Special structural component calculation and measurement parameter fusion modeling method

Abstract

The invention discloses a special structural component calculation and measurement parameter fusion modeling method, which comprises the following steps of: acquiring all-directional simulation and test scattering data, and performing uncertainty analysis to obtain an azimuth angle range in which simulation is abnormal; under each abnormal angle, two-dimensional scattering data under simulation and darkroom testing are obtained respectively, two-dimensional radar imaging is generated, similarity analysis is carried out, and the geometric position of a scattering characteristic abnormal area is analyzed according to the difference between simulation imaging and testing imaging; according to the corresponding position of the scattering characteristic abnormal area in the geometric model, the scattering type is analyzed, and the scattering data of the abnormal area is reconstructed by adopting a point scattering center model to serve as the expected value of the scattering characteristic of the special structural component; and selecting a parameterized model of the special structural component, and replacing the special structural component in the geometric model to construct a new geometric model after the scattering property expected value matching is completed. According to the method, the modeling accuracy is improved by optimizing the electromagnetic simulation grid.

Description

Technical Field

[0001] This invention relates to the field of radar target feature modeling technology, and specifically to a method for fusing calculation and measurement parameters of special structural components. Background Technology

[0002] In radar target characteristic modeling technology, the requirements for the realism of the simulation of the scattering characteristics of real targets are becoming increasingly stringent. Special structural components are very common on large and complex targets, such as aircraft air intakes and ship jet nozzles. The multiple reflection paths of radar waves on special structural components are quite complex. Since the simulation calculation complexity of electrically large targets is very high, high-frequency approximation methods are often used. The number of bounces of the simulated ray determines the difference between the modeling accuracy and the actual test results. By combining simulation and testing, an equivalent scattering center model is introduced to establish a high-confidence scattering model, thereby providing technical support for echo generation, target recognition, and other functions.

[0003] In practical calculation and measurement parameter fusion modeling, how to integrate simulation and test data is the key and difficult point of modeling. Summary of the Invention

[0004] The purpose of this invention is to propose a method for fusion modeling of calculation and measurement parameters of special structural components, which supplements and corrects the electromagnetic modeling method of special component targets, thereby improving the accuracy of modeling targets containing special components.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solution: A method for fusing calculated and measured parameters of a special structural component, comprising: Step S1: Perform omnidirectional single-frequency RCS simulation on the target. Simultaneously, under the same conditions, perform omnidirectional single-frequency RCS anechoic chamber test on the target to obtain omnidirectional single-frequency simulation data and omnidirectional single-frequency test scattering data of the same target. Perform uncertainty analysis on the omnidirectional single-frequency simulation data and omnidirectional single-frequency test scattering data to obtain the azimuth range where the simulation anomaly occurs.

[0006] Step S2: Under each abnormal azimuth angle, acquire two-dimensional scattering data under simulation and RCS anechoic chamber test respectively, and generate two-dimensional radar images based on the two-dimensional scattering data and perform similarity analysis. Based on the difference between the simulation imaging and the test imaging, analyze the corresponding position of the abnormal scattering characteristic region in the target geometric model.

[0007] Step S3: Based on the corresponding position of the scattering anomaly region in the target geometric model, analyze its scattering type, and reconstruct the scattering data of the scattering anomaly region using the point scattering center model, as the expected value of the scattering characteristics of special structural components in the target.

[0008] Step S4: Select the parametric model of the special structural component, use the least squares method to correct the geometric parameters of the special structural component, and after completing the expected value matching of scattering characteristics, replace the special structural component in the target geometric model to construct a new target geometric model and complete the equivalent modeling of the special structural component.

[0009] Optionally, step S1 includes: step S11, performing electromagnetic simulation mesh modeling on the target to obtain a mesh model, wherein the mesh model is the target geometric model after meshing; selecting a frequency. Pitch angle Based on the polarization parameters, simulation software was used to perform omnidirectional single-frequency RCS simulation on the target to obtain the omnidirectional single-frequency simulation data; simultaneously, the target was subjected to RCS anechoic chamber testing under the same conditions to obtain the omnidirectional single-frequency test scattering data.

[0010] Step S12: Perform uncertainty analysis on the scattering data from the full-range simulation and test to obtain the range of azimuth angles where the simulation anomalies occur; Uncertainty analysis is represented by root mean square error: In the formula The root mean square error, The RCS obtained from the simulation of the i-th azimuth angle sampling point is... Let N be the RCS of the i-th azimuth sampling point tested in the darkroom, and N be the number of azimuth sampling points.

[0011] Optionally, the two-dimensional scattering data refers to the scanning frequency, scanning azimuth angle, and the two-dimensional scanning scattering matrix that constitutes the target at a given abnormal angle; the imaging similarity analysis refers to the cosine similarity of the compared images.

[0012] Optionally, step S2 includes: step S21, at each abnormal angle, determining the desired scanning angle and frequency range based on the maximum size of the target, setting the scanning frequency and scanning azimuth, setting the number of scanning points according to the resolution requirements, and acquiring the two-dimensional scattering data under simulation and RCS anechoic chamber testing respectively.

[0013] Step S22: Perform inverse Fourier transform on the two-dimensional scattering data from the simulation and RCS anechoic chamber test in the range and azimuth directions to obtain the target two-dimensional radar image. Analyze the similarity between the two images. Based on the differences between the simulation and RCS anechoic chamber test images, analyze the corresponding position of the abnormal scattering characteristic region in the target geometric model.

[0014] Optionally, step S21 includes: the imaging lengths in the range and azimuth directions are: in, At the speed of light, These are the center frequency, center azimuth, and observation elevation angle, respectively. These are the scanning frequency and the scanning azimuth range, respectively. These are the imaging lengths in the range and azimuth directions, respectively, and their corresponding imaging ranges are respectively... The imaging resolution is: in, These are the resolutions in the range and azimuth directions, respectively. These represent the number of scans in the range and azimuth directions, respectively.

[0015] Optionally, step S22 includes: given two image vectors A and B, cosine similarity Represented as: in and These represent the components of vectors A and B, respectively, with the subscript i indicating the i-th element in the vector.

[0016] Optionally, step S3 includes: step S31, projecting the target geometric model onto the imaging plane, marking the scattering center positions of each component corresponding to the radar imaging, and analyzing its scattering type.

[0017] Step S32: Extract the scattering center of the abnormal region in the image, and reconstruct the scattering data of the abnormal region using the point scattering center model as the expected value of the scattering characteristics of the special structural component.

[0018] Optionally, step S4 includes: selecting a parameterized model of a special structural component, setting initial geometric parameters, sequentially adjusting the position, scale, and attitude parameters in the initial geometric parameters, reconstructing the RCS and radar imaging, calculating the error with the expected value of the scattering characteristics of the special structural component, solving for the optimal parameters through gradient descent or numerical optimization to obtain the optimal parameterized model; replacing the scattering component in the geometric model with the optimal parameterized model to construct the new target geometric model.

[0019] On the other hand, the present invention also provides an electronic device including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the method described above.

[0020] In another aspect, the present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the method described above.

[0021] The present invention has the following advantages during use: This invention analyzes the abnormal regions of the electromagnetic simulation mesh by fusing simulation and test data, and then corrects them by using radar two-dimensional imaging at a specific angle and parameterized special structural components. The model of special components can be iteratively optimized through parameter correction, which greatly improves the accuracy of modeling. Attached Figure Description

[0022] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the drawings described below are one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort: Figure 1 This is a flowchart illustrating a method for fusing and modeling the calculation parameters of a special structural component according to an embodiment of the present invention. Figure 2 This is a radar two-dimensional imaging at a specific observation angle in one embodiment of the present invention. Detailed Implementation

[0023] The following detailed description, in conjunction with the accompanying drawings and specific embodiments, provides a further detailed explanation of the method for fusing calculation parameters of a special structural component proposed in this invention. The advantages and features of this invention will become clearer from the following description. It should be noted that the accompanying drawings are in a very simplified form and use non-precise scales, used only to facilitate and clearly illustrate the embodiments of this invention. Please refer to the accompanying drawings to make the objectives, features, and advantages of this invention more apparent and understandable. It should be understood that the structures, scales, sizes, etc., depicted in the accompanying drawings are only for illustrative purposes to aid those skilled in the art and are not intended to limit the implementation conditions of this invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportional relationships, or adjustments to the size, without affecting the effects and objectives achieved by this invention, should still fall within the scope of the technical content disclosed in this invention.

[0024] Modeling special structural components (special structural scattering components) is an important issue in radar target modeling. This invention uses simulation and test comparison to analyze abnormal scattering angles, determines the location of special structural components through radar two-dimensional imaging, uses parameterized models and least squares method for correction, and improves the accuracy of modeling by optimizing the electromagnetic simulation mesh.

[0025] like Figure 1As shown, this embodiment provides a method for fusion modeling of calculation and measurement parameters of special structural components, including: step S1, performing omnidirectional single-frequency RCS simulation on the target, and simultaneously, performing omnidirectional single-frequency RCS anechoic chamber test on the target under the same conditions, to obtain omnidirectional single-frequency simulation data and omnidirectional single-frequency test scattering data of the same target; performing uncertainty analysis on the omnidirectional single-frequency simulation data and omnidirectional single-frequency test scattering data to obtain the azimuth range where the simulation anomaly occurs.

[0026] In this context, "all-around" refers to scanning a 360° azimuth angle from a fixed elevation angle; "identical state" means that both simulation and testing operate at the same frequency, azimuth angle, elevation angle, polarization, and distance from the test antenna to the target, with the simulation input model and test model being identical, including structural and material parameters; and "uncertainty" refers to the root mean square error analysis of the RCS. This definition of "identical state" ensures consistent geometric configuration between simulation and testing, improving the accuracy of RCS measurements.

[0027] In this embodiment, step S1 includes: step S11, performing electromagnetic simulation mesh modeling on the target to obtain a mesh model as input to the simulation software, wherein the mesh model is the target geometric model after meshing; selecting a frequency. Pitch angle Based on the polarization parameters, simulation software was used to perform omnidirectional single-frequency RCS simulation on the target to obtain the omnidirectional single-frequency simulation data; simultaneously, the target was subjected to RCS anechoic chamber testing under the same conditions to obtain the omnidirectional single-frequency test scattering data.

[0028] The mesh model is the input to the simulation software. CAD files cannot be directly simulated. The input for testing is the target geometric model. Here, testing refers to conducting experiments on-site (in a darkroom), which is different from simulation.

[0029] In one example, the target is a vehicle. A mesh model is built using intelligence (i.e., simulation model) and physical model (i.e. test model). The electromagnetic simulation software is set with a center frequency of 10 GHz, an elevation angle of 90°, and the RCS anechoic chamber test conditions are consistent with the simulation.

[0030] Step S12: Perform uncertainty analysis on the scattering data from the full-range simulation and test to obtain the range of azimuth angles where the simulation anomalies occur; Uncertainty analysis is represented by root mean square error: In the formula The root mean square error, The RCS obtained from the simulation of the i-th azimuth angle sampling point is... Let N be the RCS of the i-th azimuth sampling point tested in the darkroom, and N be the number of azimuth sampling points.

[0031] Step S2: Under each abnormal azimuth angle, acquire two-dimensional scattering data under simulation and RCS anechoic chamber test respectively, and generate two-dimensional radar images based on the two-dimensional scattering data and perform similarity analysis. Based on the difference between the simulation imaging and the test imaging, analyze the corresponding position of the abnormal scattering characteristic region in the target geometric model.

[0032] The two-dimensional scattering data refers to the scanning frequency, scanning azimuth angle, and the two-dimensional scanning scattering matrix that constitutes the target under a given abnormal angle; the imaging similarity analysis refers to the cosine similarity of the compared images.

[0033] In this embodiment, step S2 includes: step S21, at each abnormal angle, based on the target maximum size Determine the desired scanning angle and frequency range, and set the scanning frequency. , Scan azimuth The number of scanning points was set according to the resolution requirements, and the two-dimensional scattering data under simulation and RCS anechoic chamber test were obtained respectively.

[0034] Step S21 includes: the imaging lengths in the range and azimuth directions are: in, At the speed of light, These are the center frequency, center azimuth, and observation elevation angle, respectively. These are the scanning frequency and the scanning azimuth range, respectively. These are the imaging lengths in the range and azimuth directions, respectively. The subscript 'a' in the text is an abbreviation for azimuth and has no special meaning. The corresponding imaging ranges are as follows: The imaging resolution is: in, These are the resolutions in the range and azimuth directions, respectively. These represent the number of scans in the range and azimuth directions, respectively, with a working frequency of [missing information]. The RCS value of the scattering at time is expressed as .

[0035] This embodiment can ensure the number of scan points. Proper settings are required to obtain effective two-dimensional scattering data for radar imaging.

[0036] Step S22: Perform inverse Fourier transform on the two-dimensional scattering data from the simulation and RCS anechoic chamber test in the range and azimuth directions to obtain the target two-dimensional radar image. Analyze the similarity between the two images. Based on the differences between the simulation and RCS anechoic chamber test images, analyze the corresponding position of the abnormal scattering characteristic region in the target geometric model.

[0037] It can be understood that the corresponding position of the abnormal scattering characteristic region in the target geometric model is the geometric position of the abnormal scattering characteristic region; it can also be understood as the corresponding position of the abnormal scattering characteristic region in the mesh model.

[0038] In one example, the two-dimensional imaging sweep bandwidth was 0.5 GHz, with 51 scans, and the azimuth scan width was 3°, with 61 scans. Simulation and RCS anechoic chamber testing yielded two-dimensional scattering data. Radar imaging under anomalous angles was shown as follows: Figure 2 As shown, the differences in radar imaging before and after optimization can be observed.

[0039] Step S22 includes: given two image vectors A and B, cosine similarity Represented as: in and These represent the components of vectors A and B, respectively, with the subscript i indicating the i-th element in the vector.

[0040] This formula quantifies the difference between simulated and test images. Low-similarity regions are identified as anomalies and mapped to their coordinate positions in the mesh model by comparing image pixels (e.g., amplitude and phase differences) (step S22). For example, a difference region might correspond to a specific component (e.g., the roof of a vehicle), which is then precisely located in the geometric model. This similarity is a criterion that is continuously calculated by optimizing the scattering center parameters corresponding to the image anomaly regions until a high similarity is achieved.

[0041] Step S3: Based on the corresponding position of the scattering anomaly region in the target geometric model, analyze its scattering type, and reconstruct the scattering data of the scattering anomaly region using the point scattering center model, as the expected value of the scattering characteristics of special structural components in the target.

[0042] In this embodiment, step S3 includes: step S31, projecting the target geometric model onto the imaging plane, marking the scattering center positions of each component corresponding to the radar imaging, and analyzing its scattering type.

[0043] Specifically, as an example, the projection operation: projects the target geometry onto the radar imaging plane to generate a 2D projection image (with the same viewing angle as the imaging).

[0044] Mark the scattering center: Based on the projection map, mark the location of the scattering center of the corresponding component (such as the wing edge, air intake).

[0045] Scattering type analysis: Scattering mechanisms are classified according to location and echo characteristics (such as specular reflection, edge diffraction), refer to the type list provided in the document (specular reflection, cavity scattering, etc.).

[0046] Step S32: Extract the scattering center of the abnormal region in the image, and reconstruct the scattering data of the abnormal region using the point scattering center model as the expected value of the scattering characteristics of the special structural component.

[0047] Among them, regions inconsistent between the simulation and RCS anechoic chamber test images are defined as abnormal regions. For abnormal regions in the simulation image... There are scattering centers, and their amplitudes are denoted as follows: ,this The positions of the scattering centers are respectively , Then, the expected value E of the scattering characteristics of the special structural component can be expressed as: in, For wave vectors, It is a complex number. The RCS at that location can be represented as , Indicates the position of the i-th scattering center; Let represent the i-th scattering center; e represents the natural index.

[0048] Step S4: Select the parametric model of the special structural component, use the least squares method to correct the geometric parameters of the special structural component, and after completing the expected value matching of scattering characteristics, replace the special structural component in the target geometric model to construct a new target geometric model and complete the equivalent modeling of the special structural component.

[0049] In this embodiment, step S4 includes: selecting a parameterized model of a special structure scattering component, setting initial geometric parameters, sequentially adjusting the position, scale, and attitude parameters in the initial geometric parameters, reconstructing the RCS and radar imaging, calculating the error with the expected value of the scattering characteristics of the special structure component, solving for the optimal parameters through gradient descent or numerical optimization to obtain the optimal parameterized model; replacing the scattering component in the geometric model with the optimal parameterized model to construct the new target geometric model.

[0050] As an example, step S4 may specifically include: first performing initialization and matching: Select a parametric model and set the initial geometric parameters. Calculate the model scattering data and compare it with the expected value from step S3. Optimize the parameters using the least squares method until the error is minimized (matching complete).

[0051] Then, iterative optimization and replacement are performed: position (translation coordinates), scale (scaling size), and pose (rotation angle) are optimized sequentially. After each optimization, the RCS and imaging are reconstructed, and the similarity is verified. Once the expected value is met, the components in the original geometric model are replaced with the new parametric model to construct an equivalent geometric model.

[0052] Example: In the vehicle roof optimization, adjust the roof cap parameters and replace it.

[0053] The least-squares parameter optimization problem for a special structure scattering component can be expressed as: In the formula, This represents the geometric parameters of the optimized parametric model; This represents the scattering data corresponding to a specially structured scattering component; These are the center frequency, center azimuth, and observation elevation angle, respectively. This represents the scattering data corresponding to the parameterized model; This represents the geometric parameters of the parametric model, where the subscript i indicates the i-th geometric parameter; This represents the positional parameters of the parametric model, where the subscript i indicates the i-th positional parameter.

[0054] In one example, the top position of the vehicle mesh is optimized by replacing the original model with a circular top cap structure. (Cylindrical top cap structure parametric model) as follows: in, Where is the radius of the cylinder, h is the height of the cylinder, and d is the width of the "brim". This is a first-order Bessel function. j represents the complex unit; k represents the wave vector. ; Indicates the observed pitch angle.

[0055] Understandably, parameterized models are simplified geometric components (such as air intakes and top caps) that are mathematically represented and used to efficiently reconstruct scattering data.

[0056] In this example, the optimization and replacement process for the vehicle roof is as follows: Anomaly identification: Based on step S2 imaging, differences (low similarity) are displayed in the top region.

[0057] Parametric model: Select cylindrical cap structure (parameters: radius r, height h, cap brim d).

[0058] Optimized location: Initial settings: r=0.5m, h=0.2m, d=0.1m (based on target size).

[0059] Least squares adjustment: Change the position coordinates (x, y, z) to make the model scattering data match the expected value.

[0060] For example, shift the top cap to the coordinates of the imaging anomaly.

[0061] Reconstruction and Validation: Generate new RCS and images, calculate similarity with test data; iterate until error < threshold.

[0062] Alternative modeling: The original vehicle top components are replaced with an optimized top cap model to construct an equivalent geometric model. This process improves simulation accuracy.

[0063] On the other hand, the present invention also provides an electronic device including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it implements the method described above.

[0064] In another aspect, the present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, implements the method described above.

[0065] In summary, compared with the prior art, the computational and measurement fusion modeling method provided by this invention optimizes the mesh model by using parameterized component correction, which has strong flexibility and scalability. It confirms abnormal angles by RCS comparison and confirms the position of special components by radar imaging comparison. The scattering model established by this method has a more accurate simulation capability for special structural components and can provide technical support for echo generation, target recognition, etc.

[0066] This invention employs simulation and testing to compare and analyze abnormal scattering angles, determines the location of special structural components through radar two-dimensional imaging, uses parameterized models and least squares methods for correction, and improves the accuracy of modeling by optimizing the electromagnetic simulation mesh.

[0067] It should be noted that, in this document, 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. Unless otherwise specified, 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.

[0068] It should be noted that the apparatus and methods disclosed in the embodiments herein can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments herein. In this regard, each block in a flowchart or block diagram may represent a module, program, or part of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system to perform the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0069] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for fusing and modeling the calculated parameters of a special structural component, characterized in that, include: Step S1: Perform omnidirectional single-frequency RCS simulation on the target. At the same time, under the same conditions, perform omnidirectional single-frequency RCS anechoic chamber test on the target to obtain omnidirectional single-frequency simulation data and omnidirectional single-frequency test scattering data of the same target. Uncertainty analysis was performed on the omnidirectional single-frequency simulation data and the omnidirectional single-frequency test scattering data to obtain the azimuth range where the simulation anomaly occurred. Step S2: Under each abnormal azimuth angle, acquire two-dimensional scattering data under simulation and RCS anechoic chamber test respectively, and generate two-dimensional radar images based on the two-dimensional scattering data and perform similarity analysis. According to the difference between simulation imaging and test imaging, analyze the corresponding position of the abnormal scattering characteristic area in the target geometric model. Step S3: Based on the corresponding position of the scattering anomaly region in the target geometric model, analyze its scattering type, and reconstruct the scattering data of the scattering anomaly region using the point scattering center model as the expected value of the scattering characteristics of special structural components in the target. Step S4: Select the parametric model of the special structural component, use the least squares method to correct the geometric parameters of the special structural component, and after completing the expected value matching of scattering characteristics, replace the special structural component in the target geometric model to construct a new target geometric model and complete the equivalent modeling of the special structural component.

2. The method for fusing and modeling the measured parameters of special structural components as described in claim 1, characterized in that, Step S1 includes: Step S11: Perform electromagnetic simulation mesh modeling on the target to obtain a mesh model, which is the target geometric model after meshing; select frequency. Pitch angle Based on the polarization parameters, simulation software was used to perform omnidirectional single-frequency RCS simulation on the target to obtain the omnidirectional single-frequency simulation data; simultaneously, the target was subjected to RCS anechoic chamber testing under the same conditions to obtain the omnidirectional single-frequency test scattering data. Step S12: Perform uncertainty analysis on the scattering data from the full-range simulation and test to obtain the range of azimuth angles where the simulation anomalies occur; Uncertainty analysis is represented by root mean square error: In the formula The root mean square error, The RCS obtained from the simulation of the i-th azimuth angle sampling point is... Let N be the RCS of the i-th azimuth sampling point tested in the darkroom, and N be the number of azimuth sampling points.

3. The method for fusing and modeling the measured parameters of special structural components as described in claim 1, characterized in that, The two-dimensional scattering data refers to the scanning frequency, scanning azimuth angle, and the two-dimensional scanning scattering matrix that constitutes the target under a given abnormal angle. The imaging similarity analysis refers to the cosine similarity of the compared images.

4. The method for fusing and modeling the measured parameters of special structural components as described in claim 3, characterized in that, Step S2 includes: Step S21: At each abnormal angle, determine the scanning angle and frequency range to be obtained based on the maximum size of the target, set the scanning frequency and scanning azimuth, set the number of scanning points according to the resolution requirements, and obtain the two-dimensional scattering data under simulation and RCS anechoic chamber test respectively. Step S22: Perform inverse Fourier transform on the two-dimensional scattering data from the simulation and RCS anechoic chamber test in the range and azimuth directions to obtain the target two-dimensional radar image. Analyze the similarity between the two images. Based on the differences between the simulation and RCS anechoic chamber test images, analyze the corresponding position of the abnormal scattering characteristic region in the target geometric model.

5. The method for fusing and modeling the measured parameters of special structural components as described in claim 1, characterized in that, Step S21 includes: the imaging lengths in the range and azimuth directions are: in, At the speed of light, These are the center frequency, center azimuth, and observation elevation angle, respectively. These are the scanning frequency and the scanning azimuth range, respectively. These are the imaging lengths in the range and azimuth directions, respectively, and their corresponding imaging ranges are respectively... The imaging resolution is: in, These are the resolutions in the range and azimuth directions, respectively. These represent the number of scans in the range and azimuth directions, respectively.

6. The method for fusing and modeling the measured parameters of special structural components as described in claim 1, characterized in that, Step S22 includes: given two image vectors A and B, cosine similarity Represented as: in These represent the components of vectors A and B, respectively, with the subscript i indicating the i-th element in the vector.

7. The method for fusing and modeling the measured parameters of special structural components as described in claim 1, characterized in that, Step S3 includes: Step S31: Project the target geometric model onto the imaging plane, mark the scattering center position of each component corresponding to the radar imaging, and analyze its scattering type; Step S32: Extract the scattering center of the abnormal region in the image, and reconstruct the scattering data of the abnormal region using the point scattering center model as the expected value of the scattering characteristics of the special structural component.

8. The method for fusing and modeling the measured parameters of special structural components as described in claim 1, characterized in that, Step S4 includes: selecting a parameterized model of a special structural component, setting initial geometric parameters, sequentially adjusting the position, scale, and attitude parameters in the initial geometric parameters, reconstructing the RCS and radar imaging, calculating the error with the expected value of the scattering characteristics of the special structural component, solving for the optimal parameters through gradient descent or numerical optimization to obtain the optimal parameterized model; replacing the scattering component in the geometric model with the optimal parameterized model to construct the new target geometric model.

9. An electronic device, characterized in that, It includes a processor and a memory, wherein the memory stores a computer program, which, when executed by the processor, implements the method of any one of claims 1 to 8.

10. A readable storage medium, characterized in that, The readable storage medium stores a computer program, which, when executed by a processor, implements the method of any one of claims 1 to 8.

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