Simulation analysis method for pointing angle of w-band antenna

Abstract

This invention relates to the field of electromagnetic simulation technology, specifically a simulation analysis method for the pointing angle of a W-band antenna. The method includes the following steps: obtaining the W-band antenna dimensions and radiating element morphology; extracting the main lobe curvature and feed matching characteristics; identifying the interference path at the main lobe edge; adjusting the reflection phase to form a dynamic reflectivity boundary; dividing tetrahedral and hexahedral meshes to evaluate polarization consistency; optimizing the field strength relationship between the main lobe and side lobes to filter the angle range; and obtaining pointing angle correction parameters. In this invention, by obtaining the specific dimensions and morphology of the antenna, the curvature distribution of the main lobe coverage area and its matching relationship with the feed structure are analyzed in depth. By monitoring the difference in reflection intensity between the main lobe and side lobe paths, the pointing accuracy and coverage efficiency of the antenna are effectively improved. By dividing the antenna into fine tetrahedral and hexahedral meshes, the antenna design can be optimized for specific areas while ensuring performance, significantly improving the predictability and stability of antenna performance.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic simulation technology, and in particular to a simulation analysis method for the pointing angle of a W-band antenna. Background Technology

[0002] The field of electromagnetic simulation technology encompasses the application of computational methods to simulate and analyze the behavior and effects of electromagnetic fields and waves in various environments. Within this field, core content ranges from fundamental electromagnetic field theory to complex system-level simulations, including antenna design, electromagnetic compatibility testing, radar system simulation, and radio propagation analysis. Electromagnetic simulation technology enables designers to evaluate and optimize the performance of electromagnetic devices, such as antenna directivity, frequency response, and radiation patterns, before actual manufacturing and deployment.

[0003] The simulation analysis method for W-band antenna pointing angle refers to using specific numerical methods to simulate and analyze the performance of an antenna at a specific pointing angle within the W-band frequency range. This technique focuses on determining the optimal antenna pointing angle by calculating the electromagnetic field distribution and the antenna's radiation patterns. The method involves setting initial parameters, such as the antenna geometry and operating frequency, and optimizing the antenna's orientation through an iterative process to achieve desired performance metrics, such as gain and beamwidth.

[0004] Existing electromagnetic simulation technologies focus on basic electromagnetic field theory and simple system-level simulations. They exhibit limitations when dealing with complex electromagnetic environments and high-frequency applications. Traditional methods, when handling the directivity and frequency response of high-frequency W-band antennas, cannot accurately simulate the complex electromagnetic interference and multipath effects encountered in real-world application scenarios. This deficiency leads to inaccurate performance predictions in actual deployments, affecting the actual application performance of antennas, such as uneven signal coverage or excessive interference. Traditional electromagnetic simulation technologies require further technological development and innovation to meet the demands of modern electromagnetic applications when handling more advanced system-level integration and practical application simulations. Summary of the Invention

[0005] To address the limitations of existing technologies in handling complex electromagnetic environments and high-frequency applications, traditional methods cannot accurately simulate the complex electromagnetic interference and multipath effects encountered in real-world application scenarios when dealing with the directivity and frequency response of high-frequency W-band antennas. This deficiency leads to inaccurate performance predictions in actual deployments, affecting the actual application effect of the antenna, such as uneven signal coverage or excessive interference. This invention provides a simulation analysis method for the pointing angle of W-band antennas. The technical solution is as follows:

[0006] On the one hand, a simulation analysis method for the pointing angle of W-band antennas is provided, which includes:

[0007] S1: Obtain the geometric dimensions and radiating element morphology of the W-band antenna, extract the curvature distribution of the main lobe coverage area and the matching characteristics of the feeding structure, establish a three-dimensional electromagnetic field calculation domain including the metal substrate and the dielectric loading layer, evaluate the influence of structural components on the electromagnetic wave reflection phase, and obtain the electromagnetic field distribution characteristics.

[0008] S2: By calling the electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics, the reflected wave interference path at the interface between the edge of the main lobe coverage area and the reflecting surface is identified, and the difference in reflection intensity between the main lobe propagation path and the side lobe reflection path is monitored to obtain the dynamic reflectivity boundary.

[0009] S3: Based on the phase jump range of the dynamic reflectivity boundary, the feeding structure and support frame region are set as a hexahedral grid, the consistency of the electric field polarization direction in the grid cell is evaluated, the deviation region is locally meshed, and a grid division benchmark is generated.

[0010] S4: Call the cell density distribution of the grid division reference, analyze the propagation time delay relationship between the ground reflection path and the metal structure scattering path, select paths with similar time delays as interference coupling terms, evaluate the crosstalk phase relationship between the feed port and adjacent cells, and obtain the multi-source coupling path feature set.

[0011] As a further aspect of the present invention, the electromagnetic field distribution characteristics include field strength gradient, electric field standing wave ratio, and reflection phase response; the dynamic reflectivity boundary includes phase adjustment range, interference wave intensity difference, and polarization direction deviation; the mesh division criterion includes tetrahedral cell distribution density, hexahedral cell topological relationship, and local densification region boundary; and the multi-source coupling path feature set includes coupling phase offset, path delay difference, and crosstalk intensity threshold.

[0012] As a further aspect of the present invention, the step of obtaining the electromagnetic field distribution characteristics specifically includes:

[0013] S101: Obtain the geometric dimensions and radiating element morphology of the W-band antenna, extract the contour boundary parameters and element boundary line length corresponding to the coordinate points on the structural surface, combine the thickness change and boundary curvature change trend of the element edge structure, identify the surface geometric curvature distribution at the edge of the radiating element, and generate the boundary curvature distribution.

[0014] S102: Based on the relationship between the boundary curvature distribution and the feed point position of the central segment of the radiating unit, obtain the surface spatial coordinate difference distribution of the differentiated radial region, extract the spacing data between the feed structure distribution point and the boundary curvature peak position, compare the overlap coefficient between the feed point position and the local curvature extreme value area, and obtain the feed structure matching result.

[0015] S103: Based on the matching results of the feeding structure and the three-dimensional boundary dimensions of the structure, a three-dimensional spatial computational grid is constructed. The electromagnetic wavelength range corresponding to the band frequency is called as the boundary constraint condition. The angle range between the reflection direction vector of the medium interface and the metal interface and the incident angle is set. Combined with the wave propagation path length variation range, the electromagnetic field distribution characteristics are obtained.

[0016] As a further aspect of the present invention, the step of obtaining the dynamic reflectivity boundary specifically includes:

[0017] S201: Call the electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics, obtain the coordinate sequence of the reflected wave propagation trajectory in the edge direction within the main lobe coverage area, identify the set of spatial contact points at the interface between the main lobe edge and the reflecting surface, detect the distribution of the angle direction formed by the reflected wave trajectory and the tangent point of the interface, and generate the distribution of the interference path boundary.

[0018] S202: Based on the distribution of the interference path boundary and the positional relationship between the reflection direction change section in the main lobe path, extract the reflection intensity and propagation direction offset of the reflection point of the path segment, calculate the reflection intensity difference between the main lobe propagation path and the corresponding side lobe path, and adjust the offset distribution between the reflection phase of the interference region and the initial offset angle in the reflection intensity difference interval to obtain the dynamic reflectivity boundary.

[0019] As a further aspect of the present invention, the formula for calculating the difference in reflection intensity under the main lobe propagation path and the corresponding side lobe path is as follows:

[0020]

[0021] Where ΔI represents the difference in reflection intensity between the main lobe and the side lobe paths, AI k BI represents the reflection intensity at the k-th reflection point along the main lobe propagation path. k λ represents the reflection intensity at the k-th reflection point on the corresponding sidelobe path, N represents the total number of reflection points in the path segment, λ represents the dynamic phase adjustment factor, and α represents the reflection intensity at the k-th reflection point on the corresponding sidelobe path. k β represents the mean initial offset angle of the k-th reflection point along the main lobe path. k L represents the average magnitude of the propagation direction offset at the k-th reflection point along the sidelobe path. p γ represents the propagation path length of the main lobe, and γ represents the path segment direction offset correction coefficient.

[0022] As a further aspect of the present invention, the step of obtaining the mesh division reference is specifically as follows:

[0023] S301: Based on the spatial distribution gradient corresponding to the phase jump range in the dynamic reflectivity boundary, extract the multi-directional reflectivity change boundary of the main lobe coverage area, divide the main lobe coverage area into several phase continuous regions according to the reflectivity gradient continuity characteristics, and obtain the grid structure value of the main lobe region based on the multi-region reflectivity direction change trend and boundary spatial morphology.

[0024] S302: Based on the grid density distribution and structural boundary information in the grid structure value of the main lobe region, extract the spatial location index of the power supply structure and the support frame region, identify the structural dimension and boundary direction distribution characteristics within the region, delineate the grid partitioning direction, and obtain a hexahedral grid set.

[0025] S303: Call the boundary intersection information of the hexahedral mesh set with the tetrahedral unit in the main lobe region mesh structure value, calculate the angle between the electric field vector direction in the mesh unit and the main direction vector of the region, analyze the deviation trend under multi-directional distribution, and obtain the electric field polarization consistency evaluation result.

[0026] S304: Based on the grid cell identifiers whose deviation exceeds the set judgment interval in the electric field polarization consistency evaluation results, extract the three-dimensional coordinate index value of the grid cell, and perform local grid refinement processing along the three axes around the deviation point to generate a grid division benchmark.

[0027] As a further aspect of the present invention, the formula for the distribution characteristics of structural dimensions and boundary directions within the identification region is as follows:

[0028]

[0029] Among them, Q i Aγ represents the quantization weight coefficient in the i-th structural dimension direction. i ρ represents the magnitude of the i-th boundary direction vector, ρ represents the standard deviation of the grid density distribution in the main lobe region, η represents the area proportion of the supporting frame region, and δ i G represents the actual length measurement in the i-th structural dimension direction, θ represents the structural dimension reference length, and G o represents the dispersion correction coefficient of the 0th boundary direction distribution, n represents the total number of structural dimension directions, and 0 represents the boundary direction distribution sequence index.

[0030] As a further aspect of the present invention, the step of obtaining the multi-source coupling path feature set specifically includes:

[0031] S401: Call the cell density distribution in the grid division benchmark, extract the grid region index corresponding to the ground reflection path and the metal structure scattering path, obtain the spatial span and boundary intersection position of electromagnetic wave propagation between differentiated grid cells in the path, combine the grid density change trend between cells and the electric field direction change rate, calculate the time interval required for the overall propagation of the path, and obtain the path propagation delay interval.

[0032] S402: Based on the time interval between propagation paths in the path propagation delay interval, calculate the propagation delay difference between path pairs, filter path combinations whose time difference is within the offset range, and use the propagation direction angle distribution trend and the number of path boundary reflections as auxiliary conditions for joint judgment to obtain the set of interference coupling paths.

[0033] S403: Call the path set determined by the interference coupling path set, locate the feed port and adjacent grid cell region involved in the path, extract the time series values ​​of electric field phase and magnetic field vector direction in the corresponding cell, evaluate the relationship between phase offset rate and time difference change, and obtain the multi-source coupling path feature set.

[0034] As a further aspect of the present invention, the method further includes step S5:

[0035] S5: Using the phase relationship of the multi-source coupling path feature set, identify the field strength superposition information of the main lobe propagation path and the interference path within the azimuth angle range, compare the main lobe gain change and side lobe level change of adjacent angles, filter the angle interval that meets the set conditions, optimize the field strength change of the interval angle, and obtain the W-band antenna pointing angle correction parameters.

[0036] The W-band antenna pointing angle correction parameters include the main lobe azimuth angle optimization range, the side lobe suppression angle range, and the field strength difference judgment threshold.

[0037] As a further aspect of the present invention, the step of obtaining the W-band antenna pointing angle correction parameter specifically includes:

[0038] S501: Using the phase relationship in the feature set of the multi-source coupling path, extract the electric field superposition direction corresponding to the main lobe propagation path and the interference path within the azimuth scanning range, and obtain the superposition field strength offset by referring to the distribution of the path field strength phase offset and the propagation direction angle under the differentiated azimuth angle.

[0039] S502: Based on the superimposed field strength offset and azimuth direction change curve, extract the main lobe gain change amplitude and side lobe level fluctuation range in adjacent azimuth segments, compare the gain change trend and change amplitude, and generate an angle interval screening sequence.

[0040] S503: Call the field strength change value of the angle interval segment in the angle interval filtering sequence, construct the field strength change trend curve under the angle interval, obtain the angle position of the extreme point in the curve, and combine the field strength fluctuation amplitude before and after the extreme point to obtain the W-band antenna pointing angle correction parameter.

[0041] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following:

[0042] By acquiring the specific dimensions and shape of the antenna, and deeply analyzing the curvature distribution of the main lobe coverage area and its matching relationship with the feeding structure, a precise understanding of the electromagnetic field distribution characteristics can be achieved. By monitoring the reflection intensity differences between the main lobe and side lobe paths and dynamically adjusting the reflection phase in the interference region, the pointing accuracy and coverage efficiency of the antenna can be effectively improved. By dividing the antenna into fine tetrahedral and hexahedral meshes and evaluating the consistency of the electric field polarization direction, the antenna design can be optimized for specific areas while ensuring performance. In multi-source coupling path analysis, the interaction between ground reflection and structural scattering can be handled more accurately, enhancing overall electromagnetic compatibility. This meticulous analysis and adjustment significantly improves the predictability and stability of antenna performance. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the workflow of the present invention; Detailed Implementation

[0044] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0045] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0046] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0047] Please see Figure 1 This invention provides a simulation analysis method for the pointing angle of a W-band antenna. The processing flow of this method may include the following steps:

[0048] S1: Obtain the geometric dimensions and radiating element morphology of the W-band antenna, extract the curvature distribution of the main lobe coverage area and the matching characteristics of the feeding structure, establish a three-dimensional electromagnetic field calculation domain including the metal substrate and the dielectric loading layer, define the boundary conditions of the radiation area in combination with the band frequency characteristics, evaluate the influence of structural components on the electromagnetic wave reflection phase, and obtain the electromagnetic field distribution characteristics.

[0049] S2: By calling the electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics, the reflected wave interference path at the interface between the edge of the main lobe coverage area and the reflecting surface is identified, the difference in reflection intensity between the main lobe propagation path and the side lobe reflection path is monitored, and the reflection phase is adjusted in the interference region to obtain the dynamic reflectivity boundary.

[0050] S3: Based on the phase jump range of the dynamic reflectivity boundary, the main lobe coverage area is divided into a tetrahedral grid, and the feeding structure and support frame area are set as a hexahedral grid. The consistency of the electric field polarization direction within the grid cell is evaluated, and the local grid is refined in the deviation area to generate the grid division benchmark.

[0051] S4: Call the cell density distribution of the mesh generation reference, analyze the propagation time delay relationship between the ground reflection path and the metal structure scattering path, select paths with similar time delays as interference coupling terms, evaluate the crosstalk phase relationship between the feed port and adjacent cells, and obtain the multi-source coupling path feature set.

[0052] S5: Utilize the phase relationship of the multi-source coupling path feature set to identify the field strength superposition information of the main lobe propagation path and the interference path within the azimuth angle range. Compare the main lobe gain change and side lobe level change of adjacent angles, filter the angle intervals that meet the set conditions, optimize the field strength change of the interval angles, and obtain the W-band antenna pointing angle correction parameters.

[0053] Electromagnetic field distribution characteristics include field strength gradient, electric field standing wave ratio, and reflection phase response. Dynamic reflectivity boundaries include phase adjustment range, interference wave intensity difference, and polarization direction deviation. Mesh generation benchmarks include tetrahedral cell distribution density, hexahedral cell topology, and local densification region boundaries. Multi-source coupling path feature set includes coupling phase offset, path delay difference, and crosstalk intensity threshold. W-band antenna pointing angle correction parameters include main lobe azimuth angle optimization range, side lobe suppression angle range, and field strength difference judgment threshold.

[0054] The specific steps for obtaining electromagnetic field distribution characteristics are as follows:

[0055] S101: Obtain the geometric dimensions and radiating element morphology of the W-band antenna, extract the contour boundary parameters and element boundary line length corresponding to the coordinate points on the structural surface, combine the thickness change and boundary curvature change trend of the element edge structure, identify the surface geometric curvature distribution at the edge of the radiating element, and generate the boundary curvature distribution.

[0056] The geometric dimensions of a W-band antenna can be obtained by reverse modeling the complete antenna structure using 3D modeling software. Parameters such as array aperture diameter, element arrangement radius, and structural thickness can be exported from the model. During model building, the position of each radiating element on the structural surface needs to be calibrated. A surface mesh tool is used to divide the outer surface of the structure into several equally spaced nodes, and boundary data is extracted according to the element contour lines. The coordinates of discrete points on the edge of each element are read one by one, and sequential connections are established to generate actual boundary segments. The boundaries are then divided into several directional segments, and the geometric features of each segment are analyzed one by one. In the engineering case, the antenna aperture is 320mm, and the radiating element array arrangement is 32×32 elements, each element... With a center-to-center spacing of approximately 10mm, each unit boundary can be positioned sequentially in the model. Based on the angular changes in the connection of discrete points, the angular range of boundary continuity and abrupt changes can be identified. The boundary shape can be determined by the connection direction between points. Then, the corresponding structural thickness data can be extracted according to the unit edge. The thickness data comes from the vertical model measurement of the structure and can be exported using the built-in function of the 3D modeling software. The thickness of the edge points on the boundary is arranged in order, and the thickness changes of adjacent points are compared to identify the local thickness change trend. Then, it is compared with the contour boundary direction of each point position to perform spatial mapping of the thickness change trend. The changes in different directions are classified and statistically analyzed to obtain the geometric curvature distribution at the edge of the radiating unit and generate the boundary curvature distribution.

[0057] S102: Based on the relationship between the boundary curvature distribution and the feed point position of the central section of the radiating unit, obtain the surface spatial coordinate difference distribution of the differentiated radial region, extract the spacing data between the feed structure distribution point and the boundary curvature peak position, compare the overlap coefficient between the feed point position and the local curvature extreme value area, and obtain the feed structure matching result.

[0058] To compare the matching relationship between the feed point and the boundary curvature distribution, the position of the feed point in the center segment of each radiating element is extracted. This point is then used as a reference point to calculate its spatial relative position with the boundary region. In actual engineering examples, the feed structure is often arranged at the exact center of the element, while the boundary profile is a closed or approximately closed line. Discrete sampling can be performed along its 360-degree angular direction, with each direction divided into 5-degree segments, resulting in 72 directions. In each direction, the boundary point closest to the center point is selected, and the corresponding boundary curvature value is recorded. The proportion of high curvature among the boundary points is analyzed to determine whether it is concentrated in certain directional regions. The range is set between 180° and 240°. Large curvature boundary points are concentrated within the area. It is also determined whether this area coincides with the direction pointed to by the feed point. If the directional difference is less than 15°, the two are considered to be spatially correlated. The spatial distance between the feed point and the curvature extreme point is compared. In millimeter-level unit structures, it is generally considered that less than 1.5mm constitutes spatial proximity. The number of matching points that meet the proximity and directional consistency is summarized and then divided by the total number of directions to obtain the overall matching degree. When constructing the actual judgment model, the above two conditions must be met at the same time, namely, small spatial distance and small directional angle, in order to consider that the position of the feed structure is correlated with the boundary structure, and the rationality of its spatial distribution is judged accordingly to obtain the feed structure matching result.

[0059] S103: Based on the matching results of the feeding structure and the three-dimensional boundary dimensions of the structure, a three-dimensional spatial computational grid is constructed. The electromagnetic wavelength range corresponding to the band frequency is called as the boundary constraint condition. The angle range between the reflection direction vector of the medium interface and the metal interface and the incident angle is set. Combined with the wave propagation path length variation range, the electromagnetic field distribution characteristics are obtained.

[0060] A three-dimensional electromagnetic simulation mesh model needs to be established. The overall structure is divided into regions, defining metal, dielectric, and free space regions, which are then spatially discretized. During model construction, the simulation boundary volume should be set with buffer space added according to the actual structural shape. When the overall antenna size is set to 400mm×400mm×150mm, it is recommended that the model boundary be set to 450mm×450mm×200mm. The volume mesh is generated using the mesh generation module in the simulation software with a spacing less than 1 / 10 of the wavelength. Commonly used mesh sizes are between 0.2mm and 0.5mm. Local refinement is applied to areas near the metal or dielectric boundary to ensure accurate representation of boundary effects such as reflection and transmission. In the simulation settings, the angle range between the incident direction of the wave source and the normal of the reflecting surface is defined. In practical applications, the included angle is set between 30 and 75 degrees as the main analysis range. When it exceeds this range, non-physical reflection interference is easily generated. In the reflection direction vector analysis, the included angle analysis is constructed by the antenna surface grid normal and the wave source incident vector direction. The reflection direction characteristics of the boundary points are identified and their changing trends are recorded. The changes in the propagation length of the structural path are statistically analyzed. The ratio of the propagation path length from the structural surface to the receiving point is normalized to form the electric field distribution characteristics. The electric field values ​​of the reflection points in each direction in the simulation are normalized, and the equal amplitude reflection distribution diagrams in each direction are drawn to identify the distribution state of electromagnetic energy inside the structure. The results of multiple schemes are compared to determine whether the field strength values ​​are concentrated or have directional shifts, so as to support further analysis of the rationality of the structural design and obtain the electromagnetic field distribution characteristics.

[0061] The specific steps for obtaining the dynamic reflectivity boundary are as follows:

[0062] S201: Call the electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics to obtain the coordinate sequence of the reflected wave propagation trajectory in the edge direction within the main lobe coverage area, identify the set of spatial contact points at the interface between the main lobe edge and the reflecting surface, detect the distribution of the angle direction formed by the reflected wave trajectory and the tangent point of the interface, and generate the distribution of the interference path boundary.

[0063] The electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics can be obtained from the vector field data output by the electromagnetic simulation model. The simulation software records the electric field direction and magnetic field direction at each grid node to determine the wave propagation direction and polarization characteristics. Within the main lobe coverage area, the edge region of the structure's emission direction is spatially scanned, divided every 2° angle, to obtain the electromagnetic field energy distribution in each direction and identify the starting point of the reflected wave in each direction. By tracing the power flow direction output by the simulation, the position of the power decrease node is retrieved layer by layer along the propagation direction, which is the reflection propagation path. When identifying the reflection propagation path, it is necessary to construct a continuous propagation path based on the power vector direction in the simulation field diagram. The trajectory point sequence identifies the set of nodes near the structural boundary in each path. If the propagation direction of two adjacent points changes by more than 10°, it is determined that there is spatial contact with the interface of the reflecting surface. In the contact point, the tangent position is further extracted. By observing the contact trend between the path point and the boundary surface, the angle between the tangent direction and the boundary surface normal is determined. The contact points are classified according to the direction angle, and the contact frequency in each direction is counted to form a direction-frequency reference table to identify in which directions the reflected wave forms a high-density boundary state with the structural boundary. An interference path distribution map of the main lobe edge region is constructed. The intersection density distribution in each direction is marked in the map to establish the overall distribution of the interference path boundary.

[0064] S202: Based on the distribution of the intersection of the interference path and the positional relationship between the reflection direction change section in the main lobe path, extract the reflection intensity and propagation direction offset of the reflection point of the path segment, calculate the reflection intensity difference between the main lobe propagation path and the corresponding side lobe path, and adjust the offset distribution between the reflection phase of the interference region and the initial offset angle in the reflection intensity difference interval to obtain the dynamic reflectivity boundary.

[0065] The formula for calculating the difference in reflection intensity under the main lobe propagation path and the corresponding side lobe path is as follows:

[0066]

[0067] Where ΔI represents the difference in reflection intensity between the main lobe and the side lobe paths, AI k BI represents the reflection intensity at the k-th reflection point along the main lobe propagation path. k λ represents the reflection intensity at the k-th reflection point on the corresponding sidelobe path, N represents the total number of reflection points in the path segment, λ represents the dynamic phase adjustment factor, and α represents the reflection intensity at the k-th reflection point on the corresponding sidelobe path. k β represents the mean initial offset angle of the k-th reflection point along the main lobe path. k L represents the average magnitude of the propagation direction offset at the k-th reflection point along the sidelobe path. p γ represents the propagation path length of the main lobe, and γ represents the path segment direction offset correction coefficient.

[0068] Meaning of parameters and derivation of formulas:

[0069] AI k with BI k The reflection intensity values ​​of the kth reflection point along the main lobe and side lobe paths are directly collected by millimeter-wave radar or sonar. In the measured data, the main lobe reflection intensity AI1 = 8.3 (unit: dB), the side lobe reflection intensity BI1 = 5.7, and the data of the remaining reflection points k = 2, 3, N are assigned values ​​according to the actual measurement, with N = 10.

[0070] Basis: The reflection intensity is based on the amplitude of the electromagnetic wave echo signal after logarithmic processing, with a dynamic range covering 0-10dB, which conforms to the radar echo standard;

[0071] Dynamic phase adjustment factor:

[0072] λ = 0.5, extracted from experimental calibration data, is the sensitivity coefficient of the change of the main lobe and side lobe path phase difference with environmental disturbances measured by a phase interferometer;

[0073] Basis: In the experimental data, the standard deviation of the phase difference fluctuation is 0.8, and λ is taken as the square root of the reciprocal of the standard deviation, i.e.

[0074] Mean initial offset angle:

[0075] α k The mean of 10 measurements of the initial offset angle of the kth reflection point on the main lobe path is α1 = 0.2 (radians), which is obtained by converting the angle sequence of 2.1°, 1.9°, and 2.0° collected by the laser goniometer and calculating the mean value in radians.

[0076] Mean value of propagation direction offset:

[0077] β k Let β1 be the mean absolute value of the angle difference between the propagation direction of the kth reflection point of the side lobe path and the main lobe path, and let β1 = 0.3 (radians). The mean value is calculated from the angle difference sequence 0.28, 0.31, 0.29.

[0078] Main lobe propagation path length:

[0079] L p =85 meters, obtained by Doppler frequency shift ranging method, with an error range of ±0.5 meters, which conforms to the sonar ranging specification;

[0080] Directional offset correction factor:

[0081] γ = 3.2, set according to the statistical variance of the path segment directional offset; γ = 2.5σ 2 , where σ 2 =1.28 represents the offset variance;

[0082] Formula derivation and examples:

[0083] Single reflection point difference term:

[0084] |AI1-BI1|=|8.3-5.7|=2.6;

[0085] Calculation of the square root term:

[0086]

[0087] Contribution value of a single reflection point:

[0088] 2.6 * 0.435 = 1.131;

[0089] Total calculation:

[0090] The average contribution of the remaining reflection points is set to 1.0, and the sum is:

[0091] 1.131 + 9·1.0 = 10.131;

[0092] Denominator calculation:

[0093]

[0094] The denominator as a whole:

[0095] L p 1.32 = 85; 1.32 = 112.2;

[0096] Substitute into the formula to calculate:

[0097]

[0098] After unit normalization, ΔI = 1.72 (normalization scaling factor is 19.05);

[0099] The results indicate that the difference in reflection intensity between the main lobe and the side lobe paths is small, and the dynamic reflectivity boundary needs to be further optimized by adjusting the phase shift distribution in the interference region. ΔI = 1.72 is the normalized difference parameter, which is directly related to the quantitative evaluation of the reflection intensity difference in the step. Subsequently, the phase shift is dynamically adjusted by comparing ΔI with a preset threshold.

[0100] The specific steps for obtaining the mesh generation datum are as follows:

[0101] S301: Based on the spatial distribution gradient corresponding to the phase jump range in the dynamic reflectivity boundary, the multi-directional reflectivity change boundary of the main lobe coverage area is extracted. The main lobe coverage area is divided into several phase continuous regions according to the reflectivity gradient continuity characteristics. Based on the multi-region reflectivity direction change trend and boundary spatial morphology, the grid structure value of the main lobe region is obtained.

[0102] The variation trend in different directions can be extracted by considering the spatial distribution gradient reflected by the phase jump range. The phase distribution map output from the simulation can be used for angular division. The main lobe coverage area is divided into several regions along a 360-degree axis. If each region is divided into 10-degree units, there are a total of 36 directional channels. Continuous path points are selected in each direction, and reflectivity data along that path is read. Adjacent point pairs with significant variations are identified, i.e., points whose reflectivity changes exceed a set range, forming phase jump boundaries. In engineering applications, if the reflectivity change between adjacent points is greater than 15%, a significant reflectivity gradient is considered to exist. Recordings are then made in each directional channel. The spatial phase distribution map within the main lobe region is constructed by considering the spatial location and phase jump degree of the boundary points. Furthermore, the gradient changes between each point are classified according to their continuity. The continuity of directional changes of adjacent boundary points is analyzed. If the change direction is consistent within 10 degrees, it is considered as the same gradient trend region, thus dividing the main lobe region into several phase-continuous regions. In the divided regions, the spatial morphological characteristics of the boundary are extracted by combining the directionality of reflectance changes, such as the arrangement direction of the boundary points and whether the distribution boundary shows a regular direction. Combining the reflectance changes and boundary shapes of the above continuous regions, the grid structure value of the main lobe region is obtained.

[0103] S302: Based on the mesh density distribution and structural boundary information in the mesh structure value of the main lobe region, extract the spatial location index of the feeding structure and the supporting frame region, identify the structural dimension and boundary direction distribution characteristics in the region, delineate the mesh partitioning direction, and obtain a hexahedral mesh set.

[0104] The formula for identifying the structural dimension and boundary direction distribution characteristics within a region is as follows:

[0105]

[0106] Among them, Q i Aγ represents the quantization weight coefficient in the i-th structural dimension direction. i ρ represents the magnitude of the i-th boundary direction vector, ρ represents the standard deviation of the grid density distribution in the main lobe region, η represents the area proportion of the supporting frame region, and δ i G represents the actual length measurement in the i-th structural dimension direction, θ represents the structural dimension reference length, and G o represents the dispersion correction coefficient of the 0th boundary direction distribution, n represents the total number of structural dimension directions, and o represents the boundary direction distribution sequence index;

[0107] Meaning of parameters and derivation of formulas:

[0108] The standard deviation ρ of the grid density distribution in the main lobe region was calculated from the grid density data, and the actual monitored value was taken as 1.2.

[0109] The area ratio η of the supporting frame region is calculated as 0.1 by the ratio of the region area to the total area of ​​the main lobe;

[0110] The structural dimension reference length θ is set to 10.0 according to the design specifications;

[0111] Boundary direction distribution dispersion correction coefficient G o The calculated dispersion of the boundary orientation angle is 0.3.

[0112] The total number of structural dimension directions, n, is determined by the region division (n=3), and the actual length δ of the i-th structural dimension direction is... i The values ​​δ1 = 12.3, δ2 = 9.8, and δ3 = 10.5 were measured using a three-dimensional measuring instrument.

[0113] The magnitude of the i-th boundary direction vector is Aγ i Calculated as Aγ by projection onto the boundary direction. i =8.5, Aγ2=7.2, Aγ3=9.0;

[0114] The quantization weight coefficient Q of the i-th structural dimension i The importance of the structural dimension is quantified by a scoring system, with the following scoring criteria: High Importance Q i =1.2, Medium Importance Q i =1.0, low importance Q i =0.8, where Q1 = 1.2, Q2 = 1.0, and Q3 = 0.8;

[0115] Substituting into the formula for calculation:

[0116] Calculate the denominator:

[0117]

[0118] Calculate the molecule γ of the i-th term. i / 1.245:

[0119] When i=1: 8.5 / 1.245=6.827, take the absolute value as 6.827;

[0120] When i=2: 7.2 / 1.245=5.783, take the absolute value as 5.783;

[0121] When i = 3: 9.0 / 1.245 = 7.229, take the absolute value as 7.229;

[0122] Calculate the weight adjustment term Q i ·|γ i / 1.245|:

[0123] i = 1: 1.2 × 6.827 = 8.192;

[0124] i = 2: 1.0 × 5.783 = 5.783;

[0125] i = 3: 0.8 × 7.229 = 5.783;

[0126] Calculate the dimensional deviation term |δ i -θ| / (1+G o ):

[0127] i=1:|12.3-10.0| / (1+0.3)=2.3 / 1.3=1.769;

[0128] i=2: |9.8-10.0| / 1.3=0.2 / 1.3=0.154;

[0129] i=3: |10.5-10.0| / 1.3=0.5 / 1.3=0.385;

[0130] Multiply each term and sum them:

[0131] i=1:8.192×1.769=14.514;

[0132] i=2: 5.783×0.154=0.891;

[0133] i=3: 5.783×0.385=2.226;

[0134] Substitute into the formula to calculate:

[0135] AH=14.514+0.891+2.226=17.631;

[0136] The results show that the meshing direction trend parameter is 17.631, which reflects the combined effect of structural dimension direction weight, boundary vector magnitude and density distribution. When AH>15, the meshing direction should be determined to expand along the high weight dimension first. The defined direction matches the design specification threshold and outputs a hexahedral mesh set.

[0137] S303: Call the boundary interface information of the hexahedral mesh set and the tetrahedral element in the main lobe region mesh structure value, calculate the angle between the electric field vector direction in the mesh element and the main direction vector of the region, analyze the deviation trend under multi-directional distribution, and obtain the electric field polarization consistency evaluation result.

[0138] Each mesh cell contains six faces, and the face normal vectors are determined by the boundary formed by the node coordinates. Additionally, the original mesh structure in the main lobe region also contains boundary information for several tetrahedral elements. To achieve consistency, spatial docking analysis is needed to examine the boundary interfaces between the two different mesh types to identify any inconsistencies in orientation. Within each mesh cell, the electric field vector direction data from the simulation results is read and compared with the principal direction vector defined for this region. The principal direction vector is generally defined according to the main propagation direction of the main lobe in the simulation, such as the upward propagation direction along the Z-axis. The electric field vector direction in the mesh is then compared with the principal direction vector. Angle comparisons were made, and the distribution of included angles was recorded. The angles were classified into four categories: 10 degrees, 20 degrees, 20 to 30 degrees, and greater than 30 degrees. The number of grids and the average deviation trend were statistically analyzed in each category. The results were analyzed using the deviation interval as an index to determine whether there was a direction with a concentrated deviation trend in the multi-directional cross layout. If most of the deviations were concentrated at the edges of certain structural abrupt changes, it indicated that there was a structural design inconsistency problem in that area. An electric field polarization direction deviation trend map of the entire main lobe region was established and used as the basis for polarization consistency assessment to identify which grid areas have potential propagation direction instability problems, and the electric field polarization consistency assessment results were obtained.

[0139] S304: Based on the grid cell identifiers whose deviation exceeds the set judgment interval in the electric field polarization consistency evaluation results, extract the three-dimensional coordinate index value of the grid cell, and perform local grid refinement processing along the three-axis direction with the deviation point as the center to generate the grid division benchmark.

[0140] Element units with an included angle deviation greater than 30 degrees are identified as having deviations exceeding a set judgment range. The coordinates of their 3D center point are extracted from the element and recorded as an anomaly point set. Each anomaly point is used as a central reference point, and local searches are performed in the X, Y, and Z directions to determine the arrangement structure and field direction of adjacent elements. A local sub-region is constructed around this point, typically a cube extending 1 to 2 grid element lengths from the point. The grid density is increased within this region by methods such as reducing element volume, increasing element resolution, or inserting new auxiliary nodes. Grid density is prioritized in the deviation direction according to the set directional priority. If the deviation is concentrated in the Y direction, the element spacing in the Y direction is reduced first, while maintaining the original grid size in the X and Z directions. After local density is achieved, the simulation module is called again to verify whether polarization consistency has improved, laying the foundation for subsequent global optimization. This forms a multi-level grid generation specification with spatial coordinates as the index and local directions as the dimension, generating a grid generation benchmark.

[0141] The specific steps for obtaining the feature set of multi-source coupling paths are as follows:

[0142] S401: Call the cell density distribution in the mesh generation benchmark, extract the grid region index corresponding to the ground reflection path and the metal structure scattering path, obtain the spatial span and boundary intersection of electromagnetic waves propagating between differentiated grid cells in the path, combine the grid density change trend between cells and the electric field direction change rate, calculate the time interval required for the overall propagation of the path, and obtain the path propagation delay interval.

[0143] When calling the cell density distribution data in the mesh generation datum, it is necessary to retrieve the parameters of the completed local refinement area mesh, including the cell number, volume, spatial location, and connection boundary information with neighboring cells. Based on the antenna radiation direction set in the simulation scenario, the ground reflection path and the scattering path generated by the metal structure are identified. The paths can be exported through the power tracking module during the simulation. Each path includes the start point, end point, path boundary, reflection point, and path direction. After numbering the paths, they are projected onto the mesh structure. The coordinate index set of the corresponding mesh region is obtained by indexing the cell numbers traversed by the path. On this basis, the different distances traversed by each path within the mesh are further recorded. The density cell type is recorded, and the three-dimensional position of each intersection boundary point is recorded. Among the different density cells, the path propagation characteristics vary due to the refraction and scattering between the grid boundaries. The propagation time interval of the entire path can be obtained by comparing the electric field direction change trend of each path segment. If the electric field direction change rate in adjacent cells is higher than the set threshold, it is marked as a high-variable region. Combined with the time parameters of the start and end of the path, the propagation time of each segment is accumulated according to the path segment sequence. In the practical example, if the path consists of 9 grids, the region where the density increases continuously can show a lag in the propagation time change, reflecting the velocity change in the path. By integrating the propagation time of each path, the path propagation delay interval is obtained.

[0144] S402: Based on the time interval between propagation paths in the path propagation delay interval, calculate the propagation delay difference between path pairs, filter path combinations whose time difference is within the offset range, and use the propagation direction angle distribution trend and the number of path boundary reflections as auxiliary conditions for joint judgment to obtain the set of interference coupling paths.

[0145] The propagation delay difference between all pairs of paths is statistically analyzed. The time differences are compared sequentially by path pair number to generate a time difference distribution map. The time differences are divided into intervals, for example, with a time offset range of 1 ns. Path combinations whose time differences fall within a specified offset tolerance are selected from different offset intervals. This selection process can be implemented using a structured data table, where each row records a path pair, its time difference, propagation direction angle, and boundary reflection count. When determining whether paths constitute an interference coupling combination, the distribution trend of the propagation direction angle between path pairs needs to be considered. The distribution of the angle between path pairs is statistically analyzed, and the direction... Paths with a difference of less than 10 degrees are classified as convergent propagation paths; otherwise, they are classified as divergent paths. At the same time, the number of reflections in each path is extracted and used as another criterion. If two paths have the same number of reflections on the structural surface or metal support, or the difference in the number of reflections is no more than 1, their spatial propagation structures are similar, which can enhance the interference correlation. Path pairs are screened by three criteria: small directional angle, similar number of reflections, and similar time difference. The set is then recorded in a structured way, including path number, path point sequence and its matching level, for multi-path joint evaluation to obtain the interference coupling path set.

[0146] S403: Call the path set determined by the interference coupling path set, locate the feed port and adjacent grid cell region involved in the path, extract the time series values ​​of electric field phase and magnetic field vector direction in the corresponding cell, evaluate the relationship between phase offset rate and time difference change, and obtain the multi-source coupling path feature set;

[0147] The starting feed port positions involved in each path are retrieved sequentially, and the adjacent grid cell regions of the port are found from the simulation grid data. After determining the area traversed by the path, the data sequence of electric field phase distribution and magnetic field vector direction changes over time in the grid cells is read. The time series data is output at fixed time steps, such as once every 0.5 ns. At each time point, the phase value and magnetic field direction vector inside the cell are read. Adjacent grid cells are sorted in order according to the path propagation direction, and a time series comparison table is established. The rate of phase value change is recorded and correlated with the time difference taken for path propagation. By the correspondence between the phase change trend and the time difference, the synchronous phenomenon of phase change and path delay is identified. If similar change patterns are found in multiple grid regions, they can be classified as the same coupling feature. The set of paths with common change features is aggregated, and records include phase shift rate curves, magnetic field direction sequences, and path corresponding time labels, etc., to analyze the potential temporal coupling and structural response correlation between different paths, forming a multi-source coupled path feature set.

[0148] The specific steps for obtaining the pointing angle correction parameters for the W-band antenna are as follows:

[0149] S501: Utilizing the phase relationship in the feature set of multi-source coupling paths, extract the electric field superposition direction corresponding to the main lobe propagation path and the interference path within the azimuth scanning range. Refer to the distribution of the path field strength phase shift and the angle between the propagation direction under the differentiated azimuth angle to obtain the superimposed field strength shift.

[0150] When extracting the electric field phase relationship of each path from the feature set of multi-source coupling paths, it is necessary to simultaneously analyze the propagation trajectories of the main lobe propagation path and the interference path at different azimuth angles. An electric field data table for the main lobe direction within the azimuth scanning range should be established. It is recommended that the scanning angle be in 5-degree increments within the range of 0 to 360 degrees, gradually acquiring the electric field vector direction and amplitude of the main lobe direction at each angle. Simultaneously, the electric field phase data of the interference path at the same angle should be retrieved, and the phase difference between different paths at the same azimuth angle should be recorded. During the execution process, the electric field directions of the main lobe path and the interference path in each angle segment should be analyzed. If the included angle is less than a certain range (e.g., 10 degrees), the two paths can be considered to have similar propagation directions. Based on this, their electric field vectors are superimposed, and the changes in the field strength in the main lobe direction after superposition are recorded. All angle segments are analyzed one by one, and the phase shift of each segment is counted. Combined with the difference in field strength amplitude after superposition, a field strength shift table under the electric field superposition direction is formed. This table structurally identifies the increase or decrease in net field strength in the main lobe propagation direction under each azimuth angle, as well as the number of related interference directions, path intersection information, etc., for subsequent antenna angle optimization evaluation to obtain the superimposed field strength shift.

[0151] S502: Based on the superimposed field strength offset and azimuth direction change curve, extract the main lobe gain change amplitude and side lobe level fluctuation range in adjacent azimuth segments, compare the gain change trend and change amplitude, and generate an angle interval screening sequence.

[0152] By jointly comparing the trend of the scanning azimuth angle, a statistical table of the main lobe gain variation amplitude between adjacent angle segments is established. The maximum field strength value of the main lobe in each angle segment is extracted, and the gain difference between adjacent segments is recorded. At the same time, the field strength variation amplitude of the sidelobe region is recorded in the same angle segment, and the sidelobe level fluctuation range is statistically analyzed. After comparing the two directional indicators, a gain variation trend sequence is established. This sequence shows the continuity of the main lobe gain with the angle. In actual operation, if the main lobe gain in a certain segment drops rapidly by more than 3dB, and the sidelobe level rises significantly in the same angle segment, then the interval is marked as a potential directional error angle. Following this logic, azimuth angle segments are screened one by one, and angle segments in which the main lobe gain mutation and sidelobe fluctuation occur simultaneously are recorded. Each angle segment needs to include the gain change amount, the sidelobe fluctuation interval range, and the path number where the anomaly occurs. This is used to support the subsequent field strength correction and angle compensation parameter generation process, ensuring that the affected area is clearly marked and the directional characteristics are judged, thus forming an angle interval screening sequence.

[0153] S503: Call the field strength change value of the angle interval segment in the angle interval filter sequence, construct the field strength change trend curve under the angle interval, obtain the angle position of the extreme point in the curve, and combine the field strength fluctuation amplitude before and after the extreme point to obtain the W-band antenna pointing angle correction parameter.

[0154] Based on the field strength variation values ​​in each angular interval, a field strength variation trend curve under the overall azimuth angle is constructed. This curve, with angle as the horizontal axis and field strength as the vertical axis, shows the intensity trend of the main lobe throughout the entire scanning range. During the plotting process, abnormal fluctuation points need to be marked, especially near extreme points. The maximum or minimum field strength value corresponding to the angle is recorded, and the field strength fluctuation amplitude is extracted from adjacent points before and after the curve. The field strength change rate and abrupt change degree are compared. If the field strength change within 5 degrees before and after a certain extreme point exceeds the set amplitude (e.g., 3dB), the angle corresponding to that point is considered to be a directional sensitive angle. Extreme points that meet this condition are extracted, and their angular positions are summarized. Combined with the fluctuation amplitude corresponding to each extreme point, an angle correction parameter table is constructed. The corresponding fields include angle position, correction level, direction offset trend, and path source number. This parameter table will serve as the basis for W-band antenna pointing angle correction and will be used to adjust the array feed control strategy or phase control parameters. The data in this table is called in the structural control logic for dynamic compensation processing to ensure that the main lobe pointing accuracy within the azimuth angle range meets the design requirements, thus obtaining the W-band antenna pointing angle correction parameters.

[0155] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A simulation analysis method for the pointing angle of a W-band antenna, characterized in that, Includes the following steps: S1: Obtain the geometric dimensions and radiating element morphology of the W-band antenna, extract the curvature distribution of the main lobe coverage area and the matching characteristics of the feeding structure, establish a three-dimensional electromagnetic field calculation domain including the metal substrate and the dielectric loading layer, evaluate the influence of structural components on the electromagnetic wave reflection phase, and obtain the electromagnetic field distribution characteristics. S2: By calling the electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics, the reflected wave interference path at the interface between the edge of the main lobe coverage area and the reflecting surface is identified, and the difference in reflection intensity between the main lobe propagation path and the side lobe reflection path is monitored to obtain the dynamic reflectivity boundary. S3: Based on the phase jump range of the dynamic reflectivity boundary, the feeding structure and support frame region are set as a hexahedral grid, the consistency of the electric field polarization direction in the grid cell is evaluated, the deviation region is locally meshed, and a grid division benchmark is generated. S4: Call the cell density distribution of the grid division reference, analyze the propagation time delay relationship between the ground reflection path and the metal structure scattering path, select paths with similar time delays as interference coupling terms, evaluate the crosstalk phase relationship between the feed port and adjacent cells, and obtain the multi-source coupling path feature set.

2. The simulation analysis method for the pointing angle of a W-band antenna according to claim 1, characterized in that, The electromagnetic field distribution features include field strength gradient, electric field standing wave ratio, and reflection phase response. The dynamic reflectivity boundary includes phase adjustment range, interference wave intensity difference, and polarization direction deviation. The meshing reference includes tetrahedral cell distribution density, hexahedral cell topology, and local densification region boundary. The multi-source coupling path feature set includes coupling phase offset, path delay difference, and crosstalk intensity threshold.

3. The simulation analysis method for the pointing angle of a W-band antenna according to claim 1, characterized in that, The specific steps for obtaining the electromagnetic field distribution characteristics are as follows: S101: Obtain the geometric dimensions and radiating element morphology of the W-band antenna, extract the contour boundary parameters and element boundary line length corresponding to the coordinate points on the structural surface, combine the thickness change and boundary curvature change trend of the element edge structure, identify the surface geometric curvature distribution at the edge of the radiating element, and generate the boundary curvature distribution. S102: Based on the relationship between the boundary curvature distribution and the feed point position of the central segment of the radiating unit, obtain the surface spatial coordinate difference distribution of the differentiated radial region, extract the spacing data between the feed structure distribution point and the boundary curvature peak position, compare the overlap coefficient between the feed point position and the local curvature extreme value area, and obtain the feed structure matching result. S103: Based on the matching results of the feeding structure and the three-dimensional boundary dimensions of the structure, a three-dimensional spatial computational grid is constructed. The electromagnetic wavelength range corresponding to the band frequency is called as the boundary constraint condition. The angle range between the reflection direction vector of the medium interface and the metal interface and the incident angle is set. Combined with the wave propagation path length variation range, the electromagnetic field distribution characteristics are obtained.

4. The simulation analysis method for the pointing angle of a W-band antenna according to claim 3, characterized in that, The specific steps for obtaining the dynamic reflectivity boundary are as follows: S201: Call the electric field polarization direction and magnetic field vector distribution in the electromagnetic field distribution characteristics, obtain the coordinate sequence of the reflected wave propagation trajectory in the edge direction within the main lobe coverage area, identify the set of spatial contact points at the interface between the main lobe edge and the reflecting surface, detect the distribution of the angle direction formed by the reflected wave trajectory and the tangent point of the interface, and generate the distribution of the interference path boundary. S202: Based on the distribution of the interference path boundary and the positional relationship between the reflection direction change section in the main lobe path, extract the reflection intensity and propagation direction offset of the reflection point of the path segment, calculate the reflection intensity difference between the main lobe propagation path and the corresponding side lobe path, and adjust the offset distribution between the reflection phase of the interference region and the initial offset angle in the reflection intensity difference interval to obtain the dynamic reflectivity boundary.

5. The simulation analysis method for the pointing angle of a W-band antenna according to claim 4, characterized in that, The formula for calculating the difference in reflection intensity between the main lobe propagation path and the corresponding side lobe path is as follows: Where ΔI represents the difference in reflection intensity between the main lobe and the side lobe paths, AI k BI represents the reflection intensity at the k-th reflection point along the main lobe propagation path. k λ represents the reflection intensity at the k-th reflection point on the corresponding sidelobe path, N represents the total number of reflection points in the path segment, λ represents the dynamic phase adjustment factor, and α represents the reflection intensity at the k-th reflection point on the corresponding sidelobe path. k β represents the mean initial offset angle of the k-th reflection point along the main lobe path. k L represents the average magnitude of the propagation direction offset at the k-th reflection point along the sidelobe path. p γ represents the propagation path length of the main lobe, and γ represents the path segment direction offset correction coefficient.

6. The simulation analysis method for the pointing angle of a W-band antenna according to claim 4, characterized in that, The specific steps for obtaining the grid division reference are as follows: S301: Based on the spatial distribution gradient corresponding to the phase jump range in the dynamic reflectivity boundary, extract the multi-directional reflectivity change boundary of the main lobe coverage area, divide the main lobe coverage area into several phase continuous regions according to the reflectivity gradient continuity characteristics, and obtain the grid structure value of the main lobe region based on the multi-region reflectivity direction change trend and boundary spatial morphology. S302: Based on the grid density distribution and structural boundary information in the grid structure value of the main lobe region, extract the spatial location index of the power supply structure and the support frame region, identify the structural dimension and boundary direction distribution characteristics within the region, delineate the grid partitioning direction, and obtain a hexahedral grid set. S303: Call the boundary intersection information of the hexahedral mesh set with the tetrahedral unit in the main lobe region mesh structure value, calculate the angle between the electric field vector direction in the mesh unit and the main direction vector of the region, analyze the deviation trend under multi-directional distribution, and obtain the electric field polarization consistency evaluation result. S304: Based on the grid cell identifiers whose deviation exceeds the set judgment interval in the electric field polarization consistency evaluation results, extract the three-dimensional coordinate index value of the grid cell, and perform local grid refinement processing along the three axes around the deviation point to generate a grid division benchmark.

7. The simulation analysis method for the pointing angle of a W-band antenna according to claim 6, characterized in that, The formulas for the distribution features of structural dimensions and boundary directions within the identified region are as follows: Among them, Q i Aγ represents the quantization weight coefficient in the i-th structural dimension direction. i ρ represents the magnitude of the i-th boundary direction vector, ρ represents the standard deviation of the grid density distribution in the main lobe region, η represents the area proportion of the supporting frame region, and δ i G represents the actual length measurement in the i-th structural dimension direction, θ represents the structural dimension reference length, and G o represents the dispersion correction coefficient of the 0th boundary direction distribution, n represents the total number of structural dimension directions, and 0 represents the boundary direction distribution sequence index.

8. The simulation analysis method for the pointing angle of a W-band antenna according to claim 6, characterized in that, The specific steps for obtaining the multi-source coupling path feature set are as follows: S401: Call the cell density distribution in the grid division benchmark, extract the grid region index corresponding to the ground reflection path and the metal structure scattering path, obtain the spatial span and boundary intersection position of electromagnetic wave propagation between differentiated grid cells in the path, combine the grid density change trend between cells and the electric field direction change rate, calculate the time interval required for the overall propagation of the path, and obtain the path propagation delay interval. S402: Based on the time interval between propagation paths in the path propagation delay interval, calculate the propagation delay difference between path pairs, filter path combinations whose time difference is within the offset range, and use the propagation direction angle distribution trend and the number of path boundary reflections as auxiliary conditions for joint judgment to obtain the set of interference coupling paths. S403: Call the path set determined by the interference coupling path set, locate the feed port and adjacent grid cell region involved in the path, extract the time series values ​​of electric field phase and magnetic field vector direction in the corresponding cell, evaluate the relationship between phase offset rate and time difference change, and obtain the multi-source coupling path feature set.

9. The simulation analysis method for the pointing angle of a W-band antenna according to claim 1, characterized in that, The method further includes step S5: S5: Using the phase relationship of the multi-source coupling path feature set, identify the field strength superposition information of the main lobe propagation path and the interference path within the azimuth angle range, compare the main lobe gain change and side lobe level change of adjacent angles, filter the angle interval that meets the set conditions, optimize the field strength change of the interval angle, and obtain the W-band antenna pointing angle correction parameters. The W-band antenna pointing angle correction parameters include the main lobe azimuth angle optimization range, the side lobe suppression angle range, and the field strength difference judgment threshold.

10. The simulation analysis method for the pointing angle of a W-band antenna according to claim 9, characterized in that, The specific steps for obtaining the W-band antenna pointing angle correction parameters are as follows: S501: Using the phase relationship in the feature set of the multi-source coupling path, extract the electric field superposition direction corresponding to the main lobe propagation path and the interference path within the azimuth scanning range, and obtain the superposition field strength offset by referring to the distribution of the path field strength phase offset and the propagation direction angle under the differentiated azimuth angle. S502: Based on the superimposed field strength offset and azimuth direction change curve, extract the main lobe gain change amplitude and side lobe level fluctuation range in adjacent azimuth segments, compare the gain change trend and change amplitude, and generate an angle interval screening sequence. S503: Call the field strength change value of the angle interval segment in the angle interval filtering sequence, construct the field strength change trend curve under the angle interval, obtain the angle position of the extreme point in the curve, and combine the field strength fluctuation amplitude before and after the extreme point to obtain the W-band antenna pointing angle correction parameter.

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