Cooperative target and environment electromagnetic coupling strength evaluation method

Abstract

The invention discloses a cooperative target and environment electromagnetic coupling strength evaluation method. The method specifically comprises the following steps: step 1, establishing a target three-dimensional geometric model; 2, establishing a background model of an actual scene, and constructing a composite model of the actual scene and a target; 3, verifying and repairing the composite model established in the step 2, and performing mesh generation on the verified and repaired composite model; step 4, using a bounce ray algorithm to calculate electromagnetic scattering characteristic data of a specified bounce order of the composite model subjected to mesh generation, and obtaining scattering capability data of a target to incident electromagnetic waves; 5, associating the scattering capability data obtained in the step 4 with the number of bounces; and step 6, obtaining a coupling strength evaluation result according to the correlation structure in the step 5. According to the method, the problems that the solving difficulty of coupling scattering of the composite model is high and the efficiency is influenced due to the uncertainty and randomness of an actual rough surface background in the prior art are solved.

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 field of radar, electromagnetic scattering characteristics (RCS) are key parameters in radar system design and the main criterion for radar target recognition and detection. Using electromagnetic scattering algorithms for simulation calculations is one of the main sources of electromagnetic scattering characteristic data. Electromagnetic scattering algorithms are mainly divided into numerical algorithms and high-frequency approximate algorithms.

[0003] Usually, the real environment and the corresponding simulation model are mainly composed of multiple elements such as background, target, interference, etc. In complex scenes, the target surface is irradiated with not only direct incident waves, but also near-field scattered waves from the background. Especially for strong scattering background, the coupled scattered field is an important component of the total scattered field. Therefore, when calculating the composite RCS, if the contribution of electromagnetic coupling between the target and the environment is ignored, only simple vector superposition will often cause large errors, which will affect subsequent research and application. However, due to the uncertainty and randomness of the actual rough surface background, the solution of coupled scattering of the composite model is difficult, and the amount of calculation required is large, which greatly affects the calculation efficiency. Numerical algorithms have high accuracy in solving electromagnetic coupling problems, but in the high-frequency band, the huge amount of calculation will make the numerical algorithm consume too much time and computing resources, and become no longer applicable. The high-frequency algorithm only seeks an approximate solution, and there are some problems in accuracy.

[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 having 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 it difficult to solve the coupled scattering of the composite model, thus affecting 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 an environment, which is specifically implemented according to the following steps:

[0007] Step 1, establishing a target three-dimensional geometric model;

[0008] Step 2, establishing a background model of the actual scene, and then constructing a composite model of the actual scene and the target based on the background model and the target three-dimensional geometric model established in step 1;

[0009] Step 3, verifying and repairing the composite model established in step 2, and meshing the verified and repaired composite model;

[0010] Step 4, using a bouncing ray algorithm to calculate electromagnetic scattering characteristic data of a specified bouncing order of the meshed composite model, and obtaining 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 according to 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 modeling software Rhino is used to build the target three-dimensional geometric model.

[0016] Step 2 is specifically as follows: according to the actual scene, a random dynamic background model is generated using the Monte Carlo algorithm, and a composite model of the background and the 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, create 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, the meshing of the verified repaired composite model is as follows:

[0022] Set 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.

[0023] The subdivision accuracy is determined according to the calculated frequency band, and a quarter wavelength is selected as the subdivision accuracy. The relationship between wavelength λ and frequency f is:

[0024]

[0025] Among them, 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 number of target 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, single station or dual station;

[0029] Step 4.2, according to the parameters set in step 4.1, under corresponding conditions, an incident wave is emitted to illuminate the model meshed in step 3, and the occlusion of the surface elements in the meshed composite model is determined, which 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 face element is judged to be illuminated, and is an illuminated face element; when the angle is an acute angle, the face element is judged to be blocked and cannot be illuminated, and is a blocked face element; it can be expressed as:

[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 number of ray tracing is one, 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, and 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 the Fresnel 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. By analogy, the scattering fields of different scattering orders are calculated according to the scattering order, and then step 4.4 is executed;

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

[0034]

[0035] Among them, the i-th order scattered field intensity of the n-th surface element is calculated according to step 4.3 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 elements to obtain the total scattering field.

[0036] Step 4.5, use the total scattered field to solve the radar cross section σ, that is, 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, according to steps 4.4-4.5, by setting different scattering orders, obtain the radar scattering cross section σ under different scattering orders, that is, the radar scattering cross section σ under different numbers of bounces.

[0040] In step 4.2, if it is judged to be an illuminated surface element, then multiple occlusion judgments need to be made 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 scattering 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] In the formula, 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, 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] In the formula, T stands for The length of the projection on the polygon, M represents the number of edges of the face element 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, the scattering ability data obtained in step 4 are sequentially subjected to duplicate removal, outlier elimination, and missing value filling, and each filled scattering ability data is regarded as a vector in a multidimensional space, and the dimension of the vector is composed of 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 build a database. Specifically, the scattering power data 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 from 1 to 20. The total cohesive sum of squares SSE of 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 become flat. 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 ith 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 Represents the RCS value of the jth 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, the data in each cluster are screened for the correlation between the number of bounces and the RCS value, specifically: query the scattering ability data in all clusters, if there are scattering ability data with the same values ​​of the four parameters of frequency, azimuth, elevation angle, and polarization mode in the same cluster, and it contains data with unlimited number of bounces, take the data with the lowest number of bounces as the correct correlation result under the parameter condition;

[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] According to the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. Specifically, the correlation result with the number of bounces less than 2 indicates that the coupling strength is low and it is a low-order coupling. The correlation result with the number of bounces greater than or equal to 2 or the number of bounces is unlimited indicates that the coupling strength is high and the high-order coupling path cannot be ignored. All the correlation result data are analyzed to obtain the coupling strength evaluation result.

[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 that is 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. The coupling calculation can be effectively simplified. 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 Embodiment 6 of the present invention;

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

[0074] Figure 3 A flowchart of 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 The present invention 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 to calculate electromagnetic scattering characteristic data of a specified bouncing order of a meshed composite model. DETAILED DESCRIPTION

[0076] The present invention is 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, establishing a target three-dimensional geometric model;

[0080] Step 2, establishing a background model of the actual scene, and then constructing a composite model of the actual scene and the target based on the background model and the target three-dimensional geometric model established in step 1;

[0081] Step 3, verifying and repairing the composite model established in step 2, and meshing the verified and repaired composite model;

[0082] Step 4, using a bouncing ray algorithm to calculate electromagnetic scattering characteristic data of a specified bouncing order of the meshed composite model, and obtaining 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 according to 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: According to the actual scene, a Monte Carlo algorithm is used to generate a random dynamic background model, and a composite model of the background and the 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 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, obtain the repaired composite model, and then mesh the verified repaired composite model;

[0090] Step 4, using a bouncing ray algorithm to calculate electromagnetic scattering characteristic data of a specified bouncing order of the meshed composite model, and obtaining 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 according to the correlation structure of step 5.

[0093] Example 3

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

[0095] Set 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.

[0096] The subdivision accuracy is determined according to the calculated frequency band, and a quarter wavelength is selected as the subdivision accuracy. The relationship between wavelength λ and frequency f is:

[0097]

[0098] Among them, 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 number of target 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, single station or dual station;

[0103] Step 4.2, according to the parameters set in step 4.1, under corresponding conditions, an incident wave is emitted to illuminate the model meshed in step 3, and the occlusion of the surface elements in the meshed composite model is determined, which 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 face element is judged to be illuminated, and is an illuminated face element; when the angle is an acute angle, the face element is judged to be blocked and cannot be illuminated, and is a blocked face element; it can be expressed as:

[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 number of ray tracing is one, 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, and 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 the Fresnel 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. By analogy, the scattering fields of different scattering orders are calculated according to the scattering order, and then step 4.4 is executed;

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

[0108]

[0109] Among them, the i-th order scattered field intensity of the n-th surface element is calculated according to step 4.3 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 elements to obtain the total scattering field.

[0110] Step 4.5, use the total scattered field to solve the radar cross section σ, that is, RCS data, which is used to represent the scattering ability of the target 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, according to steps 4.4-4.5, by setting different scattering orders, obtain the radar scattering cross section σ under different scattering orders, that is, the radar scattering cross section σ under different numbers of bounces.

[0114] Example 5

[0115] On the basis of Example 3, in step 4.2, if it is judged to be an illuminated face element, then multiple occlusion judgments need to be performed based on the face element normal and the direction of the incident wave. In the case of multiple occlusions, the distance between the ray starting point and the face element is recorded, and the face element closest to the ray source point is the illuminated face 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 scattering 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] In the formula, 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, 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] In the formula, T stands for The length of the projection on the polygon, M represents the number of edges of the face element 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, the scattering ability data obtained in step 4 are sequentially subjected to duplicate removal, outlier elimination, and missing value filling, and each filled scattering ability data is regarded as a vector in a multidimensional space, and the dimension of the vector is composed of 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 build a database. Specifically, the scattering power data 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 from 1 to 20. The total cohesive sum of squares SSE of 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 become flat. 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 Represents the RCS value of the jth 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, the data in each cluster are screened for the correlation between the number of bounces and the RCS value, specifically: query the scattering ability data in all clusters, if there are scattering ability data with the same values ​​of the four parameters of frequency, azimuth, elevation angle, and polarization mode in the same cluster, and it contains data with unlimited number of bounces, take the data with the lowest number of bounces as the correct correlation result under the parameter condition;

[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] According to the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. Specifically, the correlation result with the number of bounces less than 2 indicates that the coupling strength is low and it is a low-order coupling. The correlation result with the number of bounces greater than or equal to 2 or the number of bounces is unlimited indicates that the coupling strength is high and the high-order coupling path cannot be ignored. All the correlation result data are analyzed to obtain the coupling strength evaluation result.

[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. According to the parameters and drawings of the ship model, use the curve drawing tool 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 curve according to the design drawing to make fine adjustments to make the curve more in line with the real shape.

[0149] After the curve is drawn, use the surface modeling tool in the software to sweep the drawn curve to generate the hull surface. During the modeling process, attention should be paid to the continuity and rationality of the curve to avoid distortion, gaps at intersections and other problems.

[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, establishing a composite model of target and background;

[0152] The ship-dynamic sea surface composite model is built using the typical target 3D geometric model in step 1. 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, such as 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 is required to be between one-tenth and one-eighth of a wavelength. However, in the calculation process of complex scenes, the target has an electrically large size characteristic, and using a quarter wavelength as the mesh size can obtain accurate calculation results.

[0164] When segmenting the model, 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 triangular face set is constructed, and arrays of error faces, edges and vertices 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 faces, edges and vertices 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 are far away, have low detail requirements, are too complex but do not affect ray tracing, the number and density of face elements can be appropriately reduced to obtain a more reasonable and easier to calculate mesh model.

[0167] At the same time, a reasonable meshing 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 meshing, reduce the number of mesh 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 face elements, the vertex numbers of the triangular face elements, and the spatial coordinates of the triangular face element vertices. The consistency of the included content is conducive to batch processing and storage during calculation.

[0169] Step 4, using a bouncing ray algorithm to calculate electromagnetic scattering characteristic data of a specified bouncing order of the meshed composite model, and obtaining the scattering ability data of the target to the incident electromagnetic wave;

[0170] In this embodiment, the incident wave attributes are specifically 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 is The incident pitch angle range is θ=0°-90°, with a step of 1.

[0174] The number of bounces can be set as follows: 1, 2, 3, 4, or -1 (indicating unlimited number of bounces).

[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, regard the processed data as a vector in a multidimensional space, the dimension of the vector is composed of various parameters of the scattering data, specifically: frequency, azimuth, elevation, polarization mode, amplitude, phase, RCS data, scattering order, use K-means clustering algorithm to cluster the scattering capability data, build a database, and obtain correlation results.

[0181] Step 6, based on the correlation result 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 mirror scattering of seawater is dominant, and the variation range 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 located 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 range is large with the increase of the pitch angle. However, due to the electrically large size characteristics of the ship, the data with a scattering order greater than or equal to 2 are located 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 evaluating electromagnetic coupling strength between a cooperative target and an environment, characterized in that: The specific steps are as follows: Step 1, establishing a target three-dimensional geometric model; Step 2, establishing a background model of the actual scene, and then constructing a composite model of the actual scene and the target based on the background model and the target three-dimensional geometric model established in step 1; 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 a specified bouncing order of the meshed composite model, and obtaining the scattering ability data of the target to the incident electromagnetic wave; Step 5, correlating the scattering power data obtained in step 4 with the number of bounces; Step 6: Obtain the coupling strength evaluation result according to the correlation structure of step 5.

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

3. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 2, characterized in that: The step 2 is specifically as follows: according to the actual scene, a random dynamic background model is generated by using a Monte Carlo algorithm, and a composite model of the background and the target is obtained 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, characterized in that: 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, construct 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: Set 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 subdivision accuracy is determined according to the calculated frequency band, and a quarter wavelength is selected as the subdivision accuracy. The relationship between wavelength λ and frequency f is: Among them, c is the speed of electromagnetic wave propagation, which is the speed of light in a vacuum; The model data after segmentation includes the number of target 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 6, characterized in that: Step 4 is as follows: 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, single station or dual station; Step 4.2, according to the parameters set in step 4.1, under corresponding conditions, an incident wave is emitted to illuminate the model meshed in step 3, and the occlusion of the surface elements in the meshed composite model is determined, which 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 face element is judged to be illuminated, and is an illuminated face element; when the angle is an acute angle, the face element is judged to be blocked and cannot be illuminated, and is a blocked face 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 number of ray tracing is one, 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, and 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 the Fresnel 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. By analogy, the scattering fields of different scattering orders are calculated according to the scattering order, and then step 4.4 is executed; Step 4.4, solve the total scattered field. The specific expression is: Among them, the i-th order scattered field intensity of the n-th surface element is calculated according to step 4.3 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 nth 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; Step 4.5, use the total scattered field to solve the radar cross section σ, that is, RCS data, which is used to represent the scattering ability of the target to the incident electromagnetic wave. The specific expression is: Where R represents the distance from the scatterer (target) to the receiving point, represents the electric field strength of the incident field; Step 4.6, according to steps 4.4-4.5, by setting different scattering orders, obtain the radar scattering cross section σ under different scattering orders, that is, the radar scattering cross section σ under different numbers of bounces.

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

9. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 8, 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 surface element to the far-field scattering 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: In the formula, 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: Among them, E in represents the electric field strength of the incident wave, Z0 = 377Ω, represents the wave impedance in vacuum; 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: 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, R represents the distance from the source point r′ to the observation point r; The integral term in the scattered field intensity is solved using the Gordon integral, and the formula for the Gordon integral is: In the formula, T stands for The length of the projection on the polygon, M represents the number of edges of the face element 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.

10. The method for evaluating electromagnetic coupling strength between a cooperative target and an environment according to claim 9, characterized in that: The step 5 is specifically as follows: Step 5.1, the scattering ability data obtained in step 4 are sequentially subjected to duplicate removal, outlier elimination, and missing value filling, and each filled scattering ability data is regarded as a vector in a multidimensional space, and the dimension of the vector is composed of various parameters of the scattering data, specifically: frequency, azimuth, elevation, polarization mode, amplitude, phase, RCS data, and scattering order; Step 5.2 uses the K-means clustering algorithm to cluster the scattering power data and build a database. Specifically, the scattering power data 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 from 1 to 20. The total cohesive sum of squares SSE of each K is calculated traversally. The specific calculation formula is: Where n is the total number of RCS data points, that is, the total number of scattering power data, x i Represents the RCS value of the data point, μ k The RCS value representing the centroid of the cluster; 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 become flat. This position is the elbow position, and the number of clusters K corresponding to this position is the determined optimal number of clusters; 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: 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 j represents the RCS value of the jth 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: 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; 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, the data in each cluster are screened for the correlation between the number of bounces and the RCS value, specifically: query the scattering ability data in all clusters, if there are scattering ability data with the same values ​​of the four parameters of frequency, azimuth, elevation angle, and polarization mode in the same cluster, and it contains data with unlimited number of bounces, take the data with the lowest number of bounces as the correct correlation result under the parameter condition; 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; The step 6 is specifically as follows: According to the correlation results obtained in step 5, the difference in electromagnetic coupling strength under different parameter conditions is given. Specifically, the correlation result with the number of bounces less than 2 indicates that the coupling strength is low and it is a low-order coupling. The correlation result with the number of bounces greater than or equal to 2 or the number of bounces is unlimited indicates that the coupling strength is high and the high-order coupling path cannot be ignored. All the correlation result data are analyzed to obtain the coupling strength evaluation result.

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