Evaluation method of electromagnetic coupling strength between cooperative objectives and environment

Abstract

The present invention discloses a method for assessing the electromagnetic coupling strength between a cooperative target and its environment, specifically comprising the following steps: Step 1: establishing a three-dimensional geometric model of the target; Step 2: establishing a background model of the actual scene and constructing a composite model of the actual scene and the target; Step 3: verifying and repairing the composite model established in Step 2, and meshing the verified and repaired composite model; Step 4: using a bouncing ray algorithm to calculate electromagnetic scattering characteristic data of the meshed composite model at a specified bouncing order to obtain data on the target's scattering ability for incident electromagnetic waves; Step 5: correlating the scattering ability data obtained in Step 4 with the number of bouncing times; and Step 6: obtaining a coupling strength assessment result based on the correlation structure of Step 5. The present invention solves the problem in the prior art that solving the coupled scattering of the composite model is difficult and inefficient due to the uncertainty and randomness of the actual rough surface background.

Description

Technical Field

[0001] The invention belongs to the technical field of computer simulation methods for target electromagnetic scattering characteristics, and relates to a method for evaluating electromagnetic coupling strength between a cooperative target and an environment. Background Art

[0002] In the radar field, electromagnetic scattering characteristics (RCS) are a key parameter in radar system design and a primary metric for radar target recognition and detection. Simulation and calculation using electromagnetic scattering algorithms is one of the primary sources of electromagnetic scattering characteristic data. These algorithms are primarily categorized into numerical algorithms and high-frequency approximation algorithms.

[0003] Typically, the real environment and the corresponding simulation model are primarily composed of multiple elements, including background, target, and interference. In complex scenarios, the target surface is illuminated not only by the direct incident wave but also by near-field scattered waves from the background. Especially for strong scattering backgrounds, the coupled scattered field is a non-negligible component of the total scattered field. Therefore, when calculating composite RCS, ignoring the contribution of electromagnetic coupling between the target and the environment and performing simple vector superposition often results in significant errors, which in turn affects subsequent research and applications. However, due to the uncertainty and randomness of the actual rough surface background, solving coupled scattering in composite models is difficult and requires a large amount of computation, which significantly affects computational efficiency. Numerical algorithms offer high accuracy in solving electromagnetic coupling problems, but at high frequencies, the enormous computational effort consumes excessive time and computing resources, making them unsuitable. High-frequency algorithms only provide approximate solutions and suffer from accuracy issues.

[0004] In summary, due to the complexity and randomness of electromagnetic coupling calculations, existing electromagnetic scattering algorithms often find it difficult to ensure high calculation accuracy of the composite model RCS while maintaining good efficiency. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for evaluating the electromagnetic coupling strength between a cooperative target and an environment, which solves the problem in the prior art that the uncertainty and randomness of the actual rough surface background make the solution of the composite model coupled scattering difficult and affect the efficiency.

[0006] The technical solution adopted by the present invention is a method for evaluating the electromagnetic coupling strength between a cooperative target and the environment, which is specifically implemented according to the following steps:

[0007] Step 1: Establish a target three-dimensional geometric model;

[0008] Step 2: Establish a background model of the actual scene, and then construct a composite model of the actual scene and the target based on the background model and the target 3D geometric model established in step 1;

[0009] Step 3: verify and repair the composite model established in step 2, and mesh the verified and repaired composite model;

[0010] Step 4: Using a bouncing ray algorithm, the electromagnetic scattering characteristic data of the meshed composite model with a specified bouncing order is calculated to obtain the scattering ability data of the target to the incident electromagnetic wave;

[0011] Step 5, correlating the scattering power data obtained in step 4 with the number of bounces;

[0012] Step 6: Obtain the coupling strength evaluation result based on the correlation structure of step 5.

[0013] The present invention is also characterized in that:

[0014] Step 1 is as follows:

[0015] According to the target parameters and drawings, the target three-dimensional geometric model is built using the modeling software Rhino.

[0016] Step 2 is as follows: Based on the actual scene, a random dynamic background model is generated using the Monte Carlo algorithm, and a composite model of the background and target is obtained according to the arrangement of the real scene.

[0017] The verification and repair of the composite model in step 3 is as follows:

[0018] 3D Max software is used to identify and repair topological errors in composite models.

[0019] The repair work in step 3 is as follows:

[0020] Read the STL file of the composite model, build a topological information graph and an adjacency matrix, establish an error record array and generate an error description graph based on it, repair and delete the erroneous faces, edges and vertices according to the error description graph, refresh the topological information graph after deletion, and obtain the repaired composite model.

[0021] In step 3, meshing of the verified repaired composite model is performed as follows:

[0022] The segmentation area is set according to the angle of the incident wave. The area not illuminated by the incident wave is not segmented. The area illuminated by the incident wave needs to be segmented according to the frequency of the incident wave.

[0023] Determine the subdivision accuracy based on the calculated frequency band, and select a quarter wavelength as the subdivision accuracy. The relationship between wavelength λ and frequency f is:

[0024]

[0025] Where c is the speed of electromagnetic wave propagation, which is the speed of light in a vacuum;

[0026] The model data after segmentation includes the target number of face elements, the numbers of the vertices of the triangular face elements, and the spatial coordinate target information of the vertices of the triangular face elements.

[0027] Step 4 is as follows:

[0028] Step 4.1: Set the incident wave parameters and environmental parameters, including incident wave frequency, incident elevation angle, incident azimuth angle, receiving elevation angle, receiving azimuth angle, polarization mode, and single or dual station.

[0029] Step 4.2: According to the parameters set in step 4.1, an incident wave is emitted under corresponding conditions to illuminate the model that has been meshed in step 3. The occlusion of the surface elements in the meshed composite model is determined, and the surface elements are divided into illuminated surface elements and blocked surface elements. The direction vector of the incident wave is The normal vector of the surface element is When the angle between the incident direction of the ray and the normal vector is an obtuse angle, the surface element is judged to be illuminated, and is called an illuminated surface element; when the angle is an acute angle, the surface element is judged to be blocked and cannot be illuminated, and is called an blocked surface element. The formula is:

[0030] when When , it is judged as an illuminated surface element;

[0031] when When , it is judged as an occluded surface element;

[0032] Step 4.3: Set the scattering order. If the scattering order is 1, the ray tracing is performed once, that is, the ray scattered by the corresponding surface element is not traced, and step 4.4 is directly executed. If the scattering order is greater than or equal to 2, the ray scattered by the corresponding surface element becomes the next incident wave. The center coordinate of the surface element is used as the starting point of the second-order incident wave, and the direction of the first-order reflected wave obtained by Fresnel's theorem is used as the direction of the second-order incident wave. The scattering field of the ray reaching the next surface element is traced and calculated. Similarly, the scattering fields of different scattering orders are calculated according to the scattering order, and step 4.4 is then executed again.

[0033] Step 4.4, solve the total scattered field. The specific expression is:

[0034]

[0035] According to step 4.3, the scattering field intensity of the nth element i is calculated. I is the set scattering order, N is the total number of illuminated elements, the first summation sign indicates the superposition of the scattering field intensities of the n-th illuminated element from the 1st to the Ith order scattering; the second summation sign indicates the vector superposition of the scattering field intensities of all rays illuminating the element to obtain the total scattering field.

[0036] Step 4.5: Use the total scattered field to solve the radar cross section σ, which is the RCS data, which is used to represent the scattering ability of the target to the incident electromagnetic wave. The specific expression is:

[0037]

[0038] Where R represents the distance from the scatterer (target) to the receiving point, represents the electric field strength of the incident field;

[0039] Step 4.6: Follow steps 4.4-4.5 and set different scattering orders to obtain the radar cross section σ under different scattering orders, that is, the radar cross section σ under different numbers of bounces.

[0040] In step 4.2, if the surface element is judged to be illuminated, multiple occlusion judgments need to be performed based on the surface element normal and the direction of the incident wave. In the case of multiple occlusions, the distance between the ray starting point and the surface element is recorded, and the surface element closest to the ray source point is the illuminated surface element.

[0041] When calculating the scattered field intensity of different scattering orders of the illuminated surface element in step 4.4, the contribution of the illuminated surface element to the far-field scattered field is solved by the equivalent electromagnetic flow on the illuminated surface element, that is, the scattered field intensity on the illuminated surface element. The scattered field intensity of any scattering order on any illuminated surface element is calculated according to the following process:

[0042] In a vacuum environment, the surface induced current on an ideal conductor target is The formula is:

[0043]

[0044] Where, Represented as source point The unit normal vector of the surface element at , It represents the magnetic field intensity of the incident wave. The specific formula is:

[0045]

[0046] Among them, E in represents the electric field strength of the incident wave, Z0 = 377Ω, represents the wave impedance in vacuum;

[0047] According to the far-field condition approximation |kR|>>1, the far-field scattered field intensity generated by the induced current on the surface element illuminated by the ideal conductor target is The calculation formula is as follows:

[0048]

[0049] In the formula, j represents the imaginary unit, k represents the wave number, represents the unit vector along the incident direction, represents the unit vector along the scattering direction, and R represents the distance from the source point r′ to the observation point r;

[0050] The integral term in the scattered field intensity is solved using the Gordon integral, and the formula for the Gordon integral is:

[0051]

[0052] Where, T stands for The length of the projection on the polygon, M represents the number of edges of the polygon, represents the edge vector of the mth edge of the polygon, Represents the position coordinates of the center of the mth edge of the polygon.

[0053] Step 5 is as follows:

[0054] Step 5.1: Remove duplicate values, eliminate outliers, and fill in missing values ​​for the scattering power data obtained in step 4. Treat each filled scattering power data as a vector in a multidimensional space. The dimensions of the vector are composed of the various parameters of the scattering data, specifically: frequency, azimuth, elevation, polarization mode, amplitude, phase, RCS data, and scattering order.

[0055] Step 5.2 uses the K-means clustering algorithm to cluster the scattering power data and construct a database. Specifically, the scattering power data obtained in step 5.1 are clustered according to the RCS value. The number of clusters K, that is, the number of clusters, is selected according to the elbow method. A series of different cluster numbers are selected from integers ranging from 1 to 20. The total cohesive sum of squares SSE for each K is calculated traversally. The specific calculation formula is:

[0056]

[0057] Where n is the total number of RCS data points, x i Represents the RCS value of the data point, μ k The RCS value representing the centroid of the cluster;

[0058] Draw a graph of the relationship between SSE and K, and find the position where the slope begins to increase, that is, the position where the curve begins to flatten. This position is the elbow position, and the number of clusters K corresponding to this position is the determined optimal number of clusters;

[0059] Randomly select M points as the initial centroids and calculate the Euclidean distance from each data point to the M centroids. The specific calculation formula of the Euclidean distance is:

[0060]

[0061] Among them, x i Represents the RCS value of the i-th data point, μ k Represents the RCS value of the center of mass, d is the number of centers of mass, x ij Represents the RCS value of the i-th data point in the j-th centroid, μ kj Indicates the RCS value of the j-th centroid.

[0062] Assign the data point to the cluster corresponding to the nearest centroid, and then recalculate the centroid within the cluster, which is the average value of all data points in the cluster The specific calculation formula is:

[0063]

[0064] Among them, C k represents the set of data points of the kth cluster, |C k | represents the number of data points in the cluster;

[0065] Repeat the above steps of calculating the Euclidean distance and updating the centroid until the calculation results converge and the centroid is stable;

[0066] Step 5.3: Filter the data in each cluster based on the correlation between the number of bounces and the RCS value. Specifically, query the scattering power data in all clusters. If there are scattering power data with the same values ​​of the four parameters of frequency, azimuth, elevation angle, and polarization mode in the same cluster, and if there are data with an unlimited number of bounces, the data with the lowest number of bounces is taken as the correct correlation result under the parameter conditions.

[0067] If the parameter conditions are the same, the data with unlimited bounce times are not in the same cluster as the data with other bounce times, and the data with unlimited bounce times is taken as the correct association result under the parameter conditions;

[0068] Step 6 is as follows:

[0069] Based on the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. Specifically, a correlation result with a bounce number less than 2 indicates low coupling strength and low-order coupling, while a correlation result with a bounce number greater than or equal to 2 or an unlimited bounce number indicates high coupling strength and non-negligible high-order coupling paths. All the correlation result data are analyzed to obtain the coupling strength assessment results.

[0070] The beneficial effects of the present invention are:

[0071] The present invention sets the segmentation area according to the angle of the incident wave. The area not irradiated by the incident wave is not segmented. The area irradiated by the incident wave needs to be segmented according to the frequency of the incident wave. The coupling area is divided and the coupling calculation is performed. It can effectively simplify the coupling calculation. After the calculation, according to the obtained prior data, cluster analysis is performed and the number of ray tracing is confirmed according to the cluster data. Under the premise of ensuring that the RCS calculation accuracy meets the requirements, the calculation efficiency is effectively improved and the calculation time is saved. It is a beneficial supplement and improvement to the bouncing ray method and an effective exploration and extension of the research on the electromagnetic scattering characteristics of the target. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 is the three-dimensional geometric model of the ship in Example 6 of the present invention;

[0073] Figure 2 It is the ship-dynamic sea surface composite model in Example 6 of the present invention;

[0074] Figure 3 A flowchart for repairing and optimizing the composite model in the method for evaluating the electromagnetic coupling strength between the cooperation target and the environment of the present invention;

[0075] Figure 4 This is a flow chart of using a bouncing ray algorithm in the method for evaluating the electromagnetic coupling strength between a cooperative target and an environment of the present invention to calculate electromagnetic scattering characteristic data of a specified bouncing order of a meshed composite model. DETAILED DESCRIPTION

[0076] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0077] Example 1

[0078] The method for evaluating the electromagnetic coupling strength between a cooperative target and an environment of the present invention is specifically implemented according to the following steps:

[0079] Step 1: Establish a target three-dimensional geometric model;

[0080] Step 2: Establish a background model of the actual scene, and then construct a composite model of the actual scene and the target based on the background model and the target 3D geometric model established in step 1;

[0081] Step 3: verify and repair the composite model established in step 2, and mesh the verified and repaired composite model;

[0082] Step 4: Using a bouncing ray algorithm, the electromagnetic scattering characteristic data of the meshed composite model with a specified bouncing order is calculated to obtain the scattering ability data of the target to the incident electromagnetic wave;

[0083] Step 5, correlating the scattering power data obtained in step 4 with the number of bounces;

[0084] Step 6: Obtain the coupling strength evaluation result based on the correlation structure of step 5.

[0085] Example 2

[0086] The method for evaluating the electromagnetic coupling strength between a cooperative target and an environment of the present invention is specifically implemented according to the following steps:

[0087] Step 1: Use the modeling software Rhino to build the target 3D geometric model according to the target parameters and drawings;

[0088] Step 2: Based on the actual scene, a random dynamic background model is generated using the Monte Carlo algorithm, and a composite model of the background and target is obtained according to the arrangement of the real scene;

[0089] Step 3: Use 3D Max software to identify and repair topological errors in the composite model created in step 2. The repair workflow is as follows: Figure 3 As shown, specifically: read the STL file of the composite model, build a topology information graph and an adjacency matrix, establish an error record array and generate an error description graph based on it, repair and delete the erroneous faces, edges and vertices according to the error description graph, refresh the topology information graph after deletion, obtain the repaired composite model, and then mesh the verified repaired composite model;

[0090] Step 4: Using a bouncing ray algorithm, the electromagnetic scattering characteristic data of the meshed composite model with a specified bouncing order is calculated to obtain the scattering ability data of the target to the incident electromagnetic wave;

[0091] Step 5, correlating the scattering power data obtained in step 4 with the number of bounces;

[0092] Step 6: Obtain the coupling strength evaluation result based on the correlation structure of step 5.

[0093] Example 3

[0094] Based on Example 2, the meshing of the verified and repaired composite model in step 3 is specifically as follows:

[0095] The segmentation area is set according to the angle of the incident wave. The area not illuminated by the incident wave is not segmented. The area illuminated by the incident wave needs to be segmented according to the frequency of the incident wave.

[0096] Determine the subdivision accuracy based on the calculated frequency band, and select a quarter wavelength as the subdivision accuracy. The relationship between wavelength λ and frequency f is:

[0097]

[0098] Where c is the speed of electromagnetic wave propagation, which is the speed of light in a vacuum;

[0099] The model data after segmentation includes the target number of face elements, the numbers of the vertices of the triangular face elements, and the spatial coordinate target information of the vertices of the triangular face elements.

[0100] Example 4

[0101] Based on Example 3, the process of step 4 is as follows Figure 4 As shown, specifically:

[0102] Step 4.1: Set the incident wave parameters and environmental parameters, including incident wave frequency, incident elevation angle, incident azimuth angle, receiving elevation angle, receiving azimuth angle, polarization mode, and single or dual station.

[0103] Step 4.2: According to the parameters set in step 4.1, an incident wave is emitted under corresponding conditions to illuminate the model that has been meshed in step 3. The occlusion of the surface elements in the meshed composite model is determined, and the surface elements are divided into illuminated surface elements and blocked surface elements. The direction vector of the incident wave is The normal vector of the surface element is When the angle between the incident direction of the ray and the normal vector is an obtuse angle, the surface element is judged to be illuminated, and is called an illuminated surface element; when the angle is an acute angle, the surface element is judged to be blocked and cannot be illuminated, and is called an blocked surface element. The formula is:

[0104] when When , it is judged as an illuminated surface element;

[0105] when When , it is judged as an occluded surface element;

[0106] Step 4.3: Set the scattering order. If the scattering order is 1, the ray tracing is performed once, that is, the ray scattered by the corresponding surface element is not traced, and step 4.4 is directly executed. If the scattering order is greater than or equal to 2, the ray scattered by the corresponding surface element becomes the next incident wave. The center coordinate of the surface element is used as the starting point of the second-order incident wave, and the direction of the first-order reflected wave obtained by Fresnel's theorem is used as the direction of the second-order incident wave. The scattering field of the ray reaching the next surface element is traced and calculated. Similarly, the scattering fields of different scattering orders are calculated according to the scattering order, and step 4.4 is then executed again.

[0107] Step 4.4, solve the total scattered field. The specific expression is:

[0108]

[0109] According to step 4.3, the scattering field intensity of the nth element i is calculated. I is the set scattering order, N is the total number of illuminated elements, the first summation sign indicates the superposition of the scattering field intensities of the n-th illuminated element from the 1st to the Ith order scattering; the second summation sign indicates the vector superposition of the scattering field intensities of all rays illuminating the element to obtain the total scattering field.

[0110] Step 4.5: Use the total scattered field to solve the radar cross section σ, which is the RCS data, used to represent the target's scattering ability to the incident electromagnetic wave. The specific expression is:

[0111]

[0112] Where R represents the distance from the scatterer (target) to the receiving point, represents the electric field strength of the incident field;

[0113] Step 4.6: Follow steps 4.4-4.5 and set different scattering orders to obtain the radar cross section σ under different scattering orders, that is, the radar cross section σ under different numbers of bounces.

[0114] Example 5

[0115] Based on Example 3, in step 4.2, if it is judged that the surface element is illuminated, multiple occlusion judgments need to be performed based on the surface element normal and the direction of the incident wave. In the case of multiple occlusions, the distance between the starting point of the ray and the surface element is recorded, and the surface element closest to the ray source point is the illuminated surface element.

[0116] When calculating the scattered field intensity of different scattering orders of the illuminated surface element in step 4.4, the contribution of the illuminated surface element to the far-field scattered field is solved by the equivalent electromagnetic flow on the illuminated surface element, that is, the scattered field intensity on the illuminated surface element. The scattered field intensity of any scattering order on any illuminated surface element is calculated according to the following process:

[0117] In a vacuum environment, the surface induced current on an ideal conductor target is The formula is:

[0118]

[0119] Where, Represented as source point The unit normal vector of the surface element at , It represents the magnetic field intensity of the incident wave. The specific formula is:

[0120]

[0121] Among them, E in represents the electric field strength of the incident wave, Z0 = 377Ω, represents the wave impedance in vacuum;

[0122] According to the far-field condition approximation |kR|>>1, the far-field scattered field intensity generated by the induced current on the surface element illuminated by the ideal conductor target is The calculation formula is as follows:

[0123]

[0124] In the formula, j represents the imaginary unit, k represents the wave number, represents the unit vector along the incident direction, represents the unit vector along the scattering direction, and R represents the distance from the source point r′ to the observation point r;

[0125] The integral term in the scattered field intensity is solved using the Gordon integral, and the formula for the Gordon integral is:

[0126]

[0127] Where, T stands for The length of the projection on the polygon, M represents the number of edges of the polygon, represents the edge vector of the mth edge of the polygon, Represents the position coordinates of the center of the mth edge of the polygon.

[0128] Step 5 is as follows:

[0129] Step 5.1: Remove duplicate values, eliminate outliers, and fill in missing values ​​for the scattering power data obtained in step 4. Treat each filled scattering power data as a vector in a multidimensional space. The dimensions of the vector are composed of the various parameters of the scattering data, specifically: frequency, azimuth, elevation, polarization mode, amplitude, phase, RCS data, and scattering order.

[0130] Step 5.2 uses the K-means clustering algorithm to cluster the scattering power data and construct a database. Specifically, the scattering power data obtained in step 5.1 are clustered according to the RCS value. The number of clusters K, that is, the number of clusters, is selected according to the elbow method. A series of different cluster numbers are selected from integers ranging from 1 to 20. The total cohesive sum of squares SSE for each K is calculated traversally. The specific calculation formula is:

[0131]

[0132] Where n is the total number of RCS data points, x i Represents the RCS value of the data point, μ k The RCS value representing the centroid of the cluster;

[0133] Draw a graph of the relationship between SSE and K, and find the position where the slope begins to increase, that is, the position where the curve begins to flatten. This position is the elbow position, and the number of clusters K corresponding to this position is the determined optimal number of clusters;

[0134] Randomly select M points as the initial centroids and calculate the Euclidean distance from each data point to the M centroids. The specific calculation formula of the Euclidean distance is:

[0135]

[0136] Among them, x i Represents the RCS value of the data point, μ k represents the RCS value of the centroid, d is the number of centroids; x ij Represents the RCS value of the i-th data point in the j-th centroid, μ kj Indicates the RCS value of the j-th centroid.

[0137] Assign the data point to the cluster corresponding to the nearest centroid, and then recalculate the centroid within the cluster, which is the average value of all data points in the cluster The specific calculation formula is:

[0138]

[0139] Among them, C k represents the set of data points of the kth cluster, |C k | represents the number of data points in the cluster;

[0140] Repeat the above steps of calculating the Euclidean distance and updating the centroid until the calculation results converge and the centroid is stable;

[0141] Step 5.3: Filter the data in each cluster based on the correlation between the number of bounces and the RCS value. Specifically, query the scattering power data in all clusters. If there are scattering power data with the same values ​​of the four parameters of frequency, azimuth, elevation angle, and polarization mode in the same cluster, and if there are data with an unlimited number of bounces, the data with the lowest number of bounces is taken as the correct correlation result under the parameter conditions.

[0142] If the parameter conditions are the same, the data with unlimited bounce times are not in the same cluster as the data with other bounce times, and the data with unlimited bounce times is taken as the correct association result under the parameter conditions;

[0143] Step 6 is as follows:

[0144] Based on the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. Specifically, a correlation result with a bounce number less than 2 indicates low coupling strength and low-order coupling, while a correlation result with a bounce number greater than or equal to 2 or an unlimited bounce number indicates high coupling strength and non-negligible high-order coupling paths. All the correlation result data are analyzed to obtain the coupling strength assessment results.

[0145] Example 6

[0146] Based on Example 5, this example takes a ship as an example, and the specific process is as follows:

[0147] Step 1: Establish a typical target 3D geometric model

[0148] Use professional modeling software Rhino to build the target 3D geometric model. Take the ship as an example. Figure 1 As shown. Based on the ship's parameters and blueprints, use the curve drawing tools to accurately draw the ship's contour curves, such as the longitudinal section line, transverse section line, and waterline. At the same time, you can control the curves according to the design drawings and make fine adjustments to make the curves more consistent with the actual shape.

[0149] After drawing the curve, use the surface modeling tool in the software to sweep the drawn curve to generate the hull surface. During the modeling process, pay attention to the continuity and rationality of the curve to avoid problems such as distortion and gaps at intersections.

[0150] For parts of the ship with special shapes such as the bulbous bow and stern shaft, detailed modeling can be performed through methods such as Boolean operations to ensure the integrity of the ship model.

[0151] Step 2: Establish a composite model of target and background;

[0152] Use the typical target 3D geometric model from step 1 to build a ship-dynamic sea surface composite model. This model can simulate the ship's movement in a real dynamic sea surface scene and reflect the electromagnetic scattering characteristics of the actual scene to a certain extent.

[0153] The dynamic sea surface model is established according to the PM sea spectrum, which is derived from the long-term measured data of the Atlantic sea surface and has strong rationality and authenticity. Its expression is

[0154]

[0155] Among them, K is the spatial wave number of the wave, U 19.5 is the wind speed at 19.5 m above the sea surface, α = 8.1 × 10 -3 , β=0.74,g=9.81m / s 2 .

[0156] By integrating the PM spectrum expression, the root mean square height of the sea surface can be obtained.

[0157]

[0158] The calculated wave height is

[0159]

[0160] Based on the above theory, the PM spectrum dynamic sea surface model is established using the linear filtering method. It is arranged with the ship model established in step 1 according to the actual sea battlefield environment to establish a ship-dynamic sea surface composite model, as shown in the following example: Figure 2 .

[0161] Step 3: Model verification, repair, and meshing

[0162] After completing the construction of the ship-dynamic sea surface composite model, the model needs to be meshed to facilitate the subsequent bouncing ray algorithm calculation.

[0163] In electromagnetic scattering algorithms, the model's mesh size must be between one-tenth and one-eighth of a wavelength. However, in complex scene calculations, where the target is electrically large, using a quarter-wavelength mesh size can yield accurate results.

[0164] During model segmentation, due to the multiple combinations of the target on the sea background, the model file may have a series of problems to be solved, such as incorrect opening of closed surfaces, filling of holes, and stitching of open edges. Therefore, it is necessary to first verify the integrity of the model and repair and improve the problems found.

[0165] In this embodiment, 3D Max software is used to complete the identification and repair of STL model topology errors. Before repairing, the adjacency relationship of the triangle face set is constructed, and arrays of error face, edge and vertex are established to record various errors, and an error description diagram is generated accordingly. At the same time, three arrays are set up to record the face, edge and vertex to be deleted to assist the repair process. The specific steps of model repair are as follows: Figure 3 shown.

[0166] After the repair is completed, the topology tool can be used to optimize the model. For parts that have a long sight line, low detail requirements, and are too complex but do not affect ray tracing, the number and density of facets can be appropriately reduced to obtain a more reasonable and easier to calculate mesh model.

[0167] At the same time, a reasonable subdivision area can be set according to the angle of the incident wave. The area not illuminated by the incident wave can usually increase the unit value of the grid subdivision, reduce the number of subdivision elements, and effectively improve the calculation efficiency.

[0168] The segmentation accuracy is determined according to the calculated frequency band. The model data contains target information such as the number of target facets, the vertex numbers of the triangle facets, and the spatial coordinates of the triangle facet vertices. The consistency of the included content is conducive to batch processing and storage during calculation.

[0169] Step 4: Using a bouncing ray algorithm, the electromagnetic scattering characteristic data of the meshed composite model with a specified bouncing order is calculated to obtain the scattering ability data of the target to the incident electromagnetic wave;

[0170] In this embodiment, the incident wave attributes are set as follows:

[0171] Mode setting: dual station;

[0172] Frequency settings: 4GHz, 10GHz, 16GHz, covering the C, X, and Ku bands commonly used in the military field.

[0173] Angle setting: The incident azimuth angle is The incident pitch angle range is θ=0°-90°, with a step of 1.

[0174] Bounce times settings: 1, 2, 3, 4, -1 (indicates unlimited number of times).

[0175] Polarization mode: HH polarization, VV polarization;

[0176] The obtained scattering ability data are shown in Table 1 (polarization mode 1 represents HH polarization, and 2 represents VV polarization):

[0177] Table 1 Scattering ability data table

[0178]

[0179]

[0180] Step 5: Process the scattering capability data obtained in step 4. The processed data is regarded as a vector in a multidimensional space. The dimensions of the vector are composed of various parameters of the scattering data, specifically: frequency, azimuth, elevation, polarization mode, amplitude, phase, RCS data, and scattering order. The K-means clustering algorithm is used to cluster the scattering capability data, build a database, and obtain correlation results.

[0181] Step 6. Based on the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. In this embodiment, when the incident pitch angle is less than or equal to 30°, the specular scattering of seawater is dominant, and the variation is small with the increase of the pitch angle. At this time, the coupling correlation between the ship and the sea surface is small, and the data of all scattering orders are in the same cluster. When the scattering order is set to 1, accurate results can be obtained; when the incident pitch angle is greater than 30°, that is, at medium and high incident angles, diffuse scattering is dominant, and the variation is large with the increase of the pitch angle. However, due to the electrically large size characteristics of the ship, the data of scattering orders greater than or equal to 2 are in the same cluster. When the scattering order is set to 2, accurate results can be obtained. In some special parts, such as when incident from the bow, due to the complex cavity structure on the antenna, it is necessary to set an unlimited scattering order to obtain accurate results.

Claims

1. A method for assessing electromagnetic coupling strength between a cooperative target and an environment, characterized in that: The specific implementation steps are as follows: Step 1: Establish a target three-dimensional geometric model; Step 2: Establish a background model of the actual scene, and then construct a composite model of the actual scene and the target based on the background model and the target 3D geometric model established in step 1; Step 3: verify and repair the composite model established in step 2, and mesh the verified and repaired composite model; Step 4: Using a bouncing ray algorithm, the electromagnetic scattering characteristic data of the meshed composite model with a specified bouncing order is calculated to obtain the scattering ability data of the target to the incident electromagnetic wave; Specifically: Step 4.1: Set the incident wave parameters and environmental parameters, including incident wave frequency, incident elevation angle, incident azimuth angle, receiving elevation angle, receiving azimuth angle, polarization mode, and single or dual station. Step 4.2: According to the parameters set in step 4.1, an incident wave is emitted under corresponding conditions to illuminate the model that has been meshed in step 3. The occlusion of the surface elements in the meshed composite model is determined, and the surface elements are divided into illuminated surface elements and blocked surface elements. The direction vector of the incident wave is , the normal vector of the surface element is When the angle between the incident direction of the ray and the normal vector is an obtuse angle, the surface element is judged to be illuminated, and is called an illuminated surface element; when the angle is an acute angle, the surface element is judged to be blocked and cannot be illuminated, and is called a blocked surface element; it can be expressed as: when When , it is judged as an illuminated surface element; when When , it is judged as an occluded surface element; Step 4.3: Set the scattering order. If the scattering order is 1, the ray tracing is performed once, that is, the ray scattered by the corresponding surface element is not traced, and step 4.4 is directly executed. If the scattering order is greater than or equal to 2, the ray scattered by the corresponding surface element becomes the next incident wave. The center coordinate of the surface element is used as the starting point of the second-order incident wave, and the direction of the first-order reflected wave obtained by Fresnel's theorem is used as the direction of the second-order incident wave. The scattering field of the ray reaching the next surface element is traced and calculated. Similarly, the scattering fields of different scattering orders are calculated according to the scattering order, and step 4.4 is then executed again. Step 4.4, solve the total scattered field. The specific expression is: According to step 4.3, the Surface element Order scattered field intensity , I is the set scattering order, N is the total number of illuminated elements, the first summation sign indicates the superposition of the scattered field intensities of the n-th illuminated element from the 1st to the Ith order scattering; the second summation sign indicates the vector superposition of the scattered field intensities of all rays illuminating the element to obtain the total scattered field; Step 4.5: Use the total scattered field to solve the radar cross section , which is the RCS data, is used to represent the scattering ability of the target to the incident electromagnetic wave. The specific expression is: in, represents the distance from the scatterer (target) to the receiving point, represents the electric field strength of the incident field; Step 4.6: Follow steps 4.4-4.5 and set different scattering orders to obtain radar cross sections under different scattering orders. , which is the radar cross section under different numbers of bounces ; Step 5: Correlate the scattering power data obtained in step 4 with the number of bounces; specifically: Step 5.1: Remove duplicate values, eliminate outliers, and fill in missing values ​​for the scattering power data obtained in step 4. Treat each filled scattering power data as a vector in a multidimensional space. The dimensions of the vector are composed of the various parameters of the scattering data, specifically: frequency, azimuth, elevation, polarization mode, amplitude, phase, RCS data, and scattering order. Step 5.2 Use K-means clustering algorithm to cluster the scattering ability data and build a database. Specifically, the scattering ability data obtained in step 5.1 are clustered according to the RCS value. The number of clusters is , that is, the number of clusters, is selected according to the elbow method, and a series of different cluster numbers are selected from integers from 1 to 20, and each cluster is calculated The total sum of squares of cohesion SSE is calculated as follows: Where, is the total number of RCS data points, that is, the total number of scattering power data, Represents the RCS value of the data point, The RCS value representing the centroid of the cluster; Drawing SSE with , find the position where the slope starts to increase, that is, the position where the curve starts to become flat. This position is the elbow position, and the number of clusters corresponding to this position is That is the optimal number of clusters determined; Randomly select M points as the initial centroids and calculate the Euclidean distance from each data point to the M centroids. The specific calculation formula of the Euclidean distance is: in, Represents the RCS value of the data point, Indicates the RCS value of the center of mass, is the number of centroids; Indicates the The first The RCS value of the data point, Indicates the The RCS value of the centroid; Assign the data point to the cluster corresponding to the nearest centroid, and then recalculate the centroid within the cluster, which is the average value of all data points in the cluster , the specific calculation formula is: in, Indicates the A set of data points in a cluster, Indicates the number of data points in the cluster; Repeat the above steps of calculating the Euclidean distance and updating the centroid until the calculation results converge and the centroid is stable; Step 5.3: Filter the data in each cluster based on the correlation between the number of bounces and the RCS value. Specifically, query the scattering power data in all clusters. If there are scattering power data with the same values ​​of the four parameters of frequency, azimuth, elevation angle, and polarization mode in the same cluster, and if there are data with an unlimited number of bounces, the data with the lowest number of bounces is taken as the correct correlation result under the parameter conditions. If the parameter conditions are the same, the data with unlimited bounce times are not in the same cluster as the data with other bounce times, and the data with unlimited bounce times is taken as the correct association result under the parameter conditions; Step 6: Determine the coupling strength evaluation result based on the correlation structure of step 5, specifically: Based on the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. Specifically, a correlation result with a bounce number less than 2 indicates low coupling strength and low-order coupling, while a correlation result with a bounce number greater than or equal to 2 or an unlimited bounce number indicates high coupling strength and non-negligible high-order coupling paths. All the correlation result data are analyzed to obtain the coupling strength assessment results.

2. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 1, wherein: The step 1 is specifically as follows: According to the target parameters and drawings, the target three-dimensional geometric model is built using the modeling software Rhino.

3. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 2, wherein: The step 2 specifically includes: generating a random dynamic background model using a Monte Carlo algorithm according to the actual scene, and obtaining a composite model of the background and the target according to the arrangement of the real scene.

4. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 3, wherein: The verification and repair of the composite model in step 3 is specifically as follows: 3D Max software is used to identify and repair topological errors in composite models.

5. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 4, characterized in that: The repair work in step 3 is specifically as follows: Read the STL file of the composite model, build a topological information graph and an adjacency matrix, establish an error record array and generate an error description graph based on it, repair and delete the erroneous faces, edges and vertices according to the error description graph, refresh the topological information graph after deletion, and obtain the repaired composite model.

6. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 5, characterized in that: The meshing of the verified and repaired composite model in step 3 is specifically as follows: The segmentation area is set according to the angle of the incident wave. The area not illuminated by the incident wave is not segmented. The area illuminated by the incident wave needs to be segmented according to the frequency of the incident wave. Determine the segmentation accuracy based on the calculated frequency band, and select a quarter wavelength as the segmentation accuracy. and frequency The relationship is: in, is the speed of electromagnetic wave propagation, which is the speed of light in a vacuum; The model data after segmentation includes the target number of face elements, the numbers of the vertices of the triangular face elements, and the spatial coordinate target information of the vertices of the triangular face elements.

7. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 1, wherein: In step 4.2, if it is determined that the surface element is illuminated, multiple occlusion judgments need to be performed based on the surface element normal and the direction of the incident wave. In the case of multiple occlusions, the distance between the starting point of the ray and the surface element is recorded, and the surface element closest to the ray source point is the illuminated surface element.

8. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 7, characterized in that: When calculating the scattered field intensity of different scattering orders of the illuminated surface element in step 4.4, the contribution of the illuminated surface element to the far-field scattered field is solved by the equivalent electromagnetic flow on the illuminated surface element, that is, the scattered field intensity on the illuminated surface element. The scattered field intensity of any scattering order on any illuminated surface element is calculated according to the following process: In a vacuum environment, the surface induced current on an ideal conductor target is , the formula is: Where, Represented as source point The unit normal vector of the surface element at , It represents the magnetic field intensity of the incident wave. The specific formula is: in, represents the electric field strength of the incident wave, , represents the wave impedance in vacuum; Approximation based on far-field conditions , then the far-field scattered field intensity generated by the induced current on the surface element illuminated by the ideal conductor target is The calculation formula is as follows: Where, represents the imaginary unit, represents the wave number, represents the unit vector along the incident direction, represents the unit vector along the scattering direction, Indicates that from the source To the observation point distance; The integral term in the scattered field intensity is solved using the Gordon integral, and the formula for the Gordon integral is: Where, = , express The length of the projection on the polygon, Indicates the number of polygon edges. Represents the polygon The edge vector of the edge, Represents the polygon The position coordinates of the center of the edge.

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