Sea surface imaging simulation method for variable beam SAR (Synthetic Aperture Radar) region of interest

Abstract

The invention discloses a sea surface imaging simulation method for a variable-beam SAR (Synthetic Aperture Radar) region of interest, and belongs to the technical field of radar signal simulation processing. In order to solve the problem of improving the simulation degree of echo signal simulation, the method comprises the following steps: constructing a coastal zone sea surface motion model; constructing a Kirchhoff mirror reflection model; constructing a Bragg resonance scattering model; the method comprises the following steps of: performing echo analogue simulation on a variable-beam SAR sea surface, namely updating a space-variant scattering grid by using a coastal zone sea surface motion model, performing instantaneous sea surface motion state updating, and calculating back scattering intensity of each scattering surface element in a time domain by using a Kirchhoff mirror reflection model and a Bragg resonance scattering model; and then calculating a space-variant azimuth two-way directional diagram at each distance unit for the scattering surface elements at the same azimuth position, weighting echoes of each scattering surface element, and traversing non-uniform sampling time to obtain an echo matrix of the variable-beam high-resolution wide-width SAR. According to the method, the simulation degree of echo signal simulation can be remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar signal simulation processing, and particularly relates to a simulation method for imaging the sea surface in the region of interest of a variable-beam SAR. Background Art

[0002] Spaceborne synthetic aperture radar (SAR), as a high two-dimensional resolution, active microwave sensor, has unique advantages in coastal zone remote sensing. Compared with land-based fixed monitoring equipment and sea-based buoy platforms, spaceborne SAR has a larger coverage area. Spaceborne SAR generally operates in a near-polar orbit and can achieve global coverage of the coastal zone by relying on the movement of the platform along the orbit. In contrast, land-based and buoy platforms can only observe and record a limited area, and expanding the observation range would require a large increase in the number of sensors, resulting in high costs. Among spaceborne platforms, compared with passive microwave radiometers and ocean color remote sensors in the visible and hyperspectral bands, spaceborne SAR mostly operates in the L to X band and has the ability to penetrate clouds, being unaffected by the weather conditions above. It can continuously conduct remote sensing detection of the coastal zone area all day and all weather, avoiding data gaps and missing data. Compared with other active sensors, such as microwave altimeters and microwave scatterometers, spaceborne SAR has two-dimensional imaging capabilities in both the azimuth and range directions. Compared with other active microwave sensors with only one-dimensional observation capabilities, the information obtained in a single pass is more abundant.

[0003] Coastal zone sudden disasters spread quickly and have a wide impact range, requiring flexible high-resolution wide-swath imaging capabilities for timely monitoring. The coastal zone is characterized by a wide swath and is not parallel to the satellite orbit. However, most of the existing spaceborne SAR high-resolution wide-swath imaging modes are based on the forward-looking stripmap configuration, where the imaging strip is parallel to the satellite orbit. At a constant orbital altitude, the effective observation range of spaceborne SAR depends on the nadir angle. Since the coastal zone extends from the coastline towards the land and sea on both sides, with a width of over 300 km on the ocean side and up to 100 km on the land side, and the coastal zone trend often not being parallel to the satellite orbit, it is difficult for forward-looking stripmap high-resolution wide-swath SAR to cover the entire coastal zone area in a single pass and can only splice images based on time-discontinuous data from multiple passes. The variable-beam stripmap high-resolution wide-swath SAR can flexibly adjust the azimuth and elevation pointing of the beam, making the imaging strip no longer parallel to the satellite orbit but matching the region of interest. It can make full use of the effective nadir angle range of the satellite according to the actual observation requirements. While avoiding the time discontinuity caused by repeat-pass observations, it can also increase the effective observation number of the region of interest. In addition, the flexible imaging geometry of the variable-beam stripmap high-resolution wide-swath SAR makes the distribution method of the effective swath more reasonable and can increase the information acquisition tolerance of the region of interest. Therefore, the variable-beam high-resolution wide-swath SAR has important research significance in the field of sea surface monitoring for the region of interest.

[0004] The imaging principle of spaceborne SAR for various ocean phenomena is mainly based on the change of sea surface roughness caused by sea surface motion. Compared with the static sea surface, the rough sea surface can reflect part of the incident radar wave energy back to the SAR receiver, thus showing corresponding brightness changes in the SAR image. In addition to the amplitude change of the SAR image caused by the change of sea surface roughness, the radar echo of the spaceborne SAR irradiating the moving sea surface contains the Doppler shift caused by the sea water motion. By extracting the Doppler phase information in the SAR image, the motion parameters of the sea surface can be inverted, and the motion state of the sea surface can be quantitatively analyzed. Compared with the microwave scatterometer, the spaceborne SAR image has the ability of high-resolution two-dimensional imaging. The SAR image of the ocean surface is affected by various factors, such as the ocean surface wind field, ocean current, ocean front, climate front, etc. It is necessary to analyze and model the imaging mechanism and imaging parameters of various factors in the SAR image, and study the spatial and temporal variation phenomena presented between the amplitude and phase of each factor component in the SAR image, so as to identify and classify various ocean phenomena and invert the parameters.

[0005] Sea surface echo modeling is a key technology for analyzing the imaging performance of spaceborne SAR in the coastal zone. The existing spaceborne SAR echo models can be divided into two key links: dynamic sea surface modeling, where the beam domain direction spectrum on the sea surface corresponds to the height field and normal direction of each scattering surface element; radar backscattering model, which establishes an empirical model according to the microwave scattering mechanism to analyze the backscattering components under different scattering mechanisms, such as specular reflection component, Bragg resonance scattering component, breaking wave scattering component, higher-order reflection component, etc. Finally, the backscattering intensity of each sea surface scattering surface element is mapped to the slant range coordinate system to generate the corresponding radar echo. In the variable beam strip SAR observation configuration, the antenna beam points to the strip area that is not parallel to the satellite orbit. The small facets corresponding to the range scattering grid are severely distorted with the azimuth position, and there is non-uniform sampling in the azimuth direction, which is a new problem that does not exist in the ortho-view imaging geometry. Summary of the Invention

[0006] The problem to be solved by the present invention is based on the problem that the range scattering grid facets are severely distorted with the azimuth position and there is non-uniform sampling in the azimuth direction in the variable beam strip SAR observation configuration in the existing sea surface echo simulation method. In order to improve the fidelity of the echo signal simulation, a sea surface imaging simulation method for the region of interest of variable beam SAR is proposed.

[0007] To achieve the above object, the present invention is realized through the following technical solutions:

[0008] A sea surface imaging simulation method for the region of interest of variable beam SAR includes the following steps:

[0009] S1. Construct a coastal sea surface motion model, including physical ocean equations and Elfouhaily wave spectrum;

[0010] S2. Construct the Kirchhoff specular reflection model, including constructing the target scattering electric field, the central scattering intensity of the scattering surface element, and the specular scattering component of the scattering surface element;

[0011] S3. Construct the Bragg resonance scattering model, including constructing the Bragg scattering component of the sea surface element, establishing a numerical model for the sea surface height spectrum, and calculating the instantaneous slant range of the scattering surface element;

[0012] S4. Based on the models constructed in steps S1 - S3, perform echo simulation on the variable - beam SAR sea surface, including updating the spatially variant scattering grid using the coastal sea surface motion model obtained in step S1 and updating the instantaneous sea surface motion state, calculating the backscattering intensity of each scattering surface element in the time domain using the Kirchhoff specular reflection model obtained in step S2 and the Bragg resonance scattering model obtained in step S3, then calculating the spatially variant azimuth - two - way pattern at each range cell for the scattering surface elements at the same azimuth position, weighting the echoes of each scattering surface element, and then traversing the non - uniformly sampled time to obtain the echo matrix of the variable - beam high - resolution wide - swath SAR.

[0013] Further, the specific implementation method of step S1 includes the following steps:

[0014] S1.1. Based on the one - dimensional approximate solution of the physical ocean equation, assume that the coordinates of a point on the sea surface are \(x=(x,y)\), the height \(z = 0\), \(x\) is the coordinate point on the \(x\) - axis, and \(y\) is the coordinate point on the \(y\) - axis. When a single - frequency ocean wave passes through a point on the sea surface, the expressions for the vertical motion vector \(\xi(x,t)\) and the horizontal motion vector \(D(x,t)\) of the point on the sea surface are:

[0015]

[0016] where, \(\varphi\) i is the initial phase of the \(i\) - th ocean wave, \(k\) i is the wave vector of the \(i\) - th ocean wave, \(k\) i is the wave number, \(\omega\) i is the frequency of the \(i\) - th ocean wave, \(t\) is the time, \(A\) i is the amplitude of the \(i\) - th ocean wave, and \(N\) is the total number of ocean waves;

[0017] \(k\) i =\(\vert\vert k\) i \vert\vert = 2\pi / \lambda\)

[0018] where, \(\lambda\) is the wavelength;

[0019] S1.2. Set the open - boundary sea surface as a linear superposition of a finite number of plane waves, where \(A\) i and \(k\) i are independent of the sea - surface position, \(\varphi\) iIf the independent cuts are uniformly distributed in the interval [0, 2π), then the mean value <ζ(x,t)> of the vertical motion vector of the points on the sea surface is 0, and the variance of the vertical motion vector of the points on the sea surface is

[0020] S1.3. Based on the fact that the sea surface wave is the superposition of an infinite number of plane waves, transform the variance of the vertical motion vector of the points on the sea surface into an integral form, and the expression is:

[0021]

[0022] where Ψ(k) and Ψ(k,θ) are the sea surface directional spectrum in the Cartesian coordinate system and the sea surface directional spectrum in the polar coordinate system respectively, and θ is the propagation direction of the beam;

[0023] S1.4. Divide the sea surface directional spectrum in the polar coordinate system into two components, including the sea wave spectrum S(k) and the angular spread function Φ(k,θ), and the expression is:

[0024]

[0025] Then define the sea wave spectrum as the Elfouhaily sea wave spectrum, and the expression is:

[0026] S(k) = k -3 [B l +B h (4)

[0027] where B l and B h represent the long sea wave curvature spectrum and the short sea wave curvature spectrum respectively;

[0028] S1.5. B l is defined as follows:

[0029]

[0030] where c p is the wave phase velocity of the spectral peak, c p = c(k p ), k p is the spectral peak wave number, α p is the long wave equilibrium parameter, F p is the long wave action function, and c is the phase velocity corresponding to the current beam;

[0031]

[0032] where Ω is a dimensionless parameter used to adjust the attenuation rate of the exponential term, Ω = U 10 / c p , U 10 is the wind speed at 10m above the sea surface, LPM , J p are the peak enhancement functions of the PM spectrum and JONSWAP, respectively;

[0033] L PM , J p are defined as follows:

[0034]

[0035] where γ is the peak enhancement factor, Γ is the Gaussian weight function, and σ is the spectral width parameter;

[0036] S1.6.B h is defined as follows:

[0037]

[0038] where c m is the phase velocity corresponding to the minimum wave number, F m and α m are the first dimensionless parameter and the second dimensionless parameter;

[0039]

[0040] where u * is the friction velocity of the sea surface;

[0041] The definition of the angular spreading function Φ(k,θ) is as follows:

[0042]

[0043] where Δ(k) is the upwind - crosswind ratio, used to describe the directionality of ocean waves with different wavelengths;

[0044] Δ(k) is defined as:

[0045] Δ(k) = tanh{a 0 + a p (c / c p ) 2.5 + a m (c m / c) 2.5} (12)

[0046] where a 0 is the first constant, and a p , a m are the parameters corresponding to U 10 / c p , u * / c m respectively.

[0047] Further, the specific implementation method of step S2 includes the following steps:

[0048] S2.1. Set the applicable conditions of the Kirchhoff specular reflection model as:

[0049] (k 0 r c ) 1 / 3 cosθ >> 1 (13)

[0050] where r c is the radius of the curved surface;

[0051] S2.2. Set the expression of the target scattering electric field E s constructed based on the Kirchhoff specular reflection model as:

[0052]

[0053] where K s is the central scattering intensity of the scattering surface element, p is the distribution function, k s is the scattering signal wave number of the scattering surface element, is the specular scattering component of the scattering surface element, S is the integral of the sea surface over the scattering surface element, and j is the imaginary unit;

[0054] The expression of p is as follows:

[0055]

[0056] where × represents the vector cross product, E is the electric field in the propagation medium, is the unit vector of the surface normal of the scattering surface element, H is the magnetic field in the propagation medium, and η is the dielectric constant of the medium;

[0057] The expression of K s is as follows:

[0058]

[0059] where R s is the distance between the center of the illumination area and the incident point;

[0060] The expression of

[0061]

[0062] where φ s is the azimuth angle, θ s is the elevation angle, represents the vectors in the three directions of the rectangular coordinate system;

[0063] S2.3. Assume that the incident wave is a spherical wave, then the incident field strength Εinc The expression is as follows:

[0064]

[0065] where R inc is the distance from the irradiation source to the scattering center, is the unit vector of the polarization direction of the incident wave, is the unit vector in the incident direction;

[0066]

[0067] The normalized scattering intensity has the following expression:

[0068]

[0069] where pq represents the polarization modes of the incident and scattered waves, and <·> represents taking the average.

[0070] Furthermore, the specific implementation method of step S3 includes the following steps:

[0071] S3.1. Construct the Bragg scattering component of the sea surface element according to the Bragg resonance scattering model The expression is:

[0072]

[0073] where Ψ(k) is the sea surface height spectrum, k 0 is the radar wave number (appeared in 2.1), k b is the Bragg wave number vector, s p is the tilt angle parallel to the line of sight, s n is the tilt angle perpendicular to the line of sight, θ l is the equivalent incident angle at the small facet and θ l = arccos[cos(θ - s p ) cos s n , b pp is the complex scattering coefficient of horizontal polarization, b qq is the complex scattering coefficient of vertical polarization;

[0074] The amplitude and direction are defined as follows respectively:

[0075]

[0076] where φ 0 is the radar azimuth angle, k b is the Bragg wave number, φ b is the Bragg beam direction;

[0077] Then, correct the Bragg scattering component of the sea surface element with respect to the equivalent scattering coefficient of the radar to obtain the expression:

[0078]

[0079] Among them, H 0 is the height of the radar relative to the sea level, and ζ is the height of the small surface element;

[0080] S3.2. Establish a numerical model for the sea surface height spectrum. The expression of the omnidirectional spectrum S(k) is as follows:

[0081]

[0082] Among them, P L is a function of the wind speed, U n is the reference wind speed of the sea surface, and W H is the correction function in the high-frequency band;

[0083] Model the low wavenumber roll-off and the peak of JONSWAP. The expression is as follows:

[0084]

[0085] Among them, g is the acceleration due to gravity;

[0086] W H Model the Bragg wave. The expression is as follows:

[0087]

[0088] Among them, k 6 = 280 rad / m, k 7 = 75 rad / m, k 8 = 1300 rad / m, k 9 = 8885 rad / m;

[0089] U n = 1 m / s, and β is the corresponding wind force index. The expression is:

[0090]

[0091] Among them, k 1 = 183 rad / m, k 2 = 3333 rad / m, k 3 = 33 rad / m, k 4 = 140 rad / m, k 5 = 220 rad / m;

[0092] The diffusion function obtained is:

[0093]

[0094] Among them, δ is the distribution width control parameter;

[0095]

[0096] Among them, c 1 = 400 rad / m, U n = 1 m / s, k n = 1 rad / m.

[0097] Furthermore, the specific implementation method of step S4 includes the following steps:

[0098] S4.1. Input radar and sea surface simulation parameters:

[0099] According to the simulated scenario, set the radar parameters and sea surface environment parameters. The radar parameters include center frequency, pulse width, signal bandwidth, sampling frequency, orbital altitude, azimuth resolution, center depression angle, variable beam strip angle, antenna type and antenna size, antenna beam width; the sea surface environment parameters include sea surface area size, wind speed and wind direction;

[0100] S4.2. Generation of range-dependent scattering grid in the ground range coordinate system:

[0101] Define the ground range coordinate system using a rectangular coordinate system, set the range-dependent scattering grid step size to satisfy the Nyquist sampling theorem, and generate a set of range-dependent scattering grid points for scattering calculation and sea wave dynamic simulation;

[0102] S4.3. Initialization simulation of sea surface motion state:

[0103] According to the physical ocean equation constructed in step S1, generate a time-varying sea surface through the sea wave spectrum, generate the initial sea surface state according to the Elfouhaily sea wave spectrum, and generate the real-time sea surface motion state using the Fourier superposition method;

[0104] S4.4. Update non-uniform azimuth time:

[0105] Divide the synthetic aperture into several time slices according to the antenna size. Each time slice corresponds to a position of the radar within the synthetic aperture, and update the non-uniform sampling time for each azimuth;

[0106] S4.5. Update of sea surface motion state:

[0107] It includes intercepting the range-dependent scattering grid within the beam illumination range and updating the instantaneous sea surface motion state within the beam illumination range, and calculating the sea surface motion state for all observation angles within the current time slice;

[0108] S4.6. Update of slant range scattering network:

[0109] Calculate the backscattering intensity of each scattering surface element in the time domain, calculate the specular scattering component and the Bragg scattering component of the scattering surface element according to Equations (19) and (20), and calculate the instantaneous slant range of the scattering surface element at the same time;

[0110] S4.7. Weighting of the two-way pattern of the time-domain antenna:

[0111] Calculate the spatially variant azimuth two-way pattern at each range cell for the scattering surface elements at the same azimuth position, determine whether all the scattering surface elements within the current beam range have been traversed. If yes, superimpose the echoes of the scattering surface elements within the illumination range of the current azimuth time beam; if no, return to step S4.4 to update the non-uniform azimuth time;

[0112] S4.8. Generate the sea surface echo matrix of the variable-beam high-resolution wide-swath SAR:

[0113] For the superimposed echoes of the scattering surface elements within the illumination range of the current azimuth time beam obtained in step S4.7, determine whether the azimuth end point has been reached. If no, return to step S4.4 to update the non-uniform azimuth time; if yes, output the sea surface echo matrix of the variable-beam high-resolution wide-swath SAR.

[0114] Furthermore, the calculation method of the instantaneous slant range of the scattering surface element in step S4.6 is as follows:

[0115] Assume that the satellite platform moves in a uniform linear motion in the horizontal direction relative to the observation scene, the azimuth width of the target observation area is S az , and the ground range width is S rg . Then, for the instantaneous slant range from any scattering point in the observation scene to the satellite platform, the expression of the instantaneous slant range R s (t; S) of the scattering surface element is:

[0116]

[0117] where is the ground range from the scattering point S to the satellite sub-satellite point, V is the velocity of the satellite platform, and t S is the time used to illuminate the center of the azimuth aperture of the scattering point.

[0118] Advantages of the present invention:

[0119] A method for simulating sea surface imaging of an area of interest in a variable-beam SAR solves the problems that in the existing sea surface echo simulation methods, the range-direction scattering grid cells are severely distorted with the azimuth position and the azimuth-direction non-uniform sampling under the observation configuration of the variable-beam strip SAR. A dynamic sea surface physical model is established, and a corresponding scattering intensity model is analyzed based on the sea surface echo scattering mechanism. Then, based on the imaging geometry of the variable-beam strip SAR, the azimuth non-uniform time slices, and the mapping of the slant-range space-variant scattering grid, a time-varying sea surface echo simulation method for the variable-beam strip SAR is proposed to realize the simulation of high-fidelity sea surface echo signals for the area of interest.

[0120] A method for simulating sea surface imaging of an area of interest in a variable-beam SAR realizes the matching between the imaging strip and the area of interest of the target that is not parallel to the satellite orbit, solves the problems that the range-direction scattering grid cells are severely distorted with the azimuth position and the azimuth-direction non-uniform sampling under the observation configuration of the variable-beam strip SAR, realizes the simulation of high-fidelity sea surface echo signals, the simulation results match the real sea surface height, and can significantly improve the fidelity of the echo signal simulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0121] Figure 1 shows the sea surface roughness and the radar echo situation;

[0122] Figure 2 is the Kirchhoff approximation (KA) scattering geometry model;

[0123] Figure 3 is the flow chart of the strip SAR sea surface echo simulation algorithm of the existing technology;

[0124] Figure 4 is the flow chart of the sea surface echo simulation algorithm of the variable-beam SAR of the present invention;

[0125] Figure 5 shows the sea surface height field, the sea surface height map, and the sea surface scattering intensity at the azimuth center simulated by the present invention at a wind speed of 15 m / s and a wind vector angle of 0°, where (a) is the sea surface height field, (b) is the sea surface height map, and (c) is the NRCS of the ocean surface;

[0126] Figure 6 shows the sea surface height and the scattering intensity under different sea winds of the present invention, where (a) is the sea surface height map under a 5 m / s sea wind, (b) is the sea surface scattering intensity map under a 5 m / s sea wind, (c) is the sea surface height map under a 30 m / s sea wind, and (d) is the sea surface scattering intensity map under a 30 m / s sea wind;

[0127] Figure 7For the sea surface height and scattering intensity of the present invention under different wind directions, where (a) is the sea surface height map at a wind vector angle of 45°, (b) is the sea surface scattering intensity map at a wind vector angle of 45°, (c) is the sea surface height map at a wind vector angle of 90°, and (d) is the sea surface scattering intensity map at a wind vector angle of 90°;

[0128] Figure 8 For the echo simulation sea wave spectrum and sea surface height map of the present invention, where (a) is the sea wave spectrum and (b) is the sea surface height map;

[0129] Figure 9 It is the sea surface echo focusing imaging result map of the prior art's echo simulation method based on a uniformly sampled azimuth displacement-invariant grid and the non-uniform time-slice space-variant scattering grid echo simulation method proposed by the present invention. Among them, (a) is the simulated variable beam high-resolution wide-swath SAR image of the prior art, (b) is the spectrum of the simulated variable beam high-resolution wide-swath SAR image of the prior art, (c) is the simulated variable beam high-resolution wide-swath SAR image of the method of the present invention, and (d) is the spectrum of the simulated variable beam high-resolution wide-swath SAR image of the method of the present invention;

[0130] Figure 10 It is the flow chart of a sea surface imaging simulation method for a variable beam SAR region of interest described in the present invention. Detailed implementation manners

[0131] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following further details the present invention in conjunction with the accompanying drawings and specific implementation manners. It should be understood that the specific implementation manners described herein are only used to explain the present invention and are not used to limit the present invention, that is, the described specific implementation manners are only a part of the implementation manners of the present invention, rather than all of the specific implementation manners. The components of the specific implementation manners of the present invention usually described and shown in the accompanying drawings here can be arranged and designed in various different configurations, and the present invention can also have other implementation manners.

[0132] Therefore, the following detailed description of the specific implementation manners of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but only represents the selected specific implementation manners of the present invention. Based on the specific implementation manners of the present invention, all other specific implementation manners obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0133] To further understand the content, features and effects of the present invention, the following specific implementation manners are exemplified and combined with the attached Figure 1 - Attached Figure 10 The details are as follows:

[0134] Example 1:

[0135] A simulation method for sea surface imaging in the region of interest of a variable beam SAR includes the following steps:

[0136] S1. Construct a sea surface motion model for the coastal zone, including physical ocean equations and the Elfouhaily wave spectrum;

[0137] Based on the analysis and interpretation of a large number of marine SAR images, studies have shown that SAR backscattering is largely affected by sea surface roughness. Sea surface roughness is a physical quantity reflecting the roughness of the sea surface. Its value is not only related to the roughness of the sea surface, but also different under different radar wavelengths and incident angles. For example, Figure 1 as shown, to quantitatively describe sea surface roughness, the dichotomy of the Rayleigh criterion can be adopted. That is, the sea surface satisfying the condition h r cosθ < λ R / 8 is a smooth sea surface, otherwise it is a rough sea surface. Among them, h r is the vertical height of the sea surface undulation.

[0138] The electromagnetic wave emitted by the satellite propagates downward, encounters the sea surface and undergoes physical processes such as reflection and scattering, and the returned electromagnetic wave carries information about the sea surface. This information, together with the noise, is received by the radar. For a calm and windless sea surface, specular reflection is the main process for the electromagnetic wave energy to return to the radar sensor. The sea surface can basically reflect the energy to the receiver in the nadir direction (the direction perpendicular to the sea surface, that is, the incident angle is 0°), and the microwave signal energy at other incident angles cannot be reflected back to the receiver. However, an ideal calm sea surface is rarely seen in the natural environment. Under the action of the sea surface wind, with the emergence of wind-generated surface tension waves and capillary gravity waves (collectively referred to as microscale waves), the sea surface becomes rough from smooth, which is equivalent to generating many small reflecting surfaces randomly distributed in the normal direction on the sea surface, resulting in a significant reduction in the echo in the nadir direction, and there is also corresponding scattered signal energy for the receiver deviating from the nadir direction.

[0139] For the microwave remote sensors carried on satellite platforms, the inclination angles of the small facets on the rough sea surface relative to the horizontal plane are mainly distributed within 25°. Therefore, when analyzing the backscattering component of the microwave sensor, the specular reflection component is only important at the downview angles from 0° to 15°. When the downview angle is greater than 15°, the main component of the echo signal is the scattering component based on roughness, and the strength of the echo signal depends to a large extent on the roughness of the sea surface. For a relatively calm sea surface, the amplitude of the sea surface fluctuation is small, and the inclination angles of the small facets relative to the horizontal plane change little, resulting in a specular-like reflection effect and basically no backscattering. Therefore, it appears very dark in the SAR image. For a moderately rough sea surface, the number of small facets that can form scattering conditions increases significantly, and a part of the radar wave energy incident on the sea surface can be scattered back to the receiver, and the backscattering energy is higher than that of the calm sea surface. For a rough sea surface, not only does the amplitude of the sea waves increase, but the range of inclination angle changes of each small facet is also larger. Therefore, the energy scattered back to the radar increases. Generally speaking, the backscattering is proportional to the sea surface roughness. In the SAR remote sensing image, for materials with the same scattering characteristics, the rough surface is brighter than the smooth surface.

[0140] The accurate modeling of the ocean surface is a hydrodynamics problem, which often involves solving the physical ocean nonlinear hydrodynamics equations. For the sea surface echo simulation of the spaceborne SAR system, the modeling accuracy of the sea surface usually reaches the meter level. The physical ocean equations fully consider various internal and external acting components. However, due to its complex time-domain form and the nonlinear coupling relationship between various parameters, it is not applicable to engineering practice. At this time, a linear approximate solution of the physical ocean equations can be adopted to obtain an engineering realizable sea surface motion model on the premise of sacrificing certain accuracy. Under natural conditions, the energy of the sea surface is mainly concentrated in the wind-driven surface gravity waves and capillary-gravity waves. Therefore, the existing empirical and theoretical models mainly consider the accurate modeling of these two types of waves.

[0141] Furthermore, the specific implementation method of step S1 includes the following steps:

[0142] S1.1. Based on the one-dimensional approximate solution of the physical ocean equations, assuming that the coordinates of a point on the sea surface are x = (x, y) and the height z = 0, where x is the coordinate point on the x-axis and y is the coordinate point on the y-axis. When a single-frequency ocean wave passes through the point on the sea surface, the expressions for the vertical motion vector ξ(x, t) and the horizontal motion vector D(x, t) of the point on the sea surface are:

[0143]

[0144] where, φ i is the initial phase of the i-th ocean wave, k i is the wave vector of the i-th ocean wave, k i is the wave number, ω iis the frequency of the i-th sea wave, t is the time, and A i is the amplitude of the i-th sea wave, and N is the total number of sea waves;

[0145] k i = ||k i || = 2π / λ

[0146] where λ is the wavelength;

[0147] S1.2. Set the open boundary sea surface as a linear superposition of a finite number of plane waves, where A i and k i are independent of the sea surface position, and φ i is independently and uniformly distributed in the interval [0, 2π). Then the mean value <ζ(x, t)> of the vertical motion vector of the points on the sea surface is 0, and the variance of the vertical motion vector of the points on the sea surface is

[0148] S1.3. Based on the fact that the sea surface wave is a superposition of an infinite number of plane waves, transform the variance of the vertical motion vector of the points on the sea surface into an integral form, and the expression is:

[0149]

[0150] where Ψ(k) and Ψ(k, θ) are the sea surface direction spectrum in the Cartesian coordinate system and the sea surface direction spectrum in the polar coordinate system respectively, and θ is the propagation direction of the beam;

[0151] S1.4. Divide the sea surface direction spectrum in the polar coordinate system into two components, including the sea wave spectrum S(k) and the angular spread function Φ(k, θ), and the expression is:

[0152]

[0153] The main component of the radar signal scattered by the sea surface comes from the short wave region. Therefore, a sea surface direction spectrum model that can accurately describe the short wave energy needs to be selected. After being tested by measured data, the JONSWAP model is in good agreement with the actual distribution of the long waves on the sea surface under the condition of limited fetch, while the Elfouhaily model takes into account both the long wave region and the short wave region of the sea surface. Therefore, for the sea surface modeling of microwave remote sensing, the Elfouhaily model or other improved models based on Elfouhaily are usually adopted.

[0154] Then define the sea wave spectrum as the Elfouhaily sea wave spectrum, and the expression is:

[0155] S(k) = k -3 [B l + B h (4)

[0156] where Bl With B h represent the long-wave sea surface curvature spectrum and the short-wave sea surface curvature spectrum respectively;

[0157] S1.5.B l Is defined as follows:

[0158]

[0159] Among them, c p Is the wave phase velocity of the spectral peak, c p = c(k p ), k p Is the spectral peak wave number, α p Is the long-wave equilibrium parameter, F p Is the long-wave action function, c is the phase velocity corresponding to the current beam;

[0160]

[0161] Among them, Ω is a dimensionless parameter used to adjust the attenuation rate of the exponential term, Ω = U 10 / c p , U 10 Is the wind speed at 10m above the sea surface, L PM , J p Are the peak enhancement functions of the PM spectrum and JONSWAP respectively;

[0162] L PM , J p Are defined as follows:

[0163]

[0164] Among them, γ is the peak enhancement factor, Γ is the Gaussian weight function, and σ is the spectral width parameter;

[0165] S1.6.B h Is defined as follows:

[0166]

[0167] Among them, c m Is the phase velocity corresponding to the minimum wave number, F m And α m Are the first dimensionless parameter and the second dimensionless parameter;

[0168]

[0169] Among them, u * Is the friction velocity of the sea surface;

[0170] The definition of the angular diffusion function Φ(k,θ) is as follows:

[0171]

[0172] Among them, Δ(k) is the upwind - crosswind ratio, which is used to describe the directivity of sea waves with different wavelengths;

[0173] Δ(k) is defined as:

[0174] Δ(k)=tanh{a 0 +a p (c / c p ) 2.5 +a m (c m / c) 2.5} (12)

[0175] Among them, a 0 is the first constant, and a p , a m are the parameters corresponding to U 10 / c p , u * / c m respectively.

[0176] S2. Construct a Kirchhoff specular reflection model, including constructing the target scattering electric field, the central scattering intensity of the scattering surface element, and the specular scattering component of the scattering surface element;

[0177] When the radius of curvature of the scatterer or scattering surface is much larger than the radar wavelength, the surface field can be represented by the approximation of the tangent plane at each point on the surface. The process of obtaining the scattering field according to this approximation method is called the Kirchhoff approximation (KA) or the physical optics method, as Figure 2 shown;

[0178] Furthermore, the specific implementation method of step S2 includes the following steps:

[0179] S2.1. Set the applicable conditions of the Kirchhoff specular reflection model as:

[0180] (k 0 r c ) 1 / 3 cosθ >> 1 (13)

[0181] Among them, r c is the radius of the curved surface;

[0182] S2.2. Set the expression of the target scattering electric field E s constructed based on the Kirchhoff specular reflection model as:

[0183]

[0184] Among them, K s is the central scattering intensity of the scattering surface element, p is the distribution function, and k s is the wave number of the scattering signal of the scattering surface element, is the specular scattering component of the scattering surface element, S is the integral of the sea surface over the scattering surface element, and j is the imaginary unit;

[0185] The expression of p is as follows:

[0186]

[0187] Among them, × represents the vector cross product, E is the electric field in the propagation medium, is the unit vector of the surface normal of the scattering surface element, H is the magnetic field in the propagation medium, and η is the dielectric constant of the medium;

[0188] The expression of K s is as follows:

[0189]

[0190] Among them, R s is the distance between the center of the illumination area and the incident point;

[0191] The expression of

[0192]

[0193] Among them, φ s is the azimuth angle, θ s is the elevation angle, represents the vectors in the three directions of the rectangular coordinate system;

[0194] S2.3. Assume that the incident wave is a spherical wave, then the incident field strength Ε inc has the following expression:

[0195]

[0196] Among them, R inc is the distance from the illumination source to the scattering center, is the unit vector of the polarization direction of the incident wave, is the unit vector in the incident direction;

[0197]

[0198] The normalized scattering intensity has the following expression:

[0199]

[0200] where pq represents the polarization modes of the incident and scattered waves, and <·> denotes taking the average.

[0201] Furthermore, due to the large computational amount of direct integration, in the application of the actual sea surface scattering model, some approximation algorithms are generally adopted. Among them, the Stationary-Phase Approximation (SPA) and the Facet Approach (FA) are often used in the calculation of the sea surface scattering model.

[0202] S3. Construct the Bragg resonance scattering model, including constructing the Bragg scattering component of the sea surface facet, establishing a numerical model for the sea surface height spectrum, and calculating the instantaneous slant range of the scattering facet;

[0203] According to the Bragg resonance scattering model, the normalized scattering coefficient of the rough sea surface is proportional to the Bragg wave spectrum intensity of the sea surface. Therefore, the scattering intensity of each small facet on the ocean surface is mainly contributed by the small-scale waves close to the radar wave scale, while the larger-scale sea surface waves make the incident angle and incident plane of each small facet change randomly, playing a role of random modulation. Therefore, the sea surface wave spectrum is modeled into two scales: small-scale waves k > k d and large-scale waves k < k d , where k d = d·k 0 , d is a constant less than 1. Consider a small facet on the sea surface with a slight tilt in the direction parallel to the radar line of sight;

[0204] Furthermore, the specific implementation method of step S3 includes the following steps:

[0205] S3.1. Construct the Bragg scattering component of the sea surface facet according to the Bragg resonance scattering model The expression is:

[0206]

[0207] where Ψ(k) is the sea surface height spectrum, k 0 is the radar wave number (appeared in 2.1), k b is the Bragg wave number vector, s p is the tilt angle parallel to the line of sight, s n is the tilt angle perpendicular to the line of sight, θ l is the equivalent incident angle at the small facet and θ l = arccos[cos(θ - s p )cos s n , b pp is the complex scattering coefficient for horizontal polarization, b qq is the complex scattering coefficient for vertical polarization;

[0208] The amplitude and direction are defined as follows:

[0209]

[0210] Among them, φ 0 is the radar azimuth angle, k b is the Bragg wave number, and φ b is the Bragg beam direction;

[0211] Then, correct the equivalent scattering coefficient of the Bragg scattering component of the sea surface element relative to the radar to obtain the expression:

[0212]

[0213] Among them, H 0 is the height of the radar relative to the sea level, and ζ is the height of the small surface element;

[0214] S3.2. Establish a numerical model for the sea surface height spectrum. The expression of the omnidirectional spectrum S(k) is as follows:

[0215]

[0216] Among them, P L is a function of the wind speed, U n is the sea surface reference wind speed, and W H is the correction function in the high-frequency band;

[0217] Model the low wave number roll-off and the peak of JONSWAP. The expression is as follows:

[0218]

[0219] Among them, g is the acceleration due to gravity;

[0220] W H Model the Bragg wave. The expression is as follows:

[0221]

[0222] Among them, k 6 = 280 rad / m, k 7 = 75 rad / m, k 8 = 1300 rad / m, k 9 = 8885 rad / m;

[0223] U n = 1 m / s, and β is the corresponding wind force index. The expression is:

[0224]

[0225] where k 1 = 183 rad / m, k 2 = 3333 rad / m, k 3 = 33 rad / m, k 4 = 140 rad / m, k 5 = 220 rad / m;

[0226] The diffusion function obtained is:

[0227]

[0228] where δ is the distribution width control parameter;

[0229]

[0230] where c 1 = 400 rad / m, U n = 1 m / s, k n = 1 rad / m.

[0231] S4. Based on the model constructed in steps S1 - S3, perform echo simulation on the variable - beam SAR sea surface, including updating the space - variant scattering grid using the coastal sea - surface motion model obtained in step S1 and updating the instantaneous sea - surface motion state, calculating the backscattering intensity of each scattering surface element in the time domain using the Kirchhoff specular reflection model obtained in step S2 and the Bragg resonance scattering model obtained in step S3, then calculating the space - variant azimuth - two - way pattern at each range cell for the scattering surface elements at the same azimuth position, weighting the echoes of each scattering surface element, and then traversing the non - uniform sampling time to obtain the echo matrix of the variable - beam high - resolution wide - swath SAR;

[0232] Due to the complex and fast - changing nature of the sea surface, and the complex sources of the forces causing the sea - surface changes, which are related to the terrain, meteorology, etc. of the sea area where it is located, and the complex microwave scattering characteristics of the sea surface, existing sea - surface scattering intensity models are all numerical approximations in specific scenarios, and there is no scattering model that can fully describe all the characteristics of sea - surface scattering. Existing microwave scattering models mainly target side - looking strip or scanning SARs. During the synthetic aperture time, the radar incident angle in each azimuth direction remains unchanged. Therefore, by modeling the height field of the sea surface, according to the sea - surface height field, radar incident angle, and radar wave polarization mode, inputting into the sea - surface microwave scattering model to obtain the normalized radar cross - section area in each grid on the sea surface, and then combining the slant range from each point to the radar, simulating the SAR echo, the algorithm flow is as Figure 3 shown.

[0233] In the imaging mode of variable-beam strip high-resolution wide-swath SAR, the incident angle varies along the azimuth direction, there are high-order motion components of azimuth-range coupling in the slant range, and the radar echo has non-uniform azimuth slow time in the variable PRI mode. The traditional simulation method fails, and it is necessary to analyze the spatial variation of scatter surface elements and non-uniform signal sampling in the new imaging mode to achieve accurate modeling. The flow of the proposed method for simulating sea surface echoes of variable-beam high-resolution wide-swath SAR is as follows Figure 4 shown. The existing strip SAR echo simulation method is based on the Fourier transform pair relationship between the wavenumber domain sea wave spectrum of a uniform scattering grid and the spatial sea surface motion state. The beam coverage range of uniform scattering points at each azimuth moment is the same. Based on the fast Fourier algorithm and the invariant characteristic of the number of observable scattering points at each moment, parallel computing can be used to obtain the dynamic sea surface within the SAR synthetic aperture time, and directly calculate the backscattering intensity of each range cell surface element in the range compression domain. Then, the antenna pattern is superimposed once in the azimuth Doppler domain to quickly generate the strip SAR echo matrix of the sea surface. In the variable-beam high-resolution wide-swath mode, the range center of the radar beam is always far from the sub-satellite point, and spatio-temporal continuous observation of the region of interest not parallel to the orbit direction can be carried out. Due to the non-uniform time domain sampling caused by variable PRI and the azimuth spatial variation of the beam footprint caused by variable beam pointing, the existing fast simulation method of strip SAR is not applicable. It is necessary to update the spatially variable scattering grid at each azimuth sampling time, calculate the backscattering intensity of each scatter surface element in the time domain, then calculate the spatially variable azimuth two-way pattern at each range cell for the scatter surface elements at the same azimuth position, weight the echoes of each scatter surface element, and then traverse the non-uniform sampling time to obtain the echo matrix of variable-beam high-resolution wide-swath SAR.

[0234] Furthermore, the specific implementation method of step S4 includes the following steps:

[0235] S4.1. Input radar and sea surface simulation parameters:

[0236] According to the simulated scenario, set the radar parameters and sea surface environment parameters. The radar parameters include center frequency, pulse width, signal bandwidth, sampling frequency, orbital altitude, azimuth resolution, central depression angle, variable-beam strip angle, antenna type and antenna size, antenna beam width; the sea surface environment parameters include the size of the sea surface area, wind speed and wind direction.

[0237] S4.2. Generation of spatially variable scattering grid in the ground range coordinate system:

[0238] Define the ground range coordinate system using a rectangular coordinate system, set the step size of the spatially variable scattering grid to satisfy the Nyquist sampling theorem, and generate a set of spatially variable scattering grid points for scatter calculation and sea wave dynamic simulation.

[0239] S4.3. Initialization simulation of sea surface motion state:

[0240] Based on the physical ocean equation constructed in step S1, a time-varying sea surface is generated through a wave spectrum. The initial sea surface state is generated according to the Elfouhaily wave spectrum, and the real-time sea surface motion state is generated using the Fourier superposition method;

[0241] S4.4. Update the non-uniform azimuth time:

[0242] The synthetic aperture is divided into several time slices according to the antenna size. Each time slice corresponds to a position of the radar within the synthetic aperture, and the non-uniform sampling time for each azimuth is updated;

[0243] S4.5. Update the sea surface motion state:

[0244] It includes intercepting the spatially-varying scattering grid within the beam illumination range and updating the instantaneous sea surface motion state within the beam illumination range, and calculating the sea surface motion state for all observation angles within the current time slice;

[0245] S4.6. Update the slant-range scattering network:

[0246] Calculate the backscattering intensity of each scattering surface element in the time domain. Calculate the specular scattering component and the Bragg scattering component of the scattering surface element according to equations (19) and (20), and at the same time calculate the instantaneous slant range of the scattering surface element;

[0247] Furthermore, the method for calculating the instantaneous slant range of the scattering surface element in step S4.6 is as follows:

[0248] Assume that the satellite platform moves in a uniform linear motion in the horizontal direction relative to the observation scene, the azimuth width of the target observation area is S az , and the ground range width is S rg . Then, for the instantaneous slant range from any scattering point in the observation scene to the satellite platform, the expression for the instantaneous slant range R s (t; S) of the scattering surface element is:

[0249]

[0250] Among them, is the ground range from the scattering point S to the satellite sub-satellite point, V is the satellite platform velocity, and t S is the time taken for the azimuth aperture center to illuminate the scattering point;

[0251] S4.7. Time-domain antenna two-way pattern weighting:

[0252] Calculate the spatially-varying azimuth two-way pattern at each range cell for the scattering surface elements at the same azimuth position. Determine whether all the scattering surface elements within the current beam range have been traversed. If yes, superimpose the echoes of the scattering surface elements within the beam illumination range at the current azimuth time. If no, return to step S4.4 to update the non-uniform azimuth time;

[0253] S4.8. Generate the sea surface echo matrix of variable-beam high-resolution wide-swath SAR:

[0254] For the echoes of the scattering surface elements within the illumination range of the current azimuth time beam obtained in step S4.7, determine whether the azimuth end point is reached. If not, return to step S4.4 to update the non-uniform azimuth time. If so, output the sea surface echo matrix of variable-beam high-resolution wide-swath SAR.

[0255] For a sea surface imaging simulation method of variable-beam SAR in the region of interest described in this embodiment, a specific implementation example is as follows:

[0256] Based on the Elfouhaily sea wave directional spectrum model and the combined surface scattering intensity model that combines specular reflection and Bragg scattering, simulate a moving sea surface in a certain area. The radar system and sea surface parameters are set as shown in Table 1:

[0257] Table 1:

[0258]

[0259] The radar system operates at a center frequency of 5.4 GHz, with a pulse width of 20 μs and a signal bandwidth of 50 MHz, and a sampling rate of 62.5 MHz. The radar is carried on an orbit at an altitude of 700 km, with an azimuth resolution of 5 m, a central downward viewing angle of 34.7°, and a variable-beam strip angle of 30°. The antenna uses a planar phased array design with a size of 8.86 m × 1.67 m, where the number of array elements in the azimuth direction is 12 and the number of array elements in the elevation direction is 22. The radar has an azimuth coverage width of 200 km, a range coverage swath of 400 km, an imaging range of 4 km × 4 km for the sea surface area, and a wind fetch length of 500 km. This system uses vertical polarization for detection.

[0260] Set the wind speed at 10 m above the sea surface to 15 m / s. When the wind vector angle is agreed to be 0°, the wind vector direction is opposite to the azimuth unit vector direction of the ground coordinate system and perpendicular to the range unit vector. The simulated sea surface height field, sea surface height map, and sea surface scattering intensity at the azimuth center are as Figure 5 shown;

[0261] Change the wind force intensity from 15 m / s to 5 m / s and 30 m / s, and obtain the sea surface height map and sea surface scattering intensity as Figure 6 shown. From Figure 6 it can be seen that as the wind force increases, the height difference of the wind-induced wave field also becomes larger and larger, long-wavelength sea waves are formed, the sea surface becomes rougher, and the signal energy reflected back to the SAR receiving antenna also becomes stronger. When the wind force is small, the sea surface mainly consists of short-wavelength sea waves, the scattering intensity is low, and the noise characteristics are obvious.

[0262] Let the wind force be 23 m / s, and change the wind vector angles to 45° and 90°. The sea surface height map and scattering intensity are obtained as Figure 7 shown. From Figure 7 the simulation results, it can be seen that the propagation direction of the sea surface ripples is consistent with the set conditions, indicating that the adopted moving sea surface model and sea surface backscattering intensity model can generate a dynamic sea surface and the backscattering intensity of each surface element that conform to the input simulation parameters.

[0263] Next, according to the proposed non-uniform time slice and space-variant scattering grid sea surface echo simulation method, generate variable-beam high-resolution wide-swath SAR echo data, and based on the correspondence between the imaging results and the input sea wave spectrum, verify the effectiveness of the proposed echo simulation method. Simulate a 4 km × 4 km ocean surface according to the radar parameters, with the wind vector angle of the ocean surface being 180° and the wind speed being 23 m / s. The generated sea wave spectrum and the corresponding sea surface height map are as Figure 8 shown;

[0264] Generate the SAR echo signal by the following method: ① Adopt the echo simulation method based on uniformly sampled azimuth displacement-invariant grid, change the incident angle and instantaneous slant range of each scattering surface element, and use the antenna pattern weight at the azimuth center to generate variable-beam high-resolution wide-swath SAR echo; ② Adopt the proposed non-uniform time slice space-variant scattering grid echo simulation method to generate variable-beam high-resolution wide-swath SAR echo. Then, focus the generated waves for imaging respectively, and the experimental results are as Figure 9 shown. From Figure 9 the imaging results of the simulated echo, if the existing echo simulation method is directly applied to the variable-beam high-resolution wide-swath SAR imaging mode, due to the lack of consideration of non-uniform sampling and azimuth space-variant scattering grid, the generated SAR image has interference caused by the superposition of strong non-linear components and does not conform to the input sea wave spectrum. However, the sea surface echo simulation method proposed by the present invention generates an image spectrum that is close to the SAR image spectrum of the existing strip mode and is also closer to the input sea wave spectrum, indicating that the proposed echo simulation method can solve the problem of the failure of the existing method and can provide coastal sea surface image simulation data for subsequent coastal zone imaging technology.

[0265] It should be noted that relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0266] Although the present application has been described above with reference to specific embodiments, various improvements can be made thereto and components thereof can be replaced with equivalents without departing from the scope of the present application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in the present application can be combined with each other in any way, and the reason for not exhaustively describing the situations of these combinations in this specification is only to save space and resources. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A variable beam SAR region of interest sea surface imaging simulation method, characterized in that: The steps include: S1. Construct a model of sea surface motion in the coastal zone, including physical ocean equations and Elfouhaily wave spectrum; S2. Constructing Kirchhoff specular reflection model, including constructing target scattering electric field, scattering intensity of scattering surface element center, and specular scattering component of scattering surface element; S3. Constructing a Bragg resonance scattering model, including constructing the Bragg scattering component of the sea surface element, establishing a numerical model for the sea surface height spectrum, and calculating the instantaneous slant range of the scattering element; S4. Based on the model constructed in steps S1-S3, the variable-beam SAR sea surface echo simulation is performed, including using the coastal sea surface motion model obtained in step S1 to update the space-variable scattering grid and update the instantaneous sea surface motion state, using the Kirchhoff mirror reflection model obtained in step S2 and the Bragg resonance scattering model obtained in step S3 to calculate the backscattering intensity of each scattering surface element in the time domain, then calculating the space-variable azimuth two-way radiation pattern at each distance unit for the scattering surface elements at the same azimuth position, weighting the echo of each scattering surface element, and then traversing the non-uniform sampling time to obtain the echo matrix of the variable-beam high-resolution wide-band SAR.

2. The variable beam SAR region of interest sea surface imaging simulation method according to claim 1, characterized in that: The specific implementation method of step S1 includes the following steps: S1.

1. Based on the one-dimensional approximate solution of the physical ocean equation, assuming that the coordinates of a point on the sea surface are x = (x, y), the height z = 0, x is the x-axis coordinate point, y is the y-axis coordinate point, when a single-frequency sea wave passes through the point on the sea surface, the vertical motion vector ξ(x, t) and the horizontal motion vector D(x, t) of the point on the sea surface are expressed as: Among them, φ i is the initial phase of the ith wave, k i is the wave vector of the ith sea wave, k i is the wave number, ω i is the frequency of the ith sea wave, t is the time, A i is the amplitude of the ith sea wave, and N is the total number of sea waves; k i =||k i ||=2p / l Where λ is the wavelength; S1.

2. Assume that the open boundary sea surface is a linear superposition of a finite number of plane waves, where A i With k i Independent of the sea surface position, φ i The independent cuts are uniformly distributed in the interval [0,2π), then the mean of the vertical motion vector of the point on the sea surface is <ζ(x,t)>=0, and the variance of the vertical motion vector of the point on the sea surface is S1.

3. Based on the fact that sea surface waves are the superposition of infinite plane waves, the variance of the vertical motion vector of a point on the sea surface is transformed into an integral form, and the expression is: Among them, Ψ(k) and Ψ(k,θ) are the sea surface directional spectrum in the Cartesian coordinate system and the sea surface directional spectrum in the polar coordinate system, respectively, and θ is the propagation direction of the beam; S1.

4. The sea surface directional spectrum in the polar coordinate system is divided into two components, including the wave spectrum S(k) and the angular spread function Φ(k,θ), expressed as: The wave spectrum is then defined as the Elfouhaily wave spectrum, expressed as: S(k)=k -3 [B l +B h ] (4) Among them, B l With B h denote the long and short sea wave curvature spectra, respectively; S1.5.B l The definition is as follows: Among them, c p is the wave phase velocity at the peak of the spectrum, c p =c(k p ), k p is the peak wave number, α p is the long wave equalization parameter, F p is the long-wave action function, c is the phase velocity corresponding to the current beam; Among them, Ω is a dimensionless parameter used to adjust the decay rate of the exponential term, Ω = U 10 / c p , U 10 is the wind speed at 10m above the sea surface, L PM , J p They are the peak enhancement functions of PM spectrum and JONSWAP respectively; L PM , J p The definition is as follows: Among them, γ is the peak enhancement factor, Γ is the Gaussian weight function, and σ is the spectrum width parameter; S1.6.B h The definition is as follows: Among them, c m is the phase velocity corresponding to the minimum wave number, F m With α m is the first dimensionless parameter and the second dimensionless parameter; Among them, u * is the friction speed of the sea surface; S1.

7. The angular spread function Φ(k,θ) is defined as follows: Among them, Δ(k) is the windward-crosswind ratio, which is used to describe the directionality of sea waves of different wavelengths; Δ(k) is defined as: Δ(k)=tanh{a0+a p (c / c p ) 2.5 +a m (c m / c) 2.5 } (12) Among them, a0 is the first constant, a p 、a m Respectively with U 10 / c p 、u * / c m The corresponding parameters.

3. The variable beam SAR region of interest sea surface imaging simulation method according to claim 2, characterized in that: The specific implementation method of step S2 includes the following steps: S2.

1. Set the applicable conditions of Kirchhoff's specular reflection model as follows: (k0r c ) 1 / 3 cosθ>>1 (13)where r c is the surface radius; S2.

2. Set the target scattered electric field E based on Kirchhoff specular reflection model s The expression is: Among them, K s is the central scattering intensity of the scattering surface element, p is the distribution function, k s is the scattered signal wave number of the scattering surface element, is the specular scattering component of the scattering surface element, S is the integration of the scattering surface element over the sea surface, and j is the imaginary unit; The expression of p is as follows: Where × represents vector cross product, E is the electric field in the propagation medium, is the surface normal unit vector of the scattering surface element, H is the magnetic field in the propagation medium, and η is the dielectric constant of the medium; K s The expression is as follows: Among them, R s is the distance between the center of the irradiated area and the incident point; The expression is as follows: Among them, φ s is the azimuth angle, θ s is the pitch angle, Represents the vectors in three directions of the rectangular coordinate system; S2.

3. Assuming that the incident wave is a spherical wave, the incident field intensity E inc The expression is as follows: Among them, R inc is the distance from the illumination source to the scattering center, is the unit vector of the polarization direction of the incident wave, is the unit vector of the incident direction; Get the normalized scattering intensity The expression is: Here, pq represents the polarization modes of the incident and scattered waves, and <·> means taking the average.

4. The variable beam SAR region of interest sea surface imaging simulation method according to claim 3, characterized in that: The specific implementation method of step S3 includes the following steps: S3.

1. Constructing the Bragg scattering components of the sea surface element based on the Bragg resonance scattering model The expression is: Among them, Ψ(k) is the sea surface height spectrum, k0 is the radar wave number (appeared in 2.1), k b is the Bragg wave number vector, s p is the tilt angle parallel to the viewing direction, s n Tilt angle perpendicular to the viewing direction, θ l is the equivalent incident angle at the small facet and θ l =arccos[cos(θ-s p )coss n ], b pp is the complex scattering coefficient of horizontal polarization, b qq is the complex scattering coefficient of vertical polarization; The magnitude and direction are defined as follows: Where φ0 is the radar azimuth, k b is the Bragg wave number, φ b is the Bragg beam direction; Then the Bragg scattering component of the sea surface element is corrected relative to the equivalent scattering coefficient of the radar, and the expression is obtained: Where H0 is the height of the radar relative to the sea level, ζ is the height of the small pixel; S3.

2. A numerical model is established for the sea surface height spectrum. The expression of the omnidirectional spectrum S(k) is as follows: Among them, P L is a function of wind speed, U n is the reference wind speed on the sea surface, W H is the high frequency band correction function; The low wave number roll-off and the peak of JONSWAP are modeled as follows: in, g is the acceleration due to gravity; W H The Bragg wave is modeled as follows: Among them, k6 = 280 rad / m, k7 = 75 rad / m, k8 = 1300 rad / m, k9 = 8885 rad / m; U n =1m / s, β is the corresponding wind index, the expression is: Among them, k1 = 183 rad / m, k2 = 3333 rad / m, k3 = 33 rad / m, k4 = 140 rad / m, k5 = 220 rad / m; the diffusion function is: Among them, δ is the distribution width control parameter; Where, c1 = 400 rad / m, U n =1m / s, k n =1rad / m.

5. The variable beam SAR region of interest sea surface imaging simulation method according to claim 4, characterized in that: The specific implementation method of step S4 includes the following steps: S4.

1. Input radar and sea surface simulation parameters: Set radar parameters and sea surface environment parameters according to the simulation scenario. Radar parameters include center frequency, pulse width, signal bandwidth, sampling frequency, orbit height, azimuth resolution, center downward viewing angle, variable beam strip angle, antenna type and size, and antenna beam width. Sea surface environment parameters include sea surface area size, wind speed, and wind direction. S4.

2. Generation of space-variable scattering grid in ground-distance coordinate system: The ground-distance coordinate system is defined as a rectangular coordinate system, the space-variable scattering grid step size is set to satisfy the Nyquist sampling theorem, and a space-variable scattering grid point set is generated for scattering calculation and wave dynamic simulation; S4.

3. Initialization simulation of sea surface motion state: According to the physical ocean equation constructed in step S1, a time-varying sea surface is generated through the wave spectrum, an initial sea surface state is generated according to the Elfouhaily wave spectrum, and a real-time sea surface motion state is generated using the Fourier superposition method; S4.

4. Update non-uniform bearing time: The synthetic aperture is divided into several time slices according to the antenna size. Each time slice corresponds to a position of the radar in the synthetic aperture, and the non-uniform sampling time of each azimuth is updated; S4.

5. Update of sea surface motion status: It includes intercepting the space-variable scattering grid within the beam illumination range, updating the instantaneous sea surface motion state within the beam illumination range, and calculating the sea surface motion state of all observation angles in the current time slice; S4.

6. Update the slant range scatter network: The backscattering intensity of each scattering surface element is calculated in the time domain, and the specular scattering component and Bragg scattering component of the scattering surface element are calculated according to equations (19) and (20), and the instantaneous slant range of the scattering surface element is calculated at the same time; S4.

7. Time domain antenna two-way pattern weighting: Calculate the space-variant two-way azimuth pattern at each distance unit for the scattering surface element at the same azimuth position, determine whether all scattering surface elements within the current beam range have been traversed, and determine whether the scattering surface element echo within the current azimuth time beam illumination range is superimposed. If not, return to step S4.4 to update the non-uniform azimuth time; S4.

8. Generate variable beam high resolution wide bandwidth SAR sea surface echo matrix: For the scattered surface element echo within the illumination range of the superimposed current azimuth time beam obtained in step S4.7, determine whether it has reached the azimuth end point. If not, return to step S4.4 to update the non-uniform azimuth time. If yes, output the variable beam high-resolution wide-band SAR sea surface echo matrix.

6. The variable beam SAR region of interest sea surface imaging simulation method according to claim 5, characterized in that: The instantaneous slant range calculation method of the scattering surface element in step S4.6 is: Assume that the satellite platform moves horizontally at a uniform speed relative to the observation scene, and the azimuth width of the target observation area is S az , the ground width is S rg , then for the instantaneous slant distance from any scattering point in the observation scene to the satellite platform, the instantaneous slant distance R of the scattering surface element is obtained s The expression of (t; S) is: in, is the ground distance from the scattering point S to the satellite subsatellite point, V is the satellite platform speed, t S It is the time taken for the scattering point to be illuminated to the center of the azimuth aperture.

Images