An Improved Method and System for Modeling the Electromagnetic Environment of a Monte Carlo Electromagnetic Reverberation Chamber

Abstract

This invention discloses an improved Monte Carlo electromagnetic reverberation chamber electromagnetic environment modeling method and system, relating to the field of electromagnetic environment effects. The method introduces a distribution factor function to describe the distribution weight of plane electromagnetic waves on the surface of the incident sphere, combines this with Monte Carlo sampling to generate non-uniformly distributed plane electromagnetic wave parameters, calculates the electromagnetic field distribution in the simulated space based on the principle of electromagnetic superposition, and finally outputs the electromagnetic environment characteristics through post-processing. The corresponding system includes a parameter setting module, a sampling generation module, an electromagnetic calculation module, and a result processing and output module. This invention solves the problem of deviation between the simulation results and the actual reverberation chamber environment caused by the uniform distribution of electromagnetic waves in the traditional Monte Carlo method, achieving accurate simulation of electromagnetic environment non-uniformity and providing reliable support for electromagnetic compatibility testing, antenna performance evaluation, and other applications.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic environment effects, and more particularly to an improved method and system for modeling the electromagnetic environment of a Monte Carlo electromagnetic reverberation chamber. Background Technology

[0002] In electromagnetic environment research and engineering applications, electromagnetic reverberation chambers are widely used in electromagnetic compatibility testing, antenna performance verification, and other scenarios because they can provide a statistically uniform and isotropic complex electromagnetic field environment. Current technologies often simulate the electromagnetic reverberation chamber environment by superimposing an infinite number of plane electromagnetic waves. The core idea is based on the propagation characteristics and superposition principle of plane electromagnetic waves in electromagnetic theory: constructing a large number of plane electromagnetic waves with different propagation directions, polarization modes, amplitudes, and phases, and superimposing them within a specific spatial region to reproduce the complex electromagnetic field of the reverberation chamber.

[0003] This method relies on classical electromagnetic theory. The propagation and polarization characteristics of plane electromagnetic waves have clear mathematical descriptions and physical meanings, facilitating modeling and calculation. Furthermore, it allows for the simulation of reverberation chamber environments with different characteristics by adjusting plane wave parameters (propagation direction, polarization, etc.), providing a degree of flexibility. Meanwhile, the traditional Monte Carlo method, due to its fast calculation speed, low computational resource requirements, and easily understood theoretical basis, is often used for the random generation of plane wave parameters to support the aforementioned simulation process.

[0004] However, the traditional Monte Carlo-based plane wave superposition method has significant drawbacks: it assumes that the plane electromagnetic waves are uniformly distributed on the surface of the incident sphere, resulting in a relatively homogeneous electromagnetic environment under simulated single boundary conditions, which differs greatly from the electromagnetic environment of a real reverberation chamber. In a real reverberation chamber, the wall materials exhibit electromagnetic losses, reflections, and scattering, and objects such as the equipment under test, absorbing materials, and cables all irregularly affect the electromagnetic field, causing the internal electromagnetic field to exhibit randomness and non-uniformity in spatial distribution. This deviation between the simulated environment and the real environment severely undermines the accuracy and reliability of simulation results based on traditional methods in engineering scenarios such as precise electromagnetic compatibility testing and actual equipment performance evaluation, making it difficult to meet practical application requirements. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide an improved method and system for modeling the electromagnetic environment of a Monte Carlo electromagnetic reverberation chamber. By introducing a distribution factor to modulate the electromagnetic wave distribution probability, the distribution of plane electromagnetic waves on the surface of the incident sphere is changed, making it exhibit a realistic focusing effect. This allows for a more accurate simulation of the non-uniform electromagnetic environment under single boundary conditions in the reverberation chamber, improving the fit between the simulation results and the real environment, and providing more effective support for electromagnetic-related research and applications.

[0006] An improved method for modeling the electromagnetic environment of a Monte Carlo electromagnetic reverberation chamber includes the following steps:

[0007] Step 1: Initialize parameter settings

[0008] The basic parameters for reverberation chamber simulation are set, including the simulation space size, target frequency band range, number of single-group plane electromagnetic waves N, and number of boundary conditions M, and the distribution factor function is determined. The specific expression or discrete numerical table, where The polar angle of the electromagnetic wave propagation direction relative to the reference axis. For the azimuth angle, the distribution factor function Weights used to describe the distribution of a plane electromagnetic wave at different locations on the surface of an incident sphere;

[0009] Step 2: Monte Carlo sampling to generate plane electromagnetic wave parameters

[0010] Based on the Monte Carlo sampling algorithm, combined with the aforementioned distribution factor function Based on other preset probability distribution rules, M sets of plane electromagnetic wave parameters are randomly generated, M≥12, each set containing N parameter sets of plane electromagnetic waves, N≥5000; each set of parameters includes the propagation direction, polarization, amplitude, and phase of the plane electromagnetic wave; the distribution factor function... Modulate the generation probability of electromagnetic waves in each direction to achieve a non-uniform distribution of plane electromagnetic waves on the surface of the incident sphere;

[0011] Step 3: Calculate the electromagnetic environment by superimposing plane electromagnetic waves.

[0012] The generated M sets of plane electromagnetic wave parameters are transformed into a unified coordinate system. Based on the principle of electromagnetic superposition, the electric field intensity vector and the magnetic field intensity vector are superimposed at discrete points in the simulation space to obtain the total electric field intensity and the total magnetic field intensity at each discrete point, thus constructing the spatial distribution of the electromagnetic environment.

[0013] Step 4: Post-processing and Result Output

[0014] The calculated electromagnetic environment data is post-processed to extract information such as field strength statistical characteristics and frequency band energy distribution, and the simulation results are output in a preset format.

[0015] Furthermore, the distribution factor function The value range of is [0,1], and the distribution factor function The expression or discrete numerical table is determined based on prior knowledge or experimental data of the actual electromagnetic environment of the reverberation chamber, and is used to reflect the differences in the degree of electromagnetic concentration in different boundary regions.

[0016] Furthermore, the simulated spatial dimensions in step one include length L, width W, and height H, and the target frequency band range is the entire frequency band.

[0017] Furthermore, other preset probability distribution rules in step two include: uniform distribution of polarization mode and uniform distribution of phase within the range of [0, 2π]. The amplitude parameter is set to an initial range based on the target frequency band and total energy constraints, and then combined with the distribution factor function. Adjustments will be made.

[0018] Furthermore, the post-processing in step four includes spatial averaging calculation, frequency domain analysis, and field strength statistical analysis; the electromagnetic environment characteristic information includes the statistical average value, standard deviation, and energy distribution of different frequency bands; the preset output format includes a three-dimensional field strength distribution cloud map, frequency domain characteristic curves, and statistical data tables.

[0019] A system for implementing the above method includes:

[0020] Parameter setting module: Used to receive basic reverberation chamber simulation parameters input by the user, and provides an interface for the user to define or import the distribution factor function. This ensures that the system can construct the electromagnetic environment according to the desired degree of non-uniformity and distribution characteristics;

[0021] Sampling generation module: Integrates Monte Carlo sampling algorithm and random number generation mechanism, combined with distribution factor function passed in from parameter setting module. Based on preset rules, generate M sets of plane electromagnetic wave parameters;

[0022] Electromagnetic calculation module: Performs coordinate system transformation and vector superposition operations on the plane electromagnetic wave parameters output by the sampling generation module to generate electromagnetic field distribution data in the simulated space;

[0023] Results Processing and Output Module: Post-processes the electromagnetic environment data output by the electromagnetic calculation module, extracts electromagnetic environment characteristic indicators, and outputs the results in the form of three-dimensional field strength distribution maps, frequency domain characteristic curves, etc.

[0024] Furthermore, the electromagnetic computing module employs a vector operation algorithm accelerated by SIMD instructions and supports GPU parallel computing to improve the efficiency of planar electromagnetic wave superposition calculation.

[0025] Furthermore, the result processing and output module has a built-in chart generation tool that can visualize electromagnetic environment characteristic information; the output formats supported by the result processing and output module include 3D field strength distribution cloud maps in PNG / JPG format, statistical data in Excel format, and frequency domain curve data in MATLAB format.

[0026] The beneficial effects of this invention are: by modulating the distribution of plane waves on the surface of the incident sphere by the distribution factor function, the electromagnetic focusing effect is realized, the non-uniform electromagnetic environment under the boundary conditions of the real reverberation chamber is accurately reproduced, the problem of the uniform distribution of traditional methods not matching the real environment is solved, and the accuracy of the simulation results is significantly improved.

[0027] The distribution factor function can be flexibly adjusted according to the actual reverberation chamber scenario, such as different wall materials and the layout of objects in the room, to support the simulation of a variety of extreme or special electromagnetic scenarios and adapt to different research and engineering needs.

[0028] It inherits the advantages of the traditional Monte Carlo method, such as fast calculation speed and low resource requirements, and further improves efficiency through optimized algorithms in the electromagnetic calculation module, such as parallel computing and vector acceleration, making it suitable for large-scale plane wave simulation.

[0029] The modular deconstruction function allows for convenient parameter settings and intuitive result output, supporting multiple application scenarios such as electromagnetic compatibility testing and equipment performance evaluation. It lowers the barrier to entry for users and has high engineering application value. Attached Figure Description

[0030] The present invention will be further described below with reference to the accompanying drawings:

[0031] Figure 1 This is a schematic diagram of the incident electromagnetic wave distribution using the traditional Monte Carlo method;

[0032] Figure 2 This is a schematic diagram of the incident electromagnetic wave distribution under three boundary conditions using the Monte Carlo method after adding the distribution factor;

[0033] Figure 3 It is a comparison of the probability density functions of the real part (a) and imaginary part (b) of the electromagnetic field at 1 GHz with the ideal normal distribution under the conditions of M=12 groups and N=10000 columns of plane electromagnetic waves;

[0034] Figure 4 The probability density functions of the real part (a) and imaginary part (b) of the electromagnetic field at 2 GHz under the conditions of M=12 groups and N=10000 columns of plane electromagnetic waves are compared with the ideal normal distribution law.

[0035] Figure 5 It is a comparison of the electromagnetic field modulus at 1 GHz with the cumulative probability density function of the ideal Rice distribution under the conditions of M=12 groups and N=10000 columns of plane electromagnetic waves.

[0036] Figure 6 This is a comparison of the electromagnetic field modulus at 2 GHz with the cumulative probability density function of the ideal Rice distribution under the conditions of M=12 groups and N=10000 columns of plane electromagnetic waves. Detailed Implementation

[0037] The present invention will be further described in detail below with reference to embodiments and specific implementation methods:

[0038] Example 1

[0039] The simulated electromagnetic reverberation chamber is designed as a cuboid structure with a length, width, and height of 5m, 4m, and 3m, respectively. The target frequency band is set to 1GHz-10GHz, and the plan is to use plane electromagnetic waves corresponding to M=12 sets of boundary conditions, with N=10000 electromagnetic waves in each set.

[0040] Determining the distribution factor function:

[0041] Determine the distribution factor function This function is in different and Under certain values, the plane electromagnetic wave will exhibit varying degrees of focusing effect in different regions of the incident sphere's surface, for example, in... near and Close to 0 or In areas where the distribution factor value is relatively large, it means that the probability of generating plane electromagnetic waves in this direction is higher. This simulates a phenomenon similar to the relative concentration of electromagnetic energy at certain locations on the boundary of an actual reverberation chamber. Through the system's parameter setting interface, parameters such as the simulated space size, target frequency band range, and number of plane electromagnetic waves are input, and the defined distribution factor function is applied. Import it into the system and complete the initial setup.

[0042] System module operation process:

[0043] Parameter setting module operation: The user inputs the above reverberation chamber size, target frequency band, M=12 and N=10000 parameters through the system's parameter setting interface, and inputs the above distribution factor function expression through the function editing window. The system automatically verifies the function syntax and parameter rationality, completes the initialization settings, and passes the parameters to the sampling generation module.

[0044] Sampling generation module operation:

[0045] The sampling generation module uses the Monte Carlo sampling algorithm, combined with the imported distribution factor function and preset polarization mode for uniform distribution and phase. The parameters are uniformly distributed within the range. Initially, 12 sets of 10,000 plane electromagnetic wave parameters are randomly generated. During this process, for each set of parameters, the polar angle of the propagation direction is... and azimuth The probability of taking a value is affected by the distribution factor function. The modulation of the plane electromagnetic wave causes the plane electromagnetic wave to exhibit a non-uniform distribution state that conforms to the definition of the function on the surface of the incident sphere.

[0046] Electromagnetic calculation module calculation:

[0047] After the electromagnetic calculation module obtains 12 sets of planar electromagnetic wave parameters generated by the sampling generation module, it transforms all the vector parameters of the electromagnetic waves into a rectangular coordinate system with the lower left corner of the bottom surface of the reverberation chamber as the origin through the coordinate system transformation submodule. The simulation space is divided into a discrete grid of 100×80×60 with a grid spacing of 5cm. Using multi-threaded parallel technology, the 12 sets of parameters are distributed to 12 calculation threads, and the electromagnetic field components of each grid point are superimposed and calculated simultaneously. After the calculation is completed, the total electric field strength and total magnetic field strength data of 5,760,000 discrete points are obtained. The data shows that the average field strength of the grid points near the side wall of the reverberation chamber is 2.3 times higher than that of the central area, which is consistent with the electromagnetic distribution characteristics of the actual reverberation chamber.

[0048] Based on the superposition principle of electromagnetism, the simulated space is divided into a certain discrete grid. The electric field intensity vector and magnetic field intensity vector of the plane electromagnetic wave are superimposed at each grid point. By transforming the vector parameters of each set of plane electromagnetic waves to a unified coordinate system, vector summation and other operations are performed point by point to finally obtain the total electric field intensity and total magnetic field intensity at each grid point in the entire simulated space, thus constructing the three-dimensional spatial distribution of the electromagnetic environment. Due to the non-uniform distribution of plane electromagnetic waves, the obtained electromagnetic environment exhibits obvious non-uniformity in different boundary regions. For example, in the corners of the simulated reverberation chamber, the variation of electromagnetic field intensity is more consistent with the complex distribution characteristics caused by boundary reflection, scattering and other factors in reality.

[0049] Result processing and output module processing:

[0050] Spatial averaging was performed on the above field strength data to calculate the average field strength of each 1m×1m×1m sub-region, eliminating small fluctuations at the grid level. The time-domain field strength data was converted to the frequency domain using Fast Fourier Transform to obtain the energy distribution curve in the 1GHz-10GHz frequency band. It was found that the energy concentration effect in the 8GHz-10GHz frequency band was more obvious. Finally, a three-dimensional color field strength distribution map, frequency domain energy distribution curve, and field strength statistics table were output to facilitate researchers to view the simulation results and further conduct electromagnetic compatibility testing and performance evaluation of antennas in this simulated environment based on these results.

[0051] Figure 1 In the traditional Monte Carlo method, the incident electromagnetic wave model under a single boundary condition has N-line incident electromagnetic waves that are uniformly distributed on the surface of a unit sphere, which is significantly different from the electromagnetic environment distribution in an ideal reverberation chamber. Figure 2The three figures provided illustrate three of the twelve different boundary conditions. The N-series incident electromagnetic wave incident point exhibits a significant clustering distribution effect on the unit sphere, which is closer to the distribution pattern in a real reverberation chamber.

[0052] Depend on Figures 3-6 It can be seen that the probability density function of both the real and imaginary parts of the electromagnetic field tends to be consistent with the ideal normal distribution, and the cumulative probability density function tends to be consistent with the ideal Rice distribution.

[0053] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An improved method for modeling the electromagnetic environment of a Monte Carlo electromagnetic reverberation chamber, characterized in that, Includes the following steps: Step 1: Initialize parameter settings The basic parameters for reverberation chamber simulation are set, including the simulation space size, target frequency band range, number of single-group plane electromagnetic waves N, and number of boundary conditions M, and the distribution factor function is determined. The specific expression or discrete numerical table, where The polar angle of the electromagnetic wave propagation direction relative to the reference axis. For the azimuth angle, the distribution factor function Weights used to describe the distribution of a plane electromagnetic wave at different locations on the surface of an incident sphere; Step 2: Monte Carlo sampling to generate plane electromagnetic wave parameters Based on the Monte Carlo sampling algorithm, combined with the distribution factor function and other preset probability distribution rules, M sets of plane electromagnetic wave parameters are randomly generated, M≥12, each set containing N parameter sets of plane electromagnetic waves, N≥5000; each set of parameters includes the propagation direction, polarization, amplitude, and phase of the plane electromagnetic wave; the distribution factor function... Modulate the generation probability of electromagnetic waves in each direction to achieve a non-uniform distribution of plane electromagnetic waves on the surface of the incident sphere; Step 3: Calculate the electromagnetic environment by superimposing plane electromagnetic waves. The generated M sets of plane electromagnetic wave parameters are transformed into a unified coordinate system. Based on the principle of electromagnetic superposition, the electric field intensity vector and the magnetic field intensity vector are superimposed at discrete points in the simulation space to obtain the total electric field intensity and the total magnetic field intensity at each discrete point, thus constructing the spatial distribution of the electromagnetic environment. Step 4: Post-processing and Result Output The calculated electromagnetic environment data is post-processed to extract information such as field strength statistical characteristics and frequency band energy distribution, and the simulation results are output in a preset format.

2. The improved Monte Carlo electromagnetic reverberation chamber electromagnetic environment modeling method according to claim 1, characterized in that, The distribution factor function The value range of is [0,1], and the distribution factor function The expression or discrete numerical table is determined based on prior knowledge or experimental data of the actual electromagnetic environment of the reverberation chamber, and is used to reflect the differences in the degree of electromagnetic concentration in different boundary regions.

3. The improved Monte Carlo electromagnetic reverberation chamber electromagnetic environment modeling method according to claim 1, characterized in that, The simulated spatial dimensions in step one include length L, width W, and height H, and the target frequency band range is the entire frequency band.

4. The improved Monte Carlo electromagnetic reverberation chamber electromagnetic environment modeling method according to claim 1, characterized in that, Other preset probability distribution rules in step two include: uniform distribution of polarization mode and uniform distribution of phase within the range of [0, 2π]. The amplitude parameter is set to an initial range based on the target frequency band and total energy constraints, and then combined with the distribution factor function. Adjustments will be made.

5. An improved Monte Carlo electromagnetic reverberation chamber electromagnetic environment modeling method according to claim 1, characterized in that, The post-processing in step four includes spatial averaging calculation, frequency domain analysis, and field strength statistical analysis; the electromagnetic environment characteristic information includes the statistical average value and standard deviation of field strength and the energy distribution of different frequency bands; the preset output format includes a three-dimensional field strength distribution cloud map, frequency domain characteristic curves, and statistical data tables.

6. A system for implementing the method of any one of claims 1-5, characterized in that, include: Parameter setting module: Used to receive basic reverberation chamber simulation parameters input by the user, and provides an interface for the user to define or import the distribution factor function. This ensures that the system can construct the electromagnetic environment according to the desired degree of non-uniformity and distribution characteristics; Sampling generation module: Integrates Monte Carlo sampling algorithm and random number generation mechanism, and generates M sets of plane electromagnetic wave parameters by combining the distribution factor function and preset rules passed in from the parameter setting module; Electromagnetic calculation module: Performs coordinate system transformation and vector superposition operations on the plane electromagnetic wave parameters output by the sampling generation module to generate electromagnetic field distribution data in the simulated space; Results Processing and Output Module: Post-processes the electromagnetic environment data output by the electromagnetic calculation module, extracts electromagnetic environment characteristic indicators, and outputs the results in the form of three-dimensional field strength distribution maps, frequency domain characteristic curves, etc.

7. The system according to claim 6, characterized in that, The electromagnetic computing module employs a vector operation algorithm accelerated by SIMD instructions and supports GPU parallel computing to improve the efficiency of planar electromagnetic wave superposition calculation.

8. The system according to claim 6, characterized in that, The result processing and output module has a built-in chart generation tool that can visualize electromagnetic environment characteristic information. The output formats supported by the result processing and output module include 3D field strength distribution cloud maps in PNG / JPG format, statistical data in Excel format, and frequency domain curve data in MATLAB format.

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