo. Therefore, the small incidence angle scattering mechanism is more complex, the model construction is difficult, and there is less relevant research. Related technical personnel, based on the classical theory of sea surface specular scattering and using the Gram-Charlier sea surface slope distribution model, established a radar scattering model with an incidence angle less than 20°, which does not consider the Bragg scattering principle. Related technical personnel used the quadratic polynomial method to statistically regress the relationship between sea surface temperature, sea surface wind speed, the backscattering cross-section of the SWOT wide-swath radar altimeter, and the incidence angle (0.6 - 3.9°), and established a Ka-band sea surface wind field inversion model, which is only applicable to quasi-specular scattering and is not applicable to the incidence angle range of 4° to 20°. Related technical personnel deduced a theoretical model of sea surface microwave scattering in the incidence angle range of 0 - 80°, but problems such as weak azimuth dependence and low accuracy of the crosswind / downwind ratio have not been solved. Related technical personnel, based on the data of the Chinese-French wave spectrometer, linearly added the quasi-specular scattering and the Bragg scattering with the added wind speed and incidence angle terms to obtain an improved two-scale small incidence angle (5° - 11°) sea surface scattering model, which is not applicable to the incidence angle range of 11° to 20°.

[0003] Among the randomly selected 2000 pieces of spaceborne synthetic aperture radar data, 536 pieces contain small incidence angle (<20°) data. To make full use of the precious spaceborne synthetic aperture radar detection data, there is an urgent need for a method for retrieving the sea surface wind field of synthetic aperture radar for small incidence angles. Summary of the Invention

[0004] The purpose of the present application is to provide a method and device for retrieving sea surface wind fields based on small incidence angle synthetic aperture radar data, which solves problems such as the existing small incidence angle scattering model not fully considering the Bragg scattering factor and not being applicable in the range of 11° to 20°.

[0005] To achieve the above purpose, the present application provides the following solutions:

[0006] In a first aspect, the present application provides a method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data, including:

[0007] Calculating the C-band specular scattering backscattering coefficient based on the specular scattering two-parameter model; the input parameters of the specular scattering two-parameter model include sea surface wind speed and significant wave height;

[0008] Calculating the C-band Bragg scattering backscattering coefficient based on the Bragg scattering geophysical model; the input parameters of the Bragg scattering geophysical model include sea surface wind speed and sea surface relative wind direction;

[0009] Establishing a two-dimensional variational cost function; the two-dimensional variational cost function includes a background term and an observation term; the observation term is determined by the C-band specular scattering backscattering coefficient, the C-band Bragg scattering backscattering coefficient, and the backscattering coefficient of the observation field;

[0010] Performing iterative solution on the two-dimensional variational cost function to obtain the optimal sea surface wind field; the optimal sea surface wind field includes the optimal sea surface wind speed and the optimal sea surface wind direction.

[0011] In a second aspect, the present application provides an apparatus for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data, including:

[0012] A C-band specular scattering backscattering coefficient calculation module for calculating the C-band specular scattering backscattering coefficient based on the specular scattering two-parameter model; the input parameters of the specular scattering two-parameter model include sea surface wind speed and significant wave height;

[0013] A C-band Bragg scattering backscattering coefficient calculation module for calculating the C-band Bragg scattering backscattering coefficient based on the Bragg scattering geophysical model; the input parameters of the Bragg scattering geophysical model include sea surface wind speed and sea surface relative wind direction;

[0014] A two-dimensional variational cost function establishment module for establishing a two-dimensional variational cost function; the two-dimensional variational cost function includes a background term and an observation term; the observation term is determined by the C-band specular scattering backscattering coefficient, the C-band Bragg scattering backscattering coefficient, and the backscattering coefficient of the observation field;

[0015] A two-dimensional variational cost function iterative solution module for performing iterative solution on the two-dimensional variational cost function to obtain the optimal sea surface wind field; the optimal sea surface wind field includes the optimal sea surface wind speed and the optimal sea surface wind direction.

[0016] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data.

[0017] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above method for retrieving the sea surface wind field based on small incidence angle synthetic aperture radar data is implemented.

[0018] According to the specific embodiments provided by the present application, the following technical effects are disclosed:

[0019] The present application provides a method and device for retrieving the sea surface wind field based on small incidence angle synthetic aperture radar data. The C-band specular scattering backscattering coefficient is calculated based on the specular scattering two-parameter model, the C-band Bragg scattering backscattering coefficient is calculated based on the Bragg scattering geophysical model, and a two-dimensional variational cost function is established; the two-dimensional variational cost function includes a background term and an observation term; the two-dimensional variational cost function is iteratively solved to obtain the optimal sea surface wind field. By comprehensively considering the influence of specular scattering and Bragg scattering factors, the present application is applicable to the incidence angle range of 11° to 20°, and can cover the small incidence angle range of 0 to 20°. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 It is a schematic diagram of the radar altimeter echo waveform in the related art;

[0022] Figure 2 It is an application environment diagram of a method for retrieving the sea surface wind field based on small incidence angle synthetic aperture radar data in an embodiment of the present application;

[0023] Figure 3 It is a schematic flowchart of a method for retrieving the sea surface wind field based on small incidence angle synthetic aperture radar data provided in an embodiment of the present application;

[0024] Figure 4 It is a schematic flowchart of the standard deviation calculation provided in an embodiment of the present application;

[0025] Figure 5 It is a schematic flowchart of the optimal iterative solution of the sea surface wind field provided in an embodiment of the present application;

[0026] Figure 6 It is a schematic diagram of the functional modules of a device for retrieving the sea surface wind field by synthetic aperture radar provided in an embodiment of the present application;

[0027] Figure 7Schematic diagram of the structure of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0028] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0029] The spaceborne radar altimeter is based on the quasi-specular scattering principle. Using the sea surface as a telemetry target, it emits radar pulse signals towards the sub-satellite point to obtain the echo waveform. The schematic diagram of the ideal waveform of the radar altimeter echo is as Figure 1 shown. The distance from the satellite to the sea surface can be obtained by calculating the time of its half-power point; the slope of the rising edge is closely related to the significant wave height. The steeper the rising edge, the smaller the significant wave height; the area covered by the waveform is proportional to the backscattering coefficient. The sea surface wind speed can be retrieved through parameters such as the backscattering coefficient. Currently, from Jason-1 to Jason-CS / Sentinel-6, a two-parameter model (the conversion table between sea surface wind speed and significant wave height and the backscattering coefficient) is generally used to calculate the sea surface wind speed of the radar altimeter.

[0030] When the radar incident angle is between 20° and 60°, the sea surface scattering is mainly Bragg scattering. The spaceborne microwave scatterometer and synthetic aperture radar adopt side-looking technology and utilize the sea surface microwave Bragg scattering mechanism to establish the relationship between the radar backscattering coefficient and the sea surface wind vector. Representative geophysical models include CMOD4, CMOD5, CMOD5.N, CMOD7, etc. Among them, CMOD5.N is the geophysical model default adopted by the Sentinel series satellites (Sentinel) 1A / B.

[0031] The related technologies have problems such as the small incident angle scattering model not fully considering the Bragg scattering factor or being inapplicable in the range of 11° to 20°. To address this problem, the present application comprehensively considers the influence of specular scattering and Bragg scattering factors, constructs a new method for the objective function of the specular scattering two-parameter model and the Bragg scattering geophysical model, and finally realizes the inversion of the sea surface wind field using the small incident angle data of the synthetic aperture radar.

[0032] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0033] The method for inverting the sea surface wind field based on the small incident angle synthetic aperture radar data provided by the embodiments of the present application can be applied to, for example Figure 2In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set separately, integrated on the server 104, placed on the cloud or other servers. The terminal 102 can send a sea surface wind field inversion request to be processed to the server 104. After receiving the sea surface wind field inversion request, for the sea surface wind field inversion request, the server 104 calculates the C-band specular scattering backscattering coefficient based on the specular scattering two-parameter model, calculates the C-band Bragg scattering backscattering coefficient based on the Bragg scattering geophysical model, establishes a two-dimensional variational cost function, and iteratively solves the two-dimensional variational cost function to obtain the optimal sea surface wind field. The server 104 can feedback the obtained optimal sea surface wind field for the sea surface wind field inversion request to the terminal 102. In addition, in some embodiments, the method for inverting the sea surface wind field based on small incidence angle synthetic aperture radar data can also be implemented separately by the server 104 or the terminal 102. For example, the terminal 102 can directly perform sea surface wind field inversion for the sea surface wind field inversion request, or the server 104 can obtain the sea surface wind field inversion request from the data storage system and perform sea surface wind field inversion for the sea surface wind field inversion request.

[0034] Among them, the terminal 102 can be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0035] In an exemplary embodiment, as Figure 3 shown, a method for inverting the sea surface wind field based on small incidence angle synthetic aperture radar data is provided. This method is executed by a computer device, and can be specifically executed separately by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, taking this method applied to Figure 2 the server 104 in

[0036] Step 201, calculating the C-band specular scattering backscattering coefficient based on the specular scattering two-parameter model; the input parameters of the specular scattering two-parameter model include sea surface wind speed and significant wave height.

[0037] Step 202, calculating the C-band Bragg scattering backscattering coefficient based on the Bragg scattering geophysical model; the input parameters of the Bragg scattering geophysical model include sea surface wind speed and sea surface relative wind direction.

[0038] Step 203: Establish a two-dimensional variational cost function; the two-dimensional variational cost function includes a background term and an observation term; the observation term is determined by the C-band specular scattering backscattering coefficient, the C-band Bragg scattering backscattering coefficient, and the observation field backscattering coefficient.

[0039] Step 204: Iteratively solve the two-dimensional variational cost function to obtain an optimal sea surface wind field; the optimal sea surface wind field includes an optimal sea surface wind speed and an optimal sea surface wind direction.

[0040] By implementing the above steps 201 to 204, the present application comprehensively considers the influence of specular scattering and Bragg scattering factors, and proposes a method for retrieving the sea surface wind field with a small incident angle of synthetic aperture radar covering 0 to 20°; the present application is a new method constructed based on two mature models, namely the specular scattering two-parameter model and the Bragg scattering geophysical model, and its theoretical basis is more reliable than the prior art.

[0041] In another exemplary embodiment of the present application, let the specular scattering two-parameter model be where V is the sea surface wind speed and H is the effective wave height input externally. Convert the Ku-band specular scattering backscattering coefficient to the C-band specular scattering backscattering coefficient received by the C-band radar, that is, the specular scattering two-parameter model is expressed as follows:

[0042]

[0043] where is the C-band specular scattering backscattering coefficient, is the Ku-band specular scattering backscattering coefficient, V is the sea surface wind speed of the analysis field, H is the input effective wave height, and f jiang () represents the specular scattering two-parameter function.

[0044] Let the Bragg scattering geophysical model be:

[0045]

[0046] where is the C-band Bragg scattering backscattering coefficient generated by the radar receiving the Bragg scattering signal, φ = Φ - φ la is the relative sea surface wind direction of the analysis field, that is, the difference between the sea surface wind speed Φ of the analysis field and the viewing direction φ of the synthetic aperture radar la and θ is the incident angle, and CMOD() represents the Bragg scattering geophysical function.

[0047] Based on the two-dimensional variational idea, establish a two-dimensional variational cost function, which can be expressed by the following formula.

[0048] J(V, φ, θ) = J O (V, φ, θ, H) + J B (V, φ) (3).

[0049] Among them, J B (V, φ) is the background term (background field), and J O (V, φ, θ, H) is the observation term (observation field). When the sum J(V, φ, θ) of the background term and the observation term reaches the minimum value, the corresponding V and φ are the optimal sea surface wind speed and the optimal sea surface wind direction to be determined.

[0050] The observation term J O (V, φ, θ, H) is determined by the control variables and the backscattering coefficient of the observation field and is as shown in the following formula. (The observation term is used to calculate the observation field).

[0051]

[0052] Among them, is the backscattering coefficient of the observation field, which is obtained by measuring with a synthetic aperture radar; and are the C-band specular scattering backscattering coefficient and the C-band Bragg scattering backscattering coefficient respectively; H B is the significant wave height of the background field, and H B is input externally and is a fixed value without considering its error; and are the standard deviation of the specular scattering backscattering coefficient and the standard deviation of the Bragg scattering backscattering coefficient respectively.

[0053] Among them, J B (V, φ) is the background term (used to calculate the background field), and the expression is:

[0054]

[0055] Among them, V B is the wind speed of the background field, φ B is the wind direction of the background field, ΔV B and Δφ B are the standard deviation of the wind speed of the background field and the standard deviation of the wind direction of the background field respectively.

[0056] (1) The determination process of the standard deviation of the specular scattering backscattering coefficient specifically includes the following steps 301 to 304.

[0057] Step 301: Obtain the first spatio-temporal matching historical data set; the first spatio-temporal matching historical data set includes several groups of first input parameters; the first input parameters include historical sea surface wind speed and historical significant wave height.

[0058] Step 302: For each set of first input parameters, based on the specular scattering two-parameter model, calculate the C-band specular scattering backscattering coefficient corresponding to the first input parameter according to the first input parameter.

[0059] Step 303: Calculate the mean value of the specular scattering backscattering coefficient according to the C-band specular scattering backscattering coefficients corresponding to all the first input parameters.

[0060] Step 304: Calculate the standard deviation of the specular scattering backscattering coefficient according to the mean value of the specular scattering backscattering coefficient and the C-band specular scattering backscattering coefficients corresponding to all the first input parameters.

[0061] (2) The determination process of the standard deviation of the Bragg scattering backscattering coefficient specifically includes the following steps 401 to 404.

[0062] Step 401: Obtain a second spatio-temporal matching historical data set; the second spatio-temporal matching historical data set includes several groups of second input parameters; the second input parameters include historical sea surface wind speed, historical sea surface wind direction, and incident angle.

[0063] Step 402: For each set of second input parameters, based on the Bragg scattering geophysical model, calculate the C-band Bragg scattering backscattering coefficient corresponding to the second input parameter according to the second input parameter.

[0064] Step 403: Calculate the mean value of the Bragg scattering backscattering coefficient according to the C-band Bragg scattering backscattering coefficients corresponding to all the second input parameters.

[0065] Step 404: Calculate the standard deviation of the Bragg scattering backscattering coefficient according to the mean value of the Bragg scattering backscattering coefficient and the C-band Bragg scattering backscattering coefficients corresponding to all the second input parameters.

[0066] As Figure 4 shown, collect spatio-temporally matched European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis sea surface wind vector data and significant wave height data, as well as synthetic aperture radar backscattering coefficient and incident angle data, and establish a matching data set. Denote the data including several groups of first input parameters as the first spatio-temporal matching historical data set, and denote the data including several groups of second input parameters as the second spatio-temporal matching historical data set.

[0067] When calculating the standard deviation of the specular scattering backscattering coefficient, using formula (1), calculate the C-band specular scattering backscattering coefficient corresponding to each first input parameter in the first spatio-temporal matching historical dataset according to the first input parameter where \(i = 1, 2,\cdots, N\), \(N\) is the number of sea surface wind speeds in the analysis field and also the number of first input parameters; then based on the C-band specular scattering backscattering coefficients corresponding to all first input parameters calculate the mean value of the specular scattering backscattering coefficient The calculation formula is According to the mean value of the specular scattering backscattering coefficient obtained from the above calculation and the specular scattering backscattering coefficients corresponding to all first input parameters calculate the standard deviation of the specular scattering backscattering coefficient

[0068] When calculating the standard deviation of the Bragg scattering backscattering coefficient, using formula (2), calculate the C-band Bragg scattering backscattering coefficient corresponding to each second input parameter in the second spatio-temporal matching historical dataset according to the second input parameter where \(i = 1, 2,\cdots, N\), where \(N\) is the number of first input parameters; then calculate the mean value of the Bragg scattering backscattering coefficient according to the C-band Bragg scattering backscattering coefficients corresponding to all second input parameters The calculation formula is According to the mean value of the Bragg scattering backscattering coefficient obtained from the above calculation and the C-band Bragg scattering backscattering coefficients corresponding to all second input parameters, calculate the standard deviation of the Bragg scattering backscattering coefficient The calculation formula is

[0069] When calculating the standard deviation of the background field wind speed and the standard deviation of the background field wind direction, convert the ERA5 reanalysis sea surface wind vector (as the background field) data \((u Bi , v Bi ) to the background sea surface wind speed and the background sea surface wind direction \((V Bi , \varphi Bi ), where \(i = 1, 2,\cdots, N\), where \(N\) is the number of background sea surface wind speed and background sea surface wind direction data; calculate the mean value of the background field sea surface wind speed and the mean value of the background field sea surface wind direction According to the mean value of the background field sea surface wind speed and the background sea surface wind speed data, calculate the standard deviation of the background field wind speed According to the mean value of the background field sea surface wind direction and the background sea surface wind direction data, calculate the standard deviation of the background field wind direction

[0070] Substituting formulas (4) and (5) into formula (3), the following formula can be obtained, that is, the specific expression of the two-dimensional variational cost function:

[0071]

[0072] In another exemplary embodiment of the present application, step 204 specifically includes: using the enumeration method to iteratively solve the two-dimensional variational cost function to obtain the optimal sea surface wind field.

[0073] By iterating through methods such as the enumeration method to minimize the above two-dimensional variational cost function, the optimal sea surface wind speed and sea surface wind direction (V, φ) solution of the synthetic aperture radar with a small incident angle can be obtained, that is, the optimal sea surface wind field.

[0074] As Figure 5 shown, the specific process of the optimal iterative solution of the sea surface wind field is as follows:

[0075] Let the analysis field wind speed be V i =[0.1, 0.2,......, 29.9, 30] m / s, a total of 300 groups, that is, i = 1, 2, 3... 300; the analysis field wind direction is φ j =[0, 0.1, 0.2,......, 359.8, 359.9]°, a total of 3600 groups, that is, j = 1, 2, 3... 3600;

[0076] First step, extract the backscattering coefficient and the incident angle θ of the synthetic aperture radar observation field as the observation field, and extract the sea surface wind speed, sea surface wind direction and significant wave height forecast results obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) that is spatio-temporally matched with the synthetic aperture radar as the background field, which are respectively denoted as the background field wind speed V B , the background field wind direction φ B and the background field significant wave height H B ;

[0077] Second step, substitute the i-th analysis field sea surface wind speed V i and the background field significant wave height H B into the specular scattering two-parameter model (i.e., formula (1)) to obtain the C-band specular scattering backscattering coefficient i calculated based on the i-th analysis field sea surface wind speed V

[0078] Third step, substitute the i-th analysis field sea surface wind speed V i , the j-th analysis field sea surface relative wind direction φ jand the incident angle θ into the Bragg scattering geophysical model (i.e., Equation (2)) to obtain the sea surface wind speed V of the i-th analysis field i and the relative sea surface wind direction φ of the j-th analysis field j The C-band Bragg scattering backscattering coefficient generated by the calculated Bragg scattering

[0079] Fourthly, substitute the C-band specular scattering backscattering coefficient C-band Bragg scattering backscattering coefficient Observation field backscattering coefficient Standard deviation of specular scattering backscattering coefficient and the standard deviation of Bragg scattering backscattering coefficient into the expression of the observation term (i.e., Equation (4)) to obtain the observation field J O (i,j);

[0080] Fifthly, substitute the sea surface wind speed V of the analysis field i , the relative sea surface wind direction φ of the analysis field j , the wind speed V of the background field B , the wind direction φ of the background field B , the standard deviation of the wind speed ΔV of the background field B and the standard deviation of the wind direction Δφ of the background field B into the expression of the background term (i.e., Equation (5)) to obtain the background field J B (i,j);

[0081] Sixthly, substitute the observation field J O (i,j) and the background field J B (i,j) into the two-dimensional variational cost function (i.e., Equation (3)) to obtain the cost value J(i,j);

[0082] Seventhly, calculate the minimum value of the cost value J(i,j). The sea surface wind speed V of the analysis field corresponding to the minimum value of the cost value J(i,j) i and the relative sea surface wind direction φ of the analysis field j are the optimal sea surface wind fields.

[0083] The present application also provides an application scenario, which applies the above method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data. Specifically: The method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data provided in this embodiment can be applied to the sea surface wind field retrieval scenario. The sea surface wind field retrieval scenario includes a request generation link and a sea surface wind field retrieval processing link; the sea surface wind field retrieval request enters the sea surface wind field retrieval processing link from the request generation link, and the corresponding optimal sea surface wind field is obtained through a human-machine collaboration method. The method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data provided in this embodiment belongs to the sea surface wind field retrieval processing link. Specifically, in the process of the sea surface wind field retrieval processing link for the sea surface wind field retrieval request, the C-band specular scattering backscattering coefficient can be calculated based on the specular scattering two-parameter model, the C-band Bragg scattering backscattering coefficient can be calculated based on the Bragg scattering geophysical model, a two-dimensional variational cost function can be established, and the two-dimensional variational cost function can be iteratively solved to obtain the optimal sea surface wind field.

[0084] Based on the same inventive concept, the embodiments of the present application also provide a device for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data for implementing the above-mentioned method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data. The solution provided by the device for solving the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the device for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data provided below can refer to the limitations on the method for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data in the above text, and will not be repeated here.

[0085] In an exemplary embodiment, as Figure 6 shown, a device for retrieving sea surface wind field based on small incidence angle synthetic aperture radar data is provided, including:

[0086] A C-band specular scattering backscattering coefficient calculation module T1, configured to calculate the C-band specular scattering backscattering coefficient based on the specular scattering two-parameter model; the input parameters of the specular scattering two-parameter model include sea surface wind speed and significant wave height;

[0087] A C-band Bragg scattering backscattering coefficient calculation module T2, configured to calculate the C-band Bragg scattering backscattering coefficient based on the Bragg scattering geophysical model; the input parameters of the Bragg scattering geophysical model include sea surface wind speed and sea surface relative wind direction;

[0088] A two-dimensional variational cost function establishment module T3, configured to establish a two-dimensional variational cost function; the two-dimensional variational cost function includes a background term and an observation term; the observation term is determined by the C-band specular scattering backscattering coefficient, the C-band Bragg scattering backscattering coefficient, and the observation field backscattering coefficient;

[0089] The two-dimensional variational cost function iterative solution module T4 is used to iteratively solve the two-dimensional variational cost function to obtain the optimal sea surface wind field; the optimal sea surface wind field includes the optimal sea surface wind speed and the optimal sea surface wind direction.

[0090] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 7 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store sea surface wind field inversion data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a method for inverting the sea surface wind field based on synthetic aperture radar data with a small incident angle.

[0091] Those skilled in the art can understand that Figure 7 the structure shown in

[0092] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0093] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0094] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0095] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0096] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0097] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0098] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The descriptions of the above embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A method for inverting sea surface wind field based on small incident angle synthetic aperture radar data, characterized in that: The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data includes: Calculating the C-band specular scattering backscattering coefficient based on a specular scattering dual-parameter model; the input parameters of the specular scattering dual-parameter model include sea surface wind speed and significant wave height; Calculating the C-band Bragg scattering backscattering coefficient based on a Bragg scattering geophysical model; the input parameters of the Bragg scattering geophysical model include sea surface wind speed and sea surface relative wind direction; Establishing a two-dimensional variational cost function; the two-dimensional variational cost function includes a background term and an observation term; the observation term is determined by a C-band specular scattering backscattering coefficient, a C-band Bragg scattering backscattering coefficient, and an observation field backscattering coefficient; The two-dimensional variational cost function is iteratively solved to obtain an optimal sea surface wind field; the optimal sea surface wind field includes an optimal sea surface wind speed and an optimal sea surface wind direction.

2. The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data according to claim 1 is characterized in that: The specular scattering two-parameter model is expressed as follows: in, is the C-band specular backscattering coefficient, is the Ku-band specular backscattering coefficient, V is the sea surface wind speed in the analysis field, H is the input significant wave height, and f jiang () represents a two-parameter function of specular scattering.

3. The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data according to claim 1 is characterized in that: The Bragg scattering geophysical model is expressed as follows: in, is the C-band Bragg scattering backscattering coefficient, V is the sea surface wind speed in the analysis field, φ=Φ-φ la is the relative wind direction on the sea surface in the analysis field, Φ is the wind speed on the sea surface in the analysis field, φ la is the SAR line of sight, θ is the incident angle, and CMOD() represents the Bragg scattering geophysical function.

4. The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data according to claim 1 is characterized in that: The expression of the background term is: Among them, J B (V,φ) is the background term, V B is the background wind speed, φ B is the background wind direction, V is the sea surface wind speed in the analysis field, φ=Φ-φ la is the relative wind direction on the sea surface in the analysis field, Φ is the wind speed on the sea surface in the analysis field, φ la is the synthetic aperture radar line of sight, ΔV B and Δφ B They are the standard deviation of background wind speed and background wind direction, respectively.

5. The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data according to claim 1 is characterized in that: The expression of the observation term is: Among them, J O (V,φ,θ,H B ) is the observation item, is the backscattering coefficient of the observation field, and are the C-band specular scattering backscattering coefficient and the C-band Bragg scattering backscattering coefficient, respectively, H B is the effective wave height of the background field, V is the sea surface wind speed of the analysis field, φ=Φ-φ la is the relative wind direction on the sea surface in the analysis field, Φ is the wind speed on the sea surface in the analysis field, φ la is the SAR viewing direction, θ is the incident angle, and are the standard deviation of the specular scattering backscattering coefficient and the standard deviation of the Bragg scattering backscattering coefficient, respectively.

6. The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data according to claim 5 is characterized in that: The process of determining the standard deviation of the specular backscatter coefficient includes: Acquire a first spatiotemporal matching historical data set; the first spatiotemporal matching historical data set includes a plurality of groups of first input parameters; the first input parameters include historical sea surface wind speed and historical significant wave height; For each group of first input parameters, based on the specular scattering two-parameter model, calculating the C-band specular scattering backscattering coefficient corresponding to the first input parameter according to the first input parameter; Calculate the mean value of the specular backscattering coefficient according to the C-band specular backscattering coefficients corresponding to all the first input parameters; Calculating a standard deviation of the specular scattering backscattering coefficient according to the mean value of the specular scattering backscattering coefficient and the C-band specular scattering backscattering coefficients corresponding to all the first input parameters; The process of determining the standard deviation of the Bragg scattering backscattering coefficient includes: Acquire a second spatiotemporal matching historical data set; the second spatiotemporal matching historical data set includes a plurality of sets of second input parameters; the second input parameters include historical sea surface wind speed, historical sea surface wind direction and incident angle; For each set of second input parameters, based on a Bragg scattering geophysical model, calculating a C-band Bragg scattering backscattering coefficient corresponding to the second input parameters according to the second input parameters; Calculating a mean value of the Bragg scattering backscattering coefficient according to the C-band Bragg scattering backscattering coefficients corresponding to all the second input parameters; The standard deviation of the Bragg scattering backscattering coefficient is calculated according to the mean value of the Bragg scattering backscattering coefficient and all the C-band Bragg scattering backscattering coefficients corresponding to the second input parameters.

7. The method for inverting sea surface wind field based on small incident angle synthetic aperture radar data according to claim 1 is characterized in that: The two-dimensional variational cost function is iteratively solved to obtain the optimal sea surface wind field, specifically including: The two-dimensional variational cost function is iteratively solved by using an enumeration method to obtain the optimal sea surface wind field.

8. A device for inverting sea surface wind field based on small incident angle synthetic aperture radar data, characterized in that: The device for inverting sea surface wind field based on small incident angle synthetic aperture radar data comprises: A C-band specular scattering backscattering coefficient calculation module, used to calculate the C-band specular scattering backscattering coefficient based on a specular scattering dual-parameter model; the input parameters of the specular scattering dual-parameter model include sea surface wind speed and significant wave height; A C-band Bragg scattering backscattering coefficient calculation module, used to calculate the C-band Bragg scattering backscattering coefficient based on a Bragg scattering geophysical model; the input parameters of the Bragg scattering geophysical model include sea surface wind speed and sea surface relative wind direction; A two-dimensional variational cost function establishment module, used to establish a two-dimensional variational cost function; the two-dimensional variational cost function includes a background term and an observation term; the observation term is determined by a C-band specular scattering backscattering coefficient, a C-band Bragg scattering backscattering coefficient, and an observation field backscattering coefficient; The two-dimensional variational cost function iterative solution module is used to iteratively solve the two-dimensional variational cost function to obtain an optimal sea surface wind field; the optimal sea surface wind field includes an optimal sea surface wind speed and an optimal sea surface wind direction.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for inverting sea surface wind field based on small-incident-angle synthetic aperture radar data as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for inverting sea surface wind field based on small-incident-angle synthetic aperture radar data described in any one of claims 1 to 7 is implemented.

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