Marine front imaging simulation method and related equipment thereof

Abstract

The invention relates to an ocean front imaging simulation method and related equipment thereof. The method comprises the following steps: acquiring target sea surface temperature data of a target ocean area, wherein the target ocean area comprises an ocean front area; performing feature extraction on the ocean front area based on the target sea surface temperature data to generate a front line position feature of an ocean front corresponding to the ocean front area; based on the frontal line position features, the target ocean area is divided into two to-be-processed background areas, feature enhancement processing is carried out on sea surface temperatures corresponding to the two to-be-processed background areas, enhanced target sea surface temperature data are generated, and the two to-be-processed background areas are located on the two sides of the frontal line respectively; simulating the enhanced target sea surface temperature data on the basis of a thermal wind-forming theory to generate thermal flow velocity field data; and performing simulation imaging on the target ocean area according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area. Based on the method, simulation precision and reliability can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of ocean front imaging simulation, and in particular to an ocean front imaging simulation method and related equipment. Background Art

[0002] Ocean fronts are an important part of mesoscale phenomena in the ocean, usually manifested as obvious jump zones in marine environmental parameters. The existence of frontal zones has important impacts on many fields such as marine fisheries, climate change, environmental monitoring and military activities.

[0003] Compared with other satellite detection technologies, spaceborne synthetic aperture radar (SAR) has become an important tool for ocean front monitoring and feature extraction due to its advantages of all-weather, all-day and high spatial resolution. However, the surface seawater velocity gradient on both sides of the ocean front area is significant and has different physical properties, which makes the imaging characteristics of the ocean front in SAR images show significant differences. In addition, the ocean front is affected by multiple factors such as convergence and divergence, strong shear wave flow and wind speed, which further increases the difficulty of interpreting the characteristics of the ocean front in SAR images. In summary, when the existing technology simulates the imaging of the ocean front, it is easy to cause a significant deviation between the simulation results and the actual situation, reducing the accuracy and reliability of monitoring. Summary of the invention

[0004] An ocean front imaging simulation method and related equipment provided by an embodiment of the present invention at least solve the problem in the related art that, during ocean front imaging simulation, there is a significant deviation between the simulation results and the actual situation, and the simulation accuracy and reliability are low.

[0005] According to a first aspect of an embodiment of the present invention, there is provided an ocean front imaging simulation method, comprising:

[0006] Acquiring target sea surface temperature data of a target ocean region, wherein the target ocean region includes an ocean front region;

[0007] Extracting features of the ocean front region based on the target sea surface temperature data to generate frontal position features of the ocean front corresponding to the ocean front region;

[0008] Based on the front position feature, the target ocean area is divided into two background areas to be processed, so as to perform feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed respectively, and generate enhanced target sea surface temperature data, wherein the two background areas to be processed are respectively located on both sides of the front;

[0009] Based on the thermal wind theory, the enhanced target sea surface temperature data is simulated to generate thermal flow velocity field data;

[0010] The target ocean area is simulated and imaged according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area.

[0011] According to a second aspect of an embodiment of the present invention, there is provided an ocean front imaging simulation device, comprising:

[0012] An acquisition module, used to acquire target sea surface temperature data of a target ocean area, wherein the target ocean area includes an ocean front area;

[0013] An extraction module, configured to extract features of the ocean front region based on the target sea surface temperature data, and generate front line position features of the ocean front corresponding to the ocean front region;

[0014] A division module, used for dividing the target ocean area into two background areas to be processed based on the front position characteristics, so as to perform feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed respectively, and generate enhanced target sea surface temperature data, wherein the two background areas to be processed are respectively located on both sides of the front;

[0015] A simulation module, used for simulating the enhanced target sea surface temperature data based on thermal wind theory to generate thermal flow velocity field data;

[0016] An imaging module is used to perform simulated imaging of the target ocean area according to the thermal flow velocity field data to obtain a target simulated image corresponding to the target ocean area.

[0017] According to a third aspect provided by an embodiment of the present invention, there is provided an electronic device, comprising: a processor, and a memory storing a program, wherein the program comprises instructions, and when the instructions are executed by the processor, the processor executes the method according to the first aspect.

[0018] According to a fourth aspect provided by an embodiment of the present invention, a non-transitory machine-readable medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method according to the first aspect.

[0019] Beneficial effects of the embodiments of the present invention:

[0020] The ocean front imaging simulation method provided by the embodiment of the present invention can reduce the deviation between the simulation result and the actual situation, and improve the simulation accuracy and reliability. Specifically, firstly, the sea surface temperature data of the target ocean area including the ocean front area is obtained, and the feature extraction of the ocean front area is performed based on the target sea surface temperature data, and the front position feature of the ocean front corresponding to the ocean front area is generated. The accurate extraction of the front position can effectively distinguish the ocean front from the surrounding background area, and then divide the two background areas to be processed. Then, based on the front position feature, the target ocean area is divided into two background areas to be processed, so that the sea surface temperature corresponding to each of the two background areas to be processed is subjected to feature enhancement processing, and the enhanced target sea surface temperature data is generated, wherein the two background areas to be processed are respectively located on both sides of the front. Through feature enhancement processing, the contrast and clarity of the ocean front feature can be significantly improved, so that the subsequent simulation analysis is more accurate. Since the characteristics of the ocean front often have significant temperature differences with the background area in practical applications, the use of enhancement processing can not only highlight the characteristics of the ocean front, but also effectively suppress background interference, thereby improving the overall quality of the image. Subsequently, the enhanced target sea surface temperature data was simulated based on the thermal wind theory to generate thermal flow velocity field data. The velocity field is generated by using the change of sea surface temperature gradient, which not only takes into account the influence of temperature on flow, but also reflects the dynamic characteristics of the ocean front under specific climatic conditions through an accurate calculation model. Finally, the target ocean area is simulated and imaged according to the thermal flow velocity field data to obtain the target simulation image corresponding to the target ocean area. The final generated image not only shows the spatial distribution and characteristics of the ocean front, but also reflects its dynamic change trend. Based on the above method, through accurate data acquisition, feature extraction and processing, thermal wind theory simulation, and final imaging generation, an effective ocean front imaging simulation method is formed, which not only reduces the deviation between the simulation results and the actual situation, improves the simulation accuracy and reliability, but also improves the recognizability and clarity of the ocean front features.

[0021] The details of one or more embodiments of the invention are set forth in the following drawings and description so that other features, objects, and advantages of the invention are more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other embodiments can be obtained based on these drawings without creative work.

[0023] Figure 1 A flow chart of an ocean front imaging simulation method provided in an embodiment of the present invention.

[0024] Figure 2 A schematic diagram of sea surface temperature information after interpolation processing provided by an embodiment of the present invention.

[0025] Figure 3 A schematic diagram of a front line in a coastal ocean front area provided in an embodiment of the present invention.

[0026] Figure 4 A temperature distribution diagram after enhancement processing provided by an embodiment of the present invention.

[0027] Figure 5 A distribution diagram of the thermal flow velocity field in a coastal ocean front region provided in an embodiment of the present invention.

[0028] Figure 6 A schematic diagram of a radar line-of-sight velocity gradient provided by an embodiment of the present invention.

[0029] Figure 7 A schematic diagram of the distribution of thermal sea surface backscatter coefficients provided in an embodiment of the present invention.

[0030] Figure 8 A schematic structural diagram of an ocean front imaging simulation device provided in an embodiment of the present invention.

[0031] Fig. 9 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0032] Embodiments of the present embodiment will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present embodiment are shown in the accompanying drawings, it should be understood that the present embodiment can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein, which are instead provided for a more thorough and complete understanding of the present embodiment. It should be understood that the drawings and embodiments of the present embodiment are only for exemplary purposes and are not intended to limit the scope of protection of the present embodiment.

[0033] The ocean front is an important mesoscale phenomenon in the ocean. The frontal zone corresponds to a distinct jump zone of marine environmental parameters, which has an important impact on marine fisheries, climate environment and military activities. At present, achievements have been made in the detection method of ocean fronts based on temperature and water color satellite data and ship-measured data, as well as the temporal and spatial distribution patterns.

[0034] Compared with other satellite detection methods, spaceborne SAR has obvious advantages in monitoring and extracting ocean fronts due to its all-weather, all-day, high spatial resolution and other characteristics. The surface seawater on both sides of the ocean front area has a strong velocity gradient and different physical properties, and the ocean front is affected by the interaction of convergence and divergence or strong shear wave flow and wind speed, resulting in significant differences in the imaging characteristics of the ocean front in SAR images and increased difficulty in interpreting the characteristics of the ocean front. There is no quantitative conclusion on the relationship between the ocean front in SAR images and temperature data. In summary, when the existing technology simulates the imaging of the ocean front, it is easy to cause a significant deviation between the simulation results and the actual situation, reducing the accuracy and reliability of monitoring.

[0035] In order to solve the above problems, an embodiment of the present invention provides an ocean front imaging simulation method, which can reduce the deviation between the simulation results and the actual situation and improve the simulation accuracy and reliability.

[0036] Figure 1 Flow chart of a method for simulating ocean front imaging provided by an embodiment of the present invention. Figure 1 As shown, the method includes the following steps.

[0037] Step S101, obtaining target sea surface temperature data of a target ocean area, wherein the target ocean area includes an ocean front area.

[0038] Step S102, extracting features of the ocean front region based on the target sea surface temperature data, and generating front line position features of the ocean front corresponding to the ocean front region.

[0039] Step S103, based on the front position characteristics, the target ocean area is divided into two background areas to be processed, so as to perform feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed, and generate enhanced target sea surface temperature data, and the two background areas to be processed are respectively located on both sides of the front.

[0040] Step S104, simulating the enhanced target sea surface temperature data based on the thermal wind theory to generate thermal flow velocity field data.

[0041] Step S105 , performing simulation imaging on the target ocean area according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area.

[0042] In this embodiment, first, target sea surface temperature data of a target ocean region is obtained. In this embodiment, the target ocean region includes an ocean front region.

[0043] The target ocean area refers to the sea area that needs to be studied for the simulation. It contains a specific geographical range and the ocean front is located in this area. The ocean front is the area where two different water masses meet in the ocean, usually manifested as an area with rapid changes in temperature, salinity or other physical properties. The existence of an ocean front affects local hydrodynamics, ecosystems and atmospheric conditions.

[0044] Sea surface temperature refers to the temperature at a certain depth (usually within a few meters) on the ocean surface. In this embodiment, the target sea surface temperature data of the target ocean area can be obtained by synthetic aperture radar (SAR). The target sea surface temperature data in this embodiment is the key basis for extracting the characteristics of the ocean front. Since the ocean front is usually manifested as a sharp change in water temperature, the sea surface temperature data can provide a strong basis for the positioning of the front.

[0045] Then, the features of the ocean front area are extracted based on the target sea surface temperature data to generate the front line position features of the ocean front corresponding to the ocean front area.

[0046] In this embodiment, the characteristics of the ocean front (such as the position of the front line) can be identified from the target sea surface temperature data, specifically through steps such as data processing, gradient calculation and threshold segmentation.

[0047] The front of an ocean front may include a boundary between water masses in the ocean. The water bodies on both sides of the front have different physical properties, the most significant difference being temperature. Extracting the location of the front can help distinguish the front area from the background sea area. Specifically, the location features of the front may include the geographical location of the front, i.e., longitude and latitude data. Furthermore, the morphological features and width features of the front may also be included.

[0048] After extracting the front position feature, the target ocean area can be divided into two background areas to be processed based on the front position feature. Then, the sea surface temperature corresponding to each of the two background areas to be processed can be enhanced to generate enhanced target sea surface temperature data. In this embodiment, the two background areas to be processed are located on both sides of the front.

[0049] In this embodiment, the front line of the ocean front divides the ocean area into two different water masses. The background areas on both sides of the front line usually represent the different characteristics of the two water masses, which are specifically manifested in that the temperature of one water mass is higher and the temperature of the other water mass is lower.

[0050] Feature enhancement is the processing of sea surface temperature data to make it closer to the actual observed ocean front characteristics. Since the resolution of the original temperature data may be low and the temperature change is not obvious enough, the temperature data needs to be artificially enhanced. Generally, the enhancement processing includes: for the water mass on one side of the front, if the temperature is higher, its temperature value is further enhanced; for the water mass on the other side, if the temperature is lower, the temperature value is appropriately weakened.

[0051] The enhanced temperature data can better reflect the characteristics of the real ocean front, so as to simulate the obvious temperature difference on both sides of the ocean front in reality, thereby improving the accuracy of the simulation.

[0052] Subsequently, the enhanced target sea surface temperature data can be simulated based on the thermal wind theory to generate thermal flow velocity field data.

[0053] In this embodiment, thermal winds may include changes in wind fields or water flows due to horizontal differences in temperature and density. The thermal wind effect, under the action of the earth's rotation and the Coriolis force, produces a flow perpendicular to the temperature gradient. The thermal wind theory describes how the temperature gradient affects ocean flows. Horizontal changes in temperature can cause changes in seawater density, which in turn produces water flows. This flow is called thermal wind.

[0054] The velocity field of thermal currents in the ocean is calculated using sea surface temperature data. The velocity field data of thermal currents can be calculated by convolution to calculate the temperature gradient and combining it with the thermal wind theory. The velocity field data includes the direction and size of the water flow, reflecting the flow conditions in the ocean front area.

[0055] Finally, the target ocean area is simulated and imaged according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area.

[0056] Based on the calculated thermal flow velocity field, a SAR image of the target ocean area is generated through numerical simulation. SAR imaging relies on the backscattering characteristics of radar signals. The disturbance of sea surface flow (such as thermal flow) on the waves will affect the backscattering coefficient. By calculating the changes in the wave spectrum caused by the thermal flow field, a simulated image that conforms to the actual observation characteristics can be generated.

[0057] The ocean front imaging simulation method based on the embodiment of the present invention can effectively extract the characteristics of the ocean front and generate high-quality simulation images by systematically acquiring, processing and analyzing the sea surface temperature data of the target ocean area. Specifically, the thermal wind theory is used to simulate the thermal flow velocity field, which enhances the understanding of the temperature and flow characteristics of the ocean front. Finally, based on the accurate backscattering coefficient calculation, the method can generate a target simulation image that is consistent with the actual observation data, thereby improving the accuracy of ocean front identification and analysis.

[0058] In an optional embodiment, when acquiring the target sea surface temperature data of the target ocean area, the initial sea surface temperature data of the target ocean area may be acquired first, and then the initial sea surface temperature data may be interpolated to generate the target sea surface temperature data, wherein the resolution of the target sea surface temperature data is higher than the resolution of the initial sea surface temperature data.

[0059] In this embodiment, it is first necessary to collect initial sea surface temperature data of the target ocean area. Similarly, the initial sea surface temperature data can be obtained based on SAR.

[0060] In practical applications, the initial sea surface temperature data may have a low spatial resolution, usually between a few kilometers and more than ten kilometers. This limits the accurate identification of small-scale features such as ocean fronts. Therefore, in order to improve the spatial resolution of the initial sea surface temperature data, the initial sea surface temperature data can be interpolated.

[0061] In this embodiment, the interpolation method for interpolating the initial sea surface temperature data may include DIVA interpolation (Data Interpolating Variational Analysis). Specifically, DIVA is an interpolation method based on variational analysis, which is mainly used to interpolate temperature data between uneven sampling points. It can smooth data and maintain high spatial continuity. Optionally, the interpolation method may also include Kriging interpolation, spline interpolation, and the like.

[0062] Through interpolation, the generated target sea surface temperature data has a higher spatial resolution, making the temperature value of each grid point more accurate. In this embodiment, the resolution of the target sea surface temperature data is higher than that of the initial data. For example, the resolution can be increased from 0.05° to 0.01° or less to better capture the details of the ocean front.

[0063] In an optional embodiment, when extracting features of the ocean front region based on the target sea surface temperature data and generating the front position features of the ocean front corresponding to the ocean front region, a temperature gradient threshold for distinguishing the ocean front region from the background region to be processed can be determined first. Then, based on the temperature gradient threshold, the target sea surface temperature data is processed by a gradient threshold segmentation method to extract the front position features.

[0064] In the ocean front region, a temperature gradient threshold (Ti) can be determined by analyzing the change in sea surface temperature data. The temperature gradient threshold can be used to distinguish the ocean front region from the surrounding background area to be processed. The temperature gradient in this embodiment may include the rate of temperature change within a specific spatial range, usually expressed as the amount of temperature change per unit distance. For example, if the temperature change is 0.03°C within a distance of 1 kilometer, the temperature gradient is 0.03°C / km.

[0065] Gradient threshold segmentation is an image processing method that classifies images based on data gradient changes. In image analysis, it can be used for edge detection to extract target features by setting specific gradient values.

[0066] In this embodiment, the target sea surface temperature data is processed using a gradient threshold segmentation method. Specifically, the sea surface temperature data can be divided into two categories according to a preset temperature gradient threshold Ti: one is an area with a temperature gradient greater than or equal to Ti, and the other is an area with a temperature gradient less than Ti.

[0067] In practical applications, the area with a gradient greater than Ti can be marked as an ocean front area, and the area with a gradient less than Ti can be marked as a background area to be processed.

[0068] Based on the ocean front areas divided in the above steps, the front line position of the ocean front can be determined by analyzing the spatial distribution characteristics of these areas.

[0069] In an optional embodiment, when performing feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed, the processing may be performed by the following method.

[0070] Specifically, for a target background area to be processed among the two background areas to be processed, the temperature data of the target background area to be processed is judged, and a judgment result is output.

[0071] If the judgment result indicates that the temperature data of the target background area to be processed is higher than the temperature data of the ocean front, the temperature data of the target background area to be processed is enhanced. If the judgment result indicates that the temperature data of the target background area to be processed is lower than the temperature data of the ocean front, the temperature data of the target background area to be processed is weakened.

[0072] The ocean front in this embodiment is a significant boundary in the target ocean area based on the temperature gradient change. There is usually a temperature difference on both sides of the front. The target background area to be processed refers to two areas divided in the target ocean area, and the two areas are located on both sides of the ocean front.

[0073] In the two background areas to be processed, the temperature data are compared respectively, mainly with the temperature at the front line of the ocean front. The judgment result can be used to determine whether the temperature of the area is higher or lower than the temperature on both sides of the front line.

[0074] If the judgment result shows that the temperature data of the target background area to be processed is higher than the temperature data of the ocean front, enhancement processing is performed. The purpose of enhancement processing is to make the temperature difference in the area more significant and reflect the temperature distribution in the actual ocean front phenomenon. By increasing the temperature difference, the temperature contrast on both sides of the front line can be made more distinct, so that the thermal flow velocity field of the ocean front can be simulated more accurately in the thermal wind simulation.

[0075] If the judgment result shows that the temperature data of the target background area to be processed is lower than the temperature data of the ocean front, then attenuation processing is performed. Attenuation processing is to reduce the temperature of the area to make it consistent with the cold side characteristics of the actual ocean front phenomenon. By lowering the temperature, the cold temperature difference on both sides of the front is simulated to make the simulation more realistic. Both enhancement processing and attenuation processing can be used to adjust the sea surface temperature data to make it more consistent with the observed ocean front temperature distribution characteristics. The water bodies on both sides of the ocean front usually have different thermodynamic properties. The water body on one side of the front may be heated by solar radiation and have a higher temperature; while the water body on the other side may have a lower temperature due to the influence of ocean currents or wind. Through enhancement and attenuation processing, the simulation data can better reflect this natural phenomenon.

[0076] In practical applications, the corresponding enhancement coefficients and attenuation coefficients can be determined for the background areas to be processed on both sides. Specifically, the enhancement coefficients and attenuation coefficients can be flexibly set in combination with actual ocean data and simulation requirements. In practical applications, the enhancement coefficients and attenuation coefficients can be smaller in the area near the front line and gradually increase in the area away from the front line, making the front line features more prominent.

[0077] In an optional embodiment, when simulating the enhanced target sea surface temperature data based on the thermal wind theory to generate thermal flow velocity field data, a planar convolution operation can be performed on the enhanced target sea surface temperature data by using the Sobel operator to generate sea surface temperature gradient data; then, based on the thermal wind theory and the sea surface temperature gradient data, the thermal flow velocity field data is calculated.

[0078] The Sobel operator can be used in image processing for edge detection to calculate the gradient of pixel value changes in an image. It can obtain image gradients in the horizontal and vertical directions by performing convolution operations with two-dimensional image data (sea surface temperature data in this embodiment).

[0079] In practical applications, SAR images usually have a resolution of meters or hundreds of meters. When calculating thermal flow velocity, the sea surface temperature gradient data used often has a lower spatial resolution. Since the change in temperature gradient is an important factor affecting the calculation of flow velocity, low-resolution data may lead to inaccurate estimation of the flow field and fail to reflect the true characteristics of ocean flow.

[0080] In order to improve the spatial resolution of the thermal flow velocity field data, the thermal flow velocity field data can be further interpolated. By applying a suitable interpolation algorithm, a denser and more uniform grid can be generated based on the lower resolution data. This can not only improve the spatial resolution of the velocity field, but also more accurately capture the detailed characteristics of the ocean flow.

[0081] The high-resolution thermal flow velocity field data obtained by interpolation can be effectively combined with high-resolution SAR images to enhance the understanding and monitoring capabilities of ocean dynamics.

[0082] Optionally, the sea surface temperature gradient data includes horizontal sea surface temperature gradient data and vertical sea surface temperature gradient data.

[0083] The horizontal sea surface temperature gradient data can be calculated based on the following formula (1):

[0084]

[0085] Among them, G x is the horizontal sea surface temperature gradient data, and A is the enhanced target sea surface temperature data;

[0086] The vertical sea surface temperature gradient data can be calculated based on the following formula (2):

[0087]

[0088] Among them, G y is the vertical sea surface temperature gradient data, and A is the enhanced target sea surface temperature data;

[0089] The ocean front thermal current velocity vector corresponding to the thermal current velocity field data can be calculated based on the following formula (3):

[0090] V=(F×U x ,F×U y )(3)

[0091] Wherein, V is the ocean front thermal current velocity vector, and F is the thermal wind coefficient. It should be noted that in this embodiment, assuming that the flow is in the northern hemisphere, in order to ensure the correct direction of rotation of the flow velocity, the velocity is defined as follows: U x =-G y , U y =G x .

[0092] The thermal wind coefficient can be calculated based on the following formula (4):

[0093]

[0094] Where H is the thermal wind depth, 0≥H≤5, g is the gravitational acceleration, f is the Coriolis force parameter, and ρ0 is the reference density of seawater.

[0095] In this embodiment, in the offshore surface waters, the change in seawater density is mainly affected by temperature and salinity. However, in shallow waters (within the range of 0-5 meters), due to the small changes in temperature and salinity, the density can be approximately regarded as a constant. This simplification helps to reduce the complexity of the calculation and does not significantly affect the calculation accuracy of the thermal wind effect. Therefore, the value range of the thermal wind depth H is set to 0 to 5 meters based on the reasonable assumption that the temperature gradient in the shallow seawater is significant, while the density remains relatively constant.

[0096] In an optional embodiment, after obtaining the thermal flow velocity field data, the target ocean area can be simulated and imaged according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area.

[0097] Specifically, the action spectrum balance equation is solved based on the thermal flow velocity field data and the sea surface wind field calculation.

[0099] In this embodiment, the action spectrum balance equation is first calculated and solved according to the thermal flow velocity field and the sea surface wind field. The action spectrum balance equation is shown in the following formula (5):

[0100]

[0101] Where N is the spectral density of microscale wave action, x = (x, y) is the spatial position vector, k = (k x ,k y ) is the wave number vector, U is the thermal flow velocity field, c g is the group velocity of the modulated wave, and S(x,k,t) is the source function.

[0102] In this embodiment, the source function may include the sum of wind field input, nonlinear wave-wave action, and dispersion.

[0103] Then, the sea surface backscattering coefficient caused by the thermal flow field disturbance is determined based on the action spectrum balance equation.

[0104] In this embodiment, based on the above action spectrum balance equation and the normalized backscatter coefficient of the background sea surface, the backscatter coefficient of the sea surface generated by the thermal flow velocity field disturbance is determined. The relationship between the backscatter coefficient of the sea surface generated by the thermal flow velocity field disturbance and the normalized backscatter coefficient of the background sea surface is shown in the following formula (6):

[0105]

[0106] Among them, δσ is the sea surface backscatter coefficient caused by the thermal flow velocity field disturbance, σ0 is the normalized backscatter coefficient of the background sea surface, γ is the ratio of the Bragg wave group velocity to the phase velocity, τ r represents the relaxation time, is the velocity gradient of the thermal flow velocity field and the radar line of sight, δE is the modulation of the wave energy spectrum density caused by the thermal flow velocity field, and E0 is the unmodulated wave energy spectrum density.

[0107] Then, the modulated sea surface backscatter coefficient is calculated based on the normalized backscatter coefficient of the background sea surface, and the modulation methods include tilt modulation, fluid dynamics modulation and velocity bunching modulation.

[0108] In this embodiment, firstly, the normalized backscatter coefficient (NRCS) of the background sea surface can be obtained based on the sea wave parameters and the radar parameters.

[0109] Specifically, the normalized backscatter coefficient of the background sea surface is calculated by combining sea wave parameters such as sea surface wind field, wavelength, wave height, wave direction, radar band, incident angle, resolution and other input radar parameters. The calculation formula is shown in the following formula (7):

[0110] σ0(θ) pp =4πk 4 cos 4 θ|g pp (θ)| 2 W(2k sin θ,0) (7)

[0111] Where W(·) is the two-dimensional wave power spectrum, g pp (θ) is the Fresnel coefficient, PP is the polarization mode, k = (k x ,k y ) is the wave number vector and θ is the radar incident angle.

[0112] Then, based on the above-mentioned background sea surface normalized backscatter coefficient, the modulated sea surface backscatter coefficient, that is, the modulated sea surface normalized backscatter coefficient, is calculated.

[0113] In this embodiment, the tilt, fluid mechanics and velocity beamforming modulation effects can be integrated to simulate ocean front SAR imaging.

[0114] Specifically, the sea surface is usually composed of swells with longer wavelengths and wind waves with shorter wavelengths. Long waves have linear tilt modulation and fluid dynamics modulation effects on short waves. In addition, SAR imaging needs to consider velocity beam modulation. The normalized backscatter coefficient of the sea surface is obtained by comprehensively considering tilt modulation, fluid dynamics and velocity beam modulation to achieve SAR imaging simulation of the target ocean front area. The modulated normalized backscatter coefficient of the sea surface can be calculated based on the following formula (8):

[0115]

[0116] in, is the modulation transfer function, σ is the normalized backscattering coefficient of the sea surface after modulation, - σ0 is the normalized backscatter coefficient of the background sea surface, FFT is the Fourier transform, is the velocity bunching modulation function, is the coefficient of wave spectrum correlation.

[0118] In this embodiment, the modulation method includes tilt modulation, fluid dynamics modulation and velocity bunching modulation. The tilt modulation, fluid dynamics modulation and velocity bunching modulation are described in detail below:

[0119] 1. Tilt modulation

[0120] Tilt modulation is caused by the tilt of short waves due to long waves, which causes the incident electromagnetic waves to illuminate different locations in the sea scene at different local incident angles, thereby changing the backscatter coefficient value. Long waves can be imaged in SAR images through tilt modulation. The tilt modulation transfer functions of HH and VV polarizations are different. The polarization tilt modulation transfer function of VV is As shown in the following formula (9), the polarization tilt modulation transfer function of HH is As shown in the following formula (10):

[0121]

[0122]

[0123] Among them, k l is the component of the wave vector in the radar line of sight, and θ′ is the local incident angle.

[0124] 2. Fluid mechanics modulation

[0125] Fluid mechanics modulation refers to the interaction between long waves or ocean currents and short waves, which causes the short waves to converge and diverge. Fluid mechanics modulation transfer function T h As shown in the following formula (11):

[0126]

[0127] Among them, μ is the relaxation factor, ω is the angular frequency, k is the wave number of the wave spectrum, and Y r +iY i is a complex vector representing the feedback.

[0128] 3. Velocity beamforming modulation

[0129] Velocity beamforming modulation transfer function As shown in the following formula (12):

[0130]

[0131] Where R is the distance between the target and the platform, V is the platform speed, and θ is the radar incident angle.

[0132] Finally, the overall backscattering coefficient of the target ocean front area is determined according to the sea surface backscattering coefficient generated by the thermal flow velocity field disturbance and the modulated sea surface backscattering coefficient, so as to perform simulation imaging according to the overall backscattering coefficient and obtain a simulation image corresponding to the target ocean front area.

[0133] σ f =σ+δσ (13)

[0134] In this embodiment, the sea surface backscatter coefficient generated by the thermal flow velocity field disturbance and the modulated sea surface backscatter coefficient are superimposed to obtain the overall normalized backscatter coefficient of the target ocean front area, and simulated imaging is performed to obtain a simulated image corresponding to the target ocean area.

[0135] A method for simulating ocean front imaging provided by an embodiment of the present invention is described below in conjunction with specific embodiments.

[0136] Assuming that the target ocean area is a coastal ocean front area, the sea surface temperature information of the coastal ocean front area is first obtained. In this embodiment, the fusion field OSTIA sea surface temperature data is used as an example. In order to improve the accuracy of the data, the DIVA method is used to interpolate the sea surface temperature data with a resolution of 0.02°×0.02°. Among them, the sea surface temperature information after interpolation is as follows Figure 2 shown.

[0137] After interpolation processing, the ocean front characteristics of the coastal ocean front area are more significant. The temperature gradient threshold is set to 0.09 / km. The front line is extracted through this threshold to obtain the front line position and its latitude and longitude coordinate information. Among them, the front line schematic diagram of the coastal ocean front area is as follows Figure 3 shown.

[0138] Compared with the ocean front extracted from measured data, the ocean front extracted using OSTIA is wider and weaker in strength. In order to be more consistent with the actual characteristics of the ocean front, it needs to be enhanced. The temperature data on both sides of the front are adjusted: for the high-temperature area on one side of the front (such as the warm water area along the coast), temperature enhancement processing is performed, and the specific enhancement coefficient is gradually reduced from 1.045 to 1.002; and for the low-temperature area on the other side of the front (colder offshore waters), a weakening treatment is performed, and the weakening coefficient is gradually increased from 0.96 to 0.995. After these treatments, the width and strength of the ocean front are enhanced, making the front more consistent with the characteristics of actual observations. The temperature distribution diagram after enhancement is shown below. Figure 4 shown.

[0139] After completing the temperature enhancement processing, the enhanced sea surface temperature data is simulated based on the thermal wind theory to obtain the ocean front thermal flow velocity field.

[0140] Firstly, the Sobel operator is used to perform a two-dimensional convolution operation on the enhanced sea surface temperature data to obtain the temperature gradient data in the horizontal direction and the temperature gradient data in the vertical direction respectively.

[0141] Afterwards, based on the thermal wind theory and the sea surface temperature gradient data, the thermal current velocity field data is calculated. After the thermal current velocity field data is interpolated, the distribution diagram of the thermal current velocity field in the coastal ocean front area is as follows: Figure 5 shown.

[0142] The action spectrum balance equation is solved based on the thermal flow velocity field data and the sea surface wind field calculation. The sea surface backscatter coefficient caused by the thermal flow field disturbance is determined based on the action spectrum balance equation and the normalized backscatter coefficient of the background sea surface; then the modulated sea surface backscatter coefficient is calculated based on the normalized backscatter coefficient of the background sea surface; the sea surface backscatter coefficient caused by the thermal flow data field disturbance and the modulated sea surface backscatter coefficient are combined to determine the overall backscatter characteristics of the ocean front. In this process, the backscatter coefficient is modulated based on the line-of-sight velocity gradient of the radar, and the modulation methods include tilt modulation, fluid dynamics modulation and velocity beamforming modulation. In this embodiment, when determining the sea surface backscatter coefficient caused by the thermal flow field disturbance, a schematic diagram of the line-of-sight velocity gradient of the radar that needs to be used is shown as follows. Figure 6 shown.

[0143] In this embodiment, the wind direction of the wind field is 0°, the wind speed is 7m / s, the wavelength is 300 meters, the wave height is 0.5 meters, the wave direction is 300°, the radar band is L-band, the incident angle is 45°, and the resolution is 0.002°. Based on the above parameters, the Bragg wave-current interaction theory is applied to calculate the backscattering coefficient of the ocean front. Through simulation calculation, the backscattering coefficient distribution of the ocean front region of L-band VV polarization is obtained. Among them, the schematic diagram of the backscattering coefficient distribution of the L-band VV polarization ocean thermal sea surface based on the thermal flow field is shown in Figure 7 shown.

[0144] Finally, the overall backscatter coefficient of the target area is determined based on the sea surface backscatter coefficient generated by the thermal flow field disturbance and the modulated normalized backscatter coefficient of the sea surface, and simulated imaging is performed to generate a target simulation image of the coastal ocean front area. This image can show the dynamic characteristics of the thermal flow of the ocean front, which helps to deeply understand the manifestation of the ocean front in SAR images and its role in ocean monitoring.

[0145] Based on the ocean front imaging simulation method provided by the embodiment of the present invention, the embodiment of the present invention provides an ocean front imaging simulation device. Figure 8 As shown, the device includes an acquisition module 801 , an extraction module 802 , a division module 803 , a simulation module 804 and an imaging module 805 .

[0146] The acquisition module 801 is used to acquire target sea surface temperature data of a target ocean area, where the target ocean area includes an ocean front area.

[0147] The extraction module 802 is used to extract features of the ocean front region based on the target sea surface temperature data, and generate front line position features of the ocean front corresponding to the ocean front region.

[0148] The division module 803 is used to divide the target ocean area into two background areas to be processed based on the front position characteristics, so as to perform feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed and generate enhanced target sea surface temperature data. The two background areas to be processed are located on both sides of the front.

[0149] The simulation module 804 is used to simulate the enhanced target sea surface temperature data based on the thermal wind theory to generate thermal flow velocity field data.

[0150] The imaging module 805 is used to perform simulation imaging of the target ocean area according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area.

[0151] According to an embodiment of the present invention, the acquisition module 801 is specifically used to acquire initial sea surface temperature data of a target ocean area and perform interpolation processing on the initial sea surface temperature data to generate target sea surface temperature data, wherein the resolution of the target sea surface temperature data is higher than the resolution of the initial sea surface temperature data.

[0152] According to an embodiment of the present invention, the extraction module 802 is specifically used to determine a temperature gradient threshold for distinguishing an ocean front area from a background area to be processed; based on the temperature gradient threshold, the target sea surface temperature data is processed by a gradient threshold segmentation method to extract the front position characteristics.

[0153] According to an embodiment of the present invention, the division module 803 is specifically used to judge the temperature data of the target background area to be processed among the two background areas to be processed, and output the judgment result; if the judgment result shows that the temperature data of the target background area to be processed is higher than the temperature data of the ocean front, the temperature data of the target background area to be processed is enhanced; if the judgment result shows that the temperature data of the target background area to be processed is lower than the temperature data of the ocean front, the temperature data of the target background area to be processed is weakened.

[0154] According to an embodiment of the present invention, the simulation module 804 is specifically used to generate sea surface temperature gradient data by performing a planar convolution operation with the enhanced target sea surface temperature data through the Sobel operator; and calculate the thermal flow velocity field data based on the thermal wind theory and the sea surface temperature gradient data.

[0155] According to an embodiment of the present invention, the sea surface temperature gradient data includes horizontal sea surface temperature gradient data and vertical sea surface temperature gradient data;

[0156] The horizontal sea surface temperature gradient data can be calculated based on the following formula (1):

[0157]

[0158] Among them, G x is the horizontal sea surface temperature gradient data, and A is the enhanced target sea surface temperature data;

[0159] The vertical sea surface temperature gradient data can be calculated based on the following formula (2):

[0160]

[0161] Among them, G y is the vertical sea surface temperature gradient data, and A is the enhanced target sea surface temperature data;

[0162] The ocean front thermal current velocity vector corresponding to the thermal current velocity field data can be calculated based on the following formula (3):

[0163] V=(F×U x ,F×U y )(3)

[0164] Among them, V is the ocean front thermal current velocity vector, F is the thermal wind coefficient, U x =-G y , U y =G x ;

[0165] The thermal wind coefficient can be calculated based on the following formula (4):

[0166]

[0167] Where H is the thermal wind depth, 0≥H≤5, g is the gravitational acceleration, f is the Coriolis force parameter, and ρ0 is the reference density of seawater.

[0168] According to an embodiment of the present invention, the imaging module 805 is specifically used to calculate and solve the action spectrum balance equation based on the thermal flow velocity field data and the sea surface wind field; then determine the sea surface backscattering coefficient generated by the thermal flow field disturbance based on the action spectrum balance equation and the background sea surface normalized backscattering coefficient; then calculate the modulated sea surface backscattering coefficient based on the background sea surface normalized backscattering coefficient, and the modulation method includes tilt modulation, fluid dynamics modulation and velocity beam modulation; determine the overall backscattering coefficient of the target ocean area based on the sea surface backscattering coefficient generated by the thermal flow field disturbance and the modulated sea surface backscattering coefficient, so as to perform simulated imaging based on the overall backscattering coefficient to obtain a target simulation image corresponding to the target ocean area.

[0169] An embodiment of the present invention further provides an electronic device, comprising: at least one processor; and a memory in communication with the at least one processor. The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the electronic device executes the method of the embodiment of the present invention.

[0170] An embodiment of the present invention further provides a non-transitory machine-readable medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is used to cause the computer to execute the method of the embodiment of the present invention.

[0171] An embodiment of the present invention further provides a computer program product, including a computer program, wherein the computer program, when executed by a processor of a computer, is used to enable the computer to execute the method of the embodiment of the present invention.

[0172] refer to Fig. 9 , a block diagram of an electronic device that can be used as a server or client of an embodiment of the present invention will now be described, which is an example of a hardware device that can be applied to various aspects of the present invention. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0173] like Fig. 9 As shown, the electronic device includes a computing unit 901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 902 or a computer program loaded from a storage unit 908 into a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the electronic device can also be stored. The computing unit 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0174] Multiple components in the electronic device are connected to the I / O interface 905, including: an input unit 906, an output unit 907, a storage unit 908, and a communication unit 909. The input unit 906 can be any type of device that can input information to the electronic device, and the input unit 906 can receive input digital or character information, and generate key signal input related to user settings and / or function control of the electronic device. The output unit 907 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 908 can include but is not limited to a disk, an optical disk. The communication unit 909 allows the electronic device to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0175] The computing unit 901 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a CPU, a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 901 performs the various methods and processes described above. For example, in some embodiments, the method embodiments of the present invention may be implemented as a computer program, which is tangibly contained in a machine-readable medium, such as a storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on an electronic device via a ROM 902 and / or a communication unit 909. In some embodiments, the computing unit 901 may be configured to perform the above method in any other appropriate manner (e.g., by means of firmware).

[0176] The computer programs for implementing the methods of the embodiments of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer programs may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0177] In the context of an embodiment of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable signal medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0178] It should be noted that the term "including" and its variations used in the embodiments of the present invention are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". The modifications of "one" and "multiple" mentioned in the embodiments of the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless the context clearly indicates otherwise, it should be understood as "one or more".

[0179] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of the present invention are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0180] The various steps described in the method implementation methods provided in the embodiments of the present invention may be performed in different orders and / or in parallel. In addition, the method implementation methods may include additional steps and / or omit the steps shown. The scope of protection of the present invention is not limited in this respect.

[0181] The term "embodiment" in this specification refers to specific features, structures or characteristics described in conjunction with the embodiment that can be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily mean the same embodiment, nor does it mean that it is mutually exclusive with other embodiments and is independent or optional. The various embodiments in this specification are described in a related manner, and the same or similar parts between the various embodiments refer to each other. In particular, for the device, equipment, and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts refer to the partial description of the method embodiment.

[0182] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of patent protection. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the attached claims.

Claims

1. A method for simulating ocean front imaging, characterized in that: include: Acquiring target sea surface temperature data of a target ocean region, wherein the target ocean region includes an ocean front region; Extracting features of the ocean front region based on the target sea surface temperature data to generate frontal position features of the ocean front corresponding to the ocean front region; Based on the front position feature, the target ocean area is divided into two background areas to be processed, so as to perform feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed respectively, and generate enhanced target sea surface temperature data, wherein the two background areas to be processed are respectively located on both sides of the front; Based on the thermal wind theory, the enhanced target sea surface temperature data is simulated to generate thermal flow velocity field data; The target ocean area is simulated and imaged according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area.

2. The method according to claim 1, characterized in that The step of obtaining target sea surface temperature data of a target ocean area includes: Acquiring initial sea surface temperature data of the target ocean area; The initial sea surface temperature data is interpolated to generate the target sea surface temperature data, wherein the resolution of the target sea surface temperature data is higher than the resolution of the initial sea surface temperature data.

3. The method according to claim 1, characterized in that: The extracting features of the ocean front region based on the target sea surface temperature data to generate the front line position features of the ocean front corresponding to the ocean front region includes: Determining a temperature gradient threshold for distinguishing the ocean front region from the background region to be processed; Based on the temperature gradient threshold, the target sea surface temperature data is processed by a gradient threshold segmentation method to extract the front position feature.

4. The method according to claim 1, characterized in that Performing feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed, including: For a target background area to be processed among the two background areas to be processed, judging the temperature data of the target background area to be processed, and outputting a judgment result; If the judgment result indicates that the temperature data of the target background area to be processed is higher than the temperature data of the front line position of the ocean front, then the temperature data of the target background area to be processed is enhanced; If the judgment result indicates that the temperature data of the target background area to be processed is lower than the temperature data of the front line position of the ocean front, the temperature data of the target background area to be processed is weakened.

5. The method according to claim 1, characterized in that The enhanced target sea surface temperature data is simulated based on the thermal wind theory to generate thermal flow velocity field data, including: Performing a planar convolution operation on the enhanced target sea surface temperature data through a Sobel operator to generate sea surface temperature gradient data; The thermal flow velocity field data is calculated based on the thermal wind theory and the sea surface temperature gradient data.

6. The method according to claim 5, characterized in that The sea surface temperature gradient data includes horizontal sea surface temperature gradient data and vertical sea surface temperature gradient data; The horizontal sea surface temperature gradient data can be calculated based on the following formula (1): Among them, G x is the horizontal sea surface temperature gradient data, and A is the enhanced target sea surface temperature data; The vertical sea surface temperature gradient data can be calculated based on the following formula (2): Among them, G y is the vertical sea surface temperature gradient data, and A is the enhanced target sea surface temperature data; The ocean front thermal flow velocity vector corresponding to the thermal flow velocity field data can be calculated based on the following formula (3): V=(F×U x ,F×U y ) (3) Among them, V is the ocean front thermal current velocity vector, F is the thermal wind coefficient, U x =-G y , U y =G x ; The thermal wind coefficient can be calculated based on the following formula (4): Where H is the thermal wind depth, 0≥H≤5, g is the gravitational acceleration, f is the Coriolis force parameter, and ρ0 is the reference density of seawater.

7. The method according to claim 1, characterized in that The performing simulation imaging of the target ocean area according to the thermal flow velocity field data to obtain a target simulation image corresponding to the target ocean area includes: Calculate and solve the action spectrum balance equation according to the thermal flow velocity field and the sea surface wind field; Determining the sea surface backscattering coefficient generated by the thermal flow velocity field disturbance according to the action spectrum balance equation and the background sea surface normalized backscattering coefficient; Calculating a modulated sea surface backscatter coefficient based on a background sea surface normalized backscatter coefficient, wherein the modulation method includes tilt modulation, fluid dynamics modulation and velocity bunching modulation; The overall backscatter coefficient of the target ocean area is determined according to the sea surface backscatter coefficient generated by the thermal flow field disturbance and the modulated sea surface backscatter coefficient, so as to perform simulated imaging according to the overall backscatter coefficient to obtain a target simulated image corresponding to the target ocean area.

8. An ocean front imaging simulation device, characterized in that: include: An acquisition module, used to acquire target sea surface temperature data of a target ocean area, wherein the target ocean area includes an ocean front area; An extraction module, configured to extract features of the ocean front region based on the target sea surface temperature data, and generate front line position features of the ocean front corresponding to the ocean front region; A division module, used for dividing the target ocean area into two background areas to be processed based on the front position characteristics, so as to perform feature enhancement processing on the sea surface temperatures corresponding to the two background areas to be processed respectively, and generate enhanced target sea surface temperature data, wherein the two background areas to be processed are respectively located on both sides of the front; A simulation module, used for simulating the enhanced target sea surface temperature data based on thermal wind theory to generate thermal flow velocity field data; An imaging module is used to perform simulated imaging of the target ocean area according to the thermal flow velocity field data to obtain a target simulated image corresponding to the target ocean area.

9. An electronic device, comprising: A processor, and a memory storing a program, wherein the program comprises instructions, which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory machine-readable medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 7.

Images