SAR image optimization method, apparatus, equipment and media based on data fusion

Abstract

This application discloses a SAR image optimization method, apparatus, device, and medium based on data fusion, relating to the field of image optimization technology. The method includes: preprocessing a received SAR image to establish a pixel coordinate system for the SAR image, and acquiring target data of a target object in the SAR image through an external sensor; performing an affine transformation based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates; establishing a reverse correction relationship between pixel coordinates and spherical coordinates based on the fisheye correction principle and using the pixel coordinate system to correct the initial mapping relationship, obtaining a bidirectional mapping function between pixel coordinates and target geographic coordinates; mapping the target spatial coordinates in the target data using the bidirectional mapping function to obtain the target pixel coordinates, and displaying the target data in the SAR image based on the target pixel coordinates to obtain an optimized SAR image fused with target data.

Description

Technical Field

[0001] This invention relates to the field of image optimization technology, and in particular to SAR image optimization methods, apparatus, devices and media based on data fusion. Background Technology

[0002] In applications of Synthetic Aperture Radar (SAR) imaging, SAR images are widely used for battlefield situational awareness due to their all-weather, day-and-night imaging capabilities. However, due to the unique nature of their imaging mechanism, SAR images often lack intuitive geometric and optical features, making it difficult to directly correlate them with the location and attributes of targets in the actual scene. Meanwhile, other sensors such as radar and ADS-B (Automatic Dependent Surveillance-Broadcast) can detect and identify targets within the SAR coverage area in real time, but this target information is typically displayed independently as two-dimensional map annotations. This separation of image and target information can easily lead to misunderstandings by operators when assessing the target situation, increasing the burden of information processing and comparison, and reducing the efficiency of situational awareness and decision-making.

[0003] In summary, how to achieve accurate fusion and visualization of target object data in SAR images to improve image interpretation capabilities and the efficiency of multi-source information utilization is an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a SAR image optimization method, apparatus, device, and medium based on data fusion, which can achieve accurate fusion and visualization of target object data in SAR images to improve image interpretation capabilities and the efficiency of multi-source information utilization. The specific solution is as follows: Firstly, this application provides a SAR image optimization method based on data fusion, applied to an image optimization system, comprising: The received SAR image is preprocessed to establish the pixel coordinate system of the SAR image, and the target data of the target object in the SAR image is obtained through an external sensor. An affine transformation is performed based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates; Based on the fisheye orthodontic principle and using the pixel coordinate system, a reverse correction relationship between pixel coordinates and spherical coordinates is established to correct the initial mapping relationship, thereby obtaining a bidirectional mapping function between pixel coordinates and target geographic coordinates. The target spatial coordinates in the target data are mapped by the bidirectional mapping function to obtain the target pixel coordinates, and the target data is displayed in the SAR image according to the target pixel coordinates to obtain an optimized SAR image that fuses the target data.

[0005] Optionally, the preprocessing of the received SAR image to establish the pixel coordinate system of the SAR image includes: The received SAR images are preprocessed to obtain the corresponding imaging parameters; A corresponding pixel coordinate system is established for the SAR image based on the imaging parameters.

[0006] Optionally, the step of performing an affine transformation based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates includes: The vertex pixel coordinates of each vertex of the SAR image are determined using the pixel coordinate system, and the vertex geographic coordinates of each vertex of the SAR image in the target geographic coordinate system are also determined. An affine transformation is performed based on the vertex pixel coordinates and the vertex geographic coordinates to establish an initial mapping relationship between the pixel coordinates and the target geographic coordinates.

[0007] Optionally, the step of establishing a reverse correction relationship between pixel coordinates and spherical coordinates based on the fisheye orthodontic principle and using the pixel coordinate system to correct the initial mapping relationship and obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates includes: The spherical projection distortion of the pixel coordinate system is eliminated according to the fisheye orthodontic principle to obtain distortion-free planar coordinates, and the distortion-free planar coordinates are converted into spherical coordinates to establish a reverse correction relationship between pixel coordinates and spherical coordinates. The initial mapping relationship is nonlinearly modified by the reverse correction relationship to obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates.

[0008] Optionally, the step of eliminating the spherical projection distortion of the pixel coordinate system according to the fisheye orthogonal principle to obtain distortion-free planar coordinates includes: Determine the equivalent focal length of the SAR image; Using the imaging center of the SAR image as the origin, the pixel coordinates of the pixel coordinate system are normalized and polar transformed based on the equivalent focal length to obtain the corresponding normalized polar coordinates. Based on the fisheye orthogonal principle, the normalized polar coordinates are reverse-mapped to eliminate spherical projection distortion and obtain distortion-free planar coordinates.

[0009] Optionally, the step of mapping the target spatial coordinates in the target data through the bidirectional mapping function to obtain the target pixel coordinates, and displaying the target data in the SAR image according to the target pixel coordinates to obtain an optimized SAR image fused with the target data, includes: Determine the target spatial coordinates of the target object based on the target data; The target spatial coordinates are input into the bidirectional mapping function to map the target spatial coordinates into target pixel coordinates; The target location of the target object in the SAR image is determined based on the target pixel coordinates and the pixel coordinate system. Target symbols representing the target object are superimposed on the target location in the SAR image, and the target data is displayed to obtain an optimized SAR image that fuses the target data.

[0010] Optionally, the step of displaying the target data in the SAR image based on the target pixel coordinates to obtain an optimized SAR image fused with the target data further includes: Historical target data of the target object in the SAR image is obtained, and the historical target spatial coordinates in the historical target data are mapped by the bidirectional mapping function to obtain the historical target pixel coordinates; Based on the historical target pixel coordinates and the pixel coordinate system, the historical target position of the target object in the SAR image is determined; The historical target locations in the SAR image are overlaid with target symbols used to characterize the target object, and the historical target data is displayed. Lines are also drawn connecting the historical target locations to generate the movement trajectory of the target object.

[0011] Secondly, this application provides a SAR image optimization device based on data fusion, applied to an image optimization system, comprising: The data acquisition module is used to preprocess the received SAR image to establish the pixel coordinate system of the SAR image and acquire the target data of the target object in the SAR image through an external sensor. The affine transformation module is used to perform affine transformations based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates. The relationship establishment module is used to establish a reverse correction relationship between pixel coordinates and spherical coordinates based on the fisheye orthodontic principle and using the pixel coordinate system, so as to correct the initial mapping relationship and obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates. The data display module is used to map the target spatial coordinates in the target data through the bidirectional mapping function to obtain the target pixel coordinates, and to display the target data in the SAR image according to the target pixel coordinates to obtain an optimized SAR image that fuses the target data.

[0012] Thirdly, this application provides an electronic device, comprising: Memory, used to store computer programs; A processor is used to execute the computer program to implement the aforementioned data fusion-based SAR image optimization method.

[0013] Fourthly, this application provides a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned SAR image optimization method based on data fusion.

[0014] In this application, the received SAR image is preprocessed to establish a pixel coordinate system for the SAR image, and target data of the target object in the SAR image is acquired through an external sensor; an affine transformation is performed based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates; according to the fisheye correction principle and using the pixel coordinate system, a reverse correction relationship between pixel coordinates and spherical coordinates is established to correct the initial mapping relationship, resulting in a bidirectional mapping function between pixel coordinates and target geographic coordinates; the target spatial coordinates in the target data are mapped through the bidirectional mapping function to obtain target pixel coordinates, and the target data is displayed in the SAR image based on the target pixel coordinates to obtain an optimized SAR image fused with the target data. As can be seen from the above, this application first preprocesses the SAR image and establishes a pixel coordinate system, acquires target data of the target object through an external sensor, and then performs an affine transformation based on the pixel coordinate system to construct an initial mapping relationship between pixel coordinates and target geographic coordinates. Combining the fisheye correction principle, a reverse correction relationship between pixel coordinates and spherical coordinates is established to correct the initial mapping relationship, resulting in a bidirectional mapping function between pixel coordinates and target geographic coordinates. This function is used to map the target spatial coordinates in the target data to target pixel coordinates. Finally, the target data is superimposed and displayed in the SAR image to generate an optimized SAR image that fuses the target data. In this way, through the above-described process of this application, the pixel coordinate system is established by preprocessing the SAR image and the initial mapping is constructed by using affine transformation, which can quickly establish the basic correspondence between pixels and geographic coordinates; the mapping is optimized by establishing a reverse correction relationship based on the fisheye orthogonal principle, which can effectively correct coordinate mapping deviations and improve coordinate transformation accuracy; the target data and SAR image are fused and displayed using a bidirectional mapping function, which can accurately match the target spatial information with the image position, realize the fusion display of SAR image and target information on the same screen, enhance the information integrity and positioning accuracy of SAR image, improve the effectiveness of data fusion and the reliability of task execution, and thus realize the accurate fusion and visualization display of target object data in SAR image to improve image interpretation capability and multi-source information utilization efficiency. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0016] Figure 1 This is a flowchart of a SAR image optimization method based on data fusion disclosed in this application; Figure 2 This is a system flowchart of a SAR image optimization method based on data fusion disclosed in this application; Figure 3 This is a block diagram illustrating the system composition principle of a SAR image optimization method based on data fusion disclosed in this application; Figure 4 This is a schematic diagram illustrating the effect of SAR image fusion target data disclosed in this application; Figure 5 This is a schematic diagram of the structure of a SAR image optimization device based on data fusion disclosed in this application; Figure 6 This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Due to the unique imaging mechanism, SAR images often lack intuitive geometric and optical features, making it difficult to directly correlate them with the location and attributes of targets in the actual scene. Meanwhile, other sensors such as radar and ADS-B can detect and identify targets within the SAR coverage area in real time, but this target information is typically displayed independently as two-dimensional map annotations. This separation of image and target information can easily lead to misunderstandings by operators when assessing the target situation, increasing the burden of information processing and comparison, and reducing situational awareness and decision-making efficiency.

[0019] To overcome the aforementioned technical problems, this application provides a SAR image optimization method based on data fusion, which can achieve accurate fusion and visualization of target object data in SAR images to improve image interpretation capabilities and the efficiency of multi-source information utilization.

[0020] See Figure 1 As shown, this embodiment of the invention discloses a SAR image optimization method based on data fusion, applied to an image optimization system, comprising: Step S11: Preprocess the received SAR image to establish the pixel coordinate system of the SAR image, and acquire the target data of the target object in the SAR image through an external sensor.

[0021] In this embodiment, the received SAR image is preprocessed to construct a pixel coordinate system for the SAR image, and target data of the target object within the SAR image is acquired through external sensors. These external sensors include radar, AIS (Automatic Identification System), ADS-B, and other sensors connected to the image optimization system; the target object is the object being monitored; the target data includes target spatial coordinates and data, such as radar target data (providing polar coordinates: range, azimuth, and altitude), AIS target data (providing latitude, longitude, speed, and heading), and ADS-B target data (providing latitude, longitude, altitude, and speed).

[0022] It should be noted that Synthetic Aperture Radar (SAR) imaging is an active microwave remote sensing technology capable of acquiring high-resolution images of ground features and sea surfaces under various weather conditions, both day and night. Unlike optical images, SAR images primarily reflect scattering characteristics rather than visual texture in terms of brightness, thus posing challenges for target interpretation and identification. To enhance the application value of SAR images, researchers typically need to combine them with external information sources for comprehensive analysis. While existing technologies have proposed various approaches to combining target information with SAR images, significant technical shortcomings remain: a lack of universal coordinate matching modeling leads to insufficient accuracy; a lack of real-time and interactive capabilities results in slow application response; and development is geared towards single data sources, resulting in poor scalability and difficulty in uniformly processing multi-type target information. To address the aforementioned shortcomings, this application proposes a general algorithm for matching SAR image coordinates with spatial target coordinates to display target information on radar SAR imaging images. This is essentially a SAR image optimization method based on data fusion. Through a coordinate transformation algorithm, the three-dimensional coordinates of the target are associated with the pixel coordinates of the SAR image, mapping the target position to the corresponding location in the image. This enables the display of target trajectory, identity, and other information within the image. It accurately overlays radar-detected target information onto the corresponding location in the SAR image, achieving simultaneous display of SAR image and target information, thus improving image interpretation capabilities and the efficiency of multi-source information utilization. Figure 2The diagram shows the overall system flowchart of a SAR image optimization method based on data fusion provided in this application. The process mainly includes the following steps: SAR image reception and preprocessing: The system receives SAR images generated by airborne or spaceborne radar; reads the imaging parameters of the image and establishes the pixel coordinate system of the SAR image. Target data acquisition: Target data is acquired from external sensors. Coordinate matching modeling: First, a four-vertex affine algorithm is used to establish a mapping matrix D1 between the four corner pixels of the SAR image and the corresponding geographic coordinates (WGS-84, World Geodetic System-1984, a geocentric coordinate system); due to the projection distortion in SAR imaging, a fisheye inverse distortion correction model is further introduced to calculate the correction matrix D2; finally, a bidirectional mapping function F between the pixel coordinates of the SAR image and the WGS-84 spatial coordinates is obtained. Target coordinate mapping and display: The spatial coordinates of the target are input into F, and the pixel position of the target in the SAR image is obtained. When the system receives the returned SAR image, the data analyst manually marks the position of the target in the SAR image, and the software can accurately match the target according to the above algorithm; the target symbol is superimposed on the SAR image, and the target attributes are displayed. Trajectory overlay and dynamic display: In view of the long update cycle of SAR images (usually several minutes), the target's multi-time point traces within the imaging cycle are reverse mapped; the lines connecting the various point traces form a trajectory curve, which is overlaid on the SAR image to realize the visualization of historical motion trajectory.

[0023] It should be further pointed out that, such as Figure 3 The diagram shows the system composition principle block diagram of a SAR image optimization method based on data fusion provided in this application. The system mainly includes the following modules: SAR image receiving module: responsible for receiving and buffering SAR image data, and outputting pixel matrix and imaging parameters; target data acquisition module: connected to sensors such as radar, AIS, and ADS-B, receiving target spatial coordinates and attributes; coordinate matching algorithm module: affine matrix calculation submodule: establishing an initial mapping using the coordinate relationship of the four vertices; distortion correction submodule: performing nonlinear correction based on the fisheye model; mapping function generation submodule: forming pixel coordinates. The system includes a bidirectional spatial coordinate transformation function; a fusion display module with a point mapping submodule that maps target spatial coordinates to pixel coordinates; a trajectory generation submodule that connects historical point traces of the target to generate a trajectory; and an information overlay submodule that draws target symbols, trajectories, and attribute labels on the SAR image. This allows for accurate mapping between SAR image pixels and spatial target coordinates, improving the accuracy of target overlay display on SAR images. It also enables a real-time, interactive target fusion display method, quickly overlaying target information detected by multiple sensors onto SAR images during SAR image generation or updates, improving response speed and user experience. Furthermore, it constructs an scalable fusion framework that supports not only AIS but also radar, ADS-B, and other sensor targets, achieving unified fusion display of cross-domain, multi-type target information on SAR images, thereby reducing system maintenance costs and expanding application scope. In other words, this embodiment decouples coordinate matching and display into a modular architecture of data acquisition—coordinate mapping—fusion display, and introduces height / illumination angle considerations at the mapping end (adapting to three-dimensional information sources such as ADS-B).

[0024] It should be noted that the preprocessing procedure for the received SAR image to establish its pixel coordinate system is as follows: The received SAR image is preprocessed to obtain corresponding imaging parameters; a corresponding pixel coordinate system is established for the SAR image based on these imaging parameters. These imaging parameters include, but are not limited to, resolution, slant range, antenna attitude, platform height, and velocity. In other words, SAR images generated by airborne or spaceborne radar are received and buffered; the SAR images are preprocessed to obtain imaging parameters; and a corresponding pixel coordinate system is established for the SAR image based on these imaging parameters to obtain the pixel matrix and imaging parameters. In this way, the preprocessing of SAR images to extract imaging parameters to establish a pixel coordinate system can remove image interference and obtain accurate basic positioning parameters, ensuring a high degree of matching between the coordinate system and imaging rules, standardizing image data benchmarks, and providing a unified foundation for subsequent coordinate transformation and positioning calculations. By acquiring target object data with the help of external sensors, the measured target information beyond the SAR image can be supplemented, improving the completeness of subsequent data fusion and target positioning. The coordinate matching and display are decoupled into a modular architecture of data acquisition—coordinate mapping—fusion display, and the height / illumination angle is introduced at the mapping end. The same mapping interface can uniformly process target data from different sources and dimensions, avoiding redundant development and coupling amplification. It has strong multi-source scalability, and parameter and error compensation are concentrated in the closed-loop optimization of the mapping module. The front-end and back-end interfaces are stable, and the engineering adaptation and maintenance costs are reduced. Adaptation to different platforms, different imaging geometries, and different regions only requires updating a small number of imaging / regional parameters to maintain the stability of the superposition effect, resulting in better robustness.

[0025] Step S12: Perform an affine transformation based on the pixel coordinate system to establish an initial mapping relationship between the pixel coordinates and the target geographic coordinates.

[0026] In this embodiment, an affine transformation is performed based on the pixel coordinate system to establish an initial mapping relationship between the pixel coordinates and the target geographic coordinates. The target geographic coordinates can be WGS-84 geographic coordinates.

[0027] Specifically, the vertex pixel coordinates of each vertex in the SAR image are determined using the pixel coordinate system, and the vertex geographic coordinates of each vertex in the target geographic coordinate system are also determined. An affine transformation is then performed based on the vertex pixel coordinates and the vertex geographic coordinates to establish an initial mapping relationship between the pixel coordinates and the target geographic coordinates. That is, first, the vertex pixel coordinates of each vertex in the SAR image and its vertex geographic coordinates in the target geographic coordinate system (WGS-84 coordinate system) are determined according to the pixel coordinate system. Then, a four-vertex affine transformation is performed based on the above two sets of vertex coordinates, and the initial mapping relationship between the pixel coordinates and the target geographic coordinates is constructed using the four-vertex coordinate relationship, resulting in an initial mapping matrix D1. In this way, this embodiment matches the pixel coordinates and geographic coordinates of SAR image vertices, providing reliable reference control points for coordinate transformation. Using an affine transformation to establish the initial coordinate mapping enables a rapid linear correspondence between pixel coordinates and geographic coordinates, providing a basic transformation relationship for subsequent accurate geographic positioning, while ensuring efficient and stable coordinate transformation calculations.

[0028] Step S13: Based on the fisheye orthodontic principle and using the pixel coordinate system, establish a reverse correction relationship between pixel coordinates and spherical coordinates to correct the initial mapping relationship and obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates.

[0029] In this embodiment, due to projection distortion in SAR imaging, D1 has a certain error under spherical projection. The rectangular spherical projection obtained by airborne radar scanning the Earth's surface is actually distorted after being unfolded in a two-dimensional plane. The degree of distortion is related to the latitude of the aircraft. Therefore, this embodiment further introduces a fisheye inverse distortion correction model. Based on the fisheye orthogonal principle and combined with the pixel coordinate system, an inverse correction relationship D2 between pixel coordinates and spherical coordinates is established to correct the initial mapping relationship. This allows for a more accurate calculation of the affine relationship between image coordinates and the WGS84 plane coordinates of the target, ultimately forming a bidirectional mapping function F between pixel coordinates and the target's geographic coordinates. The fisheye inverse distortion correction model is a mathematical model for wide-angle lens distortion, and this embodiment applies it analogously to the inverse correction of SAR imaging distortion.

[0030] Specifically, based on the fisheye correction principle, the spherical projection distortion of the pixel coordinate system is eliminated to obtain distortion-free planar coordinates. These distortion-free planar coordinates are then converted to spherical coordinates, establishing a reverse correction relationship between pixel coordinates and spherical coordinates. This reverse correction relationship is then used to perform a non-linear correction on the initial mapping relationship to obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates. In other words, based on the fisheye correction principle, the spherical projection distortion of the pixel coordinate system is eliminated to obtain distortion-free planar coordinates (…). , This refers to distortion-free normalized planar coordinates (distortion-free projection of spherical coordinates onto a two-dimensional plane). The distortion-free planar coordinates are then converted to spherical coordinates to obtain the corrected WGS84 coordinates. An inverse correction relationship between pixel coordinates and spherical coordinates is established. The specific conversion formula for converting distortion-free planar coordinates to spherical coordinates is as follows: ; ; Where R is the Earth's radius; lat is latitude; lon is longitude; arcsin is the arcsine function; and arctan2 is the two-parameter arctangent function. The initial mapping relationship is then nonlinearly corrected using the inverse correction relationship to finally obtain the bidirectional mapping function between SAR image pixel coordinates and target geographic coordinates, i.e., WGS-84 spatial coordinates.

[0031] It should be noted that the process of eliminating spherical projection distortion of the pixel coordinate system based on the fisheye orthogonal principle to obtain distortion-free planar coordinates is as follows: Determine the equivalent focal length of the SAR image; using the imaging center of the SAR image as the origin, normalize and polarize the coordinates of each pixel in the pixel coordinate system based on the equivalent focal length to obtain the corresponding normalized polar coordinates; perform reverse mapping on the normalized polar coordinates according to the fisheye orthogonal principle to eliminate spherical projection distortion and obtain distortion-free planar coordinates. That is, first, determine the equivalent focal length of the SAR image imaging through the near-range boundary / maximum normalized polar radius, and model the SAR distortion as fisheye projection: using the imaging center as the origin, normalize and polarize the coordinates of each pixel coordinate system, and normalize the coordinates (r, v) of each pixel (u, v) to obtain the normalized polar coordinates (r, v, v). Solving for the normalized polar coordinates yields the following formula: ; ; ; ; Where x and y are normalized planar coordinates; r and These are the normalized polar radius and normalized polar angle, respectively; f is the equivalent focal length; ( , ) represents the pixel coordinates of the imaging center; arctan is the arctangent function. Then, based on the fisheye correction principle, the normalized polar coordinates are reverse-mapped to eliminate spherical projection distortion, obtaining distortion-free planar coordinates. Specifically, the distortion-free radial distance is first calculated, and the specific formula is as follows: ; in, This represents the undistorted radial distance. The specific formula for calculating the undistorted planar coordinates is as follows: ; ; In this way, this embodiment uses the fisheye orthogonal principle to eliminate spherical projection distortion and constructs a reverse correction relationship, which can effectively correct the positional deviation caused by image projection. By using the reverse correction relationship to perform nonlinear correction on the initial mapping relationship, the coordinate transformation accuracy can be greatly improved. The resulting bidirectional mapping function can realize the mutual conversion between pixels and geographic coordinates, making positioning and data fusion more accurate and reliable. Determining the equivalent focal length and normalizing it with the imaging center can unify the coordinate scale and simplify the distortion correction calculation. By using polar coordinate transformation combined with fisheye orthogonal reverse mapping, the distortion caused by spherical projection can be accurately eliminated, making the planar coordinates more consistent with the real spatial position.

[0032] Step S14: Map the target spatial coordinates in the target data using the bidirectional mapping function to obtain the target pixel coordinates, and display the target data in the SAR image according to the target pixel coordinates to obtain an optimized SAR image that fuses the target data.

[0033] In this embodiment, the target spatial coordinates in the target data are converted into target pixel coordinates using the bidirectional mapping function, and then the target data is superimposed on the SAR image based on the target pixel coordinates to obtain an optimized SAR image that fuses the target data.

[0034] Specifically, the target spatial coordinates of the target object are determined based on the target data; the target spatial coordinates are input to the bidirectional mapping function to map the target spatial coordinates to target pixel coordinates; the target position of the target object in the SAR image is determined based on the target pixel coordinates and the pixel coordinate system; a target symbol representing the target object is superimposed on the target position in the SAR image, and the target data is displayed to obtain an optimized SAR image fused with the target data. That is, the target spatial coordinates of the target object are determined based on the target data, input to F, converted to obtain the pixel position of the target object in the SAR image (i.e., target pixel coordinates), and the target position of the target object in the SAR image is located using the pixel coordinate system. A target symbol is superimposed at the corresponding position, and the target data, such as target attributes (ID, velocity, heading, altitude, etc.), is displayed to obtain the fused optimized SAR image.

[0035] It should be noted that superimposing target data into a SAR image typically takes several minutes to generate. During this time, the target object generates multiple traces, which can be fused into the SAR image. The processing flow is as follows: acquire historical target data of the target object in the SAR image, and map the historical target spatial coordinates in the historical target data using the bidirectional mapping function to obtain historical target pixel coordinates; determine the historical target position of the target object in the SAR image based on the historical target pixel coordinates and the pixel coordinate system; superimpose target symbols representing the target object at the historical target position in the SAR image, display the historical target data, and connect the historical target positions to generate the movement trajectory of the target object. In other words, considering the long update cycle of SAR images (usually several minutes), historical target data of the target object is acquired, that is, multi-time point traces within the imaging cycle. The historical target spatial coordinates are inversely mapped to historical target pixel coordinates using the bidirectional mapping function, that is, the SAR image coordinates corresponding to the latitude and longitude of the target's historical point traces are solved in reverse. The historical target positions are located based on the pixel coordinate system, target symbols are superimposed at the corresponding positions, and historical target data is displayed. Then, lines are connected between the historical target positions to form the target object's movement trajectory, that is, the trajectory curve, which is superimposed on the SAR image to visualize the historical movement trajectory. Figure 4 The image shown is a schematic diagram illustrating the effect of SAR image fusion target data provided in this application.

[0036] It is understandable that the SAR image optimization method based on data fusion in this embodiment theoretically has several alternative technical routes that can also achieve the goal of accurately overlaying target information in SAR images. Although these schemes differ in technical details, their ultimate goal is the same: to map the target in the spatial coordinate system to the pixel coordinate system of the SAR image. For example, the joint registration method based on multi-sensor assistance is implemented by introducing optical remote sensing images, electronic nautical charts, or high-precision maps as intermediaries. The SAR image is first registered with the optical / map image, then the target coordinates are projected onto the reference image, and finally mapped back to the SAR image. This method can fuse external auxiliary data and reduce the impact of single SAR distortion; however, it relies on external data sources, resulting in higher costs and complexity. In addition, the nonlinear mapping model based on machine learning / deep learning is implemented by using paired samples of historical SAR images and real target locations to train a deep neural network (such as a convolutional neural network or a Transformer model) to directly learn the nonlinear mapping relationship from spatial coordinates to pixel coordinates. The model can adapt to complex distortions and is theoretically more accurate, but it requires a large amount of training data and has poor model interpretability, which is not conducive to engineering verification. In this way, the use of a bidirectional mapping function for coordinate transformation in this embodiment can ensure a precise correspondence between spatial coordinates and pixel coordinates, avoiding misalignment and deviation. Displaying target data intuitively in the SAR image according to pixel coordinates can achieve efficient fusion of spatial information and image information, improving the positioning accuracy and information readability of the SAR image. Using a bidirectional mapping function to transform historical spatial coordinates and overlaying, marking, and connecting historical target positions can ensure accurate and unbiased positioning of historical positions, intuitively reconstruct the target's movement path, and enhance the SAR image's ability to display dynamic changes of targets and its tracking and analysis effects.

[0037] As can be seen from the above, the embodiments of this application first preprocess the SAR image and establish a pixel coordinate system, acquire target data of the target object through an external sensor, and then perform an affine transformation based on the pixel coordinate system to construct an initial mapping relationship between pixel coordinates and target geographic coordinates. Combined with the fisheye orthogonal principle, a reverse correction relationship between pixel coordinates and spherical coordinates is established to correct the initial mapping relationship, thereby obtaining a bidirectional mapping function between pixel coordinates and target geographic coordinates. This function is used to map the target spatial coordinates in the target data to target pixel coordinates. Finally, the target data is superimposed and displayed in the SAR image to generate an optimized SAR image that fuses the target data. In this way, through the above-described process of the embodiments of this application, the pixel coordinate system is established by preprocessing the SAR image and the initial mapping is constructed by affine transformation, which can quickly establish the basic correspondence between pixels and geographic coordinates; the mapping is optimized by establishing a reverse correction relationship based on the fisheye orthogonal principle, which can effectively correct coordinate mapping deviation and improve coordinate transformation accuracy; the target data and SAR image are fused and displayed using a bidirectional mapping function, which can accurately match the target spatial information with the image position, realize the simultaneous display of SAR image and target information, enhance the information integrity and positioning accuracy of SAR image, and improve the effectiveness of data fusion and the reliability of task execution; the coordinate matching is achieved through affine initial registration (D1) + imaging distortion reverse correction (D2) + bidirectional lookup table / function F. The system establishes a computable, verifiable, and reusable universal mapping model between the pixel domain and the WGS-84 spatial domain. Coordinate transformation no longer relies on empirical comparisons or single-scene parameters, significantly improving the geometric accuracy and consistency of target overlay, reducing misalignment and misjudgment. The mapping is solidified into a lookup table / closed-loop solution chain, and the overlay display is transformed from offline post-processing to online real-time (mapping and rendering can be performed as soon as new points arrive), thereby shortening the response chain, improving interactivity and situational awareness efficiency. By utilizing the reverse mapping and trajectory generation of historical points, the target movement process can be intuitively presented on a single SAR image, reducing the cost of manual comparison and cognitive burden. This enables accurate fusion and visualization of target object data in SAR images to improve image interpretation capabilities and the efficiency of multi-source information utilization.

[0038] Accordingly, see Figure 5 As shown in the figure, this application embodiment also provides a SAR image optimization device based on data fusion, applied to an image optimization system, including: The data acquisition module 11 is used to preprocess the received SAR image to establish the pixel coordinate system of the SAR image and acquire the target data of the target object in the SAR image through an external sensor. Affine transformation module 12 is used to perform affine transformation based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates; The relationship establishment module 13 is used to establish a reverse correction relationship between pixel coordinates and spherical coordinates based on the fisheye orthodontic principle and using the pixel coordinate system, so as to correct the initial mapping relationship and obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates. The data display module 14 is used to map the target spatial coordinates in the target data through the bidirectional mapping function to obtain the target pixel coordinates, and display the target data in the SAR image according to the target pixel coordinates to obtain an optimized SAR image after fusing the target data.

[0039] In some specific embodiments, the data acquisition module 11 may specifically include: The preprocessing unit is used to preprocess the received SAR image to obtain the corresponding imaging parameters; The coordinate system establishment unit is used to establish a corresponding pixel coordinate system for the SAR image based on the imaging parameters.

[0040] In some specific embodiments, the affine transformation module 12 may specifically include: The first coordinate determination unit is used to determine the vertex pixel coordinates of each vertex of the SAR image through the pixel coordinate system, and to determine the vertex geographic coordinates of each vertex of the SAR image in the target geographic coordinate system. An affine transformation unit is used to perform an affine transformation based on the vertex pixel coordinates and the vertex geographic coordinates to establish an initial mapping relationship between the pixel coordinates and the target geographic coordinates.

[0041] In some specific embodiments, the relationship establishment module 13 may specifically include: The coordinate transformation submodule is used to eliminate the spherical projection distortion of the pixel coordinate system according to the fisheye orthogonal principle to obtain distortion-free planar coordinates, and convert the distortion-free planar coordinates into spherical coordinates to establish a reverse correction relationship between pixel coordinates and spherical coordinates. The relationship correction unit is used to perform nonlinear correction on the initial mapping relationship through the reverse correction relationship to obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates.

[0042] In some specific embodiments, the coordinate transformation submodule may specifically include: A focal length determination unit is used to determine the equivalent focal length of the SAR image; The normalization unit is used to normalize and transform the pixel coordinates of the pixel coordinate system based on the equivalent focal length, with the imaging center of the SAR image as the origin, so as to obtain the corresponding normalized polar coordinates. The reverse mapping unit is used to reverse map the normalized polar coordinates according to the fisheye orthogonal principle to eliminate spherical projection distortion and obtain distortion-free planar coordinates.

[0043] In some specific embodiments, the data display module 14 may specifically include: The second coordinate determination unit is used to determine the target spatial coordinates of the target object based on the target data; A coordinate input unit is used to input the target spatial coordinates into the bidirectional mapping function to map the target spatial coordinates into target pixel coordinates; The first position determination unit is used to determine the target position of the target object in the SAR image based on the target pixel coordinates and the pixel coordinate system. The data display unit is used to overlay target symbols representing the target object at the target location in the SAR image and display the target data to obtain an optimized SAR image after fusing the target data.

[0044] In some specific embodiments, the data display module 14 may further include: The data acquisition unit is used to acquire historical target data of the target object in the SAR image, so as to map the historical target spatial coordinates in the historical target data through the bidirectional mapping function to obtain the historical target pixel coordinates; The second location determination unit is used to determine the historical target location of the target object in the SAR image based on the historical target pixel coordinates and the pixel coordinate system. The location connection unit is used to overlay target symbols representing the target object on the historical target location of the SAR image, display the historical target data, and connect the historical target locations to generate the movement trajectory of the target object.

[0045] Furthermore, embodiments of this application also disclose an electronic device, Figure 6 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the data fusion-based SAR image optimization method disclosed in any of the foregoing embodiments. Furthermore, the electronic device 20 in this embodiment may specifically be an electronic computer.

[0046] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0047] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0048] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the data fusion-based SAR image optimization method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0049] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned disclosed SAR image optimization method based on data fusion. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0050] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0051] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0052] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0053] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0054] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A SAR image optimization method based on data fusion, characterized in that, Applications in image optimization systems include: The received SAR image is preprocessed to establish the pixel coordinate system of the SAR image, and the target data of the target object in the SAR image is obtained through an external sensor; An affine transformation is performed based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates; Based on the fisheye orthodontic principle and using the pixel coordinate system, a reverse correction relationship between pixel coordinates and spherical coordinates is established to correct the initial mapping relationship, thereby obtaining a bidirectional mapping function between pixel coordinates and target geographic coordinates. The target spatial coordinates in the target data are mapped by the bidirectional mapping function to obtain the target pixel coordinates, and the target data is displayed in the SAR image according to the target pixel coordinates to obtain an optimized SAR image that fuses the target data.

2. The SAR image optimization method based on data fusion according to claim 1, characterized in that, The preprocessing of the received SAR image to establish the pixel coordinate system of the SAR image includes: The received SAR images are preprocessed to obtain the corresponding imaging parameters; A corresponding pixel coordinate system is established for the SAR image based on the imaging parameters.

3. The SAR image optimization method based on data fusion according to claim 1, characterized in that, The step of performing an affine transformation based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates includes: The vertex pixel coordinates of each vertex of the SAR image are determined using the pixel coordinate system, and the vertex geographic coordinates of each vertex of the SAR image in the target geographic coordinate system are also determined. An affine transformation is performed based on the vertex pixel coordinates and the vertex geographic coordinates to establish an initial mapping relationship between the pixel coordinates and the target geographic coordinates.

4. The SAR image optimization method based on data fusion according to claim 1, characterized in that, The step of establishing a reverse correction relationship between pixel coordinates and spherical coordinates based on the fisheye orthodontic principle and utilizing the pixel coordinate system to correct the initial mapping relationship and obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates includes: The spherical projection distortion of the pixel coordinate system is eliminated according to the fisheye orthodontic principle to obtain distortion-free planar coordinates, and the distortion-free planar coordinates are converted into spherical coordinates to establish a reverse correction relationship between pixel coordinates and spherical coordinates. The initial mapping relationship is nonlinearly modified by the reverse correction relationship to obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates.

5. The SAR image optimization method based on data fusion according to claim 4, characterized in that, The step of eliminating the spherical projection distortion of the pixel coordinate system according to the fisheye orthogonal principle to obtain distortion-free planar coordinates includes: Determine the equivalent focal length of the SAR image; Using the imaging center of the SAR image as the origin, the pixel coordinates of the pixel coordinate system are normalized and polar transformed based on the equivalent focal length to obtain the corresponding normalized polar coordinates. Based on the fisheye orthogonal principle, the normalized polar coordinates are reverse-mapped to eliminate spherical projection distortion and obtain distortion-free planar coordinates.

6. The SAR image optimization method based on data fusion according to claim 1, characterized in that, The step of mapping the target spatial coordinates in the target data using the bidirectional mapping function to obtain the target pixel coordinates, and then displaying the target data in the SAR image based on the target pixel coordinates to obtain an optimized SAR image fused with the target data, includes: Determine the target spatial coordinates of the target object based on the target data; The target spatial coordinates are input into the bidirectional mapping function to map the target spatial coordinates into target pixel coordinates; The target location of the target object in the SAR image is determined based on the target pixel coordinates and the pixel coordinate system. Target symbols representing the target object are superimposed on the target location in the SAR image, and the target data is displayed to obtain an optimized SAR image that fuses the target data.

7. The SAR image optimization method based on data fusion according to any one of claims 1 to 6, characterized in that, The step of displaying the target data in the SAR image based on the target pixel coordinates to obtain an optimized SAR image fused with the target data further includes: Historical target data of the target object in the SAR image is obtained, and the historical target spatial coordinates in the historical target data are mapped by the bidirectional mapping function to obtain the historical target pixel coordinates; Based on the historical target pixel coordinates and the pixel coordinate system, the historical target position of the target object in the SAR image is determined; The historical target locations in the SAR image are overlaid with target symbols used to characterize the target object, and the historical target data is displayed. Lines are also drawn connecting the historical target locations to generate the movement trajectory of the target object.

8. A SAR image optimization device based on data fusion, characterized in that, Applications in image optimization systems include: The data acquisition module is used to preprocess the received SAR image to establish the pixel coordinate system of the SAR image and acquire the target data of the target object in the SAR image through an external sensor. The affine transformation module is used to perform affine transformations based on the pixel coordinate system to establish an initial mapping relationship between pixel coordinates and target geographic coordinates. The relationship establishment module is used to establish a reverse correction relationship between pixel coordinates and spherical coordinates based on the fisheye orthodontic principle and using the pixel coordinate system, so as to correct the initial mapping relationship and obtain a bidirectional mapping function between pixel coordinates and target geographic coordinates. The data display module is used to map the target spatial coordinates in the target data through the bidirectional mapping function to obtain the target pixel coordinates, and to display the target data in the SAR image according to the target pixel coordinates to obtain an optimized SAR image that fuses the target data.

9. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the SAR image optimization method based on data fusion as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program; wherein, when the computer program is executed by a processor, it implements the SAR image optimization method based on data fusion as described in any one of claims 1 to 7.

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